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It is vital to consider acoustic scattering when using geometrical acoustic simulation techniques, such as ray tracing. However, there are few methods for modelling scattering, and most rely on strong assumptions of uniformity on the distribution of scattered energy. In this paper, a model for directional scattering in ray tracers is presented. The model is based on an idealized model of a 1D scatterer, which is then used to extend the most commonly used scattering algorithm in ray tracers today. The developed algorithm is implemented in a ray tracer and tested to evaluate its performance compared to existing methods. It is found that the directional scattering algorithm can be used to replicate measured effects on room acoustic parameters caused by changes in the orientation of 1D scatterers. [ABSTRACT FROM AUTHOR]

The quality of collision detection algorithm directly affects the performance of the whole simulation system. To address the low efficiency and low accuracy in detecting the collisions of flexible cloths in virtual environments, this paper proposes an oriented bounding box (OBB) algorithm with a simplified model, tree structure for a root-node double bounding box, and continuous collision detection algorithm incorporating an OpenNN-based neural network optimization. First, for objects interacting with the cloths with more complex modeling, the model is simplified with a surface simplification algorithm based on the quadric error metrics, and the simplified model is used to construct an OBB. Second, a bounding box technique commonly used for collision detection is improved, and a root-node double bounding box algorithm is proposed to reduce the construction time for the bounding box. Finally, neural networks are used to optimize the continuous collision detection algorithm, as neural networks can efficiently process large amounts of data and remove disjoint collision pairs. An experiment shows that the construction of an OBB using the simplified model is almost identical to that of the original model, but the taken to construct the OBB is reduced by a factor of approximately 2.7. For the same cloth, it takes 5.51%–11.32% less time to run the root-node double bounding box algorithm than the traditional-hybrid bounding box algorithm. With an average removal rate nearly identical to that of the traditional filtering method, the elapsed time is reduced by 7%–11% by using the continuous collision detection algorithm based on an OpenNN neural network optimization. The simulation results are realistic and in line with the requirements for real-time cloth simulations. [ABSTRACT FROM AUTHOR]

This paper introduces a novel and innovative approach to simulating random variates from two distinct probability distributions, namely the neutrosophic uniform distribution and the neutrosophic Weibull distribution. The primary objective of this research is to present a cutting-edge methodology for generating random variates by leveraging the accept-reject simulation method, particularly in the context of managing and addressing uncertainty. In addition to introducing the simulation methodology, this work will also provide comprehensive algorithms tailored to these proposed methods. These algorithms are essential for implementing the simulation techniques and will be instrumental in their practical applications. Furthermore, this study aims to explore the relationship between the level of indeterminacy and the resulting random variates. By investigating how varying degrees of indeterminacy impact random variates, we gain valuable insights into the dynamics of these distributions under different uncertainty conditions. Preliminary results suggest that random variates exhibit a trend of decreasing as indeterminacy levels increase, shedding light on the intriguing interplay between indeterminacy and random variate generation. [ABSTRACT FROM AUTHOR]

A nonparametric procedure to estimate the conditional probability that a nonstationary geostatistical process exceeds a certain threshold value is proposed. The method consists of a bootstrap algorithm that combines conditional simulation techniques with nonparametric estimations of the trend and the variability. The nonparametric local linear estimator, considering a bandwidth matrix selected by a method that takes the spatial dependence into account, is used to estimate the trend. The variability is modeled estimating the conditional variance and the variogram from corrected residuals to avoid the biasses. The proposed method allows to obtain estimates of the conditional exceedance risk in non-observed spatial locations. The performance of the approach is analyzed by simulation and illustrated with the application to a real data set of precipitations in the USA.Supplementary materials accompanying this paper appear on-line. [ABSTRACT FROM AUTHOR]

Navigation and positioning is a new growth point of wireless services. And seamless positioning is the current development trend of navigation and positioning services. In view of the problems that dynamic handover cannot be performed during site movement, STA only selects the optimal AP according to the indication of received signal strength, and the handover delay is too long. This paper proposes a research on indoor and outdoor seamless positioning technology based on artificial intelligence and intelligent switching algorithm. The purpose is to study the influence of reducing the positioning data with too large error on the final positioning result. The method of this paper is to propose an intelligent switching algorithm and then discuss the research status and development direction of indoor positioning technology and outdoor positioning technology, respectively, and point out the switching methods between them. The role of these methods is to analyze the current situation of indoor and outdoor navigation technology, especially the development route of seamless positioning technology. It determines the strategy of integrating heterogeneous positioning systems to build a seamless positioning system to maximize the use of existing positioning system resources. This paper studies the design and implementation of the seamless positioning system through the simulation experiment of the intelligent switching algorithm and finally tests the system through the experimental vehicle. The online experiment results show that the system can achieve high positioning accuracy in indoor and outdoor environments, especially at its junction, and the positioning errors in all directions are within 0.2 m. [ABSTRACT FROM AUTHOR]

Quantifying the impact of a scholarly paper is of great significance, yet the effect of geographical distance of cited papers has not been explored. In this paper, we examine 30,596 papers published in Physical Review C, and identify the relationship between citations and geographical distances between author affiliations. Subsequently, a relative citation weight is applied to assess the impact of a scholarly paper. A higher-order weighted quantum PageRank algorithm is also developed to address the behavior of multiple step citation flow. Capturing the citation dynamics with higher-order dependencies reveals the actual impact of papers, including necessary self-citations that are sometimes excluded in prior studies. Quantum PageRank is utilized in this paper to help differentiating nodes whose PageRank values are identical. [ABSTRACT FROM AUTHOR]

To enhance the convergence performance of the affine projection sign subband adaptive filter (AP-SSAF) algorithm under highly correlated inputs, the novel AP-SSAF (NAP-SSAF) algorithm was proposed through fully utilizing the decorrelation characteristic of SAF, which obtains quicker convergence behavior than the AP-SSAF algorithm. However, under unknown system identification, the estimation accuracy of the NAP-SSAF algorithm may unavoidably decrease when the input of the adaptive filter is contaminated by noise. To alleviate this issue, in this paper, we propose the bias-compensated NAP-SSAF (BC-NAP-SSAF) algorithm to alleviate the estimated bias through employing unbiasedness criterion. Benefiting from the unbiased criterion, the proposed BC-NAP-SSAF algorithm achieves an asymptotically unbiased estimation. Moreover, the convergence bounds of the proposed BC-NAP-SSAF algorithm in the mean and mean-square senses are provided to ensure stability, which are obtained by resorting to Price's theorem along with some reasonable assumptions. The effectiveness of the derived theoretical convergence bounds is also corroborated. Finally, numerical simulations under system identification and acoustic echo cancellation applications demonstrate that the proposed BC-NAP-SSAF algorithm outperforms other algorithms in terms of estimation accuracy and tracking capability for noisy input under impulsive noise environment. [ABSTRACT FROM AUTHOR]

In this paper, the conceptualization of a control hardware architecture aimed to the implementation of integer- and fractional-order identification and control algorithms is presented. The proposed hardware architecture combines the capability of implementing PC-based control applications with embedded applications on microprocessor- and FPGA-based real-time targets. In this work, the potential advantages of this hardware architecture over other available alternatives are discussed from different perspectives. The experimental prototype that has been designed and built to evaluate the control hardware architecture proposed in this work is also described in detail. The thermal-based process taking place in the prototype is characterized for being reconfigurable and exhibiting fractional behaviour, which results in a suitable equipment for the purpose of fractional-order identification and control. In order to demonstrate the applicability and effectiveness of the proposed control hardware architecture, integer- and fractional-order identification and control algorithms implemented in various control technologies have been applied to the temperature-based experimental prototype described before. Detailed discussion about results and identification and control issues are provided. The main contribution of this work is to provide an efficient and practical hardware architecture for implementing fractional-order identification and control algorithms in different control technologies, helping to bridge the gap between real-time hardware solutions and software-based simulations of fractional-order systems and controllers. Finally, some conclusions and concluding remarks are offered in the industrial context. [ABSTRACT FROM AUTHOR]

The aim of this systematic review is to synthesize and analyze interactive collaborative work in the virtual economy of the metaverse. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout May 2022, with search terms including "metaverse interactive environment" + "virtual employee engagement and immersive workspaces," "wearable augmented reality technology," and "spatial data mining and simulation modeling algorithms." As we analyzed research published in 2022, only 158 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 30, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Distiller SR, ROBIS, and SRDR. [ABSTRACT FROM AUTHOR]

Throughout the world, the reliability-based approach to safety design of aircraft systems is quite mature and widely used. However, there are still shortcomings in the reliability-based aircraft system safety analysis method. It cannot dynamically analyze the accident evolution process and lack consideration of the complex situation of multifactor coupling. On the basis of the original aircraft system safety analysis method, this paper innovatively proposes a functional hazard analysis (FHA) method based on the analytic hierarchy process (AHP) and multifactor fuzzy comprehensive assessment (FCA). The purpose is to improve the objectivity and quantification of the FHA method in the safety design of aircraft systems. At the same time, in the terminal airworthiness verification, this paper proposes a repeatable and controllable virtual test flight verification method, which aims to reduce the cost and cycle of the terminal airworthiness verification and expand the coverage of the envelope verification. Finally, combined with the clauses in MIL-HDBK-516B, a case calculation is carried out to verify the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Digital image technology is penetrating into various fields of people's life, and it has been very mature and can effectively store and transmit data. Moreover, there are still various researches on image recognition, the core of this technology. The algorithm is mainly based on computer technology to obtain the target image for different scene categories, thus completely replacing the traditional classification form. Because of the limitations of traditional identification technology, there are some problems in the actual use. It does not depend on the prior knowledge requirements and can carry out complex feature space division. In this paper, an image recognition computer system is established by introducing an improved neural network algorithm. The algorithm is designed and tested, and the results show it has lower image recognition error rate. Subsequently, this research result is applied to the actual scene for testing. The test results show that the improved neural network optimization algorithm can make the extracted features more accurately expressed in the image processing, which is more effective than the traditional algorithm. [ABSTRACT FROM AUTHOR]

This paper does some research and discussion on the finite element analysis of a building structure, especially the computer graphics simulation method in building structure simulation. Moreover, with the support of BIM technology and computer finite element simulation technology, this paper constructs a building structure simulation system and analyzes the building structure simulation system based on actual conditions such as building structure and stress load. In addition, this paper improves the traditional structural analysis algorithm and designs experiments to evaluate the effect of the method proposed in this paper and analyze the data in the form of simulation to compare the validity of the test results. Finally, an experiment is designed to evaluate the data processing capability of the test system in this paper. The experimental analysis results verify the effectiveness of the method in this paper, which can provide relevant theoretical references for subsequent building structure simulation. [ABSTRACT FROM AUTHOR]

Integrated energy systems (IESs) can improve energy efficiency and reduce carbon emissions, essential for achieving peak carbon emissions and carbon neutrality. This study investigated the characteristics of the CHP model considering P2G and carbon capture systems, and a two-stage robust optimization model of the electricity-heat-gas-cold integrated energy system was developed. First, a CHP model considering the P2G and carbon capture system was established, and the electric-thermal coupling characteristics and P2G capacity constraints of the model were derived, which proved that the model could weaken the electric-thermal coupling characteristics, increase the electric power regulation range, and reduce carbon emissions. Subsequently, a two-stage robust optimal scheduling model of an IES was constructed, in which the objective function in the day-ahead scheduling stage was to minimize the start-up and shutdown costs. The objective function in the real-time scheduling stage was to minimize the equipment operating costs, carbon emission costs, wind curtailment, and solar curtailment costs, considering multiple uncertainties. Finally, after the objective function is linearized with a ψ-piecewise method, the model is solved based on the C&CG algorithm. Simulation results show that the proposed model can effectively absorb renewable energy and reduce the total cost of the system. [ABSTRACT FROM AUTHOR]

The trend of servitisation is increasingly affecting manufacturing enterprises. Traditional manufacturing enterprises cannot handle the related challenges of service innovation by themselves. Recently, manufacturing service ecosystem (MSE) has been proposed to support service innovation by facilitating collaboration. The construction and development of MSE need to handle a series of complexities, such as individual complexity, interaction complexity and ecological complexity. However, it is still very difficult to clearly identify the possible effect of various influence factors on MSE evolution, which is necessary analyse the complex dynamic interactive relationship among participants, so as to maintain the sustainable and healthy development of MSE. To change such a situation, this paper proposes a mapping-based computational experiment approach to analyse the evolution of MSE. This approach has three main parts, i.e. model construction of real world, model mapping of computational system and experiment evaluation of various factors of MSE evolution. By adopting the proposed approach, several case studies are conducted to investigate the possible effect of cooperation preference on the MSE evolution in various market environments. The results demonstrate that the proposed approach is effective. [ABSTRACT FROM AUTHOR]

This paper describes the development of a new reference controller framework for fixed and floating offshore wind turbines that greatly facilitates controller tuning and represents standard industry practices. The reference wind turbine controllers that are most commonly cited in the literature have been developed to work with specific reference wind turbines. Although these controllers have provided standard control functionalities, they are often not easy to modify for use on other turbines, so it has been challenging for researchers to run representative, fully dynamic simulations of other wind turbine designs. The Reference Open-Source Controller (ROSCO) has been developed to provide a modular reference wind turbine controller that represents industry standards and performs comparably to or better than existing reference controllers. The formulation of the ROSCO controller logic and tuning processes is presented in this paper. Control capabilities such as tip speed ratio tracking generator torque control, minimum pitch saturation, wind speed estimation, and a smoothing algorithm at near-rated operation are included to provide modern controller features. A floating offshore wind turbine feedback module is also included to facilitate growing research in the floating offshore arena. All of the standard controller implementations and control modules are automatically tuned such that a non-controls engineer or automated optimization routine can easily improve the controller performance. This article provides the framework and theoretical basis for the ROSCO controller modules and generic tuning processes. Simulations of the National Renewable Energy Laboratory (NREL) 5MWreference wind turbine and International Energy Agency 15MW reference turbine on the University of Maine semisubmersible platform are analyzed to demonstrate the controller's performance in both fixed and floating configurations, respectively. The simulation results demonstrate ROSCO's peak shaving routine to reduce maximum rotor thrusts by over 10% compared to the NREL 5MWreference wind turbine controller on the land-based turbine and to reduce maximum platform pitch angles by nearly 30% when using the platform feedback routine instead of a more traditional low-bandwidth controller. [ABSTRACT FROM AUTHOR]

A new method of the stochastic simulation algorithm (SSA), named the Hashing-Leaping method (HLM), for exact simulations of a class of Markov jump processes, is presented in this paper. The HLM has a conditional constant computational cost per event, which is independent of the number of exponential clocks in the Markov process. The main idea of the HLM is to repeatedly implement a hash-table-like bucket sort algorithm for all times of occurrence covered by a time step with length t. This paper serves as an introduction to this new SSA method. We introduce the method, demonstrate its implementation, analyze its properties, and compare its performance with three other commonly used SSA methods in four examples. Our performance tests and CPU operation statistics show certain advantages of the HLM for large scale problems. [ABSTRACT FROM AUTHOR]

This paper proposes the Marine Predators algorithm (MPA) linked with the reservoir simulation model and considering sedimentation, in order to improve reservoir rule curves. The release criteria of the hedging rule (HR) and standard operating policy (SOP) were investigated in this study. The results showed that the patterns of the new optimal rule curves from the MPA technique considering sedimentation and using HR were practically useful in this study, as were the patterns of the new optimal rule curves using SOP and those of the existing rule curves. Furthermore, the new optimal rule curves using HR criteria were able to alleviate both water scarcity and excess water situations better than both existing rule curves and optimal rule curves using SOP in terms of minimal average water shortage. The new curves reduced minimal average water shortage by 53% and excess release water deficit by 19%, whereas the frequency of water shortage term was increased by 3%. The results of rule curves efficiency from MPA were higher than GA and FPA techniques in terms of providing solutions. There was a significant difference in the efficiency of water problem alleviation between considering and not considering sedimentation. It can be concluded that the MPA linked with reservoir simulation using HR criteria and considering sedimentation can be used to find optimal rule curve solutions effectively. [ABSTRACT FROM AUTHOR]

The three-dimensional intelligent simulation of image art design is an important means of current image art design, which is affected by many factors. The traditional 3D intelligent simulation technology has certain defects, which leads to certain defects in 3D artwork. This paper builds a three-dimensional art design system based on dynamic image detection and genetic algorithm. The system simulates the actual dehazing method, and this paper proposes a dehazing algorithm suitable for this system and proposes to use bilateral filtering instead of median filtering. Because bilateral filtering has good edge retention, it can eliminate the blockiness caused by median filtering. Moreover, this paper uses FMM (Fast Marching Method) algorithm to repair the image. In order to verify the performance of the model, this paper conducts quantitative evaluation through system simulation and user satisfaction survey methods. The research results show that the method proposed in this paper has a certain effect and can be applied to practice. [ABSTRACT FROM AUTHOR]

By simulating the change process of the inventory of scientific papers according to a mathematical model of the publishing process, we find that publication delay would cause statistical error of the scientific paper output indicator, i.e. the quantity of published papers. Based on a simulation model and the average publication delay, we construct an optimization algorithm of the actual scientific paper output using a nonlinear least squares algorithm and validate its accuracy. To simplify the solution process, we propose an approximate algorithm of the actual scientific paper output indicator which would help science and technology managers practically deduce an approximation of the actual indicator. This has implications for strategy decision making and allocation of resources for science and technology research by policy makers. [ABSTRACT FROM AUTHOR]

This paper presents a simulation scheme for water distribution systems based on loop flows algorithms. Water networks are large scale and non-linear systems. The operational control of such system has posed difficulties in the past to the human operator that had to take the right decisions, such as pumping more water or closing a valve, within a short period of time and quite frequently in the absence of reliable measurement information such as pressure and flow values. Computer simulations of such systems have alleviated these difficulties. They allowed 'what-if' scenarios to be run by the human operator, giving him the possibility to know in advance the operational problems that can arise in the real-life networks due to malfunctions of valves or burst in pipes. However these computer simulations are generally relying on solving a system of equations and the nodal heads variables have been the most frequently used variables in these computer simulations. More recently the numerical algorithms based on loop corrective flows have started to receive more attention due to the reduce size of the matrixes involved in the numerical computations, which relies on the loop structure of the water network rather than the nodes. This can improve the numerical properties of the algorithms that model the real-time behaviour of the network. It is shown that such an efficient simulation scheme can be developed in the context of the loop flows algorithms and some problems that appear from doing this are successfully solved. [ABSTRACT FROM AUTHOR]

In this paper, a coupled interaction matrix is proposed to describe the interactions between line outages and the load shed at buses. The coupled interaction matrix is effectively estimated by the Expectation Maximization algorithm. A highly probabilistic coupled interaction model is further proposed to efficiently generate cascades with both line outages and the load shed based on the coupled interaction matrix and the distribution of initial outages. To mitigate cascading failures, critical links are identified based on the coupled interaction matrix by calculating a comprehensive severity index that considers the consequences of both line outages and the load shed. Simulation results on the IEEE 300-bus system verify the effectiveness of the proposed approach. The cascades generated from the coupled interaction model match the statistics of the original cascades very well. The identified critical links based on the comprehensive severity index enable a proper tradeoff between reducing line outages and reducing the load shed, leading to a better mitigation effect than only considering either line outages or the load shed. [ABSTRACT FROM AUTHOR]

In this paper, a symplectic algorithm is utilized to investigate constrained Hamiltonian systems. However, the symplectic method cannot be applied directly to the constrained Hamiltonian equations due to the non-canonicity. We firstly discuss the canonicalization method of the constrained Hamiltonian systems. The symplectic method is used to constrain Hamiltonian systems on the basis of the canonicalization, and then the numerical simulation of the system is carried out. An example is presented to illustrate the application of the results. By using the symplectic method of constrained Hamiltonian systems, one can solve the singular dynamic problems of nonconservative constrained mechanical systems, nonholonomic constrained mechanical systems as well as physical problems in quantum dynamics, and also available in many electromechanical coupled systems. [ABSTRACT FROM AUTHOR]

The reaction-diffusion master equation (RDME) is a model that allows for efficient on-lattice simulation of spatially resolved stochastic chemical kinetics. Compared to off-lattice hard-sphere simulations with Brownian dynamics or Green's function reaction dynamics, the RDME can be orders of magnitude faster if the lattice spacing can be chosen coarse enough. However, strongly diffusion-controlled reactions mandate a very fine mesh resolution for acceptable accuracy. It is common that reactions in the same model differ in their degree of diffusion control and therefore require different degrees of mesh resolution. This renders mesoscopic simulation inefficient for systems with multiscale properties. Mesoscopic-microscopic hybrid methods address this problem by resolving the most challenging reactions with a microscale, off-lattice simulation. However, all methods to date require manual partitioning of a system, effectively limiting their usefulness as "black-box" simulation codes. In this paper, we propose a hybrid simulation algorithm with automatic system partitioning based on indirect a priori error estimates.We demonstrate the accuracy and efficiency of the method on models of diffusion-controlled networks in 3D. [ABSTRACT FROM AUTHOR]

The service performance and life of the aero-engine are directly affected by the blade machining accuracy. In the end milling of the flexible blade, the profile tolerance would usually be violated by the deflection errors induced by excessive static deformations under the action of milling force. In order to predict the blade deflection errors, this paper presents an iterative algorithm considering the coupling relationship between milling force and elastic deformation based on the milling finite element simulation model. Then a novel multipoint rod-shaped auxiliary support technology is proposed to suppress the blade deflection errors. Taking the influence of layout parameters on blade deflection errors into account, the layout of auxiliary support is optimized by a genetic algorithm. To verify the effectiveness of the proposed method, an auxiliary support mechanism is designed and manufactured, and the deflection errors suppression experiment is implemented. The measured results show that the prediction error of blade maximum deflection is 17.6%. Furthermore, the blade average deflection error on two measured curves reduces from 45.88 μm to 24.39 μm with the support of the designed mechanism. Thus, this auxiliary support mechanism and layout optimization method can achieve higher accuracy in blade milling. [ABSTRACT FROM AUTHOR]

This paper presents a simulation scheme for water distribution systems based on loop flows algorithms. Water networks are large scale and non-linear systems. The operational control of such system has posed difficulties in the past to the human operator that had to take the right decisions, such as pumping more water or closing a valve, within a short period of time and quite frequently in the absence of reliable measurement information such as pressure and flow values. Computer simulations of such systems have alleviated these difficulties. They allowed 'what-if' scenarios to be run by the human operator, giving him the possibility to know in advance the operational problems that can arise in the real-life networks due to malfunctions of valves or burst in pipes. However these computer simulations are generally relying on solving a system of equations and the nodal heads variables have been the most frequently used variables in these computer simulations. More recently the numerical algorithms based on loop corrective flows have started to receive more attention due to the reduce size of the matrixes involved in the numerical computations, which relies on the loop structure of the water network rather than the nodes. This can improve the numerical properties of the algorithms that model the real-time behaviour of the network. It is shown that such an efficient simulation scheme can be developed in the context of the loop flows algorithms and some problems that appear from doing this are successfully solved. [ABSTRACT FROM AUTHOR]

In order to obtain the initial condition of the traffic accident and reconstruct the collision process of motorcycle and car in reverse, this paper proposes a multi-objective optimisation algorithm based on the combination of NSGA-II and surrogate model. Aiming at a collision accident between a car and motorcycle, a simulation model of the human-vehicle-road coupling system is established. First, select the optimisation variables, optimisation objectives and constraints, define the variable range, and through the Opt-LHD to sample the optimisation variables. Then, obtain and fit the sample data, and take the sample data as the initial conditions into the established motorcycle traffic accident simulation model. Next, obtain the simulation data of the optimisation variables, and establish the response surface model of the optimisation objectives in MATLAB. Finally, using NSGA-II algorithm, the individuals in the population are solved based on the response surface model in turn, the Pareto solution set is obtained, and a group of satisfactory solutions is taken back to the simulation model for verification of the optimisation model, so as to prove the correctness of the satisfactory solution, and then the initial conditions of the collision between the motorcycle and the car are obtained. [ABSTRACT FROM AUTHOR]

Product line testing is challenging due to the potentially huge number of configurations. Several approaches have tackled this challenge; most of them focused on reducing the number of tested products by selecting a representative subset. However, little attention has been paid to product line test optimization using test results, while tests are executed. This paper aims at optimizing the testing process of product lines by increasing the fault detection rate. To this end we propose a dynamic test prioritization approach. In contrast to traditional static test prioritization, our dynamic test prioritization leverages information of tests being executed in specific products. Processing this information, the initially prioritized tests are rearranged in order to find non-discovered faults. The proposed approach is valid for any kind of product lines, but we have adapted it to the context of configurable simulation models, an area where testing is especially time-consuming and optimization methods are paramount. The approach was empirically evaluated by employing two case studies. The results of this evaluation reveal that the proposed test prioritization approach improves both the static prioritization algorithm and the selected baseline technique. The results provide a basis for suggesting that the proposed dynamic test prioritization approach is appropriate to optimize the testing process of product lines. [ABSTRACT FROM AUTHOR]

This paper presents a simulation scheme for water distribution systems based on loop flows algorithms. Water networks are large scale and non-linear systems. The operational control of such system has posed difficulties in the past to the human operator that had to take the right decisions, such as pumping more water or closing a valve, within a short period of time and quite frequently in the absence of reliable measurement information such as pressure and flow values. Computer simulations of such systems have alleviated these difficulties. They allowed 'what-if' scenarios to be run by the human operator, giving him the possibility to know in advance the operational problems that can arise in the real-life networks due to malfunctions of valves or burst in pipes. However these computer simulations are generally relying on solving a system of equations and the nodal heads variables have been the most frequently used variables in these computer simulations. More recently the numerical algorithms based on loop corrective flows have started to receive more attention due to the reduce size of the matrixes involved in the numerical computations, which relies on the loop structure of the water network rather than the nodes. This can improve the numerical properties of the algorithms that model the real-time behaviour of the network. It is shown that such an efficient simulation scheme can be developed in the context of the loop flows algorithms and some problems that appear from doing this are successfully solved [ABSTRACT FROM AUTHOR]

We propose a fast method for the calculation of short-range interactions in molecular dynamics simulations. The so-called random-batch list method is a stochastic version of the classical neighbor-list method to avoid the construction of a full Verlet list, which introduces two-level neighbor lists for each particle such that the neighboring particles are located in core and shell regions, respectively. Direct interactions are performed in the core region. For the shell zone, we employ a random batch of interacting particles to reduce the number of interaction pairs. The error estimate of the algorithm is provided. We investigate the Lennard-Jones fluid by molecular dynamics simulations and show that this novel method can significantly accelerate the simulations with a factor of several fold without loss of the accuracy. This method is simple to implement, can be well combined with any linked cell methods to further speed up and scale up the simulation systems, and can be straightforwardly extended to other interactions, such as Ewald short-range part, and thus it is promising for large-scale molecular dynamics simulations. [ABSTRACT FROM AUTHOR]

The genomic scale metabolic networks of the microorganisms can be constructed based on their genome sequences, functional annotations, and biochemical reactions, reflecting almost all of the metabolic functions. Mathematical simulations of metabolic fluxes could make these functions be visualized, thereby providing guidance for rational engineering design and experimental operations. This review summarized recently developed flux simulation algorithms of microbial systems. For the single microbial systems, the optimal planning algorithm has low complexity because there is no interaction between microorganisms, and it can quickly simulate the stable metabolic states through the pseudo-steady hypothesis. Besides, the experimental conditions of single microbial systems are easier to reach or close to the optimal states of simulation, compared with polymicrobial systems. The polymicrobial culture systems could outcompete the single microbial systems as they could relieve metabolic pressure through metabolic division, resource exchange, and complex substrate coutilization. Besides, they provide varieties of intracellular production environments, which render them the potential to achieve efficient bioproduct synthesis. However, due to the quasi-steady hypothesis that restricts the simulation of the dynamic processes of microbial interactions and the algorithm complexity, there are few researches on simulation algorithms of polymicrobial metabolic fluxes. Therefore, this review also analyzed and combed the microbial interactions based on the commonly used hypothesis of maximizing growth rates, and studied the strategies of coupling interactions with optimal planning simulations for metabolism. Finally, this review provided new insights into the genomic scale metabolic flux simulations of polymicrobial systems. [ABSTRACT FROM AUTHOR]

In the light of the problems that exist in the current cutting algorithms: first, the number of tetrahedron elements increases as the cutting goes on, which leads to the decrease of the algorithm efficiency. Second, the topology structure is constantly updated during the cutting process, which leads to the stutter phenomenon in cutting display. In this paper, a cutting simulation implementation method based on transient display and delay adjustment strategy is proposed. Firstly, the feature points in the original path are screened by the feature criterion function, and the feature path is established. Then, by using the concept of minimum sum of square defined in this paper, the optimal path of the separation is found with the help of feature path points, and the pseudo effect of cutting is directly displayed by designing the transient display module. The delay adjustment is carried out in the cutting gap, and the topology separation in the delay adjustment is implemented by the node offset spread algorithm and the duplicate removal process with timeliness. Finally, the advantages and feasibility of the cutting algorithm proposed in this paper are verified by practical tests. The test results show that the transient display algorithm proposed in this paper takes about 20 ms. With the number of triangular patches increasing, the growth rate of transient display time remains low. The cutting simulation is implemented by using transient display and delay adjustment strategy, which greatly improves the simulation efficiency. [ABSTRACT FROM AUTHOR]

The stability of cable-net structures depends on the prestress of the system. Due to the large displacement and mutual effect of the cables, it is difficult to simulate the tensioning process and control the forming accuracy. The Backward Algorithm (BA) has been used to simulate the tensioning process. The traditional BA involves complicated and tedious matrix operations. In this paper, a new numerical method based on the Vector Form Intrinsic Finite Element (VFIFE) method is proposed for BA application. Moreover, the tensioning sequence of a complex cable-net structure is introduced. Subsequently, a new approach for BA application in the simulation of the tensioning process is presented, which combines the VFIFE approach and the notion of form-finding. Finally, a numerical example is simulated in detail and the results of different tensioning stages are analyzed to verify the feasibility of the proposed approach. This study provides a significant reference for improving the construction control and forming accuracy of complex prestressed cable-net structures. [ABSTRACT FROM AUTHOR]

Frequency offset estimation is an important module in the synchronisation of underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) systems. Different ways are used for carrier frequency offset (CFO) estimation such as maximum likelihood based on a cyclic prefix. In this paper, the Zadoff-Chu (ZC) sequences are used for OFDM synchronisation in underwater communications. The normalised carrier frequency offset can be estimated using the ZC cross-correlation between the primary synchronisation signal and the corresponding local signal, which causes large complexity. The ZC sequences have a time centre symmetric property, and thus the autocorrelation of the received primary synchronisation signal can be used for frequency offset estimation. In this paper, we propose a modified algorithm with low complexity for frequency offset estimation. Simulation results demonstrate that the proposed algorithm can estimate the frequency offset accurately with simple implementation in comparison with the traditional methods. [ABSTRACT FROM AUTHOR]

Purpose: The paper presents a method for the patterns simulation in the 3D virtual stitching and try-on system. Design/methodology/approach: First, the patterns are designed using the garment CAD software and stored in the DXF format. Second, the regular grid method is employed to mesh the patterns to be quadrangular, and the patterns triangular meshing can be obtained by connecting the diagonal of the quadrangular. Then a mass-spring model is established, and the forces analysis and the explicit Euler integration method are employed to accomplish the patterns simulation. The paper demonstrates the robustness of our simulation through two sets of experiments, including a lady's dress patterns meshing experiments and the experiments of the virtual stitching of the lady's dress. Findings: The patterns meshing algorithm can meet the requirements of the internal meshing and the boundary meshing, and it is very important to select an appropriate meshing density. The implementation of the virtual stitching of the lady's dress proves the effectiveness and usability of the simulation methods. Research limitations/implications: The lady's dress used in the experiments is a relatively simple fashion style, with only the front and back pattern. It is very worthy of further research on the effectiveness of the complex structure of clothing. Practical implications: The paper includes practical implications of the methods of the patterns meshing and the virtual stitching of the simple fashion styles. Originality/value: The simulation system is developed using VC++ 2015 with the help of the OpenGL functions library, which is proved as a simple, lower computation and robustness for the patterns simulation of the simple garments. [ABSTRACT FROM AUTHOR]

This paper presents a new control algorithm development approach for induction machines by using model-based design and a systematically built model architecture implemented in MATLAB/Simulink. The model architecture follows a three-layer structure, and it is developed according to the principle of functional decomposition and the needs of reusability and expandability. The first model layer consists of elementary model and algorithm components, the second contains a machine simulation model and a field-oriented control (FOC) algorithm, built upon the first layer's components, and the third realises the executable models by connecting the models and algorithms defined in the second layer. Furthermore, rapid control prototyping (RCP) is discussed as an experimental validation method, and an experimental setup with RCP is also introduced. The application of the presented methods is demonstrated by simulations as well as by experiments, and by using a control algorithm based on FOC as an example. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) load and its charging methodologies play a significant role in distribution system planning. The inaccurate modelling of EV load may overload the distribution system components, increase in Network Power Loss (NPL) and Maximum Voltage Deviation (MVD). The Constant Power (CP) load model is more popularly used to model both the conventional and EV loads in the distribution system. But the CP load modelling cannot provide accurate information of EV charging process. In this paper, the EV load is modelled as constant Impedance-constant Current-constant Power (ZIP), Exponential, Constant Current and Constant Power load models and the conventional loads are modelled as Residential–Industrial–Commercial (RIC) and Constant Power load models. With these EV and conventional load models, the optimal site and size of Fast Charging Stations (FCSs) in the distribution system have been determined. Further, to analyse the impact of load of FCSs in the distribution system, the distribution indices are calculated. The multi-objective hybrid SFL-TLBO algorithm has been used to determine the optimal location and size FCSs with the minimization of NPL, MVD and EV User Cost (EVUC) in the distribution system. To consider the uncertainty of the initial SOC of EVs, the Monte-Carlo simulation technique has been used. These studies have been carried out on 38-bus distribution system and substantiate results are presented. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to develop a meshfree algorithm based on local radial basis functions (RBFs) combined with the differential quadrature (DQ) method to provide numerical approximations of the solutions of time-dependent, nonlinear and spatially one-dimensional reaction-diffusion systems and to capture their evolving patterns. The combination of local RBFs and the DQ method is applied to discretize the system in space; implicit multistep methods are subsequently used to discretize in time. Design/methodology/approach: In a method of lines setting, a meshless method for their discretization in space is proposed. This discretization is based on a DQ approach, and RBFs are used as test functions. A local approach is followed where only selected RBFs feature in the computation of a particular DQ weight. Findings: The proposed method is applied on four reaction-diffusion models: Huxley's equation, a linear reaction-diffusion system, the Gray–Scott model and the two-dimensional Brusselator model. The method captured the various patterns of the models similar to available in literature. The method shows second order of convergence in space variables and works reliably and efficiently for the problems. Originality/value: The originality lies in the following facts: A meshless method is proposed for reaction-diffusion models based on local RBFs; the proposed scheme is able to capture patterns of the models for big time T; the scheme has second order of convergence in both time and space variables and Nuemann boundary conditions are easy to implement in this scheme. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) load and its charging methodologies play a significant role in distribution system planning. The inaccurate modelling of EV load may overload the distribution system components, increase in Network Power Loss (NPL) and Maximum Voltage Deviation (MVD). The Constant Power (CP) load model is more popularly used to model both the conventional and EV loads in the distribution system. But the CP load modelling cannot provide accurate information of EV charging process. In this paper, the EV load is modelled as constant Impedance-constant Current-constant Power (ZIP), Exponential, Constant Current and Constant Power load models and the conventional loads are modelled as Residential–Industrial–Commercial (RIC) and Constant Power load models. With these EV and conventional load models, the optimal site and size of Fast Charging Stations (FCSs) in the distribution system have been determined. Further, to analyse the impact of load of FCSs in the distribution system, the distribution indices are calculated. The multi-objective hybrid SFL-TLBO algorithm has been used to determine the optimal location and size FCSs with the minimization of NPL, MVD and EV User Cost (EVUC) in the distribution system. To consider the uncertainty of the initial SOC of EVs, the Monte-Carlo simulation technique has been used. These studies have been carried out on 38-bus distribution system and substantiate results are presented. [ABSTRACT FROM AUTHOR]

This paper focuses on the problem of maximizing the minimum power gain in a wide main lobe for an array antenna. To obtain the desired power gain pattern, current literatures solve the problem known as shaped beam pattern synthesis (SBPS) by setting the beam pattern expression as the cost function. The power gain in a certain direction of the array antenna is comprehensively decided by the array radiated power density and the total radiated power. Both these two parameters are affected by the selection of array elements’ weights. However, the SBPS-based methods do not take the total radiated power into account. Therefore, the SBPS-based methods cannot obtain the power gain pattern directly, and the optimal power gain pattern, consequently, cannot be guaranteed. To overcome this deficiency, this paper maximizes the minimum power gain in the desired wide main lobe by directly setting the power gain expression as the cost function. Aiming at optimizing the cost function, this paper first sets up a power gain optimization problem which has concave form. Termed this optimization problem as the power gain pattern synthesis (PGPS) problem. The concave PGPS problem is then converted to a series of convex subproblems and an iterative algorithm is proposed to solve it efficiently. Solution to the PGPS problem is proven to be able to achieve higher minimum power gain in a desired wide main lobe than the results from the SBPS-based algorithms. Simulations are carried out with both linear array antenna and planar array antenna. Comparisons with the existed SBPS-based algorithms validate the effectiveness and advantages of the proposed PGPS-based algorithm. In addition, further improvement on suppressing the sidelobe level for the PGPS problem is discussed. [ABSTRACT FROM AUTHOR]

The abnormal rise in contact temperature in switchgear may lead to overheating or even explosion. It is necessary to monitor the rise in real contact temperature to ensure the safety and stability of switchgear. The accurate measurement of real contact temperature is still a problem, and the continuous state of switchgear cannot be assessed accurately by the temperature monitor. In this paper, a particular installation scheme of temperature sensor is put forward and a calculation algorithm for temperature rise of tulip contacts by the measured temperature of bus bar in real time based on artificial neural network (ANN) is established. An electromagnetic-thermal-fluid coupled simulation model for 10-kV/4000-A switchgears was built, and the thermal characteristic was studied taking the influential factors such as load current, ambient temperature, and contact resistance into consideration. The effectiveness of simulation model is discussed by the comparison to temperature rise experiment. Then, an ANN with three layers of structure is established to calculate the temperature of tulip contacts. The sensitivity and accuracy of network are calculated and verified. The results of this paper may provide a novel method for the monitor of switchgear temperature and assess continuous condition of high-current switchgear. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel hybrid method to simulate discrete stochastic reaction-diffusion models arising in biochemical signaling pathways. We study moderately stiff systems, for which we can partition each reaction or diffusion channel into either a slow or fast subset, based on its propensity. Numerical approaches missing this distinction are often limited with respect to computational run time or approximation quality. We design an approximate scheme that remedies these pitfalls by using a new blending strategy of the well-established inhomogeneous stochastic simulation algorithm and the tau-leaping simulation method. The advantages of our hybrid simulation algorithm are demonstrated on three benchmarking systems, with special focus on approximation accuracy and efficiency. [ABSTRACT FROM AUTHOR]

An analytical solution of the Boussinesq equations for the motion of a viscous stably stratified fluid driven by a surface thermal forcing with large horizontal gradients (step changes) is obtained. The solution can be used to verify that computer codes for Boussinesq fluid system simulations are free of errors in formulation of wall boundary conditions, and to evaluate the relative performances of competing numerical algorithms. Because the solution pertains to flows driven by a surface thermal forcing, one of its main applications may be for testing the no-slip, impermeable wall boundary conditions for the pressure Poisson equation. Examples of such tests are presented. [ABSTRACT FROM AUTHOR]

Studies on load flow in electrical distribution system have always been an area of interest for research from the previous few years. Various approaches and techniques are brought into light for load flow studies within the system and simulation tools are being used to work out on varied characteristics of system. This study concentrates on these approaches and the improvements made to the already existing techniques considering time and the algorithms complexity. Also, the paper explains the network reconfiguration (NR) techniques considered in reconfiguring radial distribution network (RDN) to reduce power losses in distribution system and delivers an approach to how various network reconfiguration techniques support loss reduction and improvement of reliability in the electrical distribution network. [ABSTRACT FROM AUTHOR]

This article presents a distributed model predictive control algorithm including fuzzy negotiation among subsystems and a dynamic setpoint generation method, applied to a simulated sewerage network. The methodology considers WWTP as an additional objective of control. To improve the performance of a DMPC using a hydraulic model for prediction, a more detailed model has been considered including suspended solids concentration (TSS). The results obtained with the proposed methodology have been validated on a benchmark simulation model for sewer systems developed to test and compare methodologies, showing good performance. [ABSTRACT FROM AUTHOR]

With its unique array arrangement, the detection system radar has both space diversity gain and waveform diversity gain, and is currently recognized as a stealth target buster. The detection system radar is applied to a high-speed moving platform. Using distributed cooperative detection technology, non-coherent fusion detection based on signals can further improve the detection of stealthy targets. Aiming at the high-speed motion radar signal processing algorithm, this paper mainly studies the following three aspects: the first content is the analysis of the waveform characteristics: the basic principles and characteristics of the radar are explained; then the three orthogonal waveforms commonly used in the radar are introduced, including Stepwise frequency division chirp signal, quadrature phase coded signal and mixed-signal; the second content detects radar targets and analyzes the correlation between the scattering coefficients of different radar channels; for scenarios where the scattering coefficients between the channels are non-coherent Introduced two kinds of non-coherent fusion detectors based on generalized likelihood ratio algorithm: centralized detector and double threshold detector; the third content radar multi-target pairing is aimed at the problem of radar multi-target pairing with large inertial navigation error. A multi-target pairing algorithm that uses target delay information and combines the radar's multi-channel information redundancy characteristics is presented. An expression for judging the correctness of target pairing is derived, and the target pairing steps are given. The relationship between the amount of algorithm operation and the number of radar stations and the number of targets is analyzed in conclusion. [ABSTRACT FROM AUTHOR]

Recent increase of spatial resolution for satellite instruments has it made feasible to study distributions of trace gas column densities on a regional scale. For this application a new gridding algorithm was developed to map measurements from the instrument's frame of reference (Level 2) onto a longitude-latitude grid (Level 3). The algorithm is designed for the Ozone Monitoring Instrument (OMI) and can be employed easily to similar instruments, for example, the upcoming TROPOspheric Monitoring Instrument (TROPOMI). Trace gas distributions are reconstructed by a continuous parabolic spline surface. The algorithm explicitly considers the spatially varying sensitivity of the sensor resulting from the instrument function. At the swath edge, the inverse problem of computing the spline coefficients is very sensitive to measurement errors and is regularised by a second-order difference matrix. Since this regularisation corresponds to the penalty term for smoothing splines, it similarly attenuates the effect of measurement noise over the entire swath width. Monte Carlo simulations are conducted to study the performance of the algorithm for different distributions of trace gas column densities. The optimal weight of the penalty term is found to be proportional to the measurement uncertainty and the width of the instrument function. A comparison with an established gridding algorithm shows improved performance for small to moderate measurement errors due to better parametrization of the distribution. The resulting maps are smoother and extreme values are more accurately reconstructed. The performance improvement is further illustrated with high-resolution distributions obtained from a regional chemistry model. The new algorithm is applied to tropospheric NO2 column densities measured by OMI. Examples of regional NO2 maps are shown for densely populated areas in China, Europe and the United States of America. This work demonstrates that the newly developed gridding algorithm improves regional trace gas maps; its application could be very helpful for the study of satellite-derived trace gas distributions. [ABSTRACT FROM AUTHOR]

The arrangement of atoms in the microstructures of alloys plays a key role in defining their physical and functional properties. These microstructures are studied to detect deviations from the expected homogeneous distribution using frequency distribution tests and cluster detection algorithms on reconstructions obtained from atom probe microscopy. However, it is challenging to evaluate and validate the performance of these algorithms using the reconstructed data because of the experimental limitations of the atom probe data itself. Low detector efficiency and reconstructional artifacts may lead to loss of existing clusters, or introduce heterogeneities that do not reflect the original arrangement. Additionally, retrieving atom probe data is a time and cost-prohibitive process. These challenges call for the use of simulated datasets with known concentrations and distributions to evaluate algorithms that analyze distributions or detect clusters. In this paper, we extend the existing methodology to simulate the creation of solute clusters in very dilute solutions for any solution. We propose methods to create denser and wider clusters in any solution irrespective of the concentration. Three novel solute cluster simulation techniques incremental, hierarchical and gravitational clustering are presented and compared in this paper. The simulated datasets can be used to validate and compare the performance of frequency distribution or cluster discovery algorithms. We compare the cluster analysis results obtained from the single linkage algorithm and DBSCAN to highlight the utility of these datasets. [ABSTRACT FROM AUTHOR]

This study proposes an improved interferogram filtering method with mathematical morphology. The algorithm firstly converts the interferogram in cosine and sine parts to preserve the continuity of phases, then adopts the improved adaptive line structure elements to run reconstruction process on two parts based on grey scale morphological opening and closing operations. In addition combine the two filtered parts to get the wrapped phases. Simulated and real-data experiments show that the proposed algorithm is more robust in filtering compared with other algorithms referred in this study. [ABSTRACT FROM AUTHOR]