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In this paper, we present a hybrid intelligent simulation system for optimization of mesh routers in Wireless Mesh Networks (WMNs) called WMN-PSOHCDGA. We implemented six mesh router replacement methods: CM, RIWM, LDIWM, LDVM, RDVM and FC-RDVM and consider Two Islands distribution of mesh clients. We carry out a comparison study of these router replacement methods for small and middle scale WMNs. We assessed the performance by computer simulations. The simulation results show that six methods have a good performance for connectivity and coverage metrics, for both small and middle scale WMNs. However, they have different behavior for load balancing. For small scale WMNs, the load balancing of LDIWM, RIWM and FC-RDVM is better than CM, LDVM and RDVM. While, comparing LDIWM, RIWM and FC-RDVM, the LDIWM has better load balancing. We found that the load balancing for small scale WMNs is not good, because there is a concentration of mesh routers in some areas. For middle scale WMNs, the CM, LDIWM, LDVM and RDVM have not a good load balancing. While, the RIWM and FC-RDVM have better performance. Comparing RIWM and FC-RDVM, we found that the load balancing of FC-RDVM is better than RIWM. [ABSTRACT FROM AUTHOR]

The present paper deals with the photovoltaic performance‐based numerical evaluation of copper–zinc–tin–sulfur (CZTS) solar cells embedded with CZTSe as a back surface field (BSF) layer. CZTS has been considered a leading candidate for the fabrication of solar devices owing to its availability and absence of toxicity. Adding a BSF layer to a solar device is a novel way to boost efficiency. It reduces the recombination of the carriers at the back surface, thus increasing the overall current output of the solar cells. SCAPS 1D simulator is used to study the impact of several parameters on electrical properties like temperature, the thickness of the CZTS layer, acceptor doping concentration, and the impact of series and shunt resistances. Considering the optimized parameters in each layer of the solar cells, this work delivers 24.7% efficiency with the BSF layer, which is 8% more than that without the BSF layer. The results of this modeling will facilitate researchers to fabricate a highly efficient CZTS solar cell. [ABSTRACT FROM AUTHOR]

This paper presents a novel 2D analytical model for investigating the influence of the ferroelectric dielectric on the performance of pocket doped double gate tunnel FET. It takes into account the effect of the gate and drain voltages, the thickness of the gate insulator, the capacitance of the gate insulator, and source and drain depletions. The surface potential thus carefully obtained is utilized for calculating lateral electric field, drain current, gate‐to‐drain capacitance, and transconductance. As a result, it has been demonstrated that the result of our model with several device structures matches very well with the data obtained through the technology computer‐aided design (TCAD) simulation. In addition, it has also been shown that the proposed tunnel field‐effect transistors (TFET) structure, which incorporates the ferroelectric dielectric and SiGe/Si heterostructure, has the best ON current, ON/OFF ratio, transconductance, and cut‐off frequency (fT). [ABSTRACT FROM AUTHOR]

In this paper, we consider a mathematical model which describes the equilibrium of two elastic rods attached to a nonlinear spring. We derive the variational formulation of the model which is in the form of an elliptic quasivariational inequality for the displacement field. We prove the unique weak solvability of the problem, then we state and prove some convergence results, for which we provide the corresponding mechanical interpretation. Next, we turn to the numerical approximation of the problem based on a finite element scheme. We use a relaxation method to solve the discrete problems that we implement on the computer. Using this method, we provide numerical simulations which validate our convergence results. [ABSTRACT FROM AUTHOR]

This study examined whether pilots operating a flight simulator completed digital or paper flight checklists more accurately after receiving postflight graphic and verbal feedback. The dependent variable was the number of checklist items completed correctly per flight. Following treatment, checklist completion with paper and digital checklists increased from 38% and 39%, respectively, to nearly 100% and remained close to 100% after feedback and praise for improvement were withdrawn. Performance was maintained at or near 100% during follow-up probes. [ABSTRACT FROM AUTHOR]

This article explores the role of the so-called in silico experiments used in molecular biology. It is based on the analysis of some papers that present scientific applications which rely on in silico experiments. By means of this study I found two basic ways of viewing them. According to the first view, the in silico experiment is a computer program that realizes some specific operations: it constitutes some particular experimental conditions, which allow us to investigate biological phenomena, and which complement those present in in vivo and in vitro experiments. According to the second view, in silico experimentation has a different meaning, which corresponds more closely to the meaning of "simulation": its identity is linked to that of the "model" used to construct such simulation. The authors of the analysed papers never express an intention to standardize a model, so its meaning remains contingent, and cannot be turned into a technical object. [ABSTRACT FROM AUTHOR]

This paper presents a coherent approach to evaluate the roll damping derivatives for the standard Basic Finner Model. The study compares and analyses the results obtained through a range of techniques, including experimental testing, numerical simulations and semi-empirical models. The study aims to evaluate the reliability and accuracy of these methods and to identify the factors that contribute to their sensitivity. The paper concludes by summarizing the findings of the study and discussing the implications of the results for the design and operation of rockets. The experimental and numerical analysis used in this study provides a robust and comprehensive evaluation of the roll damping coefficient. [ABSTRACT FROM AUTHOR]

In this article, we review definition, origin, terminology, fundamental properties, design concepts and procedures, basic applications, modeling, and numerical simulation of metamaterials. It is shown that metamaterial origin can be easily understood by placing metamaterials in the more general context of artificial electromagnetic materials and of the efforts performed by the scientific community working in complex materials to mimic and overcome the properties of natural materials. The basic properties of some classes of metamaterials as well as the related limitations are reviewed and discussed. A new application-oriented definition of metamaterials is given in terms of a functionalizing layer placed in between the traditional concepts of materials and devices. Metamaterial applications and the design steps of metamaterial-based and metamaterial-inspired components are also discussed, with particular emphasis on the numerical simulation of ideal metamaterials through available solvers. In this frame, finite-difference time-domain (FDTD) modeling and simulation of the electromagnetic properties of metamaterials are deeply discussed. The recently introduced virtual MTM-FDTD tool is used to simulate the interaction between the electromagnetic field and metamaterials and show some metamaterial effects, such as beam focusing, existence of negative refractive angle, and so forth, through various examples in different scenarios. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE 22:422-438, 2012. [ABSTRACT FROM AUTHOR]

This article presents a discussion on a study by Bradley Jones and Rachel T. Johnson on the use of Gaussian Process model in computer simulation research. The authors believe that the uncertainty intervals on unsampled points generated by using a plug-in approach from maximum likelihood estimates may be too short. Their own experiences confirm that computer models are widely used in many areas of science and engineering, and the need to understand the performance of such models is critical.

This research paper investigates the numerical solutions of the predator–prey model through five recent numerical schemes (Adomian decomposition, El Kalla, cubic B‐spline, extended cubic B‐spline, exponential cubic B‐spline). We investigate the obtained computational solutions via the modified Khater methods. This model is considered as a well‐known bimathematical model to describe the prototype of an excitable system. The obtained solitary solutions emerge the localized wave packet as a persistent and dominant feature. The accuracy of the obtained numerical solutions is investigated by calculating the absolute error between the exact and numerical solutions. Many sketches are given to illustrate the matching between the exact and numerical solutions. [ABSTRACT FROM AUTHOR]

This paper presents the development of a method for calculating the horizontal contact forces between two bodies in a real-time ship manoeuvring simulator. The method was implemented in the simulator of the University of São Paulo, whose computing core is named "Dyna". The model proposed calculates restoration and friction forces between bodies and has a Momentum-Impulse based criterion to reduce numerical issues when the simulation numerical integration has large time-steps. The model was empirically evaluated at the simulator by deck officers, in real-time simulations with pilots and tugmasters. We also ran simulations of that model to compare its performance under different integration time-steps lengths. [ABSTRACT FROM AUTHOR]

Rectangular concrete-filled steel tubular (RCFST) columns can be designed to have unequal wall thickness to maximize their resistance to combined axial and uniaxial bending loads. However, there is very little published research on their local–global interaction buckling behavior. This paper presents an efficient fiber-based simulation model for analyzing the inelastic interaction buckling of eccentrically loaded RCFST slender columns with unequal wall thickness. The model considers the progressive local–global interaction buckling, distributed plasticity, concrete cracking and crushing, second-order effects, and geometric imperfections. The mathematical model is programmed to compute not only the axial load–displacement responses but also the interaction curves of axial load and moment of slender RCFST columns. The simulation modeling is validated by experimentally measured data. The validated computer model is used to parametrically study the interaction local–global buckling responses of RCFST columns while the range analysis is conducted to identify the relative significance of key parameters. It is demonstrated that the proposed computer model accurately simulates experimentally measured responses. Hence, it can be used with confidence in practice to analyze and design RCFST slender columns fabricated with steel plates of unequal thickness. The existing design standard AS/NZS 2327:2017 provides acceptable strength predictions of RCFST slender columns and beam-columns while the procedure specified in Eurocode 4 overestimates their capacities. [ABSTRACT FROM AUTHOR]

This paper proposes a new method to improve re performance of intra-field interpolation which is the mos~ important element of deinterlacing method. Traditional edge- based methods were poor at determining accurate edge iirection which decides interpolation performance. The 7roposed method decides the direction and slope of edge based on locally adaptive-thresholded binary image to mprove efficiency and accuracy, and it also increased the ~orizontal size of search window to 15 for better direction ietermination at gentle slope. Compared to traditional edge- based methods, interpolation based on binary image, which is ,`enerated using the proposed method, leads to great erformance improvement. With computer simulations for a ~`ariety of images, this paper shows the new approach is much ~etter than traditional methods.. [ABSTRACT FROM AUTHOR]

This paper presents an implementation of an ~daptive beamformer in a hands-free unit. The proposec~ ~daptive beamformer suppresses stationary noise an~ nterference sound. The adaptive beamformer and acoustic `cho canceller were implemented in a compact hands-free mit with a low-cost DSP. Experimental results demonstrate he noise reduction performance of the hands-free unit'. [ABSTRACT FROM AUTHOR]

The critical role that numerical simulation plays in additive manufacturing has stimulated research on the effectiveness and potential applications of mesh-free, particle-based discretisation techniques. These methods excel at handling fluid flows and are viable alternatives to the mesh-based techniques typically used in commercial simulation software. In this paper, we review recent advances in developing computational models for metal additive manufacturing (MAM) processes using particle methods, in the theoretical understanding of the fundamental mechanisms that control such processes at the powder (or melt pool) scale, and in the predictability of physics-based modelling approaches. The paper explores the applicability and performance of particle-based methods in simulating powder bed fusion, directed energy deposition, and binder jetting processes. Since the progress of MAM relies on systematic material-process-structure realisations which are often impossible to sense or observe experimentally, developing efficient particle-based and multiscale simulation tools can be essential to achieving this objective through in-situ process control and optimisation. [ABSTRACT FROM AUTHOR]

In this paper, a simulation model of reciprocating rod seal systems when there is axial texture on the rod surface due to wear is studied. The model includes macroscopic solid mechanics analysis, microscopic contact mechanics analysis and fluid mechanics analysis, and on this basis, the change of surface pressure when the sealing ring fall into a texture is calculated by the micro‐deformation mechanics analysis of the seal surface. Then, the stiffness matrix method is used to find the film thickness when the three pressures in the sealing area are in equilibrium, completing the fluid–solid coupling calculation. Combined with the above simulation process, the performance parameters of the sealing system such as leakage and friction can be obtained. Results show that axial texture will degrade sealing performance, which increases leakage and friction. The simulation results can quantitative characterise the influence of rod wear on sealing performance and provide some theoretical basis for the study of seal failure mechanism and prediction of seal life. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a deterministic mathematical model of Marburg–Monkeypox virus co-infection transmission under the Caputo fractional-order derivative. We discussed the dynamics behavior of the model and carried out qualitative and quantitative analysis, including the positivity–boundedness of solution, and the basic reproduction number ℜ o . In addition, the Banach and Schauder-type fixed point theorem is utilized to explore the existence–uniqueness of the solution in the suggested model and the proposed model stability under the Ulam–Hyers condition is demonstrated. In numerical simulation, the Predictor–Corrector method is used to determine the numerical solutions. According to the numerical result, increasing the rate of quarantine and detecting unknown Marburg virus, will be the most effective control intervention to reduce Marburg and Monkeypox virus transmission in the population. [ABSTRACT FROM AUTHOR]

The phase-field model (PFM) is gaining increasing attention in the application of multiphase flows due to its advantages, in which the phase interface is treated as a narrow layer and phase parameters change smoothly and continually at this thin layer. Thus, the construction or tracking of the phase interface can be avoided, and the bulk phase and phase interface can be simulated integrally. PFM provides a useful alternative that does not suffer from problems with either the mass conservation or the accurate computation of surface tension. In this paper, the state of the art of PFM in the numerical modeling and simulation of multiphase flows is comprehensively reviewed. Starting with a brief description of historical developments in the PFM, we continue to take a tour into the basic concepts, fundamental theory, and mathematical models. Then, the commonly used numerical schemes and algorithms for solving the governing systems of PFM in the application of multiphase flows are presented. The various applications and representative results, especially in non-match density scenarios of multiphase flows, are reviewed. The primary challenges and research focus of PFM are analyzed and summarized as well. This review is expected to provide a valuable reference for PFM in the application of multiphase flows. [ABSTRACT FROM AUTHOR]

This article presents a discussion on a study by Bradley Jones and Rachel T. Johnson on the use of Gaussian Process model in computer simulation research. The author believes that sometimes a computer simulation run is not expensive. He references a study that examined migration of radionuclides into ground water from a nuclear waste repository.

This article presents a discussion on a study by Bradley Jones and Rachel T. Johnson on the use of Gaussian Process model in computer simulation research. The author believes that the Gaussian process model often performs adequately apparent nonstationarity. He explores the topic of model calibration, the relationship between the design and the model used to fit the data, and design augmentation.

Explosion is a significant threat to chemical process safety, which often occurs suddenly with a wide range of impact, resulting in catastrophic disasters. Predictions of explosion hazards are required for regional safety assessment and disaster resilience enhancement of chemical industrial parks (CIPs). This paper, therefore, aims to develop a conceptual framework for systematically analyzing explosion evolutions and quantifying the potential hazards by combining system-theoretic process analysis (STPA) method with numerical simulation. The proposed framework consists of 5 steps: (i) establishment of hierarchical safe control structures (SCSs) of important chemical processing zones in the CIP, (ii) computational fluid dynamics (CFD) modeling for potential explosion evolutions in each zone by changing the examined parameters randomly, (iii) development of a convolutional neural network (CNN) prediction model through constant self-learning of CFD pressure field data, (iv) comprehensive assessment of blast damage by incorporating the outputs of the above numerical models into existing evaluation methods, (v) identification of unsafety control actions and causes, and safety constraints for the improvement of SCSs. Provided with monitoring data, the developed analysis architecture can predict explosion process hazards and recommend appropriate safety strategies in real time. This would service the multi-level requirements for explosion prevention and protection, supporting better-informed decision-making. The paper describes the concepts and implementation process of the method as a first step. [ABSTRACT FROM AUTHOR]

With the continuous expansion of computer system simulation applications, the dynamic system modeling problems that people face have become more and more complex. This paper mainly studies dynamic system simulation models and algorithms based on artificial neural networks. This article mainly focuses on some practical problems of dynamic system simulation, and studies the artificial neural network model and corresponding algorithm suitable for dynamic system modeling. First, it summarizes the existing artificial neural network simulation models of dynamic systems: multi-layer feedforward network relationship model without feedback, recursive network relationship model with feedback, and their network topology diagrams are drawn. Secondly, a quantum genetic algorithm is proposed to optimize the parameters of artificial neural networks and feedforward process neural networks. To achieve the preprocessing of the parameters. Next, based on the analysis and research of BP neural network theory, this paper comprehensively compares the neural network models established under various network structures and algorithms, and establishes the simulation model based on the BP neural network monitoring data system, and compares the results with the monitoring data obtained in the field. The hidden layer of neural network with 4 and 6 nodes will increase the convergence step. When the number of nodes is 10 and 12, the convergence rate may reach 46 steps. This shows that if the non-display layer with different number of nodes in the same layer is selected for the same system simulation model based on artificial neural network, the repetition number of convergence steps of the prediction model will be different. [ABSTRACT FROM AUTHOR]

In order to accomplish efficient mixing of liquids with large differences in flow rates, an efficient multi-orifice impinging transverse (MOIT) jet mixer is used in this paper. Its structure combines a conventional MOIT jet mixer with a venturi jet mixer to improve the mixing efficiency of the MOIT jet mixer. The flow characteristics and mixing effects inside the conventional and efficient jet mixer are numerically simulated by means of a Multiphase Models. Based on building the experimental platform, the maximum error between the simulation results and the experimental results obtained with the high-speed camera is 8.42%, which verifies that the model and simulation method applies to the simulation of the mixer. In addition, the paper uses MATLAB software to obtain the interphase contact area at the transverse orifice section and verifies that the contact area at the transverse orifice section affects the mixing effect of the mixer. The droplet size distribution was also analyzed by the CFD-PBM model. The results show that the efficient MOIT jet mixer has better mixing efficiency and mixing effect, and the optimal values of the number of orifices and main fluid flow rate of the jet mixer exist. In addition, the mixing effect of the mixer showed a decreasing trend with the increase of the orifice size. The results of this paper complete the optimization of the parameters of the MOIT jet mixer, facilitating its industrial application. And combining two different mixers to create a novel jet mixer, which provides a direction for the development of new jet mixers and helps to promote the development of the fine chemical industry. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the behavior of a spherical absorber composed of two parts, an inner sphere and a supporting convex spherical dish in which the ball is placed. Considering only the planar behavior of the system, a set of governing nonlinear differential equations was derived and solved numerically. Firstly, the system is exposed to the harmonic excitation of the supporting bowl and its time response is analyzed for all time dependent variables. By gradually changing the angular frequency of the excitation, a resonance curve is obtained, which is examined in detail with respect to the changing amplitudes of the excitation force and the nonlinear behavior. The effect of internal damping and different settings of the absorber characteristics are also investigated. The effect of initial conditions without the presence of an external excitation force is also numerically analyzed by means of phase portraits for selected pairs of initial conditions. [ABSTRACT FROM AUTHOR]

The space docking process must be simulated on the ground to guarantee the success of the space docking task. By synthesizing a physical simulation and a numerical simulation, a hybrid simulator can simulate the complicated contact process of space docking. A hybrid simulator consists of a robot (i.e., lower platform), upper platform, docking mechanisms, contact force and torque measurement system, and numerical simulation system. To ensure the simulation accuracy, the robot is expected to have a high structure stiffness, high structure natural frequency, and high bandwidth frequency response. However, these performances are always limited in implementation. In this paper, how the structural dynamics of the robot affect the hybrid simulation accuracy is studied. Due to the structural dynamics of the robot, the divergence and convergence of the hybrid simulation are both possible. The stability conditions are given. A distortion compensation method for the structure dynamics of the robot is proposed. The stability analysis after the compensation is given. The software emulations and experiments are used to verify the analysis and the distortion compensation method. Experiments on real docking mechanisms are given to show the applications. [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 proposes a fractional-order model of glucose–insulin interaction. In Caputo's meaning, the fractional derivative is defined. This model arises in Bergman's minimal model, used to describe blood glucose and insulin metabolism, after intravenous tolerance testing. We showed that the established model has existence, uniqueness, non-negativity, and boundedness of fractional-order model solutions. The model's local and global stability was investigated. The parametric conditions under which a Hopf bifurcation occurs in the positive steady state for a proposed model are studied. Moreover, we present a numerical treatment for solving the proposed fractional model using the generalized Euler method (GEM). The model's local stability and Hopf bifurcation of the proposed model in sense of the GEM are presented. Finally, numerical simulations of the model using the Adam–Bashforth–Moulton predictor corrector scheme and the GEM have been presented to support our analytical results. [ABSTRACT FROM AUTHOR]

In this paper, a fractional nonlinear control strategy based on the nested saturations technique and the Caputo-Fabrizio derivative for a quadrotor aircraft, to maintain desired position and orientation in stationary flight and trajectory tracking tasks, is proposed and developed. In addition, the dynamic model is obtained by using the Euler–Lagrange formulation, and then it is generalized to an arbitrary order through the Caputo-Fabrizio derivative. The traditional nonlinear control based on the nested saturation technique is also developed and implemented on the quadrotor for comparison purposes between both control schemes. Numerical simulations demonstrated the superiority of the proposed control strategy for stabilizing the quadrotor at hover and reaching the desired position and orientation, over its integer-order counterpart. In addition, three additional desired trajectories are considered, keeping the same gains and orders, to demonstrate the robustness of the proposed control scheme under different operating conditions. In this sense, our controller presents significant performance improvements, which were validated through system simulations. Our proposed control system and its traditional counterpart were tuned experimentally using the response of the system to a desired trajectory. [ABSTRACT FROM AUTHOR]

This paper deals with the modeling and numerical simulations of multilane vehicular traffic according to the kinetic theory of active particles methods. The main idea of this theory is to consider each driver–vehicle system as a micro-system, where the microscopic state of particles is described by position, velocity, and activity which is an appropriate variable for modeling the quality of the driver-vehicle. The interactions between micro-systems are modeled by stochastic game theory. This leads to the derivation of a mathematical model within the framework of the approach of kinetic theory. The well-posedness of the related Cauchy problem for the spatially homogeneous case is established. Numerical simulations are carried out to show the ability of the proposed model to reproduce the empirical data such as the asymptotic property in time and the emerging behavior of clusters with a particular focus on the road environment conditions. [ABSTRACT FROM AUTHOR]

Input model bias is the bias found in the output performance measures of a simulation model caused by estimating the input distributions/processes used to drive it. When the simulation response is a nonlinear function of its inputs, as is usually the case when simulating complex systems, input modelling bias is amongst the errors that arise. In this paper, we introduce a method that recalibrates the input parameters of parametric input models to reduce the bias in the simulation output. The proposed method is based on sequential quadratic programming with a closed form analytical solution at each step. An algorithm with guidance on how to practically implement the method is presented. The method is shown to be successful in reducing input modelling bias and the total mean squared error caused by input modelling error. Summary of Contribution: This paper furthers the understanding and treatment of input modelling error in computer simulation. We provide a novel method for reducing input model bias by recalibrating the input parameters used to drive a simulation model. A sequential quadratic programming approach with an explicit solution is provided to recalibrate the input parameters. The method is therefore computationally inexpensive. An algorithm outlining our proposed procedure is provided within the paper. An evaluation of the method shows the method successfully reduces input model bias and may also reduce the mean squared error caused by input modelling in the output of a simulation model. [ABSTRACT FROM AUTHOR]

It is crucially important to estimate unknown parameters in process-based models by integrating observation and numerical simulation. For many applications in earth system sciences, a parameter estimation method which allows parameters to temporally change is required. In the present paper, an efficient and practical method to estimate time-varying parameters of relatively low dimensional models is presented. In the newly proposed method, called Hybrid Offline Online Parameter Estimation with Particle Filtering (HOOPE-PF), an inflation method to maintain the spread of ensemble members in a Sampling-Importance-Resampling Particle Filter (SIRPF) is improved using a non-parametric posterior probabilistic distribution of time-invariant parameters obtained by comparing simulated and observed climatology. HOOPE-PF outperforms the original SIRPF in synthetic experiments with toy models and a real-data experiment with a conceptual hydrological model when an ensemble size is small. The advantage of HOOPE-PF is that its performance is not greatly affected by the size of perturbation to be added to ensemble members to maintain their spread while it is important to get the optimal performance in the original particle filter. Since HOOPE-PF is the extension of the existing particle filter which has been extensively applied to many models in earth system sciences such as land, ecosystem, hydrology, and paleoclimate reconstruction, HOOPE-PF can be applied to improve the simulation of these process-based models by considering time-varying model parameters. Plain Language Summary Computer simulation is widely used to understand earth systems such as atmosphere, ocean, land, ecosystem, and society. Many computer simulation models in earth system sciences inevitably have unknown coefficients of equations, which are called model parameters. It is important for accurate simulation of earth systems to tune these model parameters by comparing the results of computer simulation with observation. Although many previous works assumed that model parameters do not change over time, it is necessary to allow them to change over time in some applications, which makes it more difficult to estimate model parameters. In this study, a new method to estimate time-varying model parameters is proposed. The key idea of this paper is to combine two existing methods which integrate observations into computer simulation models. It is found that the proposed method works better than the existing method in three case studies. The proposed method can contribute to improving many simulations in earth system sciences by efficiently tuning time-varying model parameters. [ABSTRACT FROM AUTHOR]

The article calls for papers for the publication's special issue on methological developments in computer simulation, along with its application in scientific, industrial and business areas.

Water is the most common liquid on the Earth. At the same time, it is the strangest liquid having numerous anomalous properties. For this reason, although water was investigated in numerous studies, many questions still remain unanswered. Even the thermodynamic properties of water at high pressures are unknown. In this paper, we present an experimental study of the thermodynamic properties of water up to a pressure of 12 kbar and a temperature of 473 K far above the range of pressures and temperatures in previous studies. We compare the experimental results to the results of computer simulations of two models of water (SPC/E and TIP4P) and show that the SPC/E model is not appropriate at high pressure, while the TIP4P model describes the equation of state of water, but fails to describe the heat capacity. [ABSTRACT FROM AUTHOR]

The application and economic efficiency evaluation mode of traditional composition in the field of modern music cannot meet the needs of various types of music in China, especially Guqin music. Based on this, this paper studies the big data simulation model of Guqin sound synthesis and plucking based on computer composition technology. The computer composition technology uses the discrete dynamic modeling technology of complex system to complete the computer simulation of Guqin sound through the analysis of the correlation between Guqin music data and realizes the storage and analysis of the generated Guqin sound data. In addition, the technology can analyze the data information of composition mode in the piano sound plucking simulation model with the classical Guqin music data stored in the cloud system over the years and then feed it back to relevant professionals for verification. The experimental results show that the Guqin sound simulation model can efficiently compare and analyze the melody and other data of classical Guqin sound with the simulated Guqin sound and can realize secondary data mining. This paper studies the application of computer composition method based on discrete dynamic modeling technology in Guqin sound simulation, which has certain reference significance for improving the cloud data in China's modern music field and the intelligent construction of Guqin sound data cloud storage system. [ABSTRACT FROM AUTHOR]

This paper deals with the formulation and validation of the discrete fresh concrete (DFC) model to simulate the rheological behavior of self-consolidating, ordinary, and printable concrete in the fluid state immediately after mixing. The DFC model is formulated within the framework of the discrete-element method (DEM), and it models the interaction among coarse aggregate particles embedded in a fine mortar. The formulation is based on stress-strain constitutive equations through which the behavior of fresh concrete can be described by parameters with clear physical meaning. This study presents a rigorous methodology for estimating the model key input parameters by the comparison of numerical simulations with experimental data. This methodology includes (1) a series of sensitivity analyses and simulations to establish the relationship between constitutive parameters and macroscopic properties; and (2) numerical simulations of experimental tests commonly used to characterize the fresh state behavior of concrete. Finally, the paper discusses the application of the DFC model to the simulation of concrete additive manufacturing. [ABSTRACT FROM AUTHOR]

It is of great significance to identify structural state-parameters and the unknown seismic inputs using partial measurements of structural acceleration responses for the rapid evaluation of structures after unknown seismic excitations. However, unknown seismic inputs do not directly appear in the observation equations of measured absolute floor accelerations of building structures, i.e., there is no direct feedthrough of unknown seismic inputs in the observation equations. Current methods for the identification of joint structural systems and unknown inputs are either inapplicable or greatly influenced by measurement noises. In this paper, a method so-called smoothing extended Kalman filter with unknown input without direct feedthrough (smoothing EKF-UI-WDF) is proposed. The identification algorithm is derived in the framework of minimum-variance unbiased estimation (MVUE), and the smoothing technique is adopted to introduce subsequent observation steps in the current identification step. Then, structural states, parameters, and unknown seismic excitations without direct feedthrough are simultaneously identified recursively with only a few steps delay, and the identification results are tolerant to measurement noises. The proposed method is verified by a numerical simulation model and a practical engineering case study. Both identification results validate the effectiveness of the proposed method for the simultaneous identification of structural systems and seismic inputs without direct feedthrough. [ABSTRACT FROM AUTHOR]

A system of diffusion–reaction equations coupled with a dissolution–precipitation model is discussed in this paper. We start by introducing a microscale model together with its homogenized version. In the present paper, we first derive the corrector results to justify the obtained theoretical results. Furthermore, we perform the numerical simulations to compare the outcome of the effective (homogenized) model with the original heterogeneous microscale model. [ABSTRACT FROM AUTHOR]

Kriging or Gaussian process models are popular metamodels (surrogate models or emulators) of simulation models; these metamodels give predictors for input combinations that are not simulated. To validate these metamodels for computationally expensive simulation models, the analysts often apply computationally efficient cross-validation. In this paper, we derive new statistical tests for so-called leave-one-out cross-validation. Graphically, we present these tests as scatterplots augmented with confidence intervals that use the estimated variances of the Kriging predictors. To estimate the true variances of these predictors, we might use bootstrapping. Like other statistical tests, our tests—with or without bootstrapping—have type I and type II error probabilities; to estimate these probabilities, we use Monte Carlo experiments. We also use such experiments to investigate statistical convergence. To illustrate the application of our tests, we use (i) an example with two inputs and (ii) the popular borehole example with eight inputs. Summary of Contribution: Simulation models are very popular in operations research (OR) and are also known as computer simulations or computer experiments. A popular topic is design and analysis of computer experiments. This paper focuses on Kriging methods and cross-validation methods applied to simulation models; these methods and models are often applied in OR. More specifically, the paper provides the following; (1) the basic variant of a new statistical test for leave-one–out cross-validation; (2) a bootstrap method for the estimation of the true variance of the Kriging predictor; and (3) Monte Carlo experiments for the evaluation of the consistency of the Kriging predictor, the convergence of the Studentized prediction error to the standard normal variable, and the convergence of the expected experimentwise type I error rate to the prespecified nominal value. The new statistical test is illustrated through examples, including the popular borehole model. [ABSTRACT FROM AUTHOR]

The axial flow pump is a low-head pump widely used in farmland irrigation and water transfer engineering in plain areas. To study the effects of different guide vane rotation angles and inlet angles on the performance of axial flow pumps, based on the initial scheme of the guide vane, the efficiency of the axial flow pump is expected to be improved by adjusting the guide vane rotation angles and changing the inlet angles of the guide vane. This paper uses Computational Fluid Dynamics numerically to simulate and calculate the performance of axial flow pumps under different guide vane rotation angles and inlet angles. The results show that the influence of different guide vane rotation angles and inlet angles on the performance of the axial flow pump is reflected in the operating conditions of large-discharge conditions. Adjusting different guide vane rotation angles can significantly improve the efficiency of axial flow pumps. Moreover, the high-efficiency area of the axial flow pump is expanded nearly two times with the increase in the guide vane rotation angles under large-discharge conditions. At the same time, under the design condition, the highest efficiency of the axial flow pump is 87.69% under scheme V. However, under the linear change of the inlet angle of the guide vane, the highest efficiency of the axial flow pump can reach 87.71%. Finally, the model test verifies the reliability of the numerical simulation, and the research results are beneficial for improving the efficiency of the axial flow pump. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) systems have become an integral and widespread part of renewable energy generation. In combination with energy storage, they offer a variety of advantages such as increased self-sufficiency or improved grid stability. However, geographic location, subsidies, energy tariffs, size of PV panels and battery, and other factors significantly influence the overall performance and profitability of the system. Solving this complex task of system design and component dimensioning is not easy. The diversity and multitude of parameters therefore usually requires the help of, more or less complex, computer simulations. This led and still leads to a high publication activity on techno-economic and other optimizations for such systems. However, the operating strategies and component models are often oversimplified, leading to results with significant errors. The goal of this paper is to provide in-depth insight into component modeling and parametrization for PV module, battery energy storage, and inverter, as well as giving suggestions on appropriate control strategies. The focus lies on the description of suitable simple-but-accurate models and their parametrization. In order to avoid the effort of having to conduct measurements for component characterization, an approach relying on values presented in product data sheets is considered. Furthermore, the effects of model simplifications, as they are found in many publications, are shown. Finally, the importance of an uncertainty analysis for the entire simulation is discussed in order to gain insight into the accuracy of the calculated simulation results and their dependency on model- and input-parameters. • Photovoltaic system modeling/simulation. • Component modeling for PV module, battery energy storage and inverter. • Suitable simple-but-accurate models and their parametrization • Characterization relying on product data sheets with minimal informations. [ABSTRACT FROM AUTHOR]

The droplet impact on solid surfaces is a popular research topic in which many researchers focus on stationary surfaces, only a few researches have been conducted for moving surfaces. In this paper, a high-speed photography-based droplet impact experimental platform and a VOF-based numerical simulation model are built to study the morphology of motion of a droplet after it impacted a horizontal uniformly moving surface. In the present study, the tangential and normal Weber numbers range within 70. This is because at such low Weber numbers the droplets initially spread to their maximum diameter after impacting the moving surfaces and subsequently start to rebound. The studies have confirmed that the maximum spreading factor of the droplet increases linearly with the tangential Weber number, and the spreading time increases as well. The maximum spreading factor of the droplet increases nonlinearly as a function of the normal Weber number and corresponding time initially increases and then decreases. Finally, the expression for the maximum spreading factor is fitted according to its correlation with the We number. [ABSTRACT FROM AUTHOR]

This paper is a study on energy efficiency prediction model of heavy-duty electric vehicles using numerical simulation. Because the current energy consumption efficiency evaluation method for electric vehicles has limitations in terms of manpower, resources, and time required, therefore a simulation model development to predict electric vehicle energy consumption efficiency is needed. Furthermore, research on heavy-duty electric vehicles is relatively insufficient compared to light-duty electric vehicles, and the need of research on heavy-duty electric vehicles is increasing. Therefore, this study develops an energy efficiency prediction model for heavy-duty electric vehicles and verifies it with the experimental results. Based on this, the applicability of the simulation method using the developed prediction model to the current energy efficiency evaluation management system for heavy-duty electric vehicles was reviewed. To verify the accuracy of the simulation model, the dynamometer test results were compared to simulation results, and the UDS protocol was used to acquire internal data for heavy-duty electric vehicles. Reliability of simulation model was secured by comparing data such as motor speed, battery voltage/current, state of charge and total driving distance of the test vehicles with data from the dynamometer experiment and the simulation model. [ABSTRACT FROM AUTHOR]

The topic of this paper is the Kelvin-Helmholtz instability, a phenomenon which occurs on the interface of a stratified fluid, in the presence of a parallel shear flow, when there is a velocity and density difference across the interface of two adjacent layers. This paper focuses on a numerical simulation modelled by the Taylor-Goldstein equation, which represents a more realistic case compared to the basic Kelvin-Helmholtz shear flow. The Euler system is solved with new modelled smooth velocity and density profiles at the interface. The flux at cell boundaries is reconstructed by implementing a third order WENO (Weighted Essentially Non-Oscillatory) method. Next, a Riemann solver builds the fluxes at cell interfaces. The use of both Rusanov and HLLC solvers is investigated. Temporal discretization is done by applying the second order TVD (total variation diminishing) Runge-Kutta method on a uniform grid. Numerical simulations are performed comparatively for both Kelvin-Helmholtz and Taylor-Goldstein instabilities, on the same simulation domains. We find that increasing the number of grid points leads to a better accuracy in shear layer vortices visualization. Thus, we can conclude that applying the Taylor-Goldstein equation improves the realism in the general fluid instability modelling. [ABSTRACT FROM AUTHOR]

We present and analyse the performance of different combinations of four higher-order numerical integrators and up to nine interpolation schemes applied to the problem involving the Sun and four Gas-giants (outer planets), namely, Jupiter, Saturn, Uranus, and Neptune. The Hermite interpolation schemes obtained by one, two, and three time-step and interpolants for ODEX2 and ERKN integrators are considered in this paper. The interpolants are a special example of an interpolation scheme, which produce an approximation that is continuous across one step and across the complete interval of integration. The interpolants are quite expensive in comparison with the other interpolation schemes. Therefore, one of the objectives of this paper is to investigate the possibilities of replacing the interpolants of certain integrators by other interpolation schemes, perhaps at a cost of a little bit of accuracy. The experiments are performed to examine the error growth in the positions, velocities, and relative error in energy and angular momentum using different combinations of integrators and interpolation schemes over a long interval of integration, as long as 100 million years for the Jovian problem with local error tolerances ranging from 10-16 to 10-08. [ABSTRACT FROM AUTHOR]

Second-order macroscopic continuum models have been constantly improving for decades to reproduce the empirical observations. Recently, a series of experimental studies have suggested that the stochastic factors contribute significantly to destabilizing traffic flow. Nevertheless, the traffic flow stability of the stochastic second-order macroscopic continuum model has not received the attention it deserves in past studies. More importantly, we have found that the destabilizing aspect of stochasticity is still not correctly validated in the existing theoretical stability analysis. In this paper, we analytically study the impact of stochasticity on traffic flow stability for a general stochastic second-order macroscopic model by using the direct Lyapunov method. Numerical simulations have been carried out for different typical stochastic second-order macroscopic models. Our analytical stability analysis has been validated, and our methodology has been proved more efficient. Our study has theoretically revealed that the presence of stochasticity has a destabilizing effect in usual stochastic macroscopic models. • Stability condition of a general stochastic second-order macroscopic continuum model. • The Lyapunov method outperforms the eigenvalue method. • The stochastic macroscopic models respond differently to the presence of stochasticity. • The presence of stochasticity has a destabilizing effect in usual stochastic macroscopic models. [ABSTRACT FROM AUTHOR]

We consider globally connected coupled Winfree oscillators under the influence of an external periodic forcing. Such systems exhibit many qualitatively different regimes of collective dynamics. Our aim is to understand this collective dynamics and, in particular, the system's capability of entrainment to the external forcing. To quantify the entrainment of the system, we introduce the entrainment degree, that is, the proportion of oscillators that synchronize to the forcing, as the main focus of this paper. Through a series of numerical simulations, we study the entrainment degree for different inter-oscillator coupling strengths, external forcing strengths, and distributions of natural frequencies of the Winfree oscillators, and we compare the results for the different cases. In the case of identical oscillators, we give a precise description of the parameter regions where oscillators are entrained. Finally, we use a mean-field method, based on the Ott–Antonsen ansatz, to obtain a low-dimensional description of the collective dynamics and to compute an approximation of the entrainment degree. The mean-field results turn out to be strikingly similar to the results obtained through numerical simulations of the full system dynamics. [ABSTRACT FROM AUTHOR]

In the development of deep geological repositories (DGRs), performance assessment modeling is used to evaluate the integrity and performance of the engineered and geological barriers for thousands or millions of years of evolution of the disposal system. To evaluate the suitability of a site for a DGR, geoscientific data from dedicated site investigation programs are integrated into site-specific assessments. This paper presents the development and implementation of a modeling workflow aimed at comparing three potential siting areas for a DGR in Switzerland from the viewpoint of long-term safety and technical feasibility. The workflow follows the guidelines of the national regulator addressing safety relevant criteria such as the barrier efficiency of the host rock and its mechanical and chemical integrity in response to repository-induced influences and the long-term stability of the repository site over geological scales. In the regulatory requirements, the role of parametric, conceptual, and scenario uncertainty has been identified as an issue of special importance in the site selection process. The assessment approach comprises a portfolio of numerical models for the simulation of solute, gas and heat transport in the repository nearfield. The modeling was performed with deterministic as well as probabilistic variants integrated in an indicator-based approach that allows the consistent comparison of the candidate sites using quantitative dimensionless performance indices. The model-based assessment of the sites allows a traceable, transparent, and verifiable implementation of the site selection process. [ABSTRACT FROM AUTHOR]

In this paper, a new numerical technique is proposed for the simulations of advection-diffusion-reaction type elliptic and parabolic interface models. The proposed technique comprises of the Haar wavelet collocation method and the finite difference method. In this technique, the spatial derivative is approximated by truncated Haar wavelet series, while for temporal derivative, the finite difference formula is used. The diffusion coefficients, advection coefficients, and reaction coefficients are considered discontinuously across the fixed interface. The newly established numerical technique is applied to both linear and nonlinear benchmark interface models. In the case of linear interface models, Gauss elimination method is used, whereas for nonlinear interface models, the nonlinearity is removed by using the quasi-Newton linearization technique. The L ∞ errors are calculated for different number of collocation points. The obtained numerical results are compared with the immersed interface method. The stability and convergence of the method are also discussed. On the whole, the numerical results show more efficiency, better accuracy, and simpler applicability of the newly developed numerical technique compared to the existing methods in literature. [ABSTRACT FROM AUTHOR]