Simulation Technology Research Articles

Generative artificial intelligence of things systems, multisensory immersive extended reality technologies, and algorithmic big data simulation and modelling tools in digital twin industrial metaverse

Research background: Multi-modal synthetic data fusion and analysis, simulation and modelling technologies, and virtual environmental and location sensors shape the industrial metaverse. Visual digital twins, smart manufacturing and sensory data mining techniques, 3D digital twin simulation modelling and predictive maintenance tools, big data and mobile location analytics, and cloud-connected and spatial computing devices further immersive virtual spaces, decentralized 3D digital worlds, synthetic reality spaces, and the industrial metaverse. Purpose of the article: We aim to show that big data computing and extended cognitive systems, 3D computer vision-based production and cognitive neuro-engineering technologies, and synthetic data interoperability improve artificial intelligence-based digital twin industrial metaverse and hyper-immersive simulated environments. Geolocation data mining and tracking tools, image processing computational and robot motion algorithms, and digital twin and virtual immersive technologies shape the economic and business management of extended reality environments and the industrial metaverse. Methods: Quality tools: AMSTAR, BIBOT, CASP, Catchii, R package and Shiny app citationchaser, DistillerSR, JBI SUMARI, Litstream, Nested Knowledge, Rayyan, and Systematic Review Accelerator. Search period: April 2024. Search terms: “digital twin industrial metaverse” + “artificial Intelligence of Things systems”, “multisensory immersive extended reality technologies”, and “algorithmic big data simulation and modelling tools”. Selected sources: 114 out of 336. Published research inspected: 2022–2024. PRISMA was the reporting quality assessment tool. Dimensions and VOSviewer were deployed as data visualization tools. Findings & value added: Simulated augmented reality and multi-sensory tracking technologies, explainable artificial intelligence-based decision support and cloud-based robotic cooperation systems, and ambient intelligence and deep learning-based predictive analytics modelling tools are instrumental in augmented reality environments and in the industrial metaverse. The economic and business management of the industrial metaverse necessitates connected enterprise production and big data computing systems, simulation and modelling technologies, and virtual reality-embedded digital twins.

Innovative approaches in enhanced oil recovery: A focus on gas injection synergies with other EOR methods

Enhanced Oil Recovery (EOR) techniques have become crucial in extending the productive life of mature oil fields and maximizing resource extraction. Among these, gas injection methods, particularly those involving CO₂, nitrogen, and hydrocarbon gases, have shown significant promise. This review focuses on the innovative synergies achieved by combining gas injection with other EOR methods to enhance recovery efficiency and economic viability. Gas injection techniques work by increasing reservoir pressure and reducing oil viscosity, facilitating easier flow and extraction. When integrated with other EOR methods such as thermal, chemical, and microbial techniques, the synergistic effects can lead to even greater enhancements in oil recovery. For instance, the combination of gas injection with thermal EOR, like steam injection, can improve the displacement of heavy oils by simultaneously reducing viscosity and enhancing thermal conductivity within the reservoir. Similarly, integrating gas injection with chemical EOR methods, such as polymer flooding, can optimize the sweep efficiency by leveraging the mobility control provided by polymers and the pressure maintenance by gases. Recent advancements in monitoring and simulation technologies have further improved the effectiveness of these combined approaches. Real-time reservoir simulation and 4D seismic monitoring allow for precise tracking of gas and fluid movements, enabling dynamic adjustments to injection parameters for optimal performance. Smart well technologies, equipped with advanced downhole sensors, provide continuous data on reservoir conditions, facilitating more responsive and adaptive EOR strategies. However, these innovative synergies are not without challenges. Economic feasibility remains a significant concern, particularly given the high costs associated with gas procurement and the integration of multiple EOR techniques. Additionally, managing the complex interactions between different EOR methods and heterogeneous reservoir conditions requires sophisticated modeling and robust operational protocols. In conclusion, the integration of gas injection with other EOR methods offers a promising pathway to enhance oil recovery rates and extend the lifespan of mature reservoirs. Continued research and development, coupled with cross-industry collaboration, are essential to overcoming the economic and technical challenges associated with these innovative approaches. This review underscores the potential for gas injection synergies to revolutionize EOR practices and drive sustainable growth in the oil and gas industry.

Analysis of Reader Orientation on Detection Performance of Hilbert Curve-based Fractal Chipless RFID Tags

The role of the orientation of the radio frequency identification (RFID) reader is vital in the RFID-based communication system. This study presents the design and analysis of the impact of the orientation of the RFID reader (angle of incidence of the plane wave) on the detection and sensitivity characteristics of fractal chipless RFID tags. Four fractal (irregular) shaped tags are developed using four iterations of the Hilbert curve filling algorithm. The full-wave EM analysis of the designed tags in Matlab is performed by exporting them in Computer Simulation Technologies Micro-Wave Studio (CST MWS) in the frequency range of 2 to 20 GHz. Firstly, the performance of the tags is analyzed by observing the radar cross-section (RCS) of the tag for the fixed orientation of the incident plane wave in three different polarizations (horizontal, vertical, and oblique). Later, the variations in the EM spectrum (RCS results) are analyzed for oblique polarization by varying the incidence plane wave in both elevations (for two cases of 0∘ and 90∘) and azimuth planes (sweeping from 0∘ to 180∘ with a step size of 10∘). The analysis of the proposed aggregated RCS response for all cases in oblique polarization produces higher coding capacity (169 bits), coding spatial capacity (16.504 bits/cm2), coding spectral capacity (9.826 bits/GHz), and coding density (0.960 bits/GHz/cm2) for the realized highly irregular tag using fourth-iteration (4T) of Hilbert curve filling algorithm. The proposed procedure of detection based on aggregated response makes the developed RFID communication system more secure and reliable.

A Multiphase and Multicomponent Model and Numerical Simulation Technology for CO2 Flooding and Storage

In recent years, CO2 flooding has become an important technical measure for oil and gas field enterprises to further improve oil and gas recovery and achieve the goal of “dual carbon”. It is also one of the concrete application forms of CCUS. Numerical simulation based on CO2-EOR plays an indispensable role in the study of the mechanism of CO2 flooding and buried percolation, allowing for technical indicators to be selected and EOR/EGR prediction to be improved for reservoir engineers. This paper discusses the numerical simulation techniques related to CO2 flooding and storage, including mathematical models and solving algorithms. A multiphase and multicomponent mathematical model is developed to describe the flow mechanism of hydrocarbon components–CO2–water underground and to simulate the phase diagram of the components. The two-phase P-T flash calculation with SSI (+DEM) and the Newton method is adopted to obtain the gas–liquid phase equilibrium parameters. The extreme value judgment of the TPD function is used to form the phase stability test and miscibility identification model. A tailor-made multistage preconditioner is built to solve the linear equation of the strong-coupled, multiphase, multicomponent reservoir simulation, which includes the variables of pressure, saturation, and composition. The multistage preconditioner improves the computational efficiency significantly. A numerical simulation of CO2 injection in a carbonate reservoir in the Middle East shows that it is effective for researching the recovery factor and storage quantity of CO2 flooding based on the above numerical simulation techniques.

A high-isolated wideband two-port MIMO antenna for 5G millimeter-wave applications

Fifth-generation (5G) technology is extremely important in the current context since it seeks to fix the shortcomings of its predecessors, the 4G generation. To achieve this goal, this project entails constructing a small ultra-wideband (UWB) MIMO antenna featuring an anti-parallel layout, designed for operation within the millimeter-wave spectrum. Moreover, the investigation scrutinizes and fine-tunes the mutual coupling interaction between the two elements in detail. The presented MIMO antenna occupies a small footprint of 6 × 17.37 mm2. Despite its compact dimensions, this MIMO antenna provides an impressive isolation of 65 dB, attributed to the adequate inter-element spacing and the anti-parallel arrangement. Additionally, the integration of a defected ground structure (DGS) enhances isolation by approximately 20 dB. Furthermore, the proposed MIMO antenna demonstrates a satisfactory gain of approximately 6 dBi, boasting high efficiency surpassing 96 %, and lying between 34.1 and 39.7 GHz. The proposed antenna has undergone simulation and analysis utilizing both the High-Frequency Structure Simulator (HFSS) and Computer Simulation Technology (CST) in order to confirm its utility. Based on these findings, the suggested MIMO antenna appears to be well-suited for compatibility with 5G communication systems, specifically covering the n260 band (37–40 GHz) and the Ka-band.

Development of nano ferrite coated miniaturised jute antenna for wireless applications

In this work, a microstrip patch antenna is designed using a novel Ytterbium doped Cu-Mn Nano ferrite coated jute substrate for S band (2-4 GHz) applications. The prepared material is characterised by structural and electromagnetic properties to examine and analyse the effect of material factors on antenna substrate suitability. The antenna is designed and simulated using Computer Simulation Technology (CST) software. The antenna parameters such as gain are improved by employing super formula and meander line techniques. The fabricated antenna also shows better performance with return loss, Voltage Standing Wave Ratio (VSWR) and gain values.

Training in cardiothoracic surgery: The role for simulation.

Adequate cardiothoracic surgical training is essential for provision of quality care to patients. In recent years, simulation-based training has been advocated as an adjunct to traditional surgical training. Advances in simulation technology has resulted in many low- and highfidelity simulators being employed in cardiothoracic surgical training. Such models allow trainees to practice an array of realistic full-length procedures in a safe and controlled environment, with the window to make mistakes and consider them learning points. There is significant evidence to demonstrate the effectiveness of cardiothoracic surgery simulation in improving surgical skills and operating room performances in addition to building confidence among trainees. However, owing to the high financial cost of arranging it, simulation-based training is not widespread in low- and middle-income countries, including Pakistan. More work is warranted on the cost effectiveness of implementing simulation-based learning, which, in turn, would increase the uptake of simulation to enhance cardiothoracic surgical training in Pakistan.

Melt Pool Simulation Technology of Laser Powder Bed Fusion: A Review

Melt Pool Simulation Technology of Laser Powder Bed Fusion: A Review

Assessing Student Satisfaction When Using Virtual Reality Content on the Example of Injection Manipulations

The scientific substantiation of the effectiveness of the use of virtual simulation technologies in the system of training medical personnel will significantly improve the quality of the formation of practice-oriented competencies among students of medical universities.

An improved infrared simulation method based on generative adversarial networks

Infrared simulation technology has great application value in the fields of UAV target simulation and infrared signal processing. However, traditional infrared simulation technology has the disadvantages of poor scene adaptability, low fidelity of infrared simulation images and long training time. This paper proposes an infrared image simulation algorithm based on improved Generative Adversarial Networks(GAN) to generate multi-scene infrared images, which could provide a reliable expansion of infrared database. First, we construct a GAN model by introducing a multi-resolution hierarchical structure and attention mechanism, which can effectively enhance the model’s adaptability to different scenes during the simulation of generating infrared images. Secondly, the SSIM loss term and L1 loss term are introduced during the training process to form a composite loss function, which prompts the proposed GAN to generate high-fidelity infrared simulation images. Finally, while maintaining the quality of simulated infrared images, a lightweight model is designed through model compression to significantly reduce the number of model parameters.The traditional discriminator based on the UNet-self attention is replaced by a discriminator based on attention mechanisms and adaptive max-pooling structure. The proposed GAN is trained and tested on three public datasets. Experimental results demonstrate that the proposed method improves structural similarity by 11% compared to Pix2Pix and achieves a Peak Signal-to-Noise Ratio (PSNR) of 25.8, which is 3.9 higher than InfraGAN. At the same time, compared with InfraGAN, the number of model parameters is reduced by 68% , which makes the method efficiently obtain simulated infrared images corresponding to given visible images.

Redefining fan manufacturing: Unveiling industry 5.0's human-centric evolution and digital twin revolution

Industry 5.0 has the capacity to surpass the technology -oriented efficiency of Industry 4.0 and advance sustainable development objectives such as prioritizing human needs, ensuring socio-environmental sustainability, and enhancing resilience. Digital twins and simulation technologies improve manufacturing, evaluate products and operations, and predict any potential adverse consequences. With digital twin technology, everything that exists in the physical world will eventually be duplicated in the digital realm. Within the context of Industry 5.0, this study aims to investigate the impact of digital twin technology on the fan manufacturing sector. The proposal for implementing the enabling industry 5.0 application was presented to the chief engineers of eight distinct fan manufacturers. Out of these, five responded positively and their feedback was subsequently followed up on. Three different avenues such as production, supply chain, and testing transparency were proposed for industry 5.0 implementation. The exploration of testing transparency is being undertaken based on a consensual decision. The Web of Things standard that enables digital twin generation in industry 4.0 is implemented to enable the testing transparency. This data was linked with the internal digital twin of fan motor created using ANSYS. This digital twin can predict the lifespan of the motor by analyzing the temperature of the motor housing surface. Toward sustainability and resilience with Industry 4.0 and Industry 5.0 may provide insights into this alignment.

Ultra-thin wide-band split-ring resonator-based compact mu-negative metamaterial for terahertz applications

This paper focuses on designing and investigating a new type of metamaterial called an ultra-thin wide-band mu-negative (MNG) metamaterial. The targeted frequency range is 0.1–10 THz. At the resonance frequency of 6.37 THz, the permeability (μ) of the structure is negative, allowing it to function as an MNG metamaterial. Computer Simulation Technology (CST) and High-Frequency Structure Simulator (HFSS) 3D software simulations, examining the scattering and medium parameters of the MNG metamaterial. The findings demonstrate that the proposed MNG metamaterial exhibits resonance peaks in the mu-negative region at 6.37 THz and wide frequency bands of 8.79 THz at −10 dB in the CST simulator. The structure is adaptable based on design parameters. This MNG metamaterial is unique due to its ultra-thin, a form mu-negative wide bandwidth of 3.20 THz, and suitable resonance frequencies. The simulation results from Ansys HFSS software almost align with CST results. The structure, resonating in the THz region with wide bandwidth, shows potential applications in spectroscopy and biomedical engineering. The study encountered difficulties in achieving precise fabrication at the nanoscale and ensuring the reproducibility of metamaterial properties across various samples. Despite these challenges, the proposed metamaterial shows significant advancements in terahertz technology.

A Study on the Application of Virtual Simulation Technology in Dual-creation Education

A Study on the Application of Virtual Simulation Technology in Dual-creation Education

Investigating specimen size and shape effects on compressive mechanical behaviors of recycled aggregate concrete using discrete element mesoscale modeling

In comparison to natural aggregate concrete (NAC), recycled aggregate concrete (RAC) typically exhibits a more diverse composition of materials, heightened variability and greater inherent weaknesses. These characteristics may result in varying effects of specimen size and shape on compressive responses. Within this framework, the present study endeavors to comprehensively investigate these influences on RAC's compressive properties and their underlying mechanisms utilizing discrete element simulation technology. At the mesoscale, RAC is depicted by several components, encompassing both new and old aggregates, mortar and interfacial transition zones. Through integrating contacts for each phase, elucidating mesoscale mechanical responses with a parallel bond model and introducing Weibull random fields to delineate variations in phase properties, this study effectively simulates these mechanical responses. Subsequent extensive calculations scrutinize the repercussions of specimen size and shape on the compressive strength, elastic modulus, peak strain and failure modes of RAC across varying water-to-binder ratios. The study concludes that RAC manifests a size effect, albeit less pronounced than in NAC with an equivalent water-to-cement ratio, yet more significant than in mortar. Moreover, owing to end plate constraints, the reduction in RAC's cubic compressive strength is notably less than its prismatic compressive strength. Based on these findings, it is recommended to establish the strength size reduction coefficient and cube-to-cylinder shape coefficient for RAC at 0.86 and 0.72, respectively. Notably, these values diverge significantly from the respective 0.81 and 0.78 coefficients for NAC.

Innovative Adaptive Multiscale 3D Simulation Platform for the Yellow River Using Sphere Geodesic Octree Grid Techniques

Earth system simulation technology is fundamental for ecological protection and high-quality development in the Yellow River Basin. To address the lack of a Yellow River simulation platform, this study proposes an adaptive multiscale true 3D crust simulation platform using the Sphere Geodesic Octree Grid (SGOG). Twelve models in four categories were designed: single fine-scale models, geomorphic zone-based models, and models using both top-down and bottom-up approaches. The models were evaluated based on terrain feature representation and computational efficiency. The results show that single fine-scale models preserve detailed terrain features but are computationally intensive. They are suitable for the precise simulation of surface processes. Top-down and bottom-up models balance terrain detail and efficiency, and are thereby widely applicable. Geomorphic zone-based models provide detailed focal area representation and higher computational efficiency, being more targeted. Various methods offer flexible scale transformations, each with its own strengths, allowing researchers to select a method according to practical application needs. Consequently, this research demonstrates that spherical discrete grids offer reliable support for constructing basin simulation platforms, providing new technological and scientific insights for the Yellow River Basin’s ecological protection and development.

Perioperative medicine: is there a place for simulation technologies?

The article discusses in detail a new direction in clinical practice – perioperative medicine. Perioperative medicine is a set of measures aimed at reducing variability in care throughout the perioperative period and improving their coordination. It is emphasized that anesthesiologists and intensive care specialists have the greatest competencies for this area. The authors discuss in detail the role of simulation technologies in the training of doctors of perioperative medicine, focusing on teaching non-technical and cognitive skills.

Application of Passive Infrared Sensor to Improve the Quality of CCTV in Maintaining Home Security

Artificial intelligence, or AI, is a simulation technology that runs through human intelligence demonstrated by machines or tools. Artificial intelligence can overcome and provide a sense of comfort, especially in the application of CCTV devices that use this passive infrared sensor method. This method can detect thieves or people moving in the area of the house where CCTV is installed, by detecting human objects using IR filters. If it detects an object that has the minimum temperature possessed by humans, it will immediately direct the alarm indicator. With the existence of CCTV that applies AI, it is hoped that human life will be safe, and crime will be reduced in an area, especially quiet areas with high crime rates. The application of Passive Infrared Sensor (PIR Sensor) in this anti-theft CCTV tool can detect and be able to work with a high level of accuracy.

Digital media entertainment technology based on artificial intelligence robot in art teaching simulation

The combination of digital media entertainment technology and artificial intelligence robots provides new possibilities for art teaching, providing students with a richer and more personalized learning experience. The aim of this study is to explore the application of artificial intelligence based digital media entertainment technology in art teaching simulation. By designing an intelligent digital media system, the interactivity, personalization, and effectiveness of art teaching can be improved. Research the use of digital media interactive technology to create an immersive art learning environment. Applying artificial intelligence recommendation algorithms to recommend personalized art teaching resources to students based on their learning history, interests, and abilities, in order to improve learning efficiency and outcomes. Combining artificial intelligence recommendation algorithms, intelligently recommend suitable art teaching resources for different students’ needs and levels. Through teaching interaction simulation testing, evaluate the interaction effect and user experience of the system in simulated art teaching scenarios, identify and fix potential problems. By utilizing digital media interaction technology and personalized recommendation algorithms, designing an intelligent digital media system can effectively enhance the interactivity, personalization, and effectiveness of art teaching, providing students with a better learning experience.

Simulation and Modelling as Catalysts for Renewable Energy: A Bibliometric Analysis of Global Research Trends

This study investigates the application of advanced simulation and modeling technologies to optimize the performance and reliability of renewable energy systems. Given the urgent need to combat climate change and reduce greenhouse gas emissions, integrating renewable energy sources into existing infrastructure is essential. Using bibliometric methods, our research spans from 1979 to 2023, identifying key publications, institutions, and trends. The analysis revealed a significant annual growth rate of 16.78% in interest in simulation and modeling, with a notable surge in published articles, reaching 921 in 2023. This indicates heightened research activity and interest. Our findings highlight that optimization, policy frameworks, and energy management are central themes. Leading journals like Energies, Energy, and Applied Energy play significant roles in disseminating research. Key findings also emphasize the importance of international collaboration, with countries like China, the USA, and European nations playing significant roles. The three-field plot analysis demonstrated interconnections between keywords, revealing that terms like “renewable energy sources”, “optimization”, and “simulation” are central to the research discourse. Core funding agencies, such as the National Natural Science Foundation of China (NSFC) and the European Union, heavily support this research. This study underscores the importance of policies and sustainability indicators in promoting renewable energy technologies. These insights emphasize the need for ongoing innovation and interdisciplinary collaboration to achieve a sustainable energy future.

The influence Cl− on stress corrosion of 7xxx series aluminium alloys studied by experimental and simulation technology

The stress corrosion behavior of 7xxx series aluminium alloys in different concentrations NaCl solution was studied, and numerical simulation was conducted in COMSOL Multiphysics based on experimental results. Different stresses were applied on the experiment pieces, the pitting crater deepened with the change of stress level. The corrosion rate increased with the raising stress. There is no positive correlation between stress corrosion degree and chloride ion concentration. The most severe corrosion occurs in 5.0 wt% NaCl solution instead of 6.0 wt% NaCl solution due to the increase of water film conductivity and decrease of solubility of oxygen under high Cl− environment. The finite element model was used to analyze the stress distribution on aluminium alloy surface, to describe the dynamic equation of anodic dissolution of metal due to elastic and plastic deformation. Corrosion occurs mainly in stress concentrated areas. When the stress loading exceeds a certain threshold, plastic strain occurs on the surface of both the specimen and the structural part, the corrosion current density increases instantaneously, and the corrosion behavior in the stress concentration area gradually intensifies. The survey can provide practical theoretical guidance for predicting stress corrosion and extending the service life of equipment in (harsh) marine environments.