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Background and Objectives: Wastewater treatment of paper recycling and cardboard industries with the aim of water recycling and reducing environmental impact is one of the daily needs of industries. Therefore, the aim of the present study was to optimize the conditions of coagulation and flocculation process in wastewater treatment of paper recycling industries using the response surface method. Materials and Methods: In this laboratory study, response surface method and central composite design were used to design the experiments and to determine the effects of the studied variables (pH, concentrations of alum, Poly aluminum chloride (PAC), and cationic polymer) on the total suspended solid (TSS) and chemical oxygen demand (COD) removal efficiency. Data analysis was done using ANOVA statistical test with a significant level of 0.05. Results: The results showed that in the combination of PAC with cationic polymer (optimal conditions; pH=7.5, PAC concentration=450 mg/L, cationic polymer concentration=1.5 mg/L), the TSS and COD removal efficiency were 97.34% and 75.76%, respectively. In combination of alum with cationic polymer (optimal conditions; pH=8.5, alum concentration=550 mg/L, cationic polymer concentration=2 mg/L), removal efficiencies were 98.96% and 77.83%, respectively. The simultaneous effects of two independent variables, pH and concentration, had a significant effect (p<0.05) in removing TSS and COD variables. Conclusion: The results showed that the combination of PAC with cationic polymer had a better efficiency. Also, the COD and TSS in the final effluent were higher and lower than the standard values, respectively. Therefore, chemical coagulation process is proposed as pretreatment. [ABSTRACT FROM AUTHOR]

Multi-area economic distribution of load (MAED) is a generalization of the basic problems of economic distribution of load (ED), which evaluate the optimal power distribution of multiple areas in terms of operating costs. In the following parts of this paper, the concept of MAED is extended to multi-regional economic/environmental distribution (MAEED) by considering environmental issues. The purpose of MAEED is to distribute power among different areas by minimizing operating costs and emissions at the same time. In this paper, first the MAEED problem was expressed as a formula; then, a multi-objective and advanced particle optimization (MOPSO) algorithm was expressed to deduce its Pareto optimal solutions, during the optimization process. The transmission limits of communication lines were expressed as a set of constraints to ensure the security of the system. In addition, the rotating storage area was to increase the reliability of the system. A reserve sharing pattern was applied to ensure each region's capability to meet reserve demand. The simulation was based on the four-zone experimental power system, and it showed the effect of the proposed optimization process and the effects caused by different issues. [ABSTRACT FROM AUTHOR]

Introduction Assume the system of linear equation y Ax where A ∈ Rmxn is a known matrix it is called the dictionary or the sensing matrix with n >m and a given signal measurement y ∈ Rm. The main goal in a sparse signal recovery problem is to find the sparsest possible vector x satisfying y = Ax. A common mathematical model of this problem is (1) Po: min/x ||x||o X s.t y = Ax where ||x||0 is the LO norm defined as the number of non-zero elements of x. Since the LO norm does not have desirable properties like being continuous and differentiable, relaxation methods have been developed to solve it. In practical applications, where the available data are subject to noise and measurement errors, a study of a noisy version of the original model is inevitable; that is, Pε0: min ||x||o X s.t lly - Axll2 ≤ ε where > 0 is an upper bound for the noise. The proposed algorithm Sequential quadratic programming is an iterative method for solving constrained optimization problems. This approach determines the search direction by solving a quadratic subproblem at every iteration. This method was first proposed by Wilson in 1963 and then popularized by Han, and Powell. Consider the constraint optimization problem. P{ min/x fσ(x)=-∑n i=1exp(-x2i/σ2) s.t. c(x) = y - Ax The problem (3) can be seen as a continuous relaxation of the original problem (1). In the SQP approach, the search direction d is computed by solving the following quadratic trust-region subproblem QP(x,p) { min/d q(d) := gtd+1/2 dt Hd s.t. c+▽ctd = 0 ||d|2≤ p where p is the trust-region radius, g=(g1,...,gn)t is the gradient of the objective function and H is the Hessian of the Lagrangian or its approximation. The gradient and the Hessian of the SL0 norm are gi= 2xi/σ2exp(-xi2/σ2), H=Diag (2/σ2-4xi2/σ4)exp(-xi2/σ2) where Diag (wi) denotes a diagonal matrix with elements wi. Fortunately, Since the Hessian has a simple diagonal structure, all subproblems, as we show later, can be solved efficiently without imposing additional cost; it results to a super-linear rate of convergence. Let d be the solution of the quadratic programming subproblem (4), we define Δq:=q(0)-q(d)+-gtd-1/2dt Hd, Δf:= f(x)- f(x+d), as the predicted and the actual reduction, respectively. Conclusion In this paper, we proposed a sequential quadratic programming algorithm for solving sparse recovery problems. An efficient SQP solver for the noise-aware problems was introduced. The proposed method uses a new approach to solve subproblems. Through a set of extensive experiments on sparse signal recovery problems in various scenarios, it was demonstrated that the proposed algorithm outperforms a number of well-known algorithms. In recent years, the problem of non-negative sparse representation and recovering low-rank matrices have received more attention by researchers. In this regard, a future plan of research can be developing a suitable version of the proposed method for solving these problems. As a further plan, providing a worst-case complexity bound for the proposed algorithm, considering the specific structure of the problem at hand, can be on the agenda. Using the Filter idea from non-linear programming instead of the penalty approach also is a good point for the future development. [ABSTRACT FROM AUTHOR]

One of the ways to increase the reliability of the system is redundancy allocation to the system. The standby redundancy is divided into three categories, cold, hot, and warm, depending on the environmental conditions in which they are placed in standby mode. The cold standby redundancy is inactive in standby mode, and the possibility of its failure in this mode is considered zero. A hot standby redundancy is active in standby mode and has the same failure rate as active system components. A warm standby redundancy is also active in standby mode, but it is not subjected to the same stress as the active system components as a hot standby redundancy. In this article, we investigate the reliability of stress-strength in k out of n:G system in an H-Weibull model equipped with three types of standby redundancy and we get results about the time to add the standby component to this system. The baseline distribution function of the model is H, which is the distribution of the stress system. The contents of this article are categorized as follows. In the second part, in the general case, we will calculate the reliability of stress-strength in a k out of n:G system in an H-Weibull model equipped with a standby redundancy in H-Weibull models. In addition, we obtain a closed form for the stress-strength reliability of these systems under the exponential baseline distribution in the three standby states of cold, hot, and hot. In the third part, we study the time and cost of adding the standby component to this system. In this section, by introducing the cost function, we obtain the optimal time to add the standby component of the system with the aim of simultaneously reducing the costs and increasing the reliability of the stress-strength model under different values of the model parameters. In the last part, the conclusion of the content of the article is presented. Material and Methods In this paper, we present the general case for adding a standby component to a k out of n:G stress-strength system. Then, in the H-Weibull model, we investigate the reliability behavior of stress-strength in this system. A k out of n:G system is active, whenever at least k components out of n components are active. Consider a k out of n:G system with independent identically distributed (i.i.d) Y₁ ،...، Yn with distribution function G. Assume that the components of the above system are independent of each other putting into a common random stress Z with cumulative distribution function H and random variables Z and Yi for i = 1 ،...، n. In this case, the stress-strength reliability of this system is given as R(n. k) = P(ZYn-k+1n), where Yi:n, is i th order statistic in the random sample Y₁ ،...، Yn. Suppose that the random variable X is the lifetime of a standby redundant with the distribution function F in normal environmental conditions and with the cumulative distribution function F(γ(t)) in the standby state, where γ(t) is any ascending function meeting two requirements for every t > 0, γ(0) = 0 and γ(t) ≤t. On the other hand, the ascending function w(t) is the transformed age of the standby redundant, from the standby state to the normal condition applying to every t > 0 in two conditions w(0) = 0 and w(t) ≤t. The hot and cold ready add-ons are special modes of the above model and are obtained when w(t) = γ(t) = 0 and w(t) = γ(t) = t, respectively. Letk out of n:G mentioned stress-strength system equipped with the standby redundant with lifetime X. Here, the standby redundancy enters the system operation after observing the (n-k-m+1)th failure among the system components, where m = 0...n-k, and the system until the failure of the (m + 1)th component out of m+k remaining components is kept active. Results and Conclusion In this article, the importance of the time allocation of the standby redundant to the k-out-of-n:G stress-strength system and its effect on the stress-strength reliability and costs in the H-Weibull model are investigated. Also, the behavior of the cost function based on the H-Weibull model parameters is studied. The optimal time to add the standby component to the system performance in a k-out-of-n:G stress-strength system in the H-Weibull model is presented. Based on the results of this article, the adding time of the standby component with the aim of increasing the stress-strength reliability is dependent on the parameters of H-Weibull model, and the time changes by changing these parameters. On the other hand, the time to add the standby component to the stress-strength system in the model with the aim of increasing the stress- strength reliability and reducing the system costs simultaneously, in addition to the system parameters is dependent on the number of system components and the value of k. In any case, we can conclude that for large values of n and k, the optimal time to add is m = 0 and for small values of k and large n, this value is usually m=n k and based on the distance between the values of n and k from each other, the value of m will be changeable. [ABSTRACT FROM AUTHOR]

Energy storage systems have an important effect on increasing the flexibility of power grids and are necessary to achieve the goals of smart grids. So far, many researches have been conducted in the field of optimal utilization of batteries, but most of them have studied the effects of batteries only on the side of the transmission or distribution network. In the present study, the effect of the installation and optimal operation of energy storage systems on both sides of the transmission and distribution network has been investigated. This paper presents a bi-level optimization model for integrated energy management in transmission and distribution smart grids along with demand management issues. Considering that both proposed models are mixed integer linear programming models, it is difficult to solve them by direct methods. Therefore, a method based on the change of variables and KKT equations is presented to solve these problems, and globally optimal solutions to these problems are guaranteed. Several integrated systems that include transmission and distribution networks are considered to evaluate the proposed model and method, and the results show that the proposed model is efficient and shows the positive effect of modeling energy storage systems on both sides of the network. [ABSTRACT FROM AUTHOR]

This paper aims to develop a new approach for structural design layout of new generation unconventional aircraft especially for ULWAV. The first step in this approach is to investigate the affecting parameters on structural architecture of these aircrafts then using of modal analysis to identification the behavior of these unconventional geometries for a general methodology development. The result of this modal analysis is apportion aircraft geometry to conventional substructures with already well-established defined architect. ULWAV structure architecture has been done by combining the structural architecture of sub-sections and with respect to requirements for systems installation, stealth design objective and packaging requirements. Here the CATIA software is used to optimize general architect with parametric model. To validate the results, the maximum static stress and maximum displacement of the structure were calculated using MSC / Patran software and compared with the values obtained from the optimization process. Dynamic analysis and buckling stability of structural composite shells are also controlled below. The architect methodology was applied to a case study of an ULWAV. The weight of the optimized structure has also been confirmed by typical case study researches. [ABSTRACT FROM AUTHOR]

In this paper we try to simulate the life cycle of the electricity industry using the agent-based simulation method. For this purpose, 5 Agents were mentioned and they were simulated by Anylogic software. Then, four scenarios were investigated with experts' opinions. In the first scenario, it is assumed that the attractiveness of gas power and combined has been reduced and the attractiveness of the other two power has been added, the result of this scenario is the increase in hydroelectric power production, which is not cost effective due to the lack of water resources for the country. In the second scenario, with the arrival of a new technology, the household consumer decreased by 40%, and hydro and steam power with a capacity of 40% were working in the power generation cycle, the result of this scenario is the reduction of fuel consumption and also the shortage of electricity produced relative to the electricity consumption. In the third scenario, it is assumed that the consumption rate of all consumer factors has decreased, which results in the lack of investor factor investment. the fourth scenario assumes that all consumers' consumption is constant, as well as keeping the attractiveness developed by the government steady. As a result, the capacity of electricity generation has increased, but we are still facing power shortages. [ABSTRACT FROM AUTHOR]

In this paper, a new fractional-order fuzzy controller named proportional fuzzy ا integral fuzzy + deferential fuzzy (FP + Fla + FDp) is proposed. The proposed controller is single gain, integrate, derivative and fractional order in its structure. The controller has a structure with two adjustable fractions and is simply designed. This controller performs the stability process in a short time. The response time can also be changed by adjusting the coefficient of time scale a and p, which makes it more flexible and efficient compared to the classic PID controller. On the other hand, in the design of the proposed controller, the optimal adjustment of the controller gain and fuzzy members has turned into an optimization problem, which is done by a hybrid algorithm based on the vcs and the HBC colony (ABC) based on a function in the time domain. In the proposed hybrid algorithm, attempts have been made to take advantage of local and final search as the strengths of these controllers to dramatically reduce the possibility of locating in local points. Investigations of different load variation scenarios, better performance of the proposed controller facing load disturbances from the root mean square, rise and fall time, will show the number of oscillations, and the fall time of the frequency changes. [ABSTRACT FROM AUTHOR]

Censored sample arises in a life-testing experiment whenever the experimenter does not observe the failure times of all units placed on a lifetest. In medical or industrial studies, researchers have to treat the censored data because they usually do not have sufficient time to observe the lifetime of all subjects in the study. There are different types of censoring. The most common censoring schemes are type I and type II censoring schemes. Progressively type II censoring is also one of the most important methods of censoring. One of the most common questions any statistician gets asked is "How large a sample size do I need?". Researchers are often surprised to find out that the answer depends on a number of factors and they have to give the statistician some information before they can get an answer. So far different answers have been given to respond this question by considering different criteria. Cost criterion is one of the criteria that has always been of interest to researchers. So far, many researchers have used this criterion for determining the size of samples in different censoring methods. In some applications, such as clinical trials and quality control, it is almost impossible to have a fixed sample size all the time because some observations may be missing for various reasons. In other words, the sample size is a random variable. Material and methods In this paper, a cost function is introduced. Then, assuming that the sample size of progressively type II censoring is a random variable from the truncated binomial distribution, the optimal parameter of sample size distribution in progressively type II censoring, is determined. This optimal parameter is determined so that the introduced cost function does not exceed a predetermined value, say c* . In this article, the exponential distribution is considered for lifetimes of observations. A simulation study is also provided to evaluate the obtained results. Finally, the conclusion of the article is presented. Results and discussion We have computed the values of the expected cost function by considering three different censoring schemes. The results show that the expected cost function is an increasing function of m but a decreasing function of θ, when other components are fixed, as we expected. Also, we can find that considering type II censoring leads to better results than other censoring schemes. On the other hand, we can conclude that type II censoring provides the minimum cost among two other censoring schemes. In the sequel, by assuming an upper bound for the cost function, say c*, the optimal parameter of sample size distribution is obtained. Conclusion Determining the optimal sample size is one of the issues that has been studied by many researchers. In some cases, it is not possible for the sample size to be a fixed and pre-determined value. In other words, the sample size is a random variable. In this paper, assuming that the sample size of progressively type II censoring is a random variable from the truncated binomial distribution, the optimal parameter of the sample size distribution is determined. The criterion used in this research is the cost criterion. Next, the optimal parameter of the sample size distribution is determined so that the value of the cost function is less than the specified and predetermined value, say c* . The results of the paper show that the type II censoring provides less values for the cost function. For all three censorsing schemes, the cost function is an increasing function of m but a decreasing function of θ, when other components are fixed, as we expected. As a result, the best case scenario is taking into account the type II censoring scheme, selecting smaller values for m, larger values for θ, and smaller values for the parameter of sample size distribution. [ABSTRACT FROM AUTHOR]

Background and Aims Today, with the industrialization of societies and the reduction of the size of households and tendency to live alone, caring for the elderly and monitoring their performance in daily life has become doubly important. Carrying devices such a GPS is one of the proposed solutions, which may not be a suitable solution due to the unpleasant feeling of carrying such equipment and due to disorders such as Alzheimer’s disease. A proper solution for taking care of old people especially for their outdoor activities is to observe their behavior by using their mobile GPS sensor by which it is possible to detect possible abnormal events. An important challenge in this method is the high number of abnormal events. In this paper, this problem is solved by applying an adaptive neuro-fuzzy inference system (ANFIS). Other important challenge is how to carefully analyze the training data to achieve a powerful model. For tackling this problem, we used a deep neural network.Methods In this paper, by combination of ANFIS and convolutional neural networks (CNN), a method was proposed for anomaly detection in trajectory of patients with Alzheimer’s disease. The CNN was optimized by the Whale algorithm. The proposed method was applied on a set of movement path data with a specific origin and destination based on the mobile GPS sensor of subjects. Results The proposed method had an accuracy of 95.5% for classification of test data, which indicated the effectiveness of the proposed method.Conclusion It seems that the combination of ANFIS and a CNN is a good method for anomaly detection in trajectory of older people with Alzheimer’s disease.

Background & Aims: Cancer is one of the great human challenges in all countries, both advanced and developing. Cancer treatment management can include surgery, chemotherapy, or radiation therapy (1). Radiation therapy is done in two ways: Teletherapy and Brachytherapy. Brachytherapy involves the use of radiation sources to treat cancer by irradiating cancerous tissue from within the patient’s body (2). But the dose and how to use this method has always been questionable for researchers. Therefore, this study creates a new fuzzy approach to high-dose brachytherapy by optimizing the distribution of double roughness based on dosimetric criteria. The use of fuzzy logic itself has increased the accuracy of the mathematical model of the problem. This fuzzy model is a new study and innovation used in this paper. Due to the fuzzy nature of this method and its limitations, it is considered fuzzy. This makes the method more accurate and includes parameters such as the patient’s physical ability and age in the problem, which in itself increases the accuracy of the method for each patient. As a result, the obtained answer is improved and the executive program of brachytherapy method is more accurate. Methods: In the present study, the dose prescribed for an organ was evaluated by dosimetric indices listed in Table 1 (18). For the present study, data from 20 patients in the age range of 50 to 74 and mean age 62 years with a wide range of prostate volume between 23 and 103 cubic centimeters, and for the treatment of prostate cancer by brachytherapy from the Academic Medical Center (AMC, Amsterdam, the Netherlands) had participated. To compare brachytherapy programs with high interstitial dose, the dose rate was calculated with 192Ir beam with a radiation dose of 13 Gy, according to the standard protocol TG-43. To begin with, computed tomography (CT) scans or magnetic resonance imaging (MRI) were taken from the patients pelvis, and entered into the treatment planning software for use in treatment planning sessions. BT treatment planners and specialists then determined the input catheters, target volumes, and OARs obtained from the medical images. Depending on the size and exact location of the target volumes, between 14 and 20 catheters entered the patient’s body, reaching the target volumes. After designing and approving an acceptable treatment plan, the catheters inserted into the patient’s body were connected to a retractor 4 that controls the movement of the radiation source. After the treatment program, the source was returned to the retractor (8, 14). Then, an integer program model with fuzzy constraints was proposed for programming on high-dose brachytherapy. The description of infrastructures, parameters and variables in this model are in Table 2 (15 ). Finally, the dosimeter index is equal to the sum of all the index variables, as it turned out: The proposed model is a correct programming model called IP. In general, three evolutionary algorithms (EP), (GA) and (ES) were used in this research. The algorithms stopped after creating 20 generations of desirable answers and the best answer of each generation was determined on the chart as a point. The resulting set of answers were connected in the form of graphs, which are used to analyze the results. Each point on the graph identifies the best answer from each of the generations generated by the respective algorithms. These three algorithms were performed independently for each patient and the obtained answers were identified as dots on the chart. The graph obtained for each patient indicates the capability of each of these algorithms. Results: According to this study, each of the three algorithms (EP), (GA) and (ES) are each run independently for each of the patients with prostate cancer. At first, the genetic algorithm showed the ability to get closer to the desired answer sooner, but as the optimization process continues, the rate of convergence to the desired answer decreases, so if the time parameter is very important, the genetic algorithm can be useful. Especially for patients whose prostate volume was larger than other patients. In patients 15, 12, 8 and 9, due to their younger age than other patients and better physical condition, as well as prostate volume less than 80 ml, they had much more promising results than other patients. In contrast, for patients 4 and 19 with an age of over 70, the results were not as favorable as for other patients. The * sign in the table indicates that there is no answer through that patient-specific algorithm that covers 95 or even more of the tumor volume. Therefore, according to Table 2, it can be concluded that the best algorithm that can be considered for the case where the shortest time to reach the target coverage above 95% is the genetic algorithm. According to Table 2, it can be concluded that the best algorithm that can be considered for the case where the shortest time to reach the target coverage above 95% is the genetic algorithm. Therefore, according to Table 3, the ES algorithm has better answers than the other two algorithms for the case in which the largest volume of the tumor is covered. According to the results, the ES algorithm has obtained the best results for patients under 60 years of age and normal prostate volume. Conclusion: According to the obtained results, it can be stated that whether the main goal is the maximum coverage or the goal is the shortest possible time to reach the coverage above 95%, the best algorithm that can get a good answer for each patient is the evolutionary strategy algorithm. [ABSTRACT FROM AUTHOR]

In this paper, the effect of using trefoil and segmental baffles on heat transfer and pressure drop towards the shell of shell and tube heat exchangers is studied. Baffles are used in shell and tube heat exchangers to increase heat transfer coefficient, pipe support, flow pattern determination, structural strength and vibration prevention. Using the genetic algorithm under the same conditions, the heat transfer and pressure drop functions of the baffles are optimized as single-objective and multi-objective. The heat exchanger with the trefoil baffles is simulated by Aansys fluent software. The results show that in trefoil baffles, increasing the heat transfer coefficient will be accompanied by a greater pressure drop. The heat transfer capacity of the trefoil baffle has increased by 19.944% in the square arrangement and 16.25% in the triangle arrangement compared to the segmental baffle in the maximum state obtained from the single-objective genetic algorithm, while the pressure drop for the square arrangement of the tube bundle is 3.2 times and for the triangle arrangement tube bundle has increased 2.075 times compared to the segmental baffle. The jet fluid flow created in the trefoil perforated increase the heat transfer performance and the corrosion products and chemical sediments are reduced, which also improves the corrosion conditions of the shell and tube heat exchanger with the trefoil perforated plate. [ABSTRACT FROM AUTHOR]

In the city of Qom, there is no dual water supply network with a separate meter inside the citizens' homes. On the other hand, high quality water sources do not meet all the drinking and non-drinking needs of the consumption areas. Therefore, the water and sewage company should respond to the drinking and non-drinking needs of the citizens by optimally managing the distribution of various available water resources. In this paper, the problem has been investigated in the form of two optimization mathematical models.In the first model, the current water allocation to citizens has been modeled and optimally solved, in which water resources should be allocated to citizens at the lowest cost, provided that all the needs of citizens are covered. In the second model, it is suggested that by scheduling the allocation of water resources, citizens will have access to quality water for drinking at a certain pre-determined time, and other consumption needs of citizens will be met with low quality water during the rest hours of the day and night.In the proposed model, both the allocation of water resources for the drinking and nondrinking needs of the citizens under the condition of covering all the needs of the citizens and the allocation of water resources with the lowest cost for the needs of the citizens are included. Finally, the application of the proposed model is presented with numerical analysis. [ABSTRACT FROM AUTHOR]

In this paper, the modeling of the system under study was first proposed and then a fuzzy-PID controller was designed considering the downstream filter for optimal system performance to simulate the stability of a nonlinear system and to simulate low frequency oscillations. In designing the proposed controller, the parameters of controller and fuzzy members were considered as the variable, which ultimately turns into an optimization issue. The controlling structure of the proposed PID is such that, regardless of type and structure of the system under study, it can guarantee the stability of the system and minimize the volatility and frequency fluctuations. The most important feature of the proposed method is its independence on the structure of the system and operating conditions. On the other hand, this paper attempts to reduce the frequency deviation of the dynamic mode by improving the frequency controller and implementing a new method. The new method is based on minimizing total sum of summing time, peak time, peak value, and permanent error state over load changes using the virus search optimization algorithm. Investigations done by different criteria in time and frequency domains, using the proposed algorithm shows high efficiency in comparison with other methods in the articles. Also, the proposed fuzzy controller has a better performance for damping system disturbances in bad situations. [ABSTRACT FROM AUTHOR]

The prediction of local scouring as a dynamic and nonlinear phenomenon using methods of acceptable predictive capability has always been of interest to researchers. The shape of the bridge pier is one of the important factors in the formation and magnitude of the scour hole. In this paper, the scour depth of three bridge piers with cylindrical, sharp nose and rectangular shapes was predicted in two scenarios using the support vector machine algorithm with 395 field data obtained from the US Geological Survey and Froehlich (1988), based on different combinations of dimensionless parameters as the water attack angle (α), Froud number (Fr), the ration of pier length to width (l/b), and the ratio of mean sediment size to pier width (D50/b). The results of the study, while confirming the acceptable performance of the SVM algorithm for all piers in both scenarios, showed that in the first and second scenarios, the most optimal performance was related to the rectangular pier shape with correlation coefficient of 0.8702 and 0.8838, with and maximum Ds (DDR) values of 0.854 and 1.229 respectively, during the testing phase. The positive effect of increasing the number of data on the performance of the SVM algorithm was also confirmed by further probing the evaluation indicators. The results of the comparison pointed out the overestimation of the predicted scour depth values of absolute error between 11% to 35%. [ABSTRACT FROM AUTHOR]

In the design of tapered cascades, due to hydrodynamic problems, not every cascade can be operated. This paper describes the method of designing and optimizing a tapered cascade for the separation of stable multi-component mixtures by considering the operational parameters of the gas centrifuge machine. In this method, the hydraulic specifications and separation of the centrifuge machine are determined in the first stage. Then, using this information and optimization algorithms, the optimal cascade is designed with the least number of centrifugal machines. This paper uses the grey wolf optimization algorithm to find the optimal cascade. The cascade operation is checked using the hydraulic parameters of the gas centrifuge,. The operational limitation of the cascade is added hydraulically to the fitness function in optimization. To determine the hydraulic characteristics of the gas centrifuge, a transient simulation of the gas centrifuge hydrodynamic is presented and the relationship between product and waste pressure lines, feed flow, and cut is determined. Using the proposed design method, an operational cascade is designed using a TC-12 centrifuge machine to separate the uranium 235 isotope from the reprocessed fuel to a 4% enrichment. And the pressure variation in the cascade is presented.

In this paper, a novel Comprehensive Preference-based Design (CPD) approach is presented which attempts to achieve subjective attributes that are defined in the concept of maximization of designer/customer's satisfaction in addition to objective goals which are formulated in the form of minimization of a performance criterion in a two-phase structure using two nested optimizers. The methodology is utilized to design of a UAV with flight duration of 24 hours, 45 meters per second of cruise speed at least, payload of 200 kg and less than 1 km take-off distance. To evaluate the results of CPD, the UAV design process using MDO in All-At-Once (AAO) framework is also performed. A UAV was designed in which not only the satisfaction attribute was maximized but also the total mass value with the least difference is very close to the value obtained in the MDO method with AAO framework. Comparison of the results shows that despite the higher mass of UAV designed by CPD, overall design satisfaction is higher and designer/customer's preferences have been satisfied. [ABSTRACT FROM AUTHOR]

Design and safety of natural gas tanks Due to its high use in cars, it is of great importance. Therefore, in this paper, the empirical, numerical and optimization of these reservoirs is investigated. Experimental section designed and manufactured two metal and composite tanks that have been tested for internal pressure and their strength has been determined. Modeling of these tanks has been done in the numerical section with the help of Abaqus software 6.14. In addition to validating the results with experimental data, numerical simulation has been developed. Using the results of the development of numerical simulation and experimental design software, optimization of parameters and their relationship with pressure tolerance in these tanks have been investigated. The numerical and experimental results are in good agreement. Lightweight composite tanks are more resistant to internal pressures, which resulted in a 30% reduction in the weight of composite tanks and a 20% reduction in deformation under operating pressure. [ABSTRACT FROM AUTHOR]

Sheet metal clinching process is a forming-based method for joining sheet metal parts. To ensure sufficient joint strength, it is necessary to design the forming tool optimally. This paper deals with numerical and experimental study of the clinching process of steel sheets of dissimilar thicknesses using a fixed die in order to optimize the geometric parameters of the clinching tool. In this study, using the orthogonal experimental design (OED) method and finite element analysis in Abaqus software, the important input parameters of tool design including punch radius RP, die cavity depth Pm, die groove width Lm and punch face angle PBA were optimized in order to achieve the highest clinch strength F as the target variable. The upper and lower sheets used in this study are 1.5 and 2 mm in thickness, respectively, and made of DX51D galvanized steel, manufactured according to EN10346/00 by Mobarakeh Steel Company. After running the experiments designed based on the OED in the computer, the optimal values of RP= 2.6mm, Pm= 1.4mm, Lm= 1.2mm and PBA= 1° and F= 2319N were obtained. Next, a clinched joint tool was designed and fabricated based on the optimum geometric parameters. The evaluation and comparison of clinch geometry and tensile strength obtained from optimum design simulation and the experimental counterparts demonstrated very close correlations. [ABSTRACT FROM AUTHOR]

Purpose: Today, the digital gaming industry has a significant impact on the economic, cultural, and social spheres around the world. The advent of real and virtual reality games, particularly in medical science, has taken this industry out of the realm of mere entertainment and has become one of the applied industries. This study aims to optimize the combination of indigenous digital game development strategies, using a goal mathematical programming model. Compared to other common methods, the proposed approach can be a good alternative to studying and using mathematical planning in strategic management, when strategies are evaluated and selected. Design/methodology/approach: The research method of this study is typically mixed qualitative and quantitative for which, the main data were collected using library studies and theoretical framework review, in-depth and structured interviews with 12 experts and specialists in the digital games industry. A filled questionnaire was collected after coding variables. Thematic analysis (reasoning and rational analysis) was used to extract and classify the components. Also, an integration of House of Quality (HOQ), Analytical Hierarchy Process (AHP), and Simple Additive Weighting (SAW) techniques were used to determine the variables and parameters required in the mathematical model of the research. Finally, a goal programming model was used to determine the optimal combination of the strategies. Findings: A portfolio of optimal strategies was proposed that were effective in removing barriers and challenges in the game industry, which facilitated the achievement of game development goals with desirable capabilities in implementation. The mentioned strategies were capabilities empowerment and development of game-making experts, targeting and enriching the content of homemade games, financing and facilitating investment, and increasing the level of competitiveness of game-making groups. Research limitations/implications: The limited number of expert group members and the researcher's low access to them, in addition to creating problems related to the distribution and collection of questionnaires, review and increase the computational accuracy of validity and reliability, and also calculating the compatibility rate in the pairwise comparison questionnaires were the challenges and limitations of this study. Practical implications: The digital games industry has a great potential for growth and development, and its favorable economic, cultural and social effects are undeniable. Some of the practical findings of this study are the creation of an elite network and a strong relationship between gaming enthusiasts and the university, empowerment of game developers' knowledge and game studios in the gaming ecosystem, and monitoring and support of governmental and non-governmental policy-making institutions. Originality/value: In this paper, a new approach was proposed for evaluating and optimizing strategies for developing indigenous digital games to overcome their challenges and meet the relevant objectives in compliance with their feasibility (ease) of implementation. Also, the use of mathematical modeling in evaluating and selecting optimal strategies in this industry distinguishes this study from the literature. [ABSTRACT FROM AUTHOR]

In the design of the combustion chamber, various parameters usually are considered. These parameters include uniform temperature distribution at the outlet of the chamber, more flame stability, lower pollution, higher combustion efficiency, lower wall temperature, and lower pressure drop in the chamber. Regarding the complex condition of the flow in the combustion chamber due to the various effects of turbulence and mixing of flows as well as the behavior of turbulent flames, predicting the performance of flow in the combustion chambers is very complicated. In this paper, the swirler of Amirkabir University of Technology Combustion Chamber has been studied and optimized. It is done by using the numerical method and finally the selected swirler in the numerical method is tested in the experimental setup to investigate the optimization method. According to the optimization, a swirler with an angle of 60 degrees, 12 blades, and a thickness of 0.75 mm is selected as the final case. In the experimental results, the amount of CO pollution has been significantly reduced. The output temperature, the pattern factor and unburned hydrocarbon have been reduced in the final case. However, the temperature uniformity inside the chamber has increased. [ABSTRACT FROM AUTHOR]

In this paper, a novel multi-generation system based on gas turbine-modular helium reactor cycle is presented. Integrated system consists of a Gas turbine-modular helium reactor cycle as a base cycle and from the combination of subsystems, hydrogen production, absorption refrigeration cycle, and desalination system. Thermodynamic comprehensive modeling (energy and exergy) was done on the suggested system. The effect of various system parameters, such as turbine inlet temperature, compressor pressure ratio, carbon dioxide to methane molar ratio, vapor generator temperature, and mass flow rate of the desalination system have been evaluated on the overall performance of the system. Also, optimization of the overall system using single and multi-objective optimization method has been investigated in terms of energy and exergy compared to the base case. The results showed that the maximum net power output and the energy efficiency and exergy of the overall system in compressor pressure ratio between 2.3-2.45 were 275 MW, 72.05%, and 49.35%, respectively, and with increasing turbine inlet temperature, heat production rate and energy and exergy efficiencies of overall system increases and the cooling production rate and freshwater decreases. In addition, the optimal point of the mass flow ratio of the desalination system for the energy and exergy efficiencies of overall system is 2.857. According to the results obtained in the multi-objective optimization method, the energy and exergy efficiencies of overall system were 74.41% and 50.21%, respectively, and exergy destruction has been reduced to 0.74% compared to base case. [ABSTRACT FROM AUTHOR]

Conceptual design optimization of spacecraft systems is a complex and multidisciplinary process. In this case evaluation of the objective functions relies heavily on running iterative simulation models and analysis codes between various subsystems (such as structures, payload, electrical power supply, attitude determination and control, communication, command and data handling). The conventional sequential optimization approaches to such a complex design problem is time consuming and does not guarantee to achieve the best compromise among the various competing coupled subsystems, and may even lead to non-optimal design. In addition, the design search space can be multi-modal, non-convex with multiple local minima and hence it is time consuming or difficult to rapidly evaluate trade-offs between various subsystems (disciplines). To address these issues, in this paper an efficient surrogate (response surface) model-based multidisciplinary spacecraft systems design optimization technique with discrete and continuous design variables is presented. The methodology is based on the utilization of genetic algorithms (GA) for both system level and discipline level as an optimizer. Surrogate-modeling as an efficient tool is also used to decrease computational cost in discipline (subsystem) level within a collaborative optimization (CO) framework. Results obtained in this study show that the method introduced in this paper provides an effective way of improving computational efficiency of a complex space system design such as conceptual design optimization of a spacecraft. [ABSTRACT FROM AUTHOR]

Purpose: Today, the manufacturing industry, with the expansion of the physical constraints of trade worldwide, has adopted modern information technologies to optimize the business process and achieve integration with geographically dispersed supply chain partners. Traditional supply chain models focus on optimizing physical flows. However, it is equally important to ensure that physical units can process appropriate information. This paper aims to propose a model for the optimization of information process performance in the IoT-based virtual supply chain. Design/methodology/approach: In this study, information processing performance in the closed-loop virtual supply chain has been optimized to maximize profit and information processing speed by considering costs of virtual, information security, and energy consumption. The final programming model has been optimized using meta-heuristic algorithms, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), and the Strength Pareto Evolutionary Algorithm (SPEA-II). Findings – The results indicated that there is an inverse relationship between virtual supply chain profit and information processing speed (delay). The results of model solving using NSGA-II and SPEA-II algorithms underlined the virtual supply chain profit of 9.93×106 and 4.23×106, and the data processing speed of 337.48 and 94.07, respectively. Thus, the NSGA-II algorithm contributes more to the supply chain profitability. Research limitations/implications - The proposed model can be used in manufacturing industries equipped with IoT. Unavailability of practical examples and insufficient data are the two main limitations of the study. Practical implications:- The proposed model improves the production process and helps managers to plan better for their supply chain management and make timely decisions by sharing information across the supply chain and being aware of the flows of products and associated parts. Social implications - The Internet of Things in the virtual supply chain provides an opportunity to manage logistics systems and results in efficient online delivery with minimal cost. The information flow integrates all links and participants in the virtual supply chain. It enables each member to obtain the accurate information needed for logistics capability, reduces resource wastage, and improves customer satisfaction. Originality/value: One of the innovative aspects of this research is the use of IoT in the virtual supply chain for the integration and transparency of information in the supply chain, considering the importance of information in the virtual supply chain and examining the impact of IoT usage on closed-loop virtual supply costs and target functions. In addition to considering the physical flow costs of the closed-loop, including production costs, separation costs, repair, disposal, recycling, etc., in the cost objective function, virtual flow costs included IoT usage costs and information security costs. Energy consumption was also included in the objective function. Also, due to the virtualization of the supply chain and the significant role of information, optimization of information processing speed was considered in modeling the supply chain performance, which is another innovative aspect of research. [ABSTRACT FROM AUTHOR]

Packing is one of the well-known problems in operation research, especially in production planning. The main objective of studying the packing problem is to reduce the wastes of cutting through optimization of packing of pieces. Packing is a kind of NP-hard problem that the precise methods are not able to solve it. In this paper, in order to achieve an optimal packing of Non-guillotine cutting problems, the meta-heuristic emerging Imperialist Competitive Algorithm was used and the results were compared with the output of the genetic algorithm, which is the typical algorithm in solving packing problems. To achieve better solutions, the parameters of all meta-heuristics were calibrated with Taguchi experiment method. The efficacy of the proposed approach was tested on a set of instances, taken from the literature, and the results of the proposed algorithm were tested statistically by ANOVA. The results of this study showed that the meta-heuristic emerging Imperialist Competitive algorithm is more efficient and faster in solving packing problems. [ABSTRACT FROM AUTHOR]

Facility Layout Problem (FLP) is an important issue in plant design, which directly affects production costs as well as safety concerns. Hierarchical and integrated approaches are two main methods used for the formulation of FLP. In the hierarchical approach, FLP is solved after the completion of the process design and scheduling, while the integrated approach treats FLP simultaneously with other phases. This paper presents a new approach based on the candidate groups for interactive functions; incorporating the advantages of the previous approaches. In the new approach, the design phases prior to FLP results in a set of models introducing by the engineering team in advance. Next, the models are solved such that instead of individual designs, a set of suggested structures are generated. These structures are then fed into the FLP as input data and solved by mixed integer programming technique. Some characteristics of the models are: presence of the hub stations, different and variable dimensions for each station, possibility of rotation for the stations and incorporating safety distances. Finally, test problems are solved and results are discussed. It should be noted that if a candidate group entails a different production flow then a different optimum solution might be obtained. [ABSTRACT FROM AUTHOR]

Background and Objective: one of the steps in water treatment to protect microbial quality of water network is disinfection. Chlorine is one of disinfectants. It is necessary to maintain Free Residual Chlorine (FRC) between minimum and maximum throughout the distribution system in accordance to health standards. This study was aimed to optimize Chlorine dosage in water distribution networks using GANetXL model. Materials and Methods: In this paper for the first time using a add-in called GANetXL optimization that uses a genetic algorithm, the Chlorine injection was optimized in a reference network based on dynamic connection to EPANET2 hydraulic and qualitative analysis in Excel software. The objective function is formulated such that the squared difference between computed chlorine concentrations and the minimum residual concentration at all monitoring nodes at all times is minimum. The decision variables were the optimized injection dose at boosters' locations. Results: The injection rate was obtained (minimum: 0, average: 183.87, maximum: 776.57 and total 4412.84 mg/min per a day) at the station as the number of generation was reduced to 200. Critical nodes formed 20% of the total nodes of network. Conclusion: Based on the results, minimization of Chlorine whilst comply with FRC standard has both health and economical effects. The results can help the water distribution system management in terms of water quality (by maintaining FRC), health promotion and monetary [ABSTRACT FROM AUTHOR]

Basin irrigation is one of the conventional surface irrigation methods used to irrigate many crops all over the world. EDOBASIN, a new mathematical model for evaluation, design and optimal operation of basin irrigation has been introduced in this paper. In this model the linear combination of desired efficiencies are considered in an objective function, and based on decision variables that include discharge, length and width of basin and also restrictions of parameters, the optimal design is performed. This model is a simulation-optimization model in which the volume balance equations are used for hydrodynamic simulation and SA method are used for optimization steps. Optimization capabilities with various decision options and allowing weights to the indicators are good characteristics of this model. Comparison of advance time in this model with the well-known model SIRMOD for a real condition showed a good accuracy in the evaluation phase. In addition, the significant improvement of efficiencies after optimizing them simultaneously indicate that the model is an efficient tool for optimal design and use of this model for a data plot of an experimental field could enhance the efficiency of deep percolation ratio and application efficiency to 20% and keep constant the level of 100% for the efficiencies of water requirement and distribution uniformity [ABSTRACT FROM AUTHOR]

Here the advantages of employing a biorefinery approach in conjunction with optimization techniques were utilized to attain high overall process efficiency. Initially, an alkaline pH-shift process assisted by ultrasonic and its subsequent optimization were employed to maximize the extraction yield and whiteness index of muscle proteins isolated from lanternfish (B. pterotum). The optimal strategy was determined as follows: 6 mL g-1, pH1 (solubilization) 11.5, 310 W, and pH2 (precipitation) 5.8 with desirability of 0.84.Collagen hydrolysate was obtained from the connective tissue-containing sediment residue emerging during pH-shift process. The optimal isolated protein (OIP) was utilized to produce heat-set gels in combination with collagen hydrolysate. Breaking force and deformation of the OIP gel were measured at 123 (g) and 10.12 (mm) respectively. Collagen hydrolysate made breaking force (up to 2% w/w) and deformation (up to 10% w/w) improved and had positive effects on color characteristics (especially whiteness index) as well as water holding capacity. Hence, it can be concluded that the integration of a novel extraction technique such as ultrasonic with pH-shift process followed by optimization, as well as concurrent utilization of muscle and connective tissue proteins through a biorefinery approach; provides a significant advancement towards scaling up the extraction process. [ABSTRACT FROM AUTHOR]

In recent years, the need for L-asparaginase in different industries has increased. L-asparaginase obtained from microorganisms is cost-effective, has no harmful effects on the environment, and improves the quality of products. In the present study, L-asparaginase-producing microorganisms were isolated and optimized from different sources, and selected strain enzymes were produced. L-asparaginase-producing yeasts were randomly isolated and purified from different parts of Isfahan. Strains were screened for L-asparaginase production. Then, the superior yeast strain with the highest enzymatic activity was selected for optimization. Under suitable pH, temperature, time, carbon source, and nitrogen source, multi-factor optimization was performed using response-level statistical software to investigate the simultaneous effect of several factors on production and the highest enzyme activity. In the present study, 5S2 yeast isolate led to the formation of the highest halo of L-asparaginase. This strain was first introduced as the L-asparaginase-producing strain and was registered in the NCBI database under Diutina mesorugosa strain SBG-IAUF-2 with access number MZ901211. Yeast 5S2 with enzyme activity equivalent to 1722.8 u / ml was selected as the selected strain for optimization. The results of multivariate optimization of enzyme activity showed that at pH 7, a concentration of 2% glucose as carbon source, the attention of 10% L-asparagine, a temperature of 35°C, and a time of 120 hours, there is the highest enzyme production activity and curve RSM is located in the optimization area. In the present study, after recording 5S2 yeast isolate for the first time as an L-asparaginaseproducing strain in the NCBI database, extracellular L-asparaginase produced by the 5S2 yeast strain was introduced due to its high enzymatic activity as a potent strain in the production of Lasparaginase enzyme. [ABSTRACT FROM AUTHOR]

Objective: In today's competitive economy, the supply of a product in an optimal quantity, quality and minimum cost at the right time are the pillars of success in a business. A continually efficient supply chain also plays an important role in solidifying this success. This research aims to model an integrated supply chain network to achieve maximum profit while minimizing the overall response time.Methods: In view of the importance of supply chain management and logistics in recent times, the design and optimization of the supply chain network are extremely critical. This is mostly because, at each decision level, a well-optimized decision will result in a competitive advantage in the market. In this research, the said design and optimization is explained in two levels; a strategic level where a supply chain is designed, and a tactical level dedicated to operational planning of the supply chain. In this paper, a mathematical model has been formulated for these levels. To verify and validate the proposed model, the acquired data from a computer case manufacturing company are examined and the outcomes were highlighted.Results: This paper provides a tool in order to optimize the supply chain network. This tool can be useful for any manager or for those who are planning a supply chain from production or designing a product distribution network. Managers can also use this model to ensure the performance parameters of a particular supply chain.Conclusion: The results show that the proposed model can provide an effective and easy-to-follow method to achieve a well-established plan in an integrated supply chain

In the single-mode resource-constrained project scheduling problem, it is assumed that each activity has a specified known execution time and resource consumption can be done only in one way. In practice, there are many cases in which the make span can be reduced by providing additional resources activities. In this case, each activity can be done in one of the procedures, which is called the multi-mode resource-constrained project scheduling. In this paper, the problem includes determination of the basic schedule for the project activities which may be done in several models and the precedence relations are met, While the project make-span, cost and resource fluctuations are minimal. In this research project scheduling problem network will model using ED simulation software and the results of the simulation and a meta-heuristic algorithm has been compared. Finally, management strategies to optimize the scheduling, i.e such minimize total time, cost and resource leveling, will be offered. [ABSTRACT FROM AUTHOR]

Circular micro-plates are used in microelectromechanical systems (MEMS) such as micro-pumps and ultrasonic transducers due to their special geometry. One of the most important problems with electrostatic micro-actuators is pull-in instability which prevents large displacements. Stabilization in beyond pull-in displacements can be attained using an appropriate controller. This paper presents a position control problem for an electrostatic micro-actuator consisting of two circular clamped microplates to enhance the stroke and speed up the input commands. To consider the modeling error and geometric uncertainties, a fuzzy controller is applied. First, the equation of the plates vibration is derived using Lagrange equation with single mode assumption. Fuzzy rule-base is constructed according to static and dynamic simulations. Genetic algorithm is utilized for finding the optimum parameters of the controller to accelerate accomplishing the commands. Finally, the maximum voltage of the plates is fitted with a function using the optimization results for full range gap commands. The performance of the fuzzy controller along with this function is depicted applying step, multiple step and chirp commands. The obtained results show that the objective has been met well. [ABSTRACT FROM AUTHOR]

This paper presents a fast and efficient aerodynamic optimization method for megawatt class wind turbines. For this purpose WP_Baseline 1.5 MW wind turbine is used as a test case. Modified particle swarm optimization (PSO) algorithm is used in this study. PSO parameteric studies are conducted, to increase both efficiency and speed of optimization cycle. Since in aerodynamic optimization, it is very desirable to limit the number of the variables, in this study geometric 'class function/shape function' transformation technique (CST) is used for blade geometry parameterization and the appropriate order of shape function polynomial is proposed for S818, S825 and S826 airfoils. Improved Blade Element Momentum (IBEM) theory is implemented for wind turbine power output estimation, validated with experimental and Computational Fluid Dynamic (CFD) data of AOC wind turbine. The aerodynamic data needed for IBEM is provided by XFoil software. XFoil output data for pressure coefficient and wall shear stress which are validated against experimental and CFD data, are applied as the aerodynamic input data for IBEM method. The twist, the chord and 3 types of airfoil for all sections of the turbine blade are optimized using IBEM method. Optimization is performed with realistic constraints to produce feasible geometry. The performance of the final optimized geometry is simulated via 3D steady incompressible Navier-Stokes equations coupled with Transition SST Model CFD simulation to predict the performance improvement. The results show about 4 percent power enhancement for WP_Baseline wind turbine. [ABSTRACT FROM AUTHOR]

Heavy oil and tar sands resources comprise about 70 percent of the world's oil reserves and this reservoirs can offset the declining production from conventional reservoirs. Thermal enhanced oil recovery (EOR) methods are employed to exploit the huge reserves of heavy oil due to their high viscosity values. Thermal processes aim to increase its mobility in order to improve its production. Among these methods, the steam-assisted gravity drainage (SAGD) is one of the most efficient techniques. In this method, two horizontal wells are drilled and hot steam is injected from a well to move oil toward the other well. Optimization of operating parameters during this process is very important. The injection rate or pressure control of wells are the most common EOR methods. In this paper for the first time, in addition to the injection rate of the injector and production wells, the steam injection temperature is also optimized. It was shown that there is an optimum amount for the temperature of injected steam. In addition entropy generation analysis was performed for different cases. To simulate the process, a commercial software was used and optimization of operating parameters is performed using the pattern search algorithm. Entropy generation calculated based on the results of numerical simulations using a computational code has been written for this case. The results show that the maximum oil production corresponds with the minimum entropy generation number and thus the entropy number can be used as an appropriate objective function in order to enhance oil recovery. [ABSTRACT FROM AUTHOR]

The aim of this research is to optimize the combined system consisting of solar photovoltaic panels and a diesel generator as two independent decision variables and five responses or the optimization objective function, including system electricity consumption, system gas consumption, diesel fuel consumption, the amount of bio-pollutants reduction. The environment and the return on investment are dependent variables of this research; an optimization method is used to achieve the best possible design in Transis software, and the response level method is used to find the best combination of selected factors in the system. The main purpose of the response surface is to estimate and predict the effect of independent variables on the dependent variable after implementing the system in Transis software and optimizing by the response surface method. The results showed that the area of photovoltaic panels in the optimal state is equal to 11770 square meters and the optimal diesel generator power is equal to 984 kW. Also, in optimal conditions, the system has the best performance, and the combined utility is equal to 0.740, which indicates that the performance of the optimal system is close to the ideal state, i.e., one. In terms of energy consumption, the optimal system achieves a total electricity consumption of 1026860 kilowatts, a total gas consumption of 205182 cubic meters, a total diesel fuel consumption of 1338030 liters, an amount of environmental pollutants of 3693.23 kilograms, and an investment return period of 1.679 years. Also, strategy one, which includes the direct purchase of the total electricity demand from the grid and the direct sale of the total electricity produced by the system to the grid, seems to be economically more economical. The results of the simulation showed that the investigated combined system is a suitable solution to simultaneous energy production. It is electric and thermal, and it is capable of producing electric and thermal energy throughout the year. [ABSTRACT FROM AUTHOR]

Precise recognition of unknown variables for different types of solar cells is important in design, control, quality, cost estimation, and prediction of solar cell performance. Aggregation and development of a single solar cell to a set of cells (solar panels) is usually based on a single operating point on the current-voltage characteristic curve. In recent years, a new method to predict cell performance and cell screening by modeling the cell is represented using an equivalent electrical circuit in which each variable corresponds to a physical phenomenon in the solar cell. These analytical models can be represented by a five-variable, seven-variable, and recently nine-variable models. Due to the nonlinearities and inability of traditional methods in introducing and identifying the unknown variables of the system, recently intelligent algorithms have attracted considerable attentions in solving engineering and industrial problems. Neural network algorithm (NNA) is a metaheuristic optimization algorithm that is inspired by the function of the neural network of human brain. In this article, the optimum parameter identification technique of a silicon commercial solar cell is used for single diode, two diode, and three diode models. The obtained optimization results of this research are compared with other optimizers in the literature and the surrounding discussions are carried out. The attained numerical optimization results of the proposed NNA method have the highest accuracy among the other optimizers in the literature. Therefore, the NNA can be considered as a suitable optimizer in solar industry where high accuracy is needed. [ABSTRACT FROM AUTHOR]

The laser forming process is an emerging area of research and industry, primarily focused on materials like titanium, magnesium, steel, and their alloys. However, aluminum alloys have received less attention due to challenges related to surface reflection and low absorption coefficients. In this research, the effect of different process parameters on bending angle in the laser bending of Al 6061 sheets was investigated by experiments and finite element simulation. The parameters were optimized by Response Surface Method (RSM) to achieve the maximum bending angle. In addition, the reproducibility of the process, as well as the accuracy and validation of the simulation, were examined by conducting experiments that involved accurate measurement of the bending angle. The results revealed that the sheet thickness had the most significant effect on the bending angle. Specifically, with an increase of 1 mm in the sheet thickness, the bending angle decreased by 77%. Additionally, through process parameter optimization, the maximum bending angle achieved was 4.911 degrees. [ABSTRACT FROM AUTHOR]

Due to global warming and the increase in the population of the planet, maintaining and protecting available water resources is very important. One of the factors that has caused the reduction of water resources today is the increase in the rate of evaporation from the level of water stored in water resources. In this study, using the experimental results obtained from the work of Sina Bashir et al., the evaporation rate of the lake behind the Karkheh Dam has been modeled. This modeling has been done using the neural-adaptive fuzzy inference system. The approach of this system is considered the Mamdani approach in this modeling because this approach has a very good performance in modeling dynamic and natural processes such as evaporation. According to the laboratory results, in the presence of silica nanostructured material at 28, 32 and 40 degrees Celsius and wind conditions of 4 meters per second (similar to the prevailing wind around the Karkheh dam), the evaporation rate decreases by 33, 32 and 30%, respectively. In this modeling, the rate of reduction of evaporation is entered into the modeling as a coefficient according to the laboratory results, and as a result, the rate of evaporation obtained is the result of the decrease in the presence of nanostructured material. In this modeling, considering the creation of a nanostructured thermal insulation cover for only 20% of the lake surface, 2 million cubic meters of water can be saved and saved. [ABSTRACT FROM AUTHOR]

Taguchi method has been used since 1980 as an effective way to optimize the design process engineering tests. In this paper, optimal conditions of the mixed convection and entropy generation in a square cavity filled with Cu-water nanofluid is analyzed using Taguchi method. For this purpose an L16 (43) orthogonal Taguchi array is used. Discretization of the governing equations was achieved through a finite volume method and solved with SIMPLE algorithm. The effect of Richardson number (0.1-100 ), the volume fraction of copper nanoparticles (0-10%) and the wavelength of the wavy surface (0- 1) as effective parameters for analysis in four levels are considered. This analysis was performed for fixed Grashof number 1.4. The results show that the mean Nusselt number decreases by increase of the Richardson number, the volume fraction of nanoparticles and the wavelength of the wavy surface. It is found that the Flat plate (for wavy surface with the wavelength 0) and the volume fraction 0% in the Richardson number 0.1 is optimal design for heat transfer while the geometry with 0=5%, Φ = 100 and λ=0.25 is optimal design for entropy generation. Finally for maximum heat transfer and minimum entropy generation the geometry with O=0%, Φ =1 and λ=0.25 can be considered as an optimal design. [ABSTRACT FROM AUTHOR]

Production of double-stepped metal sheet parts is considered a complex and difficult task in industries. The crankcase is such a complex double-stepped part for the automobile industry and its production with traditional methods is associated with many problems. In this paper, the formability of this stepped part has been studied experimentally and by simulation using hydrodynamic deep-drawing with radial pressure. It is shown that the crankcase can be formed successfully in one step by the hydroforming process. Moreover, the effect of fluid pressure on the thickness distribution and die filling and the effect of geometric parameters such as punch corner radius and the height of the steps on the thinning, and also optimal shape design of the original blank were investigated. The study showed that choosing the correct forming pressure can improve formability and increase the amount of die filling. It is also illustrated that by increasing the punch corner radius, the maximum thinning is reduced and the thickness distribution is improved and, by increasing the height of the steps, thinning in the wall of the first step and the punch corner radius increase; by decreasing the height of the steps, thinning position will be shifted toward the second step. Also, by optimizing the original blank, it has been concluded that the optimization of the shape of original blank has a major impact on the material flow and will delay the sheet rupture. [ABSTRACT FROM AUTHOR]

In this paper, thermo-hydraulic behavior of a solar heater is numerically investigated and optimum geometry for the angled-rib turbulator which produces the maximum thermal enhancement factor is determined by Taguchi method. A general innovative geometry is introduced for the rib, by which changes in its geometrical parameters will lead to three convenient types of turbulators, namely triangular, rectangular and trapezoidal ribs, simultaneously. Applying Taguchi method leads to the optimum geometry parameters. A L16 [44] orthogonal Taguchi array is used. The aim of the Taguchi analysis is to maximize the thermal enhancement factor. The factors employed for the analysis are rib relative pitch, height, tip width and percentage of upstream-side perpendicularity. The analysis has been carried out for a flow of Re=10000 and a constant rib width. Due to the twofold effect of turbulators on thermo-hydraulic behavior, thermal enhancement factor concept is employed, which stands for both heat transfer rate and friction factor. Results show that rib pitch and height have the most significant effect on thermal enhancement factor, respectively. The optimum rib geometry is found to be a triangular rib which has P/H=2, e/H=0.2 and 100% perpendicularity. [ABSTRACT FROM AUTHOR]

In this paper, a single solid oxide fuel cell with internal reforming and parallel flow is modeled and optimized. The single fuel cell is a part of a stack of fuel cell system used for cogeneration of heat and work. The governing equations including the conservation equations of mass, momentum, energy and electrochemistry relations are solved by gPROMS software and validated using the data available in literature. The effect of quantities such as the rate of fuel consumption, amount of excess air and the percentage of pre reforming of fuel on the power and the efficiency of the fuel cell were evaluated. The results show that the percentage of the fuel pre reforming on the performance of fuel cell is more effective than other parameters and the power output and energy efficiency increase with it as well. Optimal working point of fuel cell with three objective functions (output power, the product of output voltage in voltage efficiency and output power in energy efficiency) has been obtained. The optimal current density is less than the current density of maximum power output. The optimal power output and energy efficiency taking minimum energy dissipation into account are 1.11W/cm² and 42%o respectively and by considering minimum exergy are 1.46 W/cm² and 24%, respectively. [ABSTRACT FROM AUTHOR]

Kinematic performance indices are used to have an evaluation of the potential efficiency of the robots. Some of these items are designing the optimal structure,trajectory planning, programming, and evaluation of behavior of the robot in positioning and orienting with desired rates or resolution. These indices will be used when the robot has even translational or rotational degrees of freedom (DoF). Due to dimensional incompatibility of the Jacobian entries in the complex DoF's robots with both types of DoF's, performance indices such as Jacobian condition index and associate singular values, are not applicable. In this paper, inhomogeneity of Jacobin matrix has been resolved by introducing a new Jacobian matrix which is called Cartesian Jacobian Matrix (CJM).Cartesian Jacobian Matrix maps Cartesian velocity vector of End-Effector (EE) to the joint space velocity vector. As a case study, the suggested method has been used for a Tricept parallel kinematic manipulator. Moreover, considering Local Conditioning Index (LCI) and associated singular values through the workspace have been led to structure optimization of the robot in order to have maximum positioning and orienting rates of EE through the maximum cuboid workspace. The optimization has been performed by Genetic algorithm via GA toolbox of MATLAB 2012 software. [ABSTRACT FROM AUTHOR]

In reverse engineering it may be required to perform multiple measurements due to the size and part complexity limitations of the physical equipment CMM/Optical Scanner and / or settings. To model the whole part it is required to bring different point sets obtained during different scans to a common coordinate system. Registration process for point clouds is to find the geometric transform between them in which all point clouds are transformed into a single absolute coordinate system. Theoretically, it is very straight forward to perform registration by finding the six components of transformation matrix (3 angles plus 3 displacements) and this can be mathematically determined if three non-linear points are known in both global and local coordinate systems. The process of registration is strongly affected by inaccurate data and may fail in the case of noisy data, hence other methods are usually sought to find the transformation matrix. This paper tries to solve the problem in practical applications. The Nelder-Mead method was employ for point clouds registration for the first time. The registration was also performed using Singular value decomposition and Genetic Algorithm methods. The three methods were compared in terms of convergence, accuracy and computation time. [ABSTRACT FROM AUTHOR]

Facility Layout Problem (FLP) is an important issue in plant design, which directly affects production costs as well as safety concerns. Hierarchical and integrated approaches are two main methods used for the formulation of FLP. In the hierarchical approach, FLP is solved after the completion of the process design and scheduling, while the integrated approach treats FLP simultaneously with other phases. This paper presents a new approach based on the candidate groups for interactive functions; incorporating the advantages of the previous approaches. In the new approach, the design phases prior to FLP results in a set of models introducing by the engineering team in advance. Next, the models are solved such that instead of individual designs, a set of suggested structures are generated. These structures are then fed into the FLP as input data and solved by mixed integer programming technique. Some characteristics of the models are: presence of the hub stations, different and variable dimensions for each station, possibility of rotation for the stations and incorporating safety distances. Finally, test problems are solved and results are discussed. It should be noted that if a candidate group entails a different production flow then a different optimum solution might be obtained. Introduction: Simultaneous optimization of facility layout with process design, automation and scheduling has been the subject of many research studies (Taghavi & Murat, 2011), (Realff et al., 1996), (Barbosa, 2007). The current research introduces a hybrid method for interactive phases of process and layout design. It starts with suggested cluster structures by process designers and attempts to decide among the choices while searching for optimum layout of facilities. In the rest of the paper, after a short description of group structures, a formulation of the MILP model is presented and the constraints, parameters and variables are briefly defined. Finally, 7 sample problems have been solved by exact methods. Then the developed model is solved such that instead of a single solution, a set of candidate groups are suggested. This set is later used as input to the layout problem. The innovation of this approach is a layout solution with the following characteristics: - Obtaining different flow process in terms of candidate groups from the initial phase. - The possibility of adding or removing the workstations in the candidate groups - The possibility of various dimensions in the group structures - MILP formulation for supporting the above characteristics In this approach, the solution space for layout problem only contains the process designs which are previously defined by in the plant design phase. This has many advantageous over the hierarchical layout methods such as less expenses and faster modelling and solution and less computational complexity. It has also the advantageous of an integrated approach in workstation layout considering different functions and interactions. Materials and Methods: Model description: For layout design in discrete production lines, an MILP model is developed. Facility layout in this research is confined to a two-dimensional (x,y) space and has the following characteristics: - One or more candidate groups can be defined, each consisting of at least two different connection structures, i.e. from-to charts with specified inner links and connecting structures (piping, conveyors or similar means of material flow). - Group centres are well defined if present. - Transportation costs and those costs related to cluster structures, e.g. extra equipment, semi-finished inventories, etc. are known in advance. - Facilities are rectangular with related fixed length and distances between facilities are rectilinear. - Facilities can rotate counter-clockwise by integer multiples of 90 degrees. - Total available area is limited and pre-specified. Objective function of the model is the sum of the investments on the physical connections, material flow costs and structural expenses of candidate groups. The constraints is related to the rotations status of the facilities, distances, available space, overlaps and safety concerns. Cost matrix is a cross product of flow matrix and transportation costs matrix. The final solution contains optimum plant layout, facilities orientations as well as optimum connections inside candidate groups. The model is solved by CPLEX which is mostly used for problem incorporating less than 15 workstations. Table 1 lists the solution time for 7 different problems. As can be seen in this table, the solution time for P7 is more than 40000 seconds with 6% gap. Therefore, the solution is used when limited number of workstations are aimed. For greater number of workstations, heuristic algorithms can be developed. Table 1. Test problems solved by CPLEX Time(sec) Opt Slution Candidate Group Quantity Station Quantity P. 461.5 451 2 11 P1 2.92 1165 1 6 P2 940.5 1217 2 9 P3 3943.8 1327.75 2 11 P4 25380.52 1641 2 13 P5 31803 1467.8 3 14 P6 40000 1850* 4 15 P7 References Barbosa-Povoa, A. P. (2007). A critical review on the design and retrofit of batch plants. Computers & Chemical Engineering, 31(7), 833–855. Realff, M. J., Shah, N., & Pantelides, C. C. (1996). Simultaneous design, layout and scheduling of pipeless batch plants. Computers & Chemical Engineering, 20(6), 869–883. Taghavi, A., & Murat, A. (2011). A heuristic procedure for the integrated facility layout design and flow assignment problem. Computers & Industrial Engineering, 61(1), 55–63.

Introduction: Among the photosynthetic microorganisms, cyanobacteria belonging to the genus Fischerella appear particularly promising for new polysaccharides producing strains. Extracellular polysaccharides (EPS) serve as a boundary to the immediate environment and play a protective role against antimicrobial agents. That iswhy cyanobacteria are so popular in the industry today as thickeners or floating agents, heavy metal absorbers, or in the case of sulfate polysaccharides as bioactive substances. This is an advantage over other polysaccharides extracted from plants or other macroalgae. There are many factors affecting cell growth and metabolite accumulation in cell cultures. However, there is insufficient knowledge about the factors affecting maximal EPS biosynthesis and antibacterial activity. In this regard, in this paper, the effect of some physical, environmental, and nutritional factors on the simultaneous production of exopolysaccharide by Fischerella sp. SH.A was investigated in order to select the best cultivation conditions for the industrial application of exopolysaccharides. Materials and methods: In this study, the cyanobacterium isolated from the fresh water of Golestan province was undertaken with the aim of investigating the key factors regulating EPS biosynthesis and antibacterial activity. After the morphological and molecular identification, the possible correlations between the type of stress and the amount of polysaccharides production were also investigated. Results: The obtained results indicated that EPS production and antibacterial activity were highly dependent on the culture conditions and light intensity. Furthermore, the production of exopolysaccharides in non-diastrophic conditions was highly correlated with the concentration of nitrate up to 500 mM and the illumination of 50 or 150 microeinsteins per second per square meter. Discussion and conclusion: Since cyanobacterial extracellular polysaccharides are interesting from the biotechnological point of view, considering some other parameters are of crucial importance for the maximization of EPS production in this genus. [ABSTRACT FROM AUTHOR]

Manufacturing products using powder compaction is one of the most widely used methods in the industry. In this paper, dynamic compaction of aluminum powder under low-velocity impact loading was investigated using a drop hammer testing machine along with the optimization of effective parameters in this process. In this series of experiments, the green density and green strength of compacted products were measured. The response surface methodology was used to study the influential parameters in the powder compaction process. In this method, the effects of independent parameters including the grain particle size, the hammer mass, and the standoff distance of the hammer on the green density and green strength were evaluated. In the current study, two separate analyses were performed for each output response and the obtained results were summarized in ANOVA tables. The results showed that the p-value for the model is less than 0.05, which means that the model is significant. The values of R2 for the green density and green strength are equal to 0.9956 and 0.9912, respectively. The results of the optimization section indicate that the optimum case, the maximum green density as well as green strength at the same time, occurs when the grain particle size, the hammer mass and the standoff distance of the hammer have the maximum values. The factors o standoff distance of hammer and grain particle size have the highest and least effect on responses. [ABSTRACT FROM AUTHOR]

In this paper, the modified bee optimization algorithm is proposed to appropriate switches placement regarding distributed generation to maximize the feeders' reliability of a typical distribution network in Mazandaran. In this regard, actual network information including number of consumers, average consumption, feeders failures, feeders access time, repair time, etc. are used to determine network reliability indices. The optimal location of switches is determined by different scenarios due to the presence of distributed generation and the importance of feeders in the studied network. Moreover, the effect of cut-out fuses and ring points on feeders is considered in determining the appropriate switches placement, which is usually not considered in the reliability analysis of the distribution network and switches placement. Different indices are considered to determine the importance of feeders and a questionnaire has been prepared to utilize the personnel experiences of the distribution company to weigh these indices. Comparing and analyzing the results shows the ability of the proposed method in determining the appropriate switches locations in a real network. [ABSTRACT FROM AUTHOR]

One of the main research areas is providing adaptive learning systems with new style for content delivery to users. Content delivery subsystem manages and selects the appropriate contents based on the user model. In order to realize the adaption and personalization, selecting approach should consider the learning capabilities and background knowledge of the learners. Therefore an optimization problem is defined and the system must optimize the difference between the learning capabilities and the learning style of the learner with the difficulty level and the presentation style of the delivered contents. This paper has focused on two aspects. In the problem modeling section, the previous defined model has been extended. The presented model has also considered the adaption between the learning style of the learner and the presentation style of the delivered contents. In problem solving section, this paper has applied two newer optimization algorithms, NBPSO and GSA, thus resulting in producing better answers (more appropriate and more adaptive selection of content). Also, according to the previous approaches, the problem has implemented and solved using PSO. The provided results of three algorithms have been evaluated using two well-known criteria: accuracy (aiming to measure optimality of the delivered answer) and stability (to ensure of getting answer in different performances). The results showed considerable progress (more personalized and adaptive contents). [ABSTRACT FROM AUTHOR]