Simulation Modeling Method Research Articles

Life Prediction and Reliability Evaluation of Reinforced Concrete Frame Structures Considering the Collision Response Under Earthquake Conditions

Firstly, in this study, we utilize the high-order element model (truss link model) simulation method in OpenSees (3.7.0) software and verify the feasibility of this method by comparing it with the shaking table test. Secondly, the structural dynamic response of adjacent structures with different performance levels, spacing, and layout forms under large earthquakes is analyzed, and the corresponding structural failure probability is studied. Furthermore, the life distribution within the design service life of the structure is predicted according to the nonparametric Kaplan–Meier estimation model. Finally, the reliability of adjacent structures is evaluated by using the joint engineering demand parameters. The analysis method of replacing the theoretical analysis based on engineering experience and certainty in the current specification with probability analysis is proposed, which provides a more reliable theoretical basis for decision-making regarding the reinforcement, maintenance, or demolition of structures in the later stage.

Equivalent Simulation Study of Delta-Rotor Engine

The mechanical structure, movement mode, and combustion process of a triangular rotor engine differ from those of a conventional engine with a crank connecting rod mechanism as the core. This makes it impossible to directly use existing simulation software to simulate the performance of the entire engine, rendering it difficult to conduct structural evaluation and performance prediction during the engine development stage. Therefore, using existing performance simulation software to establish a performance-equivalent model for a triangular rotor engine is crucial. To solve the above problems, this study proposes a performance-equivalent simulation modelling method for a triangular rotor engine based on a three-dimensional simulation model and the operating principles of the triangular rotor and four-stroke engines. Compared to various performance indicators obtained from the three-dimensional simulation model, the results show that the equivalent model established in this study has sufficient accuracy for key indicators such as the cylinder pressure, cylinder temperature, and in-cylinder quality under various working conditions. This can satisfy the requirements of the complete machine-performance simulation of a triangular rotor engine.

Data-driven machine learning approaches for precise lithofacies identification in complex geological environments

ABSTRACT Reservoir characterization is a vital task within the oil and gas industry, with the identification of lithofacies in subsurface formations being a fundamental aspect of this process. However, lithofacies identification in complex geological environments with high dimensions, such as the Lower Indus Basin in Pakistan, poses a notable challenge, especially when dealing with limited data. To address this issue, we propose four common data-driven machine learning approaches: multi-resolution graph-based clustering (MRGC), artificial neural networks (ANN), K-nearest neighbors (KNN), and self-organizing map (SOM). We utilized these proposed approaches to assess their performance in scenarios with varying core sample availability, specifically evaluating their effectiveness in identifying lithofacies within the Lower Goru formation of the middle Indus Basin. The study reveals that in scenarios with a limited number of core samples, MRGC is the preferred choice, while KNN or MRGC is more suitable for larger datasets. The results demonstrate the superior performance of MRGC and KNN in lithofacies identification within the specified geological environment, with SOM following closely behind, and ANN exhibiting comparatively lower efficacy. The accurate identification of lithofacies from the selected model is complemented by the application of the truncated Gaussian simulation method for facies modeling. Comparative results confirm the excellent agreement between the model identification of lithofacies from well logs and electro-facies obtained from the truncated Gaussian simulation electro-facies volume. This study highlights the crucial role of selecting the right machine learning approach for precise lithofacies identification and modeling in complex geological environments. The comparative analysis provides practitioners in the petroleum industry with insights into the strengths and limitations of each method, enhancing existing knowledge. In conclusion, this research emphasizes the significance of comprehensive research and method selection for advancing lithofacies identification in diverse formations or study areas, ultimately benefiting the broader field of subsurface characterization in the petroleum industry.

Применение имитационного моделирования в процессах постройки судна

This article provides an example of the application of the method of simulation modeling of ship construction processes in AnyLogic software. The process is briefly described and the logistics of building a barge produced at shipyards is characterized, and a map of the production process is prepared. In conclusion, three possible modernization options were proposed, which consist in technological, organizational improvements and a variant combining both of these solutions. AnyLogic software was used for a comparative analysis of the proposed options in relation to the process in the basic version. This method allows you to obtain accurate data for making informed decisions without the need for physical tests. The use of simulation modeling is a key tool for optimizing shipbuilding processes and further development of the industry.

Simplification and simulation of evaluation process for low efficiency constructed wetlands based on principal component analysis and machine learning

The existing performance evaluation process of constructed wetlands (CWs) is complex, with shortcomings in both simplification of method and construction of simulation model, especially for low-efficiency CWs (LECWs, with an average close-degree calculated by the entropy weight method being <0.6). This study presents a case study of LECWs in the Ningxia region (comprising 13 subsurface flow constructed wetlands (SSF CWs) and 7 surface flow constructed wetlands (SF CWs)), employs the entropy weight method (EWM) to construct an evaluation of CW operational efficiency, simplifies evaluation indicators through principal component analysis (PCA), develops two random forest (RF) models to validate the rationality of the simplified indicators, and establishes simulation models by logistic regression (LR). The results demonstrate that the evaluation indicators of CWs can be simplified to chemical oxygen demand (COD) and total nitrogen (TN), with no significant difference observed between the evaluation results and the original model (P < 0.05), thereby indicating reliability. Moreover, the simulation model performs well with R2 values for fitting SSF CWs and SF CWs exceeding 0.8. According to the simulated results of the model, the operational efficiency of LECWs is more significantly affected by the COD removal rates compared to the TN removal rates. In comparison to influent with 0 < COD/TN < 3 and 5 < COD/TN < 8, the operational efficiency of SSF CWs and SF CWs is optimal when COD/TN is between 3 and 5. These research findings may provide valuable support for streamlining evaluation processes and daily management for LECWs.

Research on the dynamic characteristics and improvement path of urban sustainable development level: Based on gravitational model and scenario simulation method

The rapid expansion of cities has brought new challenges to sustainable development (SD). Therefore, how to balance between SD and the economic growth has become the key to regional development. With the aim of enhancing the research system of SD level, founded on the deep research of SD level from a new perspective of “input-output” and the dynamic evolution law of SD level, this paper has explored the path for cities to improve their level of SD to achieve regional coordinated development. By virtue of the Super-efficiency Slack-Based Measure model based on unexpected output (unexpected super efficiency SBM model), it has measured the SD level of 21 cities in Sichuan from 2010 to 2019. Using methods such as equilibrium coefficient, obstacle analysis and gravitational model, this paper has studied the spatiotemporal evolution law of SD level and constructed six scenarios to simulate the future trend of SD level. The results have indicated that the level of SD in Sichuan is showing a gradual decline with significant constraints. The focus of SD in Sichuan is gradually shifting from Chengdu to a city cluster centered around Chengdu, Ziyang, and Meishan. In an ideal development scenario, the level of SD has significantly improved. This study has revealed the current status and potential of SD in Sichuan. In the future, with more concentration on the role of core urban agglomerations, Sichuan should adjust policies to address input–output barriers to promote SD throughout the province.

Research on risk management of ship maintenance projects based on multi agent swarm model simulation method

In recent years, the role of naval ship power has become increasingly prominent in regional conflicts and military operations worldwide, and the powerful capabilities demonstrated by naval forces have also been valued by countries around the world. While naval forces are frequently deployed to carry out various tasks, the intensity of equipment wear and tear on ships is also significantly increasing, posing a huge challenge to the maintenance and support capabilities of ship equipment. In the actual process of ship equipment maintenance, a series of risk factors such as cost, schedule, and quality will have a significant impact on the entire ship maintenance project, and even affect the success or failure of the entire project. This article first decomposes the project process of ship maintenance projects, further analyzes the various risk factors of ship maintenance projects based on the project decomposition situation, and then distinguishes the overall project, project process, and project risk factors to establish an intelligent agent group model for simulation analysis. Through the above simulation analysis, we will conduct in-depth research on the specific impact of project risks on ship maintenance projects, and analyze and verify the positive role and practical significance of project risk management in project risk control and project efficiency improvement. In the process of the above research content, methods and measures for risk management of ship maintenance projects are proposed, providing scientific and efficient risk management suggestions for such projects, improving the scientific management efficiency of ship maintenance projects, and contributing to the improvement of the quality and efficiency of project management.

Analysis of culvert design methods as methods of ensuring reliability at the design stage

This analysis focuses on the factors and methods for ensuring the reliability of metal culverts, which are essential for the trouble-free operation of motorways. Special attention is paid to the calculation methods for structures with annular cross-sections. The results of the work are conclusions about the necessity of their annular cross-section. They also conclude the importance of developing these structures to enhance culverts’ durability and failure-free operation. This involves considering the stochastic nature of load parameters, structural materials, and operating conditions. Addressing this issue is possible through the assessment of reliability indicators for culverts using simulation modeling methods.

COMPARATIVE ANALYSIS OF FORMING TECHNOLOGY MULTI-GROUP TRAINS ON DIFFERENT SORTING DEVICES

Purpose. The purpose of the work is a comparative analysis of the multi-group trains forming technology on various sorting devices for solve the task of choosing the best sorting device depending on the initial conditions (combination of train and sorting devices parameters) using both one-sided and two-sided methods of forming such trains. Method. The methods of combinatorics, mathematical statistics and simulation modeling were used for comparative analysis of the of forming multigroup trains methods. The formalization of both classical one-sided and adapted two-sided formation methods was taken from published scientific publications. Results. An illustration of the use of one-sided and two-sided forming methods for real trains allows a better understanding of the reason for the superiority of some methods over others for certain initial conditions. As a result, with the help of a simulation model, the time indicators of the formation of multi-group trains were obtained for various initial conditions, the comparison of which allows to establish the best option for the implementation of the technology of the formation of multi-group trains. Practical importance. The performed analysis allows to choose the best method for each specific case of the initial conditions which will speed up the formation process and reduce the idling time of local cars at the stations. For this purpose, it is advisable to include the specified forming algorithm in the station dispatching staff decision-making support system, which based on the data about the cars parameters and given classification tracks specialization that used to form such trains, will allow to obtain the time parameters of train forming in different ways and choose the best of them (for example, with the minimum duration of the train formation), for which a shunting work plan will be offered.

A modeling method for thermal steady-state simulation of the four-layer printed circuit board.

Thermal simulation of a Printed Circuit Board (PCB) can help identify potential overheating risks in the circuit. The proposed modeling method combines analytical temperature solutions and numerical approximations. Only Fourier-series analytical solutions related to the prepreg-layer surfaces need to be calculated, rather than the entire structure. Heat transfer through the lateral sides of a PCB is approximately considered as part of the compensated heat flux of the insulating-layer surface boundaries. Heat diffusion within or between metal layers is numerically approximated using the finite volume method. The core layer is treated as "thermally-thick". Temperature-dependent boundary conditions are considered through iterations. A test solver was developed based on the method. The modeling accuracy was validated by comparison with COMSOL Multiphysics for a four-layer structure with a moderate degree of discretization. Additionally, a PCB for generating DC 3.3V was designed, tested, and modeled, with the modeling results confirmed by the thermal images. The electro-thermal analysis of the distribution of electric potential and Joule heating in traces and vias was integrated into the PCB model. The layout maps of the PCB were further adjusted to reduce Joule heating in the output circuit, and the improvement on reducing the IR drop and hotspot temperature was examined.

Prediction of Microstructure Evolution in Ball Mill Liner Forging Process

The liner is affixed to the inner side of the ball mill cylinder to protect the cylinder. Through isothermal compression experiments, Arrhenius constitutive models, peak strain models, critical strain models, dynamic recrystallization dynamic models, and grain size models suitable for the forging process of Mn–Cr–Ni–Mo steel used in ball mill liners were established. By utilizing Deform software, a 3D thermo‐force‐structure coupling model for the hot forging process of ball mill liners was constructed, and the volume fraction of dynamic recrystallization and average grain size during forging was predicted. The response surface model was employed to investigate how process parameters interacted with each other and affected microstructure uniformity in ball mill liners. After optimization, the optimal parameters were determined: initial forging temperature at 1200 °C, forging speed at 30 mm s−1, and friction coefficient at 0.3. Subsequently, a hot forging experiment on ball mill liners was conducted using these optimized parameters; samples were analyzed through backscattered electron diffraction device experiments and microscopic tissue observations. Results demonstrated that microstructural changes observed during actual forging processes aligned with numerical simulation results—thus verifying both the accuracy of the Mn–Cr–Ni–Mo steel material model and numerical simulation method.

Failure mechanism and model study of Link16 data link limiters caused by the electromagnetic pulse

Abstract Electromagnetic pulse can easily cause interference or damage to the circuit. This study used TCAD device-level modeling and device-circuit mixed simulation methods to investigate the impact of high-power microwaves on the radar front-end limiter. In addition, the variations of the electron concentration, the hole concentration, and the external drain current of the limiter with the electromagnetic pulse radiation are given by establishing a simulation model, and the damage mechanism of the limiter under the electromagnetic pulses (HPM) radiation is revealed. This study provides an important theoretical basis for the protection and reinforcement of PIN limiters.

Wireless transmission method of electromagnetic wave of cross screw signal

Abstract Based on the near-bit azimuthing gamma measuring instrument developed by Changqing Drilling Company, this paper uses comsol multiphysics(COMSOL) numerical simulation software to build the electromagnetic wave wireless transmission model of cross-bolt signal while drilling. By using finite element method and a large amount of calculation and analysis, the influence law of source distance, drill wire conductivity, borehole and mud conductivity and other parameters on the response characteristics is obtained. The simulation modeling method presented in this paper and the conclusions obtained have important guiding significance for further optimizing and upgrading the near-bit wireless short-pass device and better understanding and mastering the signal transmission law of this kind of instrument.

ASSESSMENT OF THE FINANCIAL RESULT OF PUBLIC-PRIVATE PARTNERSHIP PROJECT IMPLEMENTATION USING THE EXAMPLE OF A CONCESSION AGREEMENT

The article is aimed at developing a methodological approach to improving the efficiency of assessing the financial results of implementing Ukrainian and European business projects. In this context, the object of study is a specific individual partnership and cooperation project. The research has established that one of the key informational aspects of such a partnership is the assessment and forecasting of the financial result. The goal of the research is to present the methodological approach to assessing financial performance for an individual project in the most detailed form possible. The article presents an approach based on modern simulation modelling methods, systems analysis methodology, and the method of composite seasonal indices. All modelling processes were conducted using MATLAB software. MATLAB is a high-level programming language and interactive environment for numerical computation, visualization, and programming. This program is widely used for modelling and data processing in fields such as engineering, scientific research, and mathematics. The research result is presented as an approach to the mathematical modelling of assessing the financial performance of partnership projects of Ukraine with representatives of EU business. It is necessary to emphasize that the presented research has limitations related to changes in Ukraine's hyperdynamic external environment provoked by war. Forecasts may vary depending on the development of military actions. Therefore, the prospects for further research should be directed towards improving the informational provision in the system of partnership and cooperation with EU countries to increase their own investment security.

Runoff simulation modeling method integrating spatial element dynamics and neural network for remote sensing precipitation data

Effective management of water resources amidst global climate change necessitates advancements in runoff simulation techniques. This study introduces a novel methodology that integrates a spatial element dynamic model with a neural network designed for satellite precipitation product (SPP) and remote sensing data to address the complex dynamics of precipitation-runoff processes. Implemented in the Songhua River basin of China, the methodology features a runoff estimation module that operates across both high-resolution and SPP grid scales. This module synergizes spatial attributes with fuzzy classification for refined confluence optimization, and yielding simulations through long short-term memory network. The results indicate that the proposed multi-scale production-confluence scheme achieved Nash-Sutcliffe efficiency (NSE) scores of 0.87 and 0.84 during calibration (2011–2015) and validation (2017 and 2018) periods, respectively, representing an 8.15% improvement in peak percentage error (PPE10%) over conventional hydrologic models. Additionally, the scheme demonstrated superior simulation performance at tributary sites set compared to main channel sites set, with differences of 0.08 and 0.07 in NSE and Kling-Gupta efficiency (KGE), respectively. The introduction of the surface Ⅱ operator for adjusting precipitation intensity effectively improved runoff estimation accuracy, reducing the average error by 25.48% across both site sets. This study provides a scientific foundation for applying SPP in hydrological modeling and offers decision support for managing water resources.

Numerical study on dynamic response of a novel ribbed thin-walled UHPC box-type utility tunnel under gas explosion

At present, RC utility tunnels are widely used in urban utility tunnels. As a typical confined space, the complex load effect generated by the internal gas explosion of the gas tank of utility tunnel may lead to local damage or overall destruction of the structure of RC utility tunnel. Therefore, it is an important topic to improve the anti-explosion capability of the utility tunnel and ensure the normal operation of the utility tunnel after gas explosion. UHPC structure is considered to have excellent anti-explosion performance, so a ribbed thin-walled UHPC utility tunnel structure was proposed, which improved the overall stiffness and anti-explosion performance of the UHPC utility tunnel through the ribbed section. In view of the shortcomings of fluid-solid coupling method in gas simulation, Computational Fluid Dynamics (CFD) was used to calculate the overpressure distribution after gas explosion in UHPC utility tunnel. The accuracy of UHPC constitutive model and prestress simulation method was verified by testing results from the gas explosion on unbonded prestressed UHPC slab. The gas explosion damage mechanism of ribbed thin-walled UHPC utility tunnel, UHPC-NC combined utility tunnel and RC utility tunnel were comparatively analyzed. And the pre-fabricated stiffener height, UHPC slab thickness and UHPC strength were investigated on the anti-explosion performance of ribbed thin-walled UHPC utility tunnel against gas explosion. It is found that the UHPC strength needs to be enhanced dramatically to improve the blast resistance. The anti-explosion capability of utility tunnel can be effectively increased by increasing the rib height or increasing the thickness of the UHPC utility tunnel structure, and the damage pattern of the utility tunnel can also be changed from flexure-shear failure to bending failure. The results of the study can provide a reference for the damage analysis and anti-explosion design of ribbed thin-walled UHPC utility tunnels.

Novel pre-pressure friction spring RC rocking column with enhanced segment: Practical design and numerical investigation

A novel pre-pressure friction spring rocking column (PFSRC) with enhanced segment is proposed to improve the seismic resilient of RC frames. The construction of the PFSRC was introduced, and parameters of pre-pressure friction spring device (PFSD), and limit state of PFSRD were analyzed. Based on seismic performance objectives, a practical design method for PFSRC was proposed. Utilizing the developed self-centering constitutive model and rocking interface three-dimensional simulation method, a macroscopic numerical model of PFSRC was established using OpenSEES, and numerical simulations of designed PFSRC under cyclic loading were conducted. Subsequently, further parameter investigations were conducted on the seismic performance of PFSRC. The results indicate that the designed PFSRC demonstrates strength and stiffness equivalent to the fixed-base column under drift limit of 1/550, and, at a drift limit of 1/50, there is no stiffness degradation, and the ultimate resistance is comparable to the fixed-base column. The steel tube effectively avoid the damage of the concrete at the foot of column. Increasing the friction coefficient of friction spring most effectively enhanced the energy dissipation of the PFSRC, and the taper angle has the most significant effect on the post-yield stiffness of the PFSRC, but increasing this parameter leads to decrease the energy dissipation. While increasing the pre-pressure effectively improves the yield strength and resistance of PFSRC. The damage extent of the PFSRC is affected by both axial compression ratio and steel tube diameter-to-thickness ration, and the low damageability of PFSRC can be achieved by adjusting the diameter-to-thickness ratio. For the buildings with unidirectional seismic demands (such as retrofit buildings), it is recommended to placed PFSD at 30° along that direction, for the general building with bidirectional seismic demands, PFSD should be arranged at 45° along that direction.

Street Community-Level Urban Flood Risk Assessment Based on Numerical Simulation

Urban waterlogging is a serious urban disaster, which brings huge losses to the social economy and environment of the city. As an important means of urban rainfall inundation analysis, numerical simulation plays an important role in promoting the risk assessment of urban waterlogging. Scientific and accurate assessment of waterlogging disaster losses is of scientific significance for the formulation of disaster prevention and mitigation measures and the guidance of post-disaster recovery and reconstruction. In this study, the SCS-CN hydrological model and GIS coupling numerical simulation method were used to simulate the inundation of urban waterlogging under four different rainfall return periods and to realize the visualization of the inundation range and waterlogging depth in Zhengzhou. At the same time, based on the numerical simulation results, the building is used as the basic assessment unit to construct a refined assessment framework for urban waterlogging risk at the street community level based on hazard, exposure, and vulnerability analysis. The refined risk assessment results have an important reference value for optimizing the working ideas of waterlogging control and providing a reference for local management departments to effectively deal with waterlogging disasters.

A Function-Based Behavioral Modeling Method for Air Combat Simulation

A Function-Based Behavioral Modeling Method for Air Combat Simulation

Deep Learning–Based Production Forecasting and Data Assimilation in Unconventional Reservoir

Summary Developing unconventional reservoirs such as shale oil is vital for fulfilling the need for energy consumption in the world. Oil production from shale reservoirs is still the most complicated and uncertain phenomenon because of its complex fracture networking, low matrix porosity, and permeability. Production forecasting is crucial for decision-making and tactical exploitation of subsurface resources during production. Traditional methods, such as the Arps decline model and reservoir simulation methods, face significant challenges in forecasting hydrocarbon production due to the highly nonlinear and heterogeneous nature of rocks and fluids. These methods are prone to substantial deviations in forecasting results and show limited applicability to unconventional reservoirs. Therefore, it is essential to improve the production forecasting capability with the help of a data-driven methodology. The data set for modeling is collected from two prominent shale oil-producing regions, the Eagle Ford and the Bakken. The Bakken data set is used to train and test the models, and the Eagle Ford data set is used to validate the model. The random search method was used to optimize the model parameters, and the window sliding technique was used to find a suitable window size to predict future values efficiently. The combination of different deep learning (DL) methods has designed a total of six hybrid models: gated recurrent unit (GRU), long short-term memory (LSTM), and temporal convolutional network (TCN). These models can capture the spatial and temporal patterns in the oil production data. The results concluded that the TCN-GRU model performed best statistically and computationally compared with other individual and hybrid models. The robust model can accelerate decision-making and reduce the overall forecasting cost.