Development Of Simulation Model Research Articles

Non-uniform temperature fields in steel tubes with different inclinations under solar radiation

The temperature distribution within steel tubes is subject to non-uniformity due to the influence of surrounding environmental factors, which could pose safety concerns for steel structures. In response, this study undertook a comprehensive long-term experimental investigation, aimed at elucidating the temperature distribution characteristics of inclined steel tubes. The results underscored the non-uniform distribution of temperature fields in steel tubes under the influence of solar radiation, with notable sensitivity to their inclinations and orientations. In addition, a numerical simulation model specifically tailored to represent the thermal behavior of inclined steel tubes was developed and subsequently validated using empirical data gathered from the aforementioned experiments. Based on the developed simulation model, the thermal behaviors of a steel-arch-tower were numerically analyzed. It was shown that distinct vertical temperature variations exist across different sections of the tower, while the horizontal temperature differentials exhibit consistent trend. The outcomes of this combined experimental and numerical study provide useful references to understand the thermal effects in steel structures.

Agent-based modeling and optimization of the characteristics for research-and-production clusters

This paper presents a developed agent-based simulation model for the development of research-and-production clusters in Russia implemented with the use of high-tech enterprises located in four science cities (Troitsk, Obninsk, Pushchino and Protvino) as the case study. A new approach to modeling and optimization of gross metropolitan product (GMP) is proposed, taking into account the influence of the “gravity effect” on the redistribution of labor resources between developing science cities and appropriate enterprises united in single research and research-and-production clusters An important element of this approach is the formation of various scenarios for the strategic development of the research-and-production clusters being assessed and support for the possibility of choosing the most preferable scenario using an evolutionary optimization algorithm. An enlarged simulation model has been developed and implemented in AnyLogic describing the possible development trajectories of science cities with a corresponding change in the values of the most important characteristics: the number of economically active population, the number of research-and-production enterprises, the volume of products produced in high-tech sectors of the economy, GMP, etc. The designed framework is intended primarily for the management of research-and-production clusters implementing the strategy of innovative development. Such a framework uses methods of system dynamics and agent-based simulation modeling supported in the AnyLogic system, genetic optimization algorithms and GIS mapping for science cities, etc. to implement the required functionality. The approbation of the framework was completed with the use of real data published in the approved strategies of the relevant science cities development. As a result of the numerical experiments carried out, some recommendations were proposed for the development of the research-and-production clusters under study considering their mutual influence and the existing base of resources.

Advanced multi-scale analysis of segregation mechanisms in twin-roll casting of Al-Cu-Li alloys

In this paper, a detailed analysis of the rheological behaviour and segregation mechanisms within twin-roll casting (TRC) processes for 2060 Al-Cu-Li alloys is presented. Building on previous research where fixed roll gaps limited the adjustability of cast-rolling speed, this study expands the scope by adjusting roll gaps from 3 mm (TRC-3), to 6 mm (TRC-6), to 10 mm (TRC-10). This approach yields three typical process ranges with gradually increasing roll gaps and a wide range of decreasing cast-rolling speeds, allowing us to investigate the inherent nature of segregation and identify conditions conducive to segregation-free processing. A significant contribution of this study is the development of a novel multi-scale simulation model that integrates the thermal, flow, mechanical, solute and phase fields. This advanced simulation framework enhances our understanding of TRC processes and aids in exploring the interplay between the various factors affecting alloy fabrication. This study identified two primary stress-induced inverse segregation mechanisms: the reflux of the semi-solid phase due to rolling stress and expansion of the solidifying shell under shearing stress. Using these insights, a low-stress, low-segregation process, termed TRC-6, was established, which showed notable improvements in the mechanical properties. Specifically, TRC-6 demonstrated a remarkable strength of 562.9 MPa post-T8-treatment, surpassing those of TRC-3 and TRC-10 by 9.0 % and 5.2 %, respectively. These findings offer valuable insights for future TRC process designs with the aim of eliminating segregation defects and enhancing the sustainable and efficient production of Al-Cu-Li alloys.

Development of electricity simulation model of urban houses and evaluating surplus electricity of photovoltaics (PV) considering housing stock transformation

The Japanese government is advocating for the introduction of decentralized renewable energy devices such as photovoltaics (PV) and high thermal performance houses in urban areas. Due to variations in housing stock among different urban areas, the implementation of these houses and devices would have diverse effects on the supply and demand sides, potentially leading to diverse overproduction of PV electricity, referred to as surplus electricity. Existing research focuses on increasing the utilization of surplus electricity and quantifying the surplus electricity from individual buildings at a regional scale. Considering the lack of research that quantifies surplus electricity through shared PVs under the urban-scale contextual changes (widespread introduction of high-performance houses). Therefore, this study aims to address this gap by utilizing an archetype house simulation model to simulate and compare two scenarios (with or without houses retrofitting) regarding electricity demand for each street-level area, maximum power and duration time of surplus electricity in areas where surplus electricity would occur in the target city Fukuoka in 2025. The results indicate that, under the current residential PV stock and existing introduction rates, the peak surplus power occurs around noon in May, approximately 396 out of 1051 areas in Fukuoka would generate surplus electricity during 2025. Houses retrofitting would increase the surplus electricity (include maximum power and duration time) in these areas. Additionally, this study identifies the residential characteristics of areas that generate surplus electricity, including construction year, household composition, and the proportion of detached houses, whether with retrofitting or not. The results suggest attention to surplus electricity increasing in areas with a high proportion of detached houses when considering houses retrofitting.

Analysis of two-terminal perovskite/silicon tandem solar cells with differing texture structure, perovskite carrier lifetime, and tunneling junction quality

Presented here is the optimization of a planar two-terminal perovskite/silicon tandem solar cell with a texture structure. The developed simulation model is fitted to published experimental results, and the importance of current matching in the two-terminal structure is discussed. With the texture structure optimized and considering current matching, the optimal texture structure improves Jsc from 17.9 to 20.87 mA/cm2 compared to the planar structure, as well as improving the power conversion efficiency from 25.8% to 35.9%. Furthermore, if the quality of the perovskite thin film and tunneling junction efficiency with a smaller voltage penalty can be improved, then the efficiency can be further improved to 38.13%. This indicates that this tandem solar cell still has much room for improvement.

Study of a Thermochemical Heat Storage Reactor Filled with Polyaluminum Sulfate for Low-Temperature Application

This paper investigates comprehensively the operational dynamics of a thermochemical heat storage (TCHS) reactor for low-temperature applications using polyaluminum sulfate and takes into consideration a developed simulation model with an experimentation validation. Significant concordances were found between the developed simulation model and the experimental results. Results reveal optimized conditions for the charging process using an electrical heater, with a heating temperature of 120°C at 10 K/min over 500 minutes. This achieves full material charging, with stabilized pressure drops at an equilibrium of 80 mbar, corresponding to a temperature of approximately 108°C, and yielding a thermal power of 950 W. An inlet vapor pressure of 18 mbar at 10°C for 5 hours is sufficient to completely discharge the bed, with pressure drops reaching around 30 mbar and a thermal power of 300 after reaction completion. Insights into conversion extents during both processes are provided, along with a remarkable thermal efficiency of 90% and a coefficient of performance (COP) of 97%, surpassing recommended theoretical values (50%). The study suggests further enhancing system performance through the design and implementation of a dedicated heat exchanger. The achievement of 75% of the targeted thermal power specification represents a significant milestone, offering valuable contributions towards the realization of sustainable technological advancements of both the reactor technology of TCHS and state-of-the-art thermal energy storage solutions. From the research, it is possible to infer further suggestions for enhancing this performance by designing and implementing a dedicated heat exchanger for both heat supply and retrieval mechanisms.

High-fidelity 3D simulation of dust-loading behavior and clogging process of coarse nonwoven filter media considering collision effect

The filter lifetime of fibrous media is important for the energy-saving application of air filters and efficient delivery of clean air. The clogging process significantly affects the dust-loading behavior of fibrous filter media. Therefore, an effective methodology for determining the deposition of dust particles inside filter structures is necessary. This study conducted numerical dust loading simulations on a three-dimensional (3D) X-ray tomographic structure of coarse nonwoven filter media. Spherical particles with a density of 1808 kg/m3 were used in the simulations instead of plate-like dust particles with a higher silica density. A high-fidelity simulation model was successfully developed by considering collision effects. Key factors were determined, including the Hamaker constant for the adhesion energy, restitution coefficient for the particle kinetic energy, and sliding motion. Remarkably, the deviation between the simulated and experimental dust holding capacity was less than 1 %. The developed simulation model enabled a quantitative evaluation of the clogging process and 3D in-situ evolution of particle deposition and pore structures. It was observed that 95.6 % of the maximum deposited dust mass within the fibrous structure was captured at the clogging point. Several computational methods yielded accurate pore size evaluations and clear 3D pore structure visualizations. The developed methodology for high-fidelity simulation and 3D analysis can be further applied to other two-phase filtration and separation fields, including aerosol filtration, coalescence filtration, membrane fouling, micro/nanoplastic capture, and oil/water separation.

Experimental process characterisation for high-volume compression moulding of hybrid-architecture composites

Compression moulding of woven fabric prepreg and sheet moulding compound (SMC) in a single-shot process combines the superior mechanical properties of continuous fibre composites and the high design flexibility of discontinuous fibre composites. This experimental study presents insights into the moulding characteristics of prepreg and SMC and explores the interaction between these two materials during manufacturing of hybrid-architecture composites. All tests were performed under typical compression moulding conditions using a squeeze flow testing rig. The response of each material was interpreted through proposed material models applied to the data acquired from single architecture tests. Critical interaction mechanisms were identified from hybrid architecture tests, alongside some additional deformation mechanisms, such as high level of in-plane fibre tow deformation not observed in single-architecture tests. Novel experimental methods were also introduced to quantify the change in meso-scale fibre architecture in the prepreg induced by the flow of SMC. The outcomes of this study not only shed light on the essential interaction mechanisms of hybrid-architecture composites but also provide valuable insights into deformation mechanisms not apparent in isolated material studies. Ultimately, these findings will facilitate the future development of a numerical simulation model for hybrid moulding processes.

Implementation of Simulation Modeling of Single and High-Volume Machine-Building Productions

The authors of this article analyze the existing methods and models of technological preparation of machine-building industries. The structure of a three-level simulation model with network-centric control, the structures of individual elements of the simulation model, and the process of simulation modeling are described. The criteria for choosing a rational option for the processing technological route have been determined. During this research, a simulation program was implemented in C++. It allows you to select the optimal scenario for the operation of a production site based on two criteria: time and cost. The volume of implementation is about 2 × 103 lines of code. A diagram of the modeling algorithm for the implemented program and a description of the classes and their interactions are given in the article. The developed simulation model was tested at a machine-building enterprise using the example of the “Pusher” part, manufactured under single-unit production conditions. The technological equipment used for the manufacture of this part was formed in the form of input data of the simulation model. The results of simulation modeling for the selected part are described. For each variant of the technological processing route, the values of variable costs and the duration of the production cycle were determined.

Simulation and feasibility assessment of a green hydrogen supply chain: a case study in Oman.

The transition to sustainable energy is crucial for mitigating climate change impacts. This study addresses this imperative by simulating a green hydrogen supply chain tailored for residential cooking in Oman. The supply chain encompasses solar energy production, underground storage, pipeline transportation, and residential application, aiming to curtail greenhouse gas emissions and reduce the levelized cost of hydrogen (LCOH). The simulation results suggest leveraging a robust 7 GW solar plant. Oman achieves an impressive annual production of 9.78 TWh of green hydrogen, equivalent to 147,808 tonnes of H2, perfectly aligning with the ambitious goals of Oman Vision 2040. The overall LCOH for the green hydrogen supply chain is estimated at a highly competitive 6.826 USD/kg, demonstrating cost competitiveness when benchmarked against analogous studies. A sensitivity analysis highlights Oman's potential for cost-effective investments in green hydrogen infrastructure, propelling the nation towards a sustainable energy future. This study not only addresses the pressing issue of reducing carbon emissions in the residential sector but also serves as a model for other regions pursuing sustainable energy transitions. The developed simulation models are publicly accessible at https://hychain.co.uk , providing a valuable resource for further research and development in the field of green hydrogen supply chains.

Design and Optimization of a Robot Dosing Device for Aliquoting of Biological Samples Based on Genetic Algorithms

Aliquoting of biological samples refers to the process of dividing a larger biological sample into smaller, representative portions known as aliquots. This procedure is commonly employed in laboratories, especially in fields like molecular biology, genetics, and clinical research. Currently, manual dosing devices are commonplace in laboratories, but they demand a significant amount of time for their manual operation. The automated dosing devices available are integrated into narrowly focused aliquoting systems and lack versatility as manipulator equipment. Addressing this limitation, a novel technical solution is proposed in this paper for a modular dosing device compatible with robotic manipulators. The paper introduces and details a mathematical model, optimizes its parameters, and constructs a detailed 3D model using the NX environment to demonstrate the engineering feasibility of our concept. It further outlines the development of a three-dimensional dynamic simulation model for the dosing device, comparing analytical calculations with simulation results. The construction of a dosing device prototype is discussed, followed by a comprehensive experimental validation.

Development and Validation of a Dynamic Simulation Model for Water Storage Heating Systems Powered by Electric Boilers in Elementary Schools

Development and Validation of a Dynamic Simulation Model for Water Storage Heating Systems Powered by Electric Boilers in Elementary Schools

Numerical simulation and spray model development of liquid ammonia injection under diesel-engine conditions

Ammonia is regarded as a promising alternative fuel in internal combustion engine for its potential to reduce carbon emissions. Injection process of liquid ammonia will affect air-fuel mixture distribution and therefore combustion efficiency and NOx emissions. However, the experimental studies of liquid ammonia injection under engine conditions are limited, and the key impact factors of spray evolution are still unclear. This study aims to evaluate the applicability of numerical models for liquid ammonia spray, and numerically investigate spray characteristics under diesel-engine conditions (ambient temperature > 800K, ambient pressure > 2 MPa). Large eddy simulation coupled with Lagrangian particle tracking method were conducted, and the results show that the non equilibrium - Frössling phase change model coupled with Schiller-Naumann drag model can provide a good prediction of spray penetration. Liquid penetration increases with ambient pressure decreasing; vapor penetration increases with ambient density decreasing, but insensitive to ambient temperature. Temperature - mixture fraction distribution is sensitive to ambient temperature and superheat degree. Besides, a three-stage 0D model of spray tip penetration under diesel-engine conditions is developed firstly, which can reflect the key impact factors of ammonia spray evolution and provide theoretical support to optimize fuel injection strategy of liquid ammonia-fueled engines.

High spatiotemporal-resolution mapping for a seasonal erosion flooding inundation using time-series Landsat and MODIS images

Seasonal erosion flooding events present a significant challenge for effective disaster monitoring and land degradation studies. This research addresses this challenge by harnessing the combined capabilities of time-series Landsat and MODIS images to achieve high spatiotemporal-resolution mapping of flooding during such events. The study underscores the critical importance of precise flood monitoring for disaster mitigation and informed land management. To overcome the limitations posed by the trade-off between spatial and temporal resolution in current satellite sensors, we emplyedand theflexible spatiotemporal data fusion (FSDAF) methods to produce synthetic flood images with enhanced spatiotemporal resolutions for mapping by using MODIS and Landsat data from August 29 to September 3, 2016. A comparison was made between flood maps from several post-disaster forecasts based on ground-obtained time-series images of the Tumen River flood in China. According to the FSDAF approach, the input Landsat image of March 25, 2016, and the fused results had a root mean square error (RMSE) of 0.0301, average difference of 0.001, r of 0.941, and structure similarity indexof 0.939, indicating that temporal variation data had been effectively incorporated into a forecast on August 16, 2016. Results also indicated that the FSDAF forecast values are lower than those from the actual Landsat image. The results of the study also showed that the generated images could be effectively used for flood mapping. By using our newly developed simulation model, we were able to produce a comprehensive map of the inundated areas during the event from August 29 to September 3, 2016. This shows that FSDAF holds great potential for flood prediction and study and has the potential to benefit further disaster-related land degradation by combining multi-source images to provide high temporal and spatial resolution remote sensing information.

Modelling motorized and non-motorized vehicle conflicts using multiagent inverse reinforcement learning approach

Microsimulation models are effective for analysing road users’ interaction behaviour and assessing different facilities’ performance. However, only a few studies have developed simulation models for studying motorized and non-motorized vehicles conflicts. This is likely due to mixed traffic’s complexity and heterogeneity and the difficulty in accurately capturing road users’ avoidance maneuver. This study aims to adopt a multiagent simulation model to replicate road users’ microscopic behaviour and collision avoidance mechanisms in traffic conflict scenarios. Road users’ reward functions are recovered by the multiagent inverse reinforcement learning approach. The multiagent Actor-Critic deep learning algorithm is used to predict road users’ evasive action and assess their optimal policies. The findings demonstrate that the multiagent simulation model provides highly accurate predictions of road users’ trajectories and collision avoidance strategies. Furthermore, the results demonstrate a strong correlation between the predicted traffic conflict indicator from the simulated trajectories and that from the actual trajectories.

Trauma surgical simulation: discussing the replacement of live animals used as human patient simulators

BackgroundDespite advances in simulator technology, live anaesthetised animals continue to be used as human patient simulators for medical professionals to practice techniques in the management of surgical trauma. This article describes the process of convening a working group of individuals with a professional interest in simulation to discuss the use of live animals and consider if and how they can be replaced in the future.Main bodyA working group was formed of voluntary attendees to a workshop held at the SESAM 2023 conference. Iterative discussions reflecting on the topic were used to produce statements summarising the working group’s opinions. The working group determined that live animals are used as human patient simulators due to the presence of accurate and responsive physiology in the presence of bleeding, realistic tissue tactility and an emotional response experienced by the learner due to interaction with the animal. They were unable to reach a consensus on replacement, determining that there is currently no single model which is able to provide all the learning aspects which a live animal model can provide. Several suggestions were made regarding development of technologies and pedagogical change.ConclusionReplacement of live animals in surgical simulation is not straightforward but should be an aspiration, if possible. For the ongoing development of trauma surgical simulation models, it is important to combine the knowledge, skills and perspectives of medical stakeholders and educators, academic researchers and industry experts in producing alternative options to the use of live animal simulators.

Development and tuning of models for accurate simulation of CT spatial resolution using CatSim.

Objective. We sought to systematically evaluate CatSim's ability to accurately simulate the spatial resolution produced by a typical 64-detector-row clinical CT scanner in the projection and image domains, over the range of clinically used x-ray techniques.Approach.Using a 64-detector-row clinical scanner, we scanned two phantoms designed to evaluate spatial resolution in the projection and image domains. These empirical scans were performed over the standard clinically used range of x-ray techniques (kV, and mA). We extracted projection data from the scanner, and we reconstructed images. For the CatSim simulations, we developed digital phantoms to represent the phantoms used in the empirical scans. We developed a new, realistic model for the x-ray source focal spot, and we empirically tuned a published model for the x-ray detector temporal response. We applied these phantoms and models to simulate scans equivalent to the empirical scans, and we reconstructed the simulated projections using the same methods used for the empirical scans. For the empirical and simulated scans, we qualitatively and quantitatively compared the projection-domain and image-domain point-spread functions (PSFs) as well as the image-domain modulation transfer functions. We reported four quantitative metrics and the percent error between the empirical and simulated results.Main Results.Qualitatively, the PSFs matched well in both the projection and image domains. Quantitatively, all four metrics generally agreed well, with most of the average errors substantially less than 5% for all x-ray techniques. Although the errors tended to increase with decreasing kV, we found that the CatSim simulations agreed with the empirical scans within limits required for the anticipated applications of CatSim.Significance.The new focal spot model and the new detector temporal response model are significant contributions to CatSim because they enabled achieving the desired level of agreement between empirical and simulated results. With these new models and this validation, CatSim users can be confident that the spatial resolution represented by simulations faithfully represents results that would be obtained by a real scanner, within reasonable, known limits. Furthermore, users of CatSim can vary parameters including but not limited to system geometry, focal spot size/shape and detector parameters, beyond the values available in physical scanners, and be confident in the results. Therefore, CatSim can be used to explore new hardware designs as well as new scanning and reconstruction methods, thus enabling acceleration of improved CT scan capabilities.

Optimizing intracranial electric field distribution through temperature-driven scalp conductivity adjustments in transcranial electrical stimulation

Transcranial electrical stimulation (TES) is a promising non-invasive neuromodulation technique. How to increase the current intensity entering the skull and reduce scalp shunting has become a key factor significantly influencing regulatory efficacy. In this study, we introduce a novel approach for optimizing TES by adjusting local scalp temperature to modulate scalp conductivity. We have developed simulation models for TES-induced electric fields and for temperature-induced alterations in scalp conductivity. Two common types of stimulation montage (M1-SO and 4 × 1 montage) were adopted for the evaluation of effectiveness. We observed that the modulation of scalp temperature has a significant impact on the distribution of the electric field within the brain during TES. As local scalp temperature decreases, there is an increase in the maximum electric field intensity within the target area, with the maximum change reaching 18.3%, when compared to the electric field distribution observed under normal scalp temperature conditions. Our study provide insights into the practical implementation challenges and future directions for this innovative methodology.

Trans-Caspian International Transport Route Infrastructure Assessment Using Simulation Modelling

Abstract The Trans-Caspian International Transport Route (TITR) is one of the main transport corridors between China and Europe. It passes through the territory of Kazakhstan, as well as the countries of the South Caucasus, Turkey, and Iran, and contributes to the full realisation of transit and export opportunities of these countries. Each country participating in the development of TITR is implementing projects to increase the capacity of its transit infrastructure, but the potential of this route has not yet been fully realised. The reason for this is both high tariffs for sea and rail transport and insufficiently short transport times, which are dependent on the parameters and methods of using the infrastructure. This paper is devoted to the study of the TITR railway infrastructure located in Kazakhstan. The developed simulation model allows estimating the impact of infrastructure parameters of the railway track on the movement time of a container train from the PRC border to the ports of Aktau and Kuryk on the Caspian Sea coast.

Heat source models for numerical simulation of laser welding processes – a short review

In recent decades, numerical modeling and computer simulation have become an integral part of the design, analysis and optimization of fusion welding processes, including laser welding. In general, laser welding processes involve the interaction of multiple physical phenomena, such as thermal, fluid, metallurgical, chemical, mechanical, and diffusion effects, which makes the development of a simulation model difficult and complex. In addition to the geometric characteristics of the parts to be welded, their material properties must be specified in a wide temperature range, as well as the conditions for heat removal to the environment or shielding gas. One of the most complex tasks in the preparation of a simulation model of the laser welding processes consists in the selection of an appropriate heat source model to accurately determine the heat input to the weld. Very important is also the process of experimental verification and validation of the developed simulation models. In this paper, a short examination of significant mathematical heat source models for numerical simulation of laser welding is provided. Numerical analysis of laser welding of sheets made of S650MC steel is accomplished using conical 3D heat source model with the support of the ANSYS code. The effect of geometrical characteristics of the conical volumetric heat source model on the computed width, length, and depth of the weld pool is discussed, along with evaluation of maximum weld pool temperature.