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To enhance the quality and efficiency of computer-enabled generation of papers for Test for English Majors Band 8 (TEM-8), a paper generation model supported by sparrow search algorithm-genetic algorithm was studied. First, a simplified test paper generation mathematical model was set up after analyzing and studying types and characteristics of TEM-8 tasks. In the model, quantity, type, difficulty, discrimination degree, scores, exposure, and answering time of test questions were taken into consideration. To enhance the optimizing effect of the genetic algorithm for searching test questions, the traditional genetic algorithm was improved by introducing the sparrow search algorithm into the model to achieve a better crossover rate, variance rate, optimization precision, and speed of the genetic algorithm. A new sparrow search-genetic algorithm (SSA-GA) was designed, and the optimizing effect of SSA-GA was verified to be ideal through optimizing six standard test functions. Then, SSA-GA was applied to conduct experimentation with test paper generation, and comparison with traditional genetic algorithms was also made. The values of best and average fitness of SSA-GA were better than those of the traditional genetic algorithm (GA) in the paper generation. Exposure rate and success rate in TEM-8 paper generation of SSA-GA were higher than those of traditional GA in TEM-8 paper generation. Results showed that the studied SSA-GA could implement test paper generation with higher speed and better quality. [ABSTRACT FROM AUTHOR]

The influence of nonuniform aging has not been considered in the prediction of the frequency domain spectroscopy (FDS) of the transformer oil-paper insulation (OPI) when using the finite element method (FEM). Given this issue, the modified simulation model was constructed based on the XY model and FEM. In the current work, the dielectric response property of the pressboards with different aging conditions in the modified model was characterized by its dielectric response parameters measured in the lab. Then the modified simulation model constructed in a 3-D system would be applied to study the effect of both nonuniform aging and the axial geometry on the FDS of OPI. Finally, the feasibility of the proposed models was verified by comparing the measured FDS and the predicted FDS. This article is expected to provide a model for predicting the FDS of the transformer OPI including the effect of nonuniform aging. [ABSTRACT FROM AUTHOR]

Between 2014 and 2018, the National Oceanic and Atmospheric Administration conducted the NOAA Satellite Observing System Architecture (NSOSA) study to plan for the next generation of operational environmental satellites. The study generated some important questions that could be addressed by observing system simulation experiments (OSSEs). This paper describes a series of OSSEs in which benefits to numerical weather prediction from existing observing systems are combined with enhancements from potential future capabilities. Assessments include the relative value of the quantity of different types of thermodynamic soundings for global numerical weather applications. We compare the relative impact of several sounding configuration scenarios for infrared (IR), microwave (MW), and radio occultation (RO) observing capabilities. The main results are 1) increasing the revisit rate for satellite radiance soundings produces the largest benefits but at a significant cost by requiring an increase in the number of polar-orbiting satellites from 2 to 12; 2) a large positive impact is found when the number of RO soundings per day is increased well beyond current values and other observations are held at current levels of performance; 3) RO can be used as a mitigation strategy for lower MW/IR sounding revisit rates, particularly in the tropics; and 4) smaller benefits result from increasing the horizontal resolution along the track of the satellites of MW/IR satellite radiances. Furthermore, disaggregating IR and MW instruments into six evenly distributed sun-synchronous orbits is slightly more beneficial than when the same instruments are combined and collocated on three separate orbits. SIGNIFICANCE STATEMENT: The results of this paper are significant because they inform decision-makers about the future configuration of the NOAA's environmental satellite constellation, which serves millions of diverse users. [ABSTRACT FROM AUTHOR]

This paper presents a model for determining the availability of continuous systems at open pits using the neuro-fuzzy system. The concept of availability is divided into partial indicators (synthetic indicators and sub-indicators). The presented model in relation to already existing models for determining availability uses a combination of the advantages of artificial neural networks and fuzzy logic. The case study addressed the I ECC (bucket wheel excavator–conveyors–crushing plant) system of the open pit Drmno, Kostolac. In this paper, in addition to the ANFIS model for determining the availability of continuous systems, a simulation model was developed. The obtained results of the ANFIS model were verified with the help of a simulation model that uses certain assumptions about the distribution of failures. This paper was created as a result of several years of field and theoretical research into the availability of continuous systems in open pits, and completes a cycle that consists of several published articles on the subject of modeling the behavior of these systems in real time using a time picture of the state, expert assessment, simulation and AI models, while respecting the multidisciplinarity of the problem (mining technological, mechanical, and information technological aspects). The developed ANFIS model is a key instrument for improving operational efficiency and resource management in the mining sector. Its ability to accurately predict the availability of the ECC system brings not only operational benefits through reduced downtime and optimized maintenance, but also a potential reduction in overall costs at coal open pits. Such an innovative model marks a significant step forward in the mining industry, especially when it comes to continuous systems in coal open pits. [ABSTRACT FROM AUTHOR]

Gold tube thermal simulation experiments represent a pivotal tool in exploring hydrocarbon generation kinetics in hydrocarbon source rocks. Compared to other reaction systems, the reaction environment and the pyrolysis product composition within the gold tube display a greater resemblance to actual geological conditions, especially for coal-based hydrocarbon rocks with poor hydrocarbon removal capacity. The kerogen is in close contact with various pyrolysis products and reacts with each other in the gold tube. Researchers have carried out extensive research and application in hydrocarbon generation kinetics based on gold tubes in recent years. But a systematic and comprehensive summary of these studies is lacking. This paper provides a review of the kinetic study based on golden tubes in recent years from the perspectives of research objects, influencing factors, applications and problems. The main targets of hydrocarbon generation kinetics based on gold tubes include CH4, C1-5, C8+ and so on. Elucidating the kinetics of diverse pyrolysis products aids comprehension of the mechanism of organic matter pyrolysis. Reaction condition, minerals and organic structure all influence hydrocarbon production kinetics. Clarifying the effects of these influencing factors is of great importance in understanding the pyrolysis mechanism of hydrocarbon source rocks and pyrolysis research in the domain of hydrocarbons. Golden tube-based kinetic studies of hydrocarbon production have good potential application, not only in determining the hydrocarbon generation history of hydrocarbons in the study area, but also in studying the genesis, origin, and reservoir formation mode of natural gas. This paper also summarizes some problems and solutions of the gold tube hydrocarbon generation kinetics, such as the inhomogeneity of the samples, the difference between the gold tube system and natural conditions, and the determination of the time point of oil secondary cracking. Continuous optimization of the solution enhances the authenticity of the golden tube simulation experiment. This review aims to offer a theoretical foundation and research suggestions for investigating pyrolysis kinetics of hydrocarbon source rocks and hydrocarbons based on golden tubes. [ABSTRACT FROM AUTHOR]

The paper presents a fault region identification method for the active distribution network (ADN) with limited PMU. First, PMU configuration and region division strategies are proposed based on the network topology. Next, the difference in three-phase current variations between the normal and fault regions of the ADN is analyzed. A multi-dimensional state monitoring matrix is built using the measured current data. The spectral norm ratio coefficient is constructed based on the 2-norm to lower the complexity of the multi-dimensional state monitoring matrix and quantify the difference in state changes before and after the fault occurs in each region. Then, the fault region is identified by combining each region's spectral norm ratio coefficient and the change of the current phase. Finally, an IEEE 33-node simulation model is created to simulate faults under different working conditions. According to the simulation results, the suggested approach is less impacted by fault type, neutral point grounding mode, and transition resistance. Furthermore, even if the communication does not match the rigorous synchronization requirements, the proposed method can still complete the fault identification of the distribution network correctly and has high robustness. [ABSTRACT FROM AUTHOR]

This paper constructs a data-driven demand purchasing confidence rule-based model based on the theory of evidential reasoning to address the problem of purchasing decision bias in which the decision maker anchors the prior demand. First, we apply a synthetic algorithm to reason about the confidence structure distribution of the purchasing decision and then iteratively optimize the purchasing quantity according to the confidence structure distribution to minimize the cost loss function. Finally, we choose the average cost loss and service level value as the evaluation indexes to explore the purchasing confidence rule model. The simulation shows that compared with the expected purchasing decision based on the stochastic cumulative distribution function, the decision based on the confidence structure distribution can reduce the purchasing decision bias, manifested in the lower mean cost loss and a higher mean value of service level. Sensitivity analyses of the number of rules, product shelf life, and critical values show that the purchasing confidence rule base is highly adaptable. [ABSTRACT FROM AUTHOR]

This paper presents a simulation model for a preemptive transportation system where vehicles can have tasks dynamically reassigned to optimize overall efficiency. The model, built using Flexsim software, includes 9 storage areas and 8 vehicles. Exponential distributions, validated with real logistics warehouse data, generate stochastic task arrivals. Recursive logic implements the preemption algorithm. Comparative analysis over a 10-hour duration shows that the preemptive mode increases average transport volume by 13 % and reduces vehicle travel distance by 13 % compared to a non-preemptive baseline. The results demonstrate the value of preemptive transportation in enhancing system responsiveness and operational efficiency. [ABSTRACT FROM AUTHOR]

This paper presents the observational, remote sensing, and model simulation used to analyze southern Brazil Antarctic ozone hole influence (SBAOHI) events that occurred between 2005 and 2014. To analyze it, we use total ozone column (TOC) data provided by a Brewer spectrophotometer (BS) and the OMI (Ozone Monitoring Instrument). In addition to the AURA/MLS (Microwave Limb Sounder) instrument, satellite ozone profiles were utilized with DYBAL (Dynamical Barrier Localization) code in the MIMOSA (Modélisation Isentrope du Transport Mésoéchelle de l'Ozone Stratosphérique par Advection) model Potential Vorticity (PV) fields. TOC has 7.0 ± 2.9 DU reductions average in 62 events. October has more events (30.7%). Polar tongue events are 19.3% in total, being more frequently observed in October (50% of cases), with medium intensity (58.2%), and in the stratosphere medium levels (55.0%). Already, polar filament events (80.7%) are more frequent in September (32.0%), with medium intensity (42.0%), and stratosphere medium levels (40.7%). [ABSTRACT FROM AUTHOR]

A chemo-mechanical model is developed to investigate the effects on the stress development of the coating of polycrystalline Ni-rich LiNixMnyCozO2 (x ⩾ 0.8) (NMC) particles with poly(3,4-ethylenedioxythiophene) (PEDOT). The simulation results show that the coating of primary NMC particles significantly reduces the stress generation by efficiently accommodating the volume change associated with the lithium diffusion, and the coating layer plays roles both as a cushion against the volume change and a channel for the lithium transport, promoting the lithium distribution across the secondary particles more homogeneously. Besides, the lower stiffness, higher ionic conductivity, and larger thickness of the coating layer improve the stress mitigation. This paper provides a mathematical framework for calculating the chemo-mechanical responses of anisotropic electrode materials and fundamental insights into how the coating of NMC active particles mitigates stress levels. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient method for quantifying the stratigraphic uncertainties and modeling the geological formations based on boreholes. Two Markov chains are used to describe the soil transitions along different directions, and the transition probability matrices (TPMs) of the Markov chains are analytically expressed by copulas. This copula expression is efficient since it can represent a large TPM by a few unknown parameters. Due to the analytical expression of the TPMs, the likelihood function of the Markov chain model is given in an explicit form. The estimation of the TPMs is then re-casted as a multi-objective constrained optimization problem that aims to maximize the likelihoods of two independent Markov chains subject to a set of parameter constraints. Unlike the method which determines the TPMs by counting the number of transitions between soil types, the proposed method is more statistically sound. Moreover, a random path sampling method is presented to avoid the directional effect problem in simulations. The soil type at a location is inferred from its nearest known neighbors along the cardinal directions. A general form of the conditional probability, based on Pickard's theorem and Bayes rule, is presented for the soil type generation. The proposed stratigraphic characterization and simulation method is applied to real borehole data collected from a construction site in Wuhan, China. It is illustrated that the proposed method is accurate in prediction and does not show an inclination during simulation. [ABSTRACT FROM AUTHOR]

Reference stations constitute important elements within the global navigation satellite system (GNSS) infrastructure, as they provide valuable measurements for performance monitoring. For high-quality measurements from such stations, local error sources should be properly characterized and compensated for or minimized. Multipath remains a major contributor to these errors. In severe occurrences, multipath can cause critical errors in sensitive systems such as those utilized for code-dependent applications. This paper discusses a method for GNSS multipath characterization in challenging installation scenarios, based on a dual-polarization antenna and its integration in a hybrid measurement-simulation framework. A dedicated dual-polarized probe, which houses both an effective geodetic antenna and a multipath-susceptible antenna, was designed, manufactured, and assessed. The dual-sensing nature of the probe allows auxiliary information to be acquired about multipath generated by nearby objects and can be used to infer a plausible range of expected multipath-induced code error at a GNSS sensor station. In addition, a ray-tracing method is discussed, in which antenna measurements are integrated into digital-twin simulations of installations for characterizing multipath conditions. Finally, this study demonstrates that by combining the DPA with digital-twin simulations, it is possible to predict multipath error bounds at an installation in advance. This combined technique presents a flexible tool that is useful for planning system performance with respect to multipath, site layout/selection, and even optimal receiving antenna placement at a given installation. The proposed simulative method is validated through field experiments, and tests with commercial geodetic-grade antennas are presented to confirm the capability of this method to predict their performance ranges. [ABSTRACT FROM AUTHOR]

This paper presents a dynamic-phasor-based, average-value modeling method for power systems with extensive converter-tied subsystems. In the proposed approach, the overall system model is constructed using modular functions, interfacing both conventional and converter-tied resources. Model validation is performed against detailed Electro-Magnetic Transient (EMT) simulations. The analytical capabilities offered by the proposed modeling method are demonstrated on a modified IEEE 9-bus system. A Graphics Processing Unit (GPU)-based parallel computing approach for the solution of the resulting model is presented and exemplified on a modified IEEE 118-bus system, showing significant improvements in computing efficiency over EMT solvers. A co-simulation approach using a Central Processing Unit (CPU) and a GPU is also presented and exemplified using a modified version of the IEEE 118-bus system, demonstrating the model's parallelization. [ABSTRACT FROM AUTHOR]

As one of the four major bay areas in the world, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a highly integrated mega urban agglomeration and its unparalleled urbanization has induced prominent land contradictions between humans and nature, which hinders its sustainability and has become the primary concern in this region. In this paper, we probed the historical characteristics of land use and land cover change (LUCC) in the GBA from 2005 to 2015, and forecasted its future land use pattern for 2030, 2050, and 2070, using a cellular automata–Markov (CA–Markov) model, under three typical tailored scenarios, i.e., urban development (UD), cropland protection (CP), and ecology security (ES), for land use optimization. The major findings are as follows: (1) The encroachments of build-up land on the other land uses under rapid urbanization accounted for the leading forces of LUCCs in the past decade. Accordingly, the urban sprawl was up to 1441.73 km2 (23.47%), with cropland, forest land, and water areas reduced by 570.77 km2 (4.38%), 526.05 km2 (1.76%), and 429.89 km2 (10.88%), respectively. (2) Based on the validated CA–Markov model, significant differences are found in future land use patterns under multiple scenarios, with the discrepancy magnified over time and driven by different orientations. (3) Through comprehensive comparisons and tradeoffs, the ES scenario mode seems optimal for the GBA in the next decades, which optimizes the balance between socio-economic development and ecological protection. These results serve as an early warning for future land problems and can be applied to land use management and policy formulation to promote the sustainable development of the GBA. [ABSTRACT FROM AUTHOR]

The launcher recovery method known as 'In-Air Capturing' is an innovative approach where a winged rocket stage is captured mid-air by an aircraft and subsequently towed back to the launch site. To achieve this, a capturing device attached to a tether is released from the towing aircraft. This device autonomously connects the reusable launch vehicle to the aircraft, while the two vehicles are in proximity. The tether's flexible dynamics have a strong influence on the maneuverability of the capturing device. Thus, it is critical to model the dynamics of the tether to get a realistic understanding and to evaluate feasibility of the concept. However, precise modelling and control of highly flexible systems with large deformations is both challenging and computationally intensive. For engineering applications which involve closed-loop simulations, finding a trade-off between accuracy and computational effort is crucial. In this paper, the tether is modelled as a discretized chain of rigid bodies connected by rotational springs at the joints. The tether along with the capture system is integrated in a simulation model and open loop tests are performed to analyse the system characteristics. The tether properties are studied to find a suited configuration for 'In-Air Capturing'. • Multibody modelling approach for long cable like bodies with large deformation. • Capture system dynamics for the unique 'In-Air Capturing' launcher recovery concept. • Dynamic modelling for the complete capturing system including towing aircraft, capturing device and tether. • Assessment of tether properties suited for 'In-Air Capturing' with sensitivity studies. [ABSTRACT FROM AUTHOR]

The global navigation satellite system radio occultation (GNSS-RO) is an important means of space-based meteorological observation. It is necessary to test the Global Navigation Satellite System Occultation signal receiver on the ground before the deployment of space-based occultation detection systems. The current approach of testing the GNSS signal receiver on the ground is mainly the mountaintop-based testing approach, which has problems such as high cost and large simulation error. In order to overcome the limitations of the mountaintop-based test approach, this paper proposes an accurate, repeatable, and controllable GNSS atmospheric occultation simulation system and builds a load performance evaluation approach based on the ground-based GNSS atmospheric occultation simulation system on the basis of it. The GNSS atmospheric occultation simulation system consists of the visualization and interaction module, the GNSS-RO simulation signal generation module, the GNSS-RO simulator module, the GNSS-RO signal receiver module, and the GNSS-RO inversion and evaluation module, combined with the preset atmospheric model to generate GNSS-RO simulation signals with a high degree of simulation, and comparing the atmospheric parameters of the inversion performance of the GNSS-RO signal receiver with the parameters of the preset atmospheric model to obtain the error data. The overall performance of the GNSS-RO signal receiver can be evaluated based on the error information. The novel approach to evaluate the GNSS-RO signal receiver performance proposed in this paper is validated by using the FY-3E (FengYun-3E) receiver qualification parts that have been verified in orbit, and the results confirm that the approach can meet the requirements of the GNSS-RO receiver performance test. This study shows that the novel approach to evaluate the GNSS-RO signal receiver performance in terms of the ground-based atmospheric occultation simulation system can efficiently and accurately be used to carry out the receiver test and provides an effective solution for the ground-based test of GNSS-RO signal receivers. [ABSTRACT FROM AUTHOR]

With the advancement of IT technology, intelligent devices such as autonomous vehicles, unmanned equipment, and drones are rapidly evolving. Consequently, the proliferation of defense systems based on these technologies is increasing worldwide. In response, the U.S. Department of Defense is implementing the RMF (Risk Management Framework) to ensure the cybersecurity of defense systems and conducting cybersecurity T&E (test and evaluation) concurrently. However, RMF and cybersecurity T&E conducted during the acquisition phase of defense systems often result in fragmented cybersecurity assessments, excluding the operational environment of the defense systems. This omission fails to account for the complex network integration, data exchange functionalities, and mission-specific requirements in actual cyber attack scenarios. For these reasons, vulnerabilities in defense systems that remain unidentified during the acquisition phase can potentially pose significant cybersecurity threats during operational phases, necessitating substantial costs and efforts for remediation. Therefore, this paper proposes a mission-based cybersecurity T&E model using a Multi-Cyber Range to effectively apply these two systems in a practical manner. The Multi-Cyber Range integrates independently operated cyber ranges into a network to expand the evaluation environment, which better reflects the mission environment of defense systems. The proposed model's effectiveness is validated using a cyber attack simulation system targeting a virtualized arbitrary defense system. This paper not only presents an enhanced model for mission-based cybersecurity T&E, but also contributes to the advancement of cybersecurity T&E methodologies by providing a concrete application process. [ABSTRACT FROM AUTHOR]

The yield of energy crops has been widely questioned by the public, but few researchers have analyzed the yield prediction of these crops, which has greatly limited their distribution and use. Based on this, in this study, a machine learning algorithm was used to design an energy crop yield simulation and prediction system, and this system was used to analyze the yields of four common energy crops. First the factors that affect the yield of energy crops are discussed, and then, the analysis of the machine learning algorithm and its application in the yield prediction of energy crops is presented, followed by an introduction to the framework of the energy crop yield simulation and prediction system. At the end of this paper, the effect of the energy crop yield simulation and prediction system was analyzed, and the feasibility conclusion was finally reached. The energy crop yield simulation and prediction system designed in this paper can greatly improve the accuracy of yield prediction when forecasting and analyzing energy crop yields. The sugarcane yield measured by the back propagation (BP) neural network model was 8694 kg/hm2, with a relative deviation of 0.86% from the actual. The BP neural network algorithm is widely used in energy crop yield prediction, and can greatly improve the accuracy. In the future, with the maturity and development of a BP neural network algorithm, it would promote the development of crop yield prediction. [ABSTRACT FROM AUTHOR]

The article is an editorial introducing a special issue of the scientific journal Axioms titled "Mathematical Models and Simulations." The issue contains 13 papers that cover various mathematical models and simulations in fields such as physics, biology, finance, and engineering. The papers explore different types of mathematical models, including deterministic and stochastic models, and discuss their applications and numerical simulations. The authors provide a brief overview of each paper, highlighting their main findings and methodologies. The article aims to provide library patrons with a concise summary of the special issue, allowing them to decide if they want to explore the individual papers further. [Extracted from the article]

In this paper, we improved a mathematical model of monkeypox disease with a time delay to a crossover model by incorporating variable-order and fractional differential equations, along with stochastic fractional derivatives, in three different time intervals. The stability and positivity of the solutions for the proposed model are discussed. Two numerical methods are constructed to study the behavior of the proposed models. These methods are the nonstandard modified Euler Maruyama technique and the nonstandard Caputo proportional constant Adams-Bashfourth fifth step method. Many numerical experiments were conducted to verify the efficiency of the methods and support the theoretical results. This study's originality is the use of fresh data simulation techniques and different solution methodologies. [ABSTRACT FROM AUTHOR]

Simulation models are used to emulate real-world phenomena, and errors are inevitable in the numerical computation process. Owing to that, simulation models need to be verified and validated to ensure the models and their implementations are correct. In this paper, V&V has been done for the micro3d discrete dislocation dynamics (DDD) model by comparing simulation results with corresponding theory, including any analytical solutions, other numerical solutions and experimental data. DDD simulations are a powerful simulation methodology that can help researchers better understand the plastic behavior of crystalline materials. In this study, parametric analyses for DDD simulations parameters have been performed. In addition, simulation results are verified and validated. [ABSTRACT FROM AUTHOR]

Virtual synchronous generator (VSG) technology has achieved some results in distributed generation networks and enhanced system stability. For problems that may occur in the system due to ignoring parameter linkages, this paper designs a synergistic controller that establishes the connection between the active frequency and the reactive voltage control loop based on synergy theory. As the output of the synergetic controller, the derived control law u is added to the power frequency control in the form of negative feedback. Two disturbance forms, a step disturbance, and a three-phase short-circuit fault, are set up. The conventional droop control and synergetic droop control results are compared using a MATLAB simulation system. Then, the system parameter variations were studied and analyzed, and the sensitivity of the control system with different values of parameters K1, K2, and K3 in the case of a three-phase short circuit was analyzed, which provides a reference guide for selecting parameters in later control optimization. Finally, the control effectiveness of a multi-machine VSG system was tested. The simulation results show that the proposed method has a pronounced effect on making the system stabilize quickly, which illustrates the effectiveness of this technique. [ABSTRACT FROM AUTHOR]

Earthquake hazards may cause a significant loss to urban hospital network system (UHNS), including hospitals and medical transportation networks. As such, systematic seismic resilience assessment of such systems is of paramount importance to reduce loss and optimize casualty care during earthquakes. For that purpose, this paper proposes a novel method for assessing the seismic resilience of UHNS that considers the logical dependencies or coupling among the system's components, such as the casualty sources, the hospitals and the medical transportation networks. A resilience index is defined as the ratio between the average "shortest" time for a casualty to receive medical treatment before and after an earthquake. The time consists of both transportation time to a hospital and queuing time at the hospital. To obtain the shortest time, a real-time simulation model is proposed that considers the casualty sources, the changes in road traffic, the updates of Origin-Destination (OD) matrix for transportation time, the modifications of waiting time in hospital, the path reselection by casualty, and the changes in functionalities of bridges, hospitals and roads. The functionalities are obtained by analyzing fragility models, calculating residual functionality and estimating functionality recovery times. To calculate the fragilities of bridges and hospitals, a refined nonlinear finite element (FE) analysis is performed based on a general FE software, OpenSees, and the damages are obtained for various structural and nonstructural components, e.g. column, stairs and CT scanner of hospitals, as well as piers, bearings and abutments of bridges. The proposed method is demonstrated in a seismic resilience assessment of a realistic UHNS in Xiamen city of China and provides valuable references to assessments of seismic resilience of UHNS. [ABSTRACT FROM AUTHOR]

Misinformation has posed significant threats to all aspects of people's lives. One of the most active areas of research in misinformation examines how individuals are misinformed. In this paper, we study how and to what extent agents are misinformed in an extended bounded confidence model, which consists of three parts: (i) online selective neighbors whose opinions differ from their own but not by more than a certain confidence level; (ii) offline neighbors, in a Watts–Strogatz small-world network, whom an agent has to communicate with even though their opinions are far different from their own; and (iii) a Bayesian analysis. Furthermore, we introduce two types of epistemically irresponsible agents: agents who hide their honest opinions and focus on disseminating misinformation and agents who ignore the messages received and follow the crowd mindlessly. Simulations show that, in an environment with only online selective neighbors, the misinforming is more successful with broader confidence intervals. Having offline neighbors contributes to being cautious of misinformation, while employing a Bayesian analysis helps in discovering the truth. Moreover, the agents who are only willing to listen to the majority, regardless of the truth, unwittingly help to bring about the success of misinformation attempts, and they themselves are, of course, misled to a greater extent. [ABSTRACT FROM AUTHOR]

Non-stationary methods of flood frequency analysis are widespread in research but rarely implemented by practitioners. One reason may be that research papers on non-stationary statistical models tend to focus on model fitting rather than extracting the sort of results needed by designers and decision makers. It can be difficult to extract useful results from non-stationary models that include stochastic covariates for which the value in any future year is unknown. We explore the motivation for including such covariates, whether on their own or in addition to a covariate based on time. We set out a method for expressing the results of non-stationary models as an integrated flow estimate, which removes the dependence on the covariates. This can be defined either for a particular year or over a longer period of time. The methods are illustrated by application to a set of 375 river gauges across England and Wales. We find annual rainfall to be a useful covariate at many gauges, sometimes in conjunction with a time-based covariate. For estimating flood frequency in future conditions, we advocate exploring hybrid approaches that combine the best attributes of non-stationary statistical models and simulation models that can represent changes in climate and river catchments. [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]

In the era of self-media, the spontaneity and anonymity of information dissemination have led to a surge in rumors, posing significant challenges to cybersecurity. This paper introduces a novel dual-layer V R − S H I 1 I 2 R rumor control model for studying collaborative rumor-debunking efforts. Utilizing mathematical modeling and simulation methods, we propose key thresholds for rumor propagation from both theoretical and simulation perspectives, and explore optimal methods for rumor control. Our model is validated with real data from actual cases, confirming its accuracy and the effectiveness. The study shows that without intervention, rumors will spread rapidly. Both constant and dynamically optimized control significantly slow down the spread of rumors. However, dynamic optimization control significantly reduces control costs compared to fixed control schemes. Moreover, we find that controlling only the media layer is insufficient. These findings highlight the importance of meticulous approaches to rumor control in the digital age. [ABSTRACT FROM AUTHOR]

Autonomous and AI-enabled systems present a challenge for integration within the System of Sys-tems (SoS) paradigm. A full system of systems (SoS) testbed is necessary to verify the integrity of a given system and preserve the modularization and accountability of its constituent systems. This integrated system needs to support iterative, continuous testing and development. This need war-rants the development of a virtual environment that provides the ground truth in a simulated sce-nario, interfaces with real-world data, and uses various domain-specific and domain-agnostic simulation systems for development, testing, and evaluation. These required features present a non-trivial challenge wherein constructive models and systems at different levels of fidelity need to interoperate to advance the testing, evaluation, and integration of complex systems. Such a virtual and constructive SoS architecture should be independent of the underlying computational infra-structure but must be cloud-enabled for wider integration of AI-enabled software components. This paper will present a modular Simulation, Experimentation, Analytics, and Test (SEAT) Lay-ered Architecture Framework, a 10-step methodology. This paper will also demonstrate a case study of a hybrid cloud-enabled simulation SoS that allows extensibility, composability, and de-ployability in different target environments. [ABSTRACT FROM AUTHOR]

Logistical risks are now significantly more acute due to epidemics, economic recession and local political turmoil. Cross-border logistics risks are particularly prevalent given the large number of participants and the long transport distances involved. This paper develops a system dynamics model to analyse the key factors of cross-border logistics risk. In previous studies, people usually consider the risk factors as many independent individuals. But actually, there is a causal relationship as well as conduction effects between risk factors. Therefore, this paper analyses the relationship between risk factors through qualitative analysis and establishes a system dynamics model to indicate the direction of risk transmission. The rate of risk transmission was analysed using quantitative methods. Finally, this paper conducts simulations using survey data of cross-border e-commerce enterprises in Chengdu, indicating that the industry currently has more prominent customs risks, process risks, and cooperation risks. For these more serious risks, this paper proposes corresponding prevention and control measures. [ABSTRACT FROM AUTHOR]

This document is a summary of a special issue of the journal Mathematics, titled "Mathematical Modeling and Simulation in Mechanics and Dynamic Systems, 2nd Edition." The special issue focuses on the development of sophisticated models to predict phenomena in dynamic systems using experiments and computer models. The issue includes papers on topics such as modeling mechanical systems, new methods in dynamic systems, and the behavior simulation of mechanical systems. The papers were written by authors from 13 different countries, and the majority of the articles adhere well to the theme of the special issue. The document also provides a table showing the geographic distribution of authors by country. The authors of the special issue have made significant contributions to the field, and the document concludes by stating that the authors have no conflicts of interest. [Extracted from the article]

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 a review of studies that have provided evidence supporting metaphorical embodiment. These studies are divided into three categories of behavioral, neuroimaging, and corpus studies. After summing up the findings of these studies, it is concluded that metaphorical embodiment is supported by these three lines of research. This is followed by a review of a number of studies that have measured sensorimotor and action effector strengths of various concepts. Then, the idea of sensorimotor and action effector strength of concepts is linked to metaphorical embodiment to present the main idea of the paper. Based on the findings of studies that have measured sensorimotor and action effector strengths of concepts, it is suggested that the degree of involvement of sensorimotor systems in mental simulation of metaphoric actions may not be at the same level in all metaphors. It depends on the sensorimotor strength of the base of the metaphor in various modalities. If the base of a metaphor has a high degree of perceptual strength in a certain modality, that modality plays the most important role in the processing of that metaphor, while other modalities take less important roles. In other words, depending on the sensorimotor strengths of the base of a metaphor in various modalities, those modalities have various levels of importance in the processing of that metaphor. If the base of the metaphor is weak in all modalities, modal resources can come into play to process that metaphor. [ABSTRACT FROM AUTHOR]

Research on collaborative manufacturing process modelling and simulation is of great significance in improving production efficiency and product quality, reducing costs, promoting collaborative work, and supporting decision-making. However, current studies have not offered the optimal costs of node enterprises participating in collaborative manufacturing, and ignored the impact of demand uncertainty of suppliers, manufacturers and customers on costs and economic benefits. Therefore, this paper aimed to study the collaborative manufacturing process modelling and simulation of production cost and economic benefit accounting analysis. First, this paper summarized three cost types, conducted cost accounting for the collaborative manufacturing process, and analysed its economic benefits. Second, based on the basic timed automata (TA) model, this paper used a timed input/output automata with port labels (Lp-TIOA) for modelling test cases of the simulation system. Finally, the experimental results verified the effectiveness of the constructed simulation model. [ABSTRACT FROM AUTHOR]

This paper provides an overview of an early attempt at developing a simulation model on a solid-state transformer (SST) based on input-serial and output-parallel (ISOP) topology. The proposed SST is designed as a base for a smart grid (SG). The paper provides a theoretical review of the power converters under consideration, as well as their control techniques. Further, the paper presents a simulation model of the proposed concept with a PLECS circuit simulator. The proposed simulation model examines bidirectional energy flow control between the medium-voltage AC grid and DC smart grid, while evaluating power flow efficiency and qualitative indicators of the AC grid. After the completion of design verification and electrical properties analysis by the PLECS simulation models, the synthesis offers recommendations on the optimal layout of the proposed SST topology for smart grid application. [ABSTRACT FROM AUTHOR]

With the penetration of distributed resources into power distribution networks, power distribution networks are transforming into active distribution networks with a high proportion of distributed generations and power electronic equipment. Efficient modeling and simulation methods are essential to perform dynamic response analysis. In order to satisfy the fast/steady/slow multiple time-scale simulation requirements of active distribution networks, a fast/medium/slow time partition model and a network decoupling method for short line characteristic lines is proposed in this paper. Through the decomposition coordination simulation method, the network is decomposed into multiple regions that can be simulated in parallel. Based on the interconnection of fiber optic network cards, a multi-rate parallel simulation and synchronization strategy is proposed, which significantly improves the simulation speed of active distribution networks while ensuring simulation accuracy. The numerical experiments have been conducted based on a modified IEEE 33-bus and a PG&E 69-bus, and simulation results show the feasibility of the proposed method. The verification results of the example show that using adaptive variable-step-size multi-rate parallel simulation technology can increase the subnet computation-time balance rate and simulation acceleration ratio to 119.90% and 121.31% in the same rate-parallel mode. [ABSTRACT FROM AUTHOR]

E-scooter vibrations are a problem recently studied. Theoretical models based on dynamic simulations and also real measurements have confirmed the high impact of e-scooter vibrations on driver comfort and health. Some authors recommend improving e-scooter damping systems, including tyres. However, it has not been suggested nor has any research been published studying how to improve e-scooter frame design for reducing driver vibrations and improving comfort. In this paper, we have modelled a real e-scooter to have a reference. Then, we have developed a multibody dynamic model for running dynamic simulations studying the influence of mass geometry parameters of the e-scooter frame (mass, centre of gravity and inertia moment). Acceleration results have been analysed based on the UNE-2631 standard for obtaining comfort values. Based on results, a qualitative e-scooter frame design guide for mitigating vibrations and increasing the comfort of e-scooter driver has been developed. Some application cases have been running on the multibody dynamic simulation model, finding improvements of comfort levels higher than 9% in comparison with the e-scooter reference model. The dynamic model has been qualitatively validated from real measurements. In addition, a basic sensor proposal and comfort colour scale is proposed for giving feedback to e-scooter drivers. [ABSTRACT FROM AUTHOR]

This paper aims to improve the strength of soft clay soil using thermal treatment through a laboratory study that simulates the field application. The laboratory work consisted of preparing a soft clay (Cu = 14 kPa) inside a metal box (92.5 × 92.5 × 92.5) cm3. Boreholes of diameter 43 mm, with different lengths, spacing, and arrangements, were made inside the soil to work as a guide for heating pipes which connected to a controlled heating system. A novel heating system, using gas as a heat source, was developed and manufactured. After the end of the treatment periods, a load was applied until failure on a (20 × 20) cm2 square footing. Various parameter spacings (3, 4, and 5 times the outer diameter of the borehole), depths (1, 1.5, 2, and 2.5 times the width of the model footing), arrangements (square, circular, and triangular), and heating periods (2, 4, 6, 8, and 10 h) were investigated. The results showed the strength and behavior of the soil when subjected to the heated boreholes at different spacings, depths, and heating times, which were determined to be three times the outer diameter of the borehole, two times the width of the square footing, and eight hours, respectively, while the effect of the arrangement of the heated borehole casings was small. Also, a cone penetration probe (CPT) conducted on the heated soil showed that the unconsolidated shear strength (Cu) increased from 14 to 360 kPa and then decreased to 140 kPa (as an average with depth). In contrast, the average angle of internal friction (Ø) increased from 0 to 52 degrees and decreased to 16 degrees (as an average with depth) from the center of the heating model to the furthest point affected by heating. The EDS formula showed that components such as silicon, aluminum, and iron decreased at 300 °C and increased at 400 °C in the treated soils. The calcium content increased at 200 °C and then decreased sharply at 400 °C. The carbon percentage increased at 300 °C and decreased at 400 °C. The elemental proportions showed little change or remained stable at temperatures between 400 °C and 600 °C. [ABSTRACT FROM AUTHOR]

Solving multiple objective optimization problems can be computationally intensive even when experiments can be performed with the help of a simulation model. There are many methodologies that can achieve good tradeoffs between solution quality and resource use. One possibility is using an intermediate "model of a model" (metamodel) built on experimental responses from the underlying simulation model and an optimization heuristic that leverages the metamodel to explore the input space more efficiently. However, determining the best metamodel and optimizer pairing for a specific problem is not directly obvious from the problem itself, and not all domains have experimental answers to this conundrum. This paper introduces a discrete multiple objective simulation metamodeling and optimization methodology that allows algorithmic testing and evaluation of four Metamodel-Optimizer (MO) pairs for different problems. For running our experiments, we have implemented a test environment in R and tested four different MO pairs on four different problem scenarios in the Operations Research domain. The results of our experiments suggest that patterns of relative performance between the four MO pairs tested differ in terms of computational time costs for the four problems studied. With additional integration of problems, metamodels and optimizers, the opportunity to identify ex ante the best MO pair to employ for a general problem can lead to a more profitable use of metamodel optimization. [ABSTRACT FROM AUTHOR]

This paper presents the high-fidelity physical modeling of a Thrust Vector Control (TVC) system operated by Electro-Mechanical Actuators (EMAs) for Reusable Launch Vehicles (RLVs). In contrast to simplified, often linear, models, high-fidelity physical models enable a better assessment of the actual system performance and a deeper verification of the on-board software robustness against disturbances, unmodeled dynamics or degradation. This aspect is essential to enable the reusability concept as driven by long-term reliability requirements. Moreover, critical systems like Fault Detection, Isolation and Recovery (FDIR) logic, whose robustness and efficacy are often difficult to prove, can be thoroughly tested without requiring hardware experiments with eventual invasive modifications for fault injections. This work captures the whole dynamics of the EMA and TVC components, including the power drive electronics, the electrical motor, and the mechanical transmission for the EMA, as well as the mechanical properties of the engine nozzle acting as a load. The resulting differential algebraic equation system is modeled in the Modelica acausal object-oriented modeling language. An ad-hoc framework is implemented to guarantee flexibility and modularity, which allows models with different fidelity levels to be easily exchanged to achieve the simulation objectives and needed accuracy level. The impact of the different models on the closed-loop TVC dynamics is analyzed in both the frequency and time domain, and then benchmarked with a realistic RLV mission. The results show that the high-fidelity physical models provide a better understanding of the more complex effects governing the TVC dynamics and can, in turn, effectively improve its requirement definition process. • The physical modeling and simulation of an EMA-based TVC system is presented. • High-fidelity physical models help assessing TVC system control software performance. • EMA component models with incremental fidelity levels are proposed. • EMA and TVC system models are integrated in a Modelica-based framework. • Different closed-loop responses are analyzed in the frequency and time domains. [ABSTRACT FROM AUTHOR]

Introduction/purpose: The study of vehicle suspension is a challenge for researchers in the field of vehicles regarding the impact of the suspension system on vehicle performances such as ride comfort, road holding, and working space. This paper presents the simulation of the Land Rover Defender 110 vehicle in the roll plane (half vehicle) in Simulink/MATLAB. The obtained results were compared with the results obtained in the ADAMS/CAR software package of the Land Rover Defender 110 simulation model previously experimentally validated. The Defender 110 vehicle has a dependent suspension system in both axles and a passive suspension type with four degrees of freedom (4 DOF). Methods: The equations of the system can be solved mathematically with a scheme in Simulink/MATLAB while half-vehicle modeling has been done in ADAMS/CAR. Results: The comparison of the vehicle characteristics obtained by the two simulation methods was done for three different scenarios, and it was noticed that there is a good correlation between them. Conclusion: It was concluded that the Defender 110 vehicle simulation model in Simulink/MATLAB is validated. The validated model can be used to perform suspension system optimization in future work [ABSTRACT FROM AUTHOR]

Currently, the simulation parameters for the model of the interaction between the transplanter, the plug seedlings, the soil, and the pot damage mechanism still need to be clarified. The optimization design of the planters and the improvement of planting quality are still urgent issues that need to be solved. In this paper, the simulation parameters of the pot and the soil were calibrated based on the pressure distribution measurement technology. With the actual collision impact force and matrix loss rate as the targets, a four-factor, three-level orthogonal test was designed to obtain the optimal parameters. Through the optimization analysis of the experimental results, it could be concluded that the pot–soil restitution coefficient, the pot–soil static friction coefficient, the pot–soil rolling friction coefficient, and the surface energy were 0.31, 0.88, 0.35, and 1.07 J/m2, respectively. The experimental verification of the optimal parameter combination showed that the relative error of the collision impact force was 1.65% and that the relative error of the matrix loss rate was 2.32%, which verified the model's reliability. Based on the optimal parameters, the movement law of the hole tray seedlings was studied at different positions during the transplanting process. The plug seedlings collided not only with the planter but also with the soil, which led to the breakage and looseness of the pot structure. The relative error between the matrix loss rate of the transplanter inserting soil, the matrix loss rate of the transplanter that did not enter the soil, and the simulated matrix loss rate was less than 10%, which further proved the accuracy of the simulation model. [ABSTRACT FROM AUTHOR]

Out-of-step (OOS) condition is a potential problem in the power system and uncontrolled islanding is one of the severe consequences of out-of-step condition which leads to cascaded tripping of the system. To avoid this undesired cascaded tripping, early prediction of out-of-step condition is essential before losing the synchronization of generators and between the system areas. Controlled islanding is the last emergency action that can be taken by splitting the system intentionally into coherent islands. Conventionally, OOS condition has been detected with impedance-based measurement techniques which have their own limitations. With the implementation of a wide-area measurement system with synchrophasor measurement units (PMUs) in the power system, it is now possible to measure the bus voltage angle at a much faster rate than with SCADA. In this paper, synchrophasor-based bus voltage angle measurement has been used for early prediction of OOS condition in power systems. A new algorithm has been formulated for both generator and tie lines based on the trajectory of first and second derivatives of the bus voltage phase angle for early detection of OOS condition. The prediction speed of proposed method is found to be between 5% and 70% of time to OOS, after disturbance clearance. The proposed algorithm has been mathematically formulated and evaluated with three benchmark systems in real-time simulation environment with an OPAL-RT real-time simulator and a HYPERSIM platform. [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]

Objectives: There are so many names to refer to the discipline that investigates alternative futures. futures studies, foresight, futures literacy, futures thinking, anticipation, futurism, futurology, and many others. Future studies that can also be referred to as future science seeks to analyze resources, models, and reasons of a subject's change or stability in order to develop and expand the scope of foresight, and consider different options and possibilities. Also, futures study of postulating possible, probable, and preferable futures and the worldviews that underlie them. It can be considered as a branch of the social sciences and parallel to the field of history. Futurology is the systematic, interdisciplinary and holistic study of social, technological advancement, and other environmental trends. This research aims to future-studying in public libraries and its role in their development and progress with an emphasis on the libraries covered by Iran Public Libraries Foundation. Methodology: It is among future research methods, scenario planning, road map, Landscape, modeling, simulation and Delphi. The method of research in this research is surveying and descriptive using interview and questionnaire through Delphi approach. A questionnaire was first used to collect data, and then face-to-face interviews were used with 11 people for some issues and to complete the opinions. The questionnaire was distributed among the statistical population of the research in three periods. Regarding determining the validity of the research tool, the problems in the questionnaire were identified and resolved by using the opinion of a number of experts in the field of information science. Sampling was done based on the structure of the Delphi method and data analysis was done. The reliability of the research tool was determined by Cronbach's alpha test at 0.810. Findings: Using the gained results from interviewee's findings, a series of elements which are effective on library and especially development are extracted such as: internet, digitalization, updating the library system, using librarians and experts, economic conditions, virtual reference services, serials and open access, Mass media and social networks, and Mobile phone technology. The experts believed that the presence of librarians, both now and in the future, is important and that professional librarians should also be used. Conclusion: By analyzing technological evolutions in libraries, we conclude that in future libraries, materials and informational contents in library are going toward decreasing the volume and weight. From consequence of interviewees' ideas as well as variation trend in type of libraries' resources, it can be predicted that paper resources will remain persistent beside electronic resources and each of the resources will keep its own certain users. Mostly, in this period, printed or digital resources will coexist and the libraries will be conducted based on two-type materials. For comprehensive development in public libraries, it is necessary to pay attention to all the mentioned components. [ABSTRACT FROM AUTHOR]

Current physical systems are built in more that one coordinate: for example, electrical power systems, aeronautical systems and robotic systems can be modeled in multibond graphs (M B G) . However, in these systems, some elements use only one axis or dimension—for example, actuators and controllers—which can be modeled in bond graphs (B G) . Therefore, in this paper, modeling of systems in multibond graphs and bond graphs ( M B G - B G ) is presented. Likewise, the junction structure of systems represented by ( M B G - B G ) is introduced. From this structure, mathematical modeling in the state space is presented. Likewise, modeling of systems on a platform ( M B G - B G ) can be seen as symmetric to the mathematical model that represents these systems. Finally, a synchronous generator modeled by ( M B G - B G ) as a case study is developed, and simulation results using 20-Sim software are shown. Furthermore, an electrical power system connected to the power supply of a DC motor as another case study is explained. [ABSTRACT FROM AUTHOR]

Short-circuit (SC) of power components in inverters is one of the most serious faults that are vulnerable to occur. It is critical to quickly and accurately detect and locate SC faults in power devices, especially to determine their severity. Therefore, the paper proposes a fault diagnosis algorithm that combined the rough set genetic algorithm (RS-GA) and the Bayesian network (BN). The algorithm uses the RS for attribute reduction and the GA for global optimization to reduce numerous fault attributes and obtains several kinds of reduction results. According to the reduction results, BN diagnostic models are established for optimization, and the optimal RS-GA-BN diagnostic model is determined by an optimization evaluation algorithm based on time and accuracy. More importantly, by the fault attribute values of the optimal reduction attribute of the RS-GA-BN model, the fault severity can be diagnosed, and the fault and its trend can be predicted in advance, which provides an important idea for the prevention of SC. The experimental platform and simulation model are built to obtain fault diagnosis data. The experimental results show that the RS-GA-BN model presents higher fault diagnosis accuracy than the BP neural network, and the experiment verifies the feasibility and correctness of the method. [ABSTRACT FROM AUTHOR]

This paper presents a simulation technique for optimizing a hydrogen integration network. By applying this technique, the minimum fresh hydrogen consumption can be determined. Quantitative relationship between sources and sinks streams were studied to get the flow rates of coupled source and sink, hydrogen consumption and hydrogen concentration in each stream. The introduced technique was applied on twelve sources and twelve sinks with any purity of hydrogen concentration. The hydrogen integration network was designed through two steps, the first step considers applying the data given in the LINGO program, while the second step considers using the LINGO results in the introduced excel program to obtain the retrofitted hydrogen integration network. The proposed technique was applied on several case studies to achieve the minimum consumption of fresh hydrogen for the obtained hydrogen integrated networks. The introduced model for simulation and retrofitting of mass exchange networks is easy to understand and the results showed that this model is more efficient for fertilizer, petrochemical and refinery plants. [ABSTRACT FROM AUTHOR]

In this study, we investigate the potential of artificial intelligence (AI), specifically Generative Pre-trained Transformer 4 (GPT-4), to accelerate the development of system dynamics simulations within the broader context of systems engineering. The research aims to uncover the opportunities and limitations of leveraging AI to assist humans in constructing and refining system dynamics models. Through a systematic iterative process, GPT-4 was engaged in tasks such as creating, expanding, and stabilising simulations, identifying errors, generating expansion ideas, and converting models to Python code. Our findings reveal that GPT-4, while not flawless, can significantly enhance the modelling process, reduce human error, and expedite learning. This paper critically examines the role of AI in model development, emphasising the continued importance of human expertise in the evaluation and testing of simulations. Ultimately, we argue for a symbiotic relationship between AI and human modellers, harnessing the power of GPT-4 to augment human capabilities and advance the fields of system dynamics and systems engineering. [ABSTRACT FROM AUTHOR]