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A lime–sand pile is a three-phase particle composite material composed of a lime matrix, sand, and a loess aggregate at the meso level. Establishing a random aggregate model that can reflect the actual aggregate gradation, content, and morphology is the premise of numerical simulations of the meso-mechanics of lime–sand piles. In this paper, the secondary development of Abaqus 2022 is realized by writing Python 3.12 scripts, and a parameterized three-phase mixed lime–sand pile random meso-spherical aggregate model is obtained. A meso-modeling idea of lime–sand piles is creatively proposed, the integrated-generation algorithm of a spherical aggregate of different materials is written, and the material's properties and mesh generation are given by the algorithm. Finally, a numerical simulation of temperature–expansion statics is carried out using an established mesoscopic model. Under different mixing ratios, the expansion force increases with an increase in the lime proportion. The increase in the expansion force is approximately 45% of that without an increased lime proportion. The simulated expansion forces are 8.81 kN, 12.61 kN, and 18.89 kN, respectively, which are similar to the experimental results for laboratory specimens, and the relative error is less than 3%. In the case of different height ratios, with increases in height, the change in the expansion force is very small, and the relative error between the simulated value and the experimental value is less than 2%, which further verifies the reliability of the mesoscopic random model of lime–sand piles. The model can be used to guide the practical application of engineering. [ABSTRACT FROM AUTHOR]

With the continuous progress in integrated circuit technology, single-event effect (SEE) has become a key factor affecting the reliability of aerospace integrated circuits. Simulating fault injection using the computer simulation technique effectively reflects the SEE in aerospace integrated circuits. Due to various masking effects, only a small number of faults will result in errors; the traditional method of injecting one fault in one workload execution is inefficient. The method of injecting multiple faults in one workload execution will make it impossible to judge which fault results in errors because the propagation characteristic of SEE and faults may affect each other. This paper proposes an improved multi-point fault injection method to improve simulation efficiency and solve the problems of the general multi-point fault injection method. If one workload execution does not result in errors, multiple faults can be verified by one workload execution. If one workload execution results in errors, a specific grouping method can be used to determine which faults result in errors. The experimental results show that the proposed method achieves a good acceleration effect and significantly improves the simulation efficiency. [ABSTRACT FROM AUTHOR]

The occurrence of a disaster and the appearance of a new product are items of news that can reach many people rapidly. Decision-makers would like to know how many individuals will obtain such information. In this paper, we study the case in which there are spreaders who think that the news is true and others that claim it is false. We simulate the propagation of a rumour and propose an algorithm for estimating the parameters of the resulting dynamical system. The relation between the parameters defining the simulation and the dynamical system is also studied. We conclude that the simulation describes the phenomenon well, in particular when the method proposed in this paper is used to estimate the parameters. [ABSTRACT FROM AUTHOR]

Time-domain numerical simulation is generally considered an accurate method to predict the mooring system performance, but it is also time and resource-consuming. This paper attempts to completely replace the time-domain numerical simulation with machine learning approaches, using a catenary anchor leg mooring (CALM) system design as an example. An adaptive sampling method is proposed to determine the dataset of various parameters in the CALM mooring system in order to train and validate the generated machine learning models. Reasonable prediction accuracy is achieved by the five assessed machine learning algorithms, namely random forest, extremely randomized trees, K-nearest neighbor, decision tree, and gradient boosting decision tree, among which random forest is found to perform the best if the sampling density is high enough. [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]

This paper takes a tunnel through a landslide in Northwest China as an example, constructs a mechanical model of a tunnel–landslide orthogonal system, and explores the deformation mechanism of a tunnel–landslide system and the technology of early warnings of near-slips. Given the problem that it is difficult to accurately monitor the deformation and damage characteristics of the tunnel–landslide system using conventional methods, FLAC3D was used to analyze the deformation mechanism of the tunnel–landslide orthogonal system and numerical simulation of the NPR constant resistance large deformation anchors for the early warning of near-slips. Based on the strength reduction method, by reducing the mechanical parameters of the shear strength of the slip zone and simulating different degrees of landslides, we obtained the change rules of the displacement and the axial force of the NPR constant-resistance large deformation anchor cable in the tunnel–landslide orthogonal system, established the warning mode of the Newtonian force tunnel–landslide orthogonal system, and successfully issued a near-slip warning in actual engineering applications. The above research is of great significance to the stability monitoring and risk assessment of tunnel–landslide systems. [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 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]

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]

This paper gives an account of three projects funded by the European Union that heavily rely on numerical modeling and simulations of nuclear reactors: the CORTEX project (CORe monitoring Techniques and EXperimental validation and demonstration), the McSAFER project (High-Performance Advanced Methods and Experimental Investigations for the Safety Evaluation of Generic Small Modular Reactors), and the METIS project (MEthods and Tools Innovations for Seismic risk assessment). The CORTEX project focuses on neutronic simulations, the McSAFER project considers neutronic, thermal-hydraulic, and thermo-mechanic simulations, whereas the METIS project investigates simulations for seismic assessments. Although the projects have different objectives, they present some common features in terms of the complementary modeling approaches used in each project and in terms of verification and validation programs. The main achievements of the projects are presented in the paper covering the technical aspects of the respective projects, training, education, and dissemination activities, as well as utilization and cross-fertilization. All three projects lead to the advancement in nuclear reactor modeling in the above areas, with the development of new simulation capabilities beyond the state-of-the-art. [ABSTRACT FROM AUTHOR]

The low-fidelity simulation method cannot meet the requirements for predicting the performance of an adaptive cycle engine (ACE), especially when considering tip clearance variations in the compression and expansion systems. The tip clearances of the components of an ACE, such as the adaptive fan and turbine, vary drastically under different operating conditions. Though the tip clearance significantly impacts the engine's performance, including its thrust and fuel consumption, variations in tip clearance are not considered in traditional ACE simulation models. This paper developed a new integrated model for predicting ACE performance, including multi-fidelity simulation models of the components and a newly developed, simplified model for predicting tip clearance. Specifically, the integrated model consists of a zero-dimensional (0D) engine performance simulation model, a three-dimensional (3D) adaptive fan numerical simulation model, a one-dimensional (1D) low-pressure-turbine (LPT) mean line model, and a multi-dimensional (MD) tip clearance prediction model. The integrated model solved the problem of considering the impact of tip clearance on an ACE and further improved the accuracy of thrust and fuel consumption predictions. Specifically, considering variations in the tip clearances under the design conditions, the differences in the thrust and specific fuel consumption (SFC) of the ACE are 1% and 0.3%, respectively. In conclusion, the integrated model provides a useful tool for evaluating the performance of an ACE while considering tip clearance variations. [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]

Numerical simulations consist of many components that affect the simulation accuracy and the required computational resources. However, finding an optimal combination of components and their parameters under constraints can be a difficult, time-consuming and often manual process. Classical adaptivity does not fully solve the problem, as it comes with significant implementation cost and is difficult to expand to multi-dimensional parameter spaces. Also, many existing data-based optimization approaches treat the optimization problem as a black-box, thus requiring a large amount of data. We present a constrained, model-based Bayesian optimization approach that avoids black-box models by leveraging existing knowledge about the simulation components and properties of the simulation behavior. The main focus of this paper is on the stochastic modeling ansatz for simulation error and run time as optimization objective and constraint, respectively. To account for data covering multiple orders of magnitude, our approach operates on a logarithmic scale. The models use a priori knowledge of the simulation components such as convergence orders and run time estimates. Together with suitable priors for the model parameters, the model is able to make accurate predictions of the simulation behavior. Reliably modeling the simulation behavior yields a fast optimization procedure because it enables the optimizer to quickly indicate promising parameter values. We test our approach experimentally using the multi-scale muscle simulation framework OpenDiHu and show that we successfully optimize the time step widths in a time splitting approach in terms of minimizing the overall error under run time constraints. [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]

This paper presents an optimal control of intervention strategies for the menace of Banditry taking into account media campaign against Banditry u2(t) rehabilitation of Bandits detainees u5(t) and use of military force against Banditry u6(t) as control strategies. The Banditry free equilibrium, Banditry present equilibrium and the basic reproduction number of Banditry R0B were obtained. The stability analysis results suggest that the Banditry free equilibrium is locally asymptotically stable when R0B>1 and otherwise when R0B>1. The Boko Haram presence equilibrium is globally asymptotically stable when R0B>1 and unstable if R0B>1. We used the three control strategies and updated the Banditry menace model. The optimal control issue was resolved using Pontryagin's Maximum Principle (PMP). It was discovered that there is a significant decrease in the population of Bandits and increase in the number of rehabilitated Bandits and detained Bandits when the control measures are implemented compared to the case without control. We solved the optimality control using a forward-backward sweep strategy implemented in MATLAB for numerical simulation. Additionally, we saw that the number of people detained fluctuates as the number of people receiving rehabilitation rises. We argue that in order to lessen or completely erase the menace caused by Bandits in society, the government should fund media campaigns and rehabilitation initiatives. [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 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]

In this paper, a boost converter emulator with a memristive load instead of a resistive load is proposed, and a fractional-order model of the memristive boost converter is created. Firstly, the fractional-order models of the memristor and the memristive boost converter are established respectively, and then based on different switching states, the circuit equations of the fractional-order memristive boost converter operating in continuous conduction mode are derived. Secondly, the dynamic characteristics of the fractional-order system are analyzed by numerical simulations and are compared with the integer-order memristive boost converter. Furthermore, the effects of the memristive load on the system is studied by comparing it to the traditional boost converter with resistive load. The results indicate that the fractional-order memristive boost converter can exhibit rich dynamic behavior by adjusting bifurcation parameters, and the fractional-order circuit system expands the stable working regions of the integer-order circuit system. Meanwhile, the addition of the memristive load significantly widens the normal working regions. Finally, simulations of the fractional-order system circuit based on PSIM further verify the correctness of the theoretical analysis. [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]

Copyright of Iraqi Journal of Chemical & Petroleum Engineering is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An appropriate numerical computational method and simplest model captures the performance of Switched Reluctance Machines (SRMs). Several papers and computer software-based simulation models are reported in the literature. Each model has its own merits and demerits. This paper proposes a mathematical model, based on a combination of voltage and mechanical equations, suitable for the transient running of a switched reluctance machine. The simulation results of current, torque and speed profile of SRM are produced under current chopping control and voltage pulse width modulation control. The proposed work has used experimental data of flux linkage and static torque in the mathematical model for best performance and control of the machine. The obtained simulation results are verified with experimental results. This model can be extended to a range of rotor position where the machine can be switched at decreased and increased inductance region which gives motoring and generating operation mode. [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]

When solving the Laplace equation numerically via computer simulation, in order to determine the field values at the surface of a shape model that represents a field emitter, it is necessary to define a simulation box and, within this, a simulation domain. This domain must not be so small that the box boundaries have an undesirable influence on the predicted field values. A recent paper discussed the situation of cylindrically symmetric emitter models that stand on one of a pair of well-separated parallel plates. This geometry can be simulated by using two-dimensional domains. For a cylindrical simulation box, formulas have previously been presented that define the minimum domain dimensions (MDD) (height and radius) needed to evaluate the apex value of the field enhancement factor for this type of model, with an error-magnitude never larger than a "tolerance" ε tol . This MDD criterion helps to avoid inadvertent errors and oversized domains. The present article discusses (in greater depth than previously) a significant improvement in the MDD method; this improvement has been called the MDD extrapolation technique (MDDET). By carrying out two simulations with relatively small MDD values, it is possible to achieve a level of precision comparable with the results of carrying out a single simulation using a much larger simulation domain. For some simulations, this could result in significant savings of memory requirements and computing time. Following a brief restatement of the original MDD method, the MDDET method is illustrated by applying it to the hemiellipsoid-on-plane and hemisphere-on-cylindrical-post emitter shape models. [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]

This paper aims to improve the transparency of agent-based social simulation (ABSS) models and make it easier for various actors engaging with these models to make sense of them. It studies what ABSS is and juxtaposes its basic conceptual elements with insights from the agency/structure debate in social theory to propose a framework that captures the ‘conceptual anatomy’ of ABSS models in a simple and intuitive way. The five elements of the framework are: agency, social structure, environment, actions and interactions, and temporality. The paper also examines what is meant by the transparency or opacity of ABSS in the rapidly growing literature on the epistemology of computer simulations. It deconstructs the methodological criticism that ABSS models are black boxes by identifying multiple categories of transparency/opacity. It argues that neither opacity nor transparency is intrinsic to ABSS. Instead, they are dependent on research habitus - practices that are developed in a research field that are shaped by structure of the field and available resources. It discusses the ways in which thinking about the conceptual anatomy of ABSS can improve its transparency. [ABSTRACT FROM AUTHOR]

Vacuum carburizing and high-pressure gas quenching process is being widely used in the heat treatment industry. There is an urgent need for a mature technology to predict the influence of carbon content and quenching gas flow on the microstructure and mechanical performance of workpieces. In this paper, a coupling simulation system of the flow field, temperature field, phase field, and stress–strain field was established. And simulations and experiments were carried out for an 18CrNiMo cylindrical sample and a 20CrMnTi gear hub. The results prove that this system can realize the synchronous coupling simulation of the above physical fields, and the simulation results are accurate and applicable to complex shape parts, therefore can guide the design of the process control scheme of the vacuum carburizing and high-pressure gas quenching process. [ABSTRACT FROM AUTHOR]

A new simulation model for the development of gas condensate reservoirs is introduced based on the influence that phase change, non-Darcy flow, and capillary pressure have on the production of gas condensates. The model predicts well performance, including bottom-hole pressure, oil/gas production rate, oil/gas recovery, gaseoil ratio, and the change in produced fluid composition. It also calculates dynamic characters, such as the change of pressure field and oil/gas saturation field during the development of gas condensate reservoirs. The model is applicable to different boundary conditions (both constant-pressure and sealed boundary) and different production modes (both constant-pressure and constant-volume production modes). Model validation attempted using numerical simulation results for sealed boundary conditions with constant-pressure production mode has shown a relatively good match, proving its validity. For constant-pressure boundary conditions with constant-volume production mode, four stages are defined according to the dynamic behavior of production performance in the development of gas condensate reservoirs. [ABSTRACT FROM AUTHOR]

In previous studies, the numerical modeling and analyzing methods onto industrial or vehicle airbags dynamics were revealed to have high accuracy regarding their actual dynamic properties, but there are scarcely airbag stiffness modeling and comfortableness investigations of nursing cushion or mattress airbags. This study constructs a numerical model illustrating the association between the stiffness property and the internal gas mass of the wedge-shaped airbag of nursing appliance, and then the airbag stiffness variation discipline is described based on various inflation volumes. To start with, based on an averaged pressure prerequisite, a dynamic simulation model of the wedge-shaped airbag is established by the fluid cavity approach. For this modeling, the elastic mechanical behaviors of airbag material are determined according to a material constitutive model built by the quasi-static uniaxial tensile test. Besides, verification experiments clarify that the presented modeling method is accurate for airbag stiffness behavior prediction, and then can be effectively applied into design and optimization phases of wedge-shaped airbags. Ultimately, based on the simulation and experimental results, it is found that the wedge-shaped airbag stiffness exhibits a three stages characteristic evolution with the gas mass increase. Then the mathematical relationship between the airbag stiffness and gas mass is obtained by numerical fitting, which provides a vital basis for structural optimization and differentiated control of nursing equipment airbags. [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]

Numerical simulation plays a crucial role in polymer processing. This paper analyzes the extrusion of two rubber blends using the Bird–Carreau viscous model and the Phan‐Thien–Tanner (PTT) viscoelastic model. The study found that wall slip phenomena occurred in both rubber blends when the apparent shear stress exceeded the critical value. Under these conditions, the physical parameters of the two constitutive models, along with the wall slip parameters that describe the degree of rubber sliding, were obtained. This information provided a theoretical basis for the numerical simulation of the extrusion process. The PTT model was found to be superior to the Bird–Carreau rheological model in predicting the rheological behavior of die swell, velocity field, and pressure field distribution in the extrusion process of the two rubber blends. Highlights: Based on the numerical simulation analysis of the capillary extrusion process, we designed a more feasible method for fitting the physical parameters of the constitutive equation and parameters of the Navier slip model and established the foundation for the subsequent numerical simulation of extrusion processing.Phan‐Thien–Tanner model is proved to be the best candidate for predicting the extrusion of rubber blends with high Mooney viscosity, including die swell, velocity, and pressure distribution.Demonstrates that wall slip is an important factor in rubber extrusion.Combining simulation results with experimental data improves the accuracy and predictability of the simulation. [ABSTRACT FROM AUTHOR]

In this paper, a potential use of the basic parameters of a road collision in a forensic activity was analyzed. A selected case of a frontal, eccentric, and oblique collision between two motor vehicles was analyzed from the point of view of both a computer simulation and a model. The case has been presented as an attempt to identify the collision parameters necessary to conduct the analytical calculations useful in analyzing specific road accidents. The simulation results were obtained in V-SIM software, which is widely used in collision reconstructions by forensic experts and appraisers. It was further analyzed from the point of view of a mathematical model, with the use of the force–impulse method and avoiding the use of the coefficients of restitution in the normal and tangential directions versus the adopted coordinate frame. In the analytical calculations, apart from the masses and the velocities of vehicles, the collision angles and the vicarial coefficient of adhesion between the colliding vehicles (µ) are also important. The approach presented in the article enables an expert to verify the obtained results of a computer program simulation. [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]

Cyclic steam stimulation (CSS) is successfully applied to increase heavy oil recovery in heavy oil reservoirs in Bohai Bay, China. However, during the CSS processes, hydrogen sulfide (H2S) was detected in some heavy oil reservoirs. The existing literature mainly focused on the H2S generation of onshore heavy oil. There is no concrete experimental data available, especially about the level of H2S generation during CSS of offshore heavy oil. In addition, there is still a lack of effective reaction kinetic models and numerical simulation methods to simulate H2S generation during the CSS of offshore heavy oil. Therefore, this paper presents a case study from Bohai Bay, China. First, the laboratory aquathermolysis tests were conducted to simulate the gases that are produced during the CSS processes of heavy oil. The effects of the reaction temperature and time on the H2S generation were studied. Then, a one-dimensional CSS experiment was performed to predict H2S generation under reservoir conditions. A kinetic model for the prediction of H2S generation during the CSS of heavy oil was presented. The developed model was calibrated with the experimental data of the one-dimensional CSS experiment at a temperature of 300 °C. Finally, a reservoir model was developed to predict H2S generation and investigate the effects of soaking time, steam quality, and steam injection volume on H2S generation during CSS processes. The results show that the H2S concentration increased from 0.77 ppm in the first cycle to 1.94 ppm in the eighth cycle during the one-dimensional CSS experiment. The average absolute error between the measured and simulated H2S production was 12.46%, indicating that the developed model can accurately predict H2S production. The H2S production increase with soaking time, steam quality, and steam injection volume due to the strengthened aquathermolysis reaction. Based on the reservoir simulation, the H2S production was predicted in the range of 228 m3 to 2895 m3 within the parameters of this study. [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]

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]

In this paper, we consider the evolution of an ensemble of noninteracting classical particles confined in a closed region. Each one of these particles experiences several elastic collisions with a rigid-smooth oval-like boundary. As known in the literature, numerical simulations for this kind of system demand too much time, mostly because of the time spent in solving transcendental equations. To deal with that, we highlight an alternative approach to speed up the search of solutions for the transcendental equations via the tangent method, which has proved to be a faster way to solve this problem when compared with other methods, like the bisection one. The methods applied here are generic and can be used or adapted for other billiard boundaries. [ABSTRACT FROM AUTHOR]

Background: The overcrowded patients, which cause the long waiting time in public hospitals, become significant problems that affect patient satisfaction toward the hospital. Particularly, the bottleneck usually happens at front-end departments (e.g., the triage and medical record department) as every patient is firstly required to visit these departments. The problem is mainly caused by ineffective resource management. In order to support decision making in the resource management at front-end departments, this paper proposes a framework using simulation and multi-objective optimization techniques considering both operating cost and patient satisfaction.Methods: To develop the framework, first, the timestamp of patient arrival time at each station was collected at the triage and medical record department of Thammasat University Hospital in Thailand. A patient satisfaction assessment method was used to convert the time spend into a satisfaction score. Then, the simulation model was built from the current situation of the hospital and was applied scenario analyses for the model improvement. The models were verified and validated. The weighted max-min for fuzzy multi-objective optimization was done by minimizing the operating cost and maximizing the patient satisfaction score. The operating costs and patient satisfaction scores from various scenarios were statistically compared. Finally, a decision-making guideline was proposed to support suitable resource management at the front-end departments of the hospital.Result: The three scenarios of the simulation model were built (i.e., a real situation, a one-stop service, and partially shared resources) and ensured to be verified and valid. The optimized results were compared and grouped into three situations which are (1) remain the same satisfaction score but decrease the cost (cost decreased by 2.8%) (2) remain the same satisfaction score but increase the cost (cost increased up to 80%) and (3) decrease the satisfaction score and decrease the cost (satisfaction decreased up to 82% and cost decreased up to 59%). According to the guideline, the situations 1 and 3 were recommended to use in the improvement and the situation 2 was rejected.Conclusion: This research demonstrates the resource management framework for the front-end department of the hospital. The experimental results imply that the framework can be used to support the decision making in resource management and used to reduce the risk of applying a non-improvement model in a real situation. [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]

Modelling the human cardiorespiratory system using computer simulation tools can serve to help physicians to comprehend the causes and development of cardiorespiratory diseases. The objective of this paper is to develop an integrated model of the cardiovascular and respiratory systems, along with their intrinsic control mechanisms, by combining analogous hydraulic-electric and diffusion-electric circuits, respectively. This modelling task is performed in object-oriented language in SIMSCAPE using the physical interconnected components to define the underlying dynamic equations. Simulation steady state results under rest and under variable physical exercise conditions, as well as under limiting conditions show a high qualitative agreement with clinical observations reported in literature. This object-oriented modelling approach, based on the combined use of electrical analogies, proves to be avaluable tool as a test bench for different strategies aimed to qualitative prediction of the effects of cardiorespiratory interactions during exercise, thus avoiding the formulation of complex mathematical models. [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]

This paper confronts the numerical simulation of steady flows of fluid layers through channels of varying bed and width. The fluid consists of two immiscible fluid layers with constant density, and it is assumed to be of a one-dimensional shallow flow. The governing equation is a coupled system of two-layer shallow water models. In this paper, we apply a direct extension of the momentum conserving scheme previously used for solving the one layer shallow water equations. Computations of various steady-state solutions are used to demonstrate the performance of the proposed numerical scheme. Under the influence of a given flow rate, the numerical steady interface is generated in a channel topography with a hump. The results obtained confirm the analytic steady interface of the two-layer rigid-lid model. Furthermore, the same scheme was used with an additional artificial damping to simulate the maximal exchange flow in channels of varying width. The numerical steady interface agreed well with the analytical steady solutions. [ABSTRACT FROM AUTHOR]

Background: In many clinical applications, evolution of a longitudinal marker is censored by an event occurrence, and, symmetrically, event occurrence can be influenced by the longitudinal marker evolution. In such frameworks joint modeling is of high interest. The Joint Latent Class Model (JLCM) allows to stratify the population into groups (classes) of patients that are homogeneous both with respect to the evolution of a longitudinal marker and to the occurrence of an event; this model is widely employed in real-life applications. However, the finite sample-size properties of this model remain poorly explored.Methods: In the present paper, a simulation study is carried out to assess the impact of the number of individuals, of the censoring rate and of the degree of class separation on the finite sample size properties of the JLCM. A real-life application from the neurology domain is also presented. This study assesses the precision of class membership prediction and the impact of covariates omission on the model parameter estimates.Results: Simulation study reveals some departures from normality of the model for survival sub-model parameters. The censoring rate and the number of individuals impact the relative bias of parameters, especially when the classes are weakly distinguished. In real-data application the observed heterogeneity on individual profiles in terms of a longitudinal marker evolution and of the event occurrence remains after adjusting to clinically relevant and available covariates; CONCLUSION: The JLCM properties have been evaluated. We have illustrated the discovery in practice and highlights the usefulness of the joint models with latent classes in this kind of data even with pre-specified factors. We made some recommendations for the use of this model and for future research. [ABSTRACT FROM AUTHOR]

The paper deals with the study of deformations within the roller screw from the feed system, used in ultrasonically aided micro electrical discharge machining (µEDM+US). The study is focused on the deformation of the roller screw's threads in contact with the three rollers, components of the nut, in two constructive variants. The contact surfaces are determined and isolated on the roller screw, which is then introduced in a numerical simulation module, to calculate its deformation in different positions of the nut. The results pointed out that the load deformations of the roller screw are less than 0.1 µm, so µEDM+US precision would not be affected significantly. [ABSTRACT FROM AUTHOR]

In this paper, two new climate change mathematical models are extended using the stochastic-deterministic piecewise hybrid fractional derivatives, where the hybrid fractional order operator is applied to extend the deterministic model and the fractional Brownian motion operator is applied to extend the stochastic model. The steady states analysis of the propsed models are discussed. Two numerical methods are constructed to study the behavior of the proposed models. These methods are Caputo proportional constant Adams-Bashfourth fifth step method for solving the hyprid fractional deterministic model and the modified nonstandard Euler Maruyama technique to study numerically the fractional Brownian motion stochastic model. Several numerical test examples are given to demonstrate the efficiency of the methods and to support the theoretical 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]

Noise pollution is a major problem nowadays. In urban context, road traffic is the main source of noise pollution. People directly exposed to road traffic noise suffer from moderate to severe annoyance, headache, stress, feeling of exhaustion, and reduced work performance efficiency. As the sources and severity of noise pollution continue to grow, new approaches are needed to reduce the exposure. In this research, noise abatement has been investigated using a computer simulation model (SoundPLAN essential 4.0). Noise maps were developed using SoundPLAN essential 4.0 software. Noise maps are very beneficial to identify the impact of noise pollution. Data required for mapping are noise data (LAeq), road inventory data, geometric features of mapping area, category wise traffic counts, category wise vehicle speed, meteorological data such as wind velocity, humidity, temperature, air pressure. LAeq observed on all locations of the Central zone of Surat city was greater than the prescribed central pollution control board (CPCB) limits during day time and night time. This paper is focused on using acoustic software for the simulation and calculation methods of controlling the traffic noise. According to the characteristics of traffic noise and the techniques of noise reduction, road traffic noise maps were developed using SoundPLAN essential 4.0 software to predict the scope of road traffic noise. On this basis, four reasonable noise control schemes were used to control noise, and the feasibility and application effect of these control schemes can be verified by using the method of simulation modelling. The simulation results show that LAeq is reduced by up to 5 dB(A). The excess noise can be efficiently reduced by using the corresponding noise reduction methods. [ABSTRACT FROM AUTHOR]

The predator-prey model is powerful mathematical tool to describe the dynamics of biological systems and promote research on biological populations. In this paper, we present a lumped mass finite element method for solving the predator-prey models on surfaces. The main purpose of the proposed method is to overcome the difficulty of the positivity preservation of the solutions. Based on positivity preservation results, we investigate the stabilities of semi-discrete and fully discrete approximations. Besides, numerical simulations are considered to illustrate the feasibility of the numerical method by convergence tests. Two classical phenomena of the predator-prey model are simulated on three different implicit surfaces. [ABSTRACT FROM AUTHOR]

This paper discusses a prominent way in which social simulations can contribute (and have contributed) to the advance of science; namely, by refuting some of our incorrect beliefs about how the real world works. More precisely, social simulations can produce counter-examples that reveal something is wrong in a prevailing scientific assumption. Indeed, here we argue that this is a role that many well-known social simulation models have played, and it may be one of the main reasons why such well-known models have become so popular. To test this hypothesis, here we examine several popular models in the social simulation literature and we find that all these models are most naturally interpreted as providers of compelling and reproducible (computer-generated) evidence that refuted some assumption or belief in a prevailing theory. By refuting prevailing theories, these models have greatly advanced science and, in some cases, have even opened a new field of research. [ABSTRACT FROM AUTHOR]