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In this paper, a fractional-order SIRD mathematical model is presented with Caputo derivative for the transmission of COVID-19 between humans. We calculate the steady-states of the system and discuss their stability. We also discuss the existence and uniqueness of a non-negative solution for the system under study. Additionally, we obtain an approximate response by implementing the fractional Euler method. Next, we investigate the first and the second waves of the disease in Iran and Japan; then we give a prediction concerning the second wave of the disease. We display the numerical simulations for different derivative orders in order to evaluate the efficacy of the fractional concept on the system behaviors. We also calculate the optimal control of the system and display its numerical simulations. [ABSTRACT FROM AUTHOR]

Abstract: The paper outlines the application of a mathematical model of sustainability to an Environmental Impact Assessment (EIA) of two opencast iron ore mines in Iran. The model’s application to the EIA, which used the Folchi method, was undertaken for the purpose of indicating the potential level and nature of sustainability (if appropriate) of the two mines. The results indicated that both Chogart and Gol-e-Gohar iron ore mine were deemed to be potentially unsustainable. The results suggests the delicate balance and failure of achieving some form of sustainability in regards to mining in Iran, due to the impacts it has upon the local environment and community affected. The paper concludes as to the potential significance of the model’s application in the attainment of the goal of sustainable mining. [Copyright &y& Elsevier]

• Developing a multi-objective optimization model to redesign of GSBE-SNR considering incoterms. • Integrating social objectives into multi-objective model. • Greenhouse gas emission savings are maximized in the global sustainable bioenergy network. • Using GIS software to draw precise maps of the studied countries before and after redesigning. • Iran-o-Armenia case study with taking the sustainability conditions of each country into account. In today's industrial world, depletion of fossil resources and the adverse environmental effects of consuming fossil fuels have become one of the serious challenges in sustainable development of the societies. In recent years, substantial attention has been paid to using biomass for producing bioenergy in order to increase economic performance, reduce environmental effects, and providing new opportunities in different societies in pursuit of sustainable development. The complexities related to procurement, logistics, technology selection, raw material management (biomass), and product distribution planning are the main causes of using the optimization models to design the bioenergy supply chains. On the other hand, the globalization of economy and industry increased the significance of the subjects related to global logistics and the ecological and social objectives of the countries have undeniable influences on each other. Hence, in this paper, a mathematical model has been developed to redesign a global bioenergy supply network. This model has simultaneously studied the economic, environmental, and social objectives and the environmental coefficients of the model were calculated using SimaPro software. The multi-objective model was solved by augmented ɛ-constraint method and the decision makers were informed of the obtained Pareto solutions. Data taken from the study on Iran and Armenia was used to validate the model and the Geographic information system (GIS) software was used with the goal of studying the geographical map of each country more accurately. [ABSTRACT FROM AUTHOR]

Abstract: In recent years, BOT approach has provided an increasingly popular project financing to move toward infrastructure development in Asian countries such as Iran. There are many complexities in projects because of the variety of factors in project’s trend and also the dependence of project on mainly national factors. Due to these complexities and their long-term operating, the projects meet with uncertainty and numerous risks. In this paper, an attempt is made at identifying common risks in BOT projects. A novel hierarchical structure of risks is presented on the basis of the project-oriented point of view; next, some effective criteria for risk ranking in BOT projects are introduced. Then, the problem is defined in Fuzzy Multi Attribute Decision Making (FMADM) field. Therefore, Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) and Fuzzy Linear Programming Technique for Multidimensional Analysis of Preference (FLINMAP) methods are presented in order to rank high risks in BOT projects. In this study, these two methods are compared in four respects: separation among alternatives, fuzzy error in criteria’s weights, risk response planning, and numerousness of alternatives in proportion to criteria. The proposed model is used for identifying and assessing risks in Iran BOT power plant project. Finally, the rankings of high risks are determined according to their results at the end of this paper. [Copyright &y& Elsevier]

In the railway, the fright car classification takes place in the terminals. This classification always imposes a remarkable delay to the movement of the cars from origin to destination. To reduce car handling, it is necessary to group various shipments together with respect to their destination in the railroad blocking plan. In this paper, for the first time, a railroad blocking model with fuzzy travel costs is proposed. In the model, the preferred fuzzy paths are determined by a fuzzy shortest path method. Then, the fuzzy model is transformed into a classic railroad blocking model. The real-life blocking problems are very large with many variables and constraints, and modeling and solving them using commercially available software is very time consuming. Therefore, a solution method based on genetic algorithm is developed. To evaluate the performance of the solution method, several simulated problems are tested and the solutions of genetic algorithm are compared with those of the CPLEX software. The results reveal the algorithm has promising accuracy and computing speed for solving the railroad blocking problem. As a case study, the proposed model for creating the Iranian railway blocking plan is utilized. Iran railways can significantly diminish the some costs and save the time in delivering the loads. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, technical procedure for developing energy performance label for office buildings in Iran is presented. According to inappropriate energy consumption indexes of the office buildings in Iran, present research was conducted for this group of buildings. For this purpose, a building energy simulator software tool was developed, validated, and applied to simulate an exhaustive sample society of office buildings. A widespread field activity was conducted to gather the modeling data from 285 office buildings through all the 4 climatic zones in Iran. Moreover, Reference Buildings as the energy efficient buildings were defined and modeled in the software environment. Energy consumption indexes from modeling of sample society and Reference Buildings were applied to conclude the boundaries for grades A–G of the label. Finally, the label appearance was designed and authorized to be applied for both the existent and new buildings. The upper limit for grade A is determined as: 84, 75, 78, and 82 (kWh/Y/m2) and the upper limit of grade G (the failing point) is concluded as: 588, 525, 546, and 574 (kWh/Y/m2) for cold, mild, hot and dry, and hot and wet climatic zones, respectively. [Copyright &y& Elsevier]

Abstract: In some countries that energy prices are low, price elasticity of demand may not be significant. In this case, large increase or hike in energy prices may impact energy consumption in a way which cannot be drawn from historical data. This paper proposes an integrated adaptive fuzzy inference system (FIS) to forecast long-term natural gas (NG) consumption when prices experience large increase. To incorporate the impact of price hike into modeling, a novel procedure for construction and adaptation of Takagi–Sugeno fuzzy inference system (TS-FIS) is suggested. Linear regressions are used to construct a first order TS-FIS. Furthermore, adaptive network-based FIS (ANFIS) is used to forecast NG consumption in power plants. To cope with random uncertainty in small historical data sets, Monte Carlo simulation is utilized to generate training data for ANFIS. To show the applicability and usefulness of the proposed model, it is applied for forecasting of annual NG consumption in Iran where removing energy subsidies has resulted in a hike in NG prices. [Copyright &y& Elsevier]

Abstract: This paper treats with K-shortest viable path problem in a transportation network including multiple modes. The considered modes are metro, rapid-bus, private and walking. In this network, a viable path is one that the number of mode changes is limited and the traverse time and also the walking, metro and private usage are restricted subjected to some constraints. The traverse time is defined dependent on congestion level. Because constrained shortest path is NP-hard, we extend two metaheuristic algorithms namely GASA and BACS for the given problem. GASA is a Greedy Algorithm Simulated Annealing and BACS is a bi-direction searching Ant Colony System made by two colonies of ants. We evaluate the validation of these algorithms applying several multimodal random networks. In addition, their results are compared with CPLEX 12.1. We find that GASA is appropriate for small networks and BACS has better performance in median and large-scale networks. Our results on Tehran network also demonstrate that BACS provides better objective values than BACS ones because Tehran public transportation is sparse. [Copyright &y& Elsevier]

Abstract: Energy supply to Iran requires the substitution of an energy model based on fossil by one based on renewable energy sources. The building sector, about 40% of total annual energy consumption, has an important share in energy demand in Iran. Iran as a Middle Eastern country has recently begun to use renewable energies. Solar energy, because of its availability and large number of sunny days in this country, is mostly concentrated. In this paper vented thermal storage wall that is used for heating of Isfahan buildings, Central of IRAN, are studied. The heating loads for a residential building which has about 800m2 floor area at four floor are calculated. Then the vented thermal storage wall are designed and the amount of annual energy saving is calculated. It is shown that more than 60 percent of winter energy consumption will saved by using this system. [Copyright &y& Elsevier]

Abstract: Spatial outliers in wind erosion are associated with severe weather events so, high rate of erosion or sedimentation in relevance to their spatial vicinity is called outlier. The aim of this paper is to investigate the influence of outliers on variogram model and their parameters in east of Iran. For measuring of soil erosion and sedimentation, some pins were established in nested grids. Decreasing and increasing of pin height, show sedimentation and erosion, respectively. Spatial analysis illustrate that outliers locate in NW-SE direction roughly in the same direction of predominant wind. The maximum amount of outlier is 22cm soil sedimentation. [Copyright &y& Elsevier]

Abstract: There is an increasing trend in using heat pumps in air conditioning (heating/cooling) systems of residential and commercial buildings. The required power to drive the compressor of vapor compression heat pump cycles may be provided by either an electrical motor or an internal combustion engine. In this paper thermal modeling and economic analysis of gas engine heat pumps (GEHPs) are presented based on energy and mass balance equations as well as the gas engine operating parameters (such as thermal efficiency, fuel consumption and fuel mass flow rate) and heat pump operating parameters (such as evaporator and condenser capacity and compressor input power). Based on the modeling results and with estimating GEHP fuel consumption, the economic analysis of using gas engine heat pumps (in comparison with the electrical heat pumps) at various climate regions of Iran, for both residential and commercial (office) buildings, and for both cooling and heating modes, was performed. Appropriate cost functions for predicting GEHP capital investment were proposed. Three approaches including equivalent uniform annual cost (EUAC), the annual cost of energy consumption, and payback period were applied in the economic analysis. [Copyright &y& Elsevier]

Abstract: Longwall mining is a common mining method in Iran that is often affected by out-of-seam dilution (OSD). The field investigations performed in Tabas coal mine show that OSD often occurs due to roof falls in front of the face area before support setting and also removing some floor material. The increase in unsupported roof span above the shearer may cause difficulty in controlling the roof and consequently increases dilution of the run of mine (ROM) coal. The paper presents the results of a study on some dominant factors causing OSD in prop-free front of the face in longwall retreat mining method. A series of two-dimensional numerical models are developed and analyzed to examine the effects of mining depth, in-situ stress, unsupported roof geometry above the shearer as well as roof and floor strata quality and dip of coal seam on OSD. Two criteria were established, one considers the roof falls, defined as low stress level or plasticity zones under yield tension which roof material unravels and other is about removing floor, defined as depth of support and shearer sinking into the floor. The equivalent linear relaxation depth (ELRD) and depth of removing floor (DRF) concepts were used to quantify OSD. The methodology presented in this study is useful since it can be applied to develop mine-specific design tools for the prediction of OSD. [Copyright &y& Elsevier]

Abstract: The stochastic nature of the cyclic swelling behavior of mudrock and its dependence on a large number of interdependent parameters was modeled using Time Delay Neural Networks (TDNNs). This method has facilitated predicting cyclic swelling pressure with an acceptable level of accuracy where developing a general mathematical model is almost impossible. A number of total pressure cells between shotcrete and concrete walls of the powerhouse cavern at Masjed–Soleiman Hydroelectric Powerhouse Project, South of Iran, where mudrock outcrops, confirmed a cyclic swelling pressure on the lining since 1999. In several locations, small cracks are generated which has raised doubts about long term stability of the powerhouse structure. This necessitated a study for predicting future swelling pressure. Considering the complexity of the interdependent parameters in this problem, TDNNs proved to be a powerful tool. The results of this modeling are presented in this paper. [Copyright &y& Elsevier]