3D Simulation Research Articles

The Effect of Oil Contaminated on Collapse Pattern in Gypseous Soil Using Particle Image Velocimetry and Simulation

Gypseous soil covers approximately 30% of Iraqi lands and is widely used in geotechnical and construction engineering as it is. The demand for residential complexes has increased, so one of the significant challenges in studying gypsum soil due to its unique behavior is understanding its interaction with foundations, such as strip and square footing. This is because there is a lack of experiments that provide total displacement diagrams or failure envelopes, which are well-considered for non-problematic soil. The aim is to address a comprehensive understanding of the micromechanical properties of dry, saturated, and treated gypseous sandy soils and to analyze the interaction of strip base with this type of soil using particle image velocimetry (PIV) measurement and Plaxis 3D simulation. The results showed that high-resolution digital cameras captured soil deformation using PIV, displacement fields, and velocity vectors were generated, which helped identify different sand movement zones. Further, PIV showed punching and general shear failure in uncontaminated and soaked contaminated gypsum soils, respectively. Moreover, the Plaxis results corresponded well with the PIV, as material behavior models are essentially simplified representations of the actual behavior of footing and soil. Understanding soil deformation behavior is crucial for accurate engineering calculations and designs, making these findings valuable for geotechnical and construction engineering applications. Doi: 10.28991/CEJ-2024-010-07-016 Full Text: PDF

3D Modelling and Simulation Based on Kinematic Analysis for Hippotherapy

The engineering perspective on the physiology and anatomy of living things has led to the emergence of the science of biomechanics. Developing computer technologies have made it possible to examine the behaviour of living things in more detail and to develop technologies that enable kinetic and kinematic analysis of movements to imitate real limbs. In this study, the natural gaits of horses (Walk, Canter and Trot) were analysed with image processing techniques, kinematic analyses were made and three-dimensional solid models were created. Giving movement ability to the extracted solid models was carried out with the simulation software prepared on the Matlab-SimMechanic platform. By comparing the findings obtained as a result of image processing and simulation, the success of transferring the movements to a developed system was evaluated. After mathematical equations were created in the MATLAB environment, the equations were tested on the developed system and their performance rates were determined. With the developed system, joint angles, ability to reach the correct position and movement ability were analysed and it was shown how the mathematical equations required to perform the movements could be derived. As a result, a design process model for movement analysis, simulation and control of different living groups is presented with the equations obtained by formulating the information obtained from the developed system.

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.

SIMULACIÓN AVANZADA DE UN BRAZO ROBÓTICO CON 2 GRADOS DE LIBERTAD, CONTROLADO EN SIMSCAPE

In this project, a robotic arm was developed, modeled, and implemented using the Matlab Simulink programming platform. The robotic arm was designed with 2 degrees of freedom and equipped with three motors, allowing for precise and coordinated control of its movements. For simulating the dynamic and kinematic behavior of the arm, Simscape blocks were used, facilitating a detailed three-dimensional representation of the system. The main objective of the project was to demonstrate a simulation of the robotic arm that allows for precise control of the movement angles. Through a detailed 3D simulation in Simscape, the movement and interaction of the arm's components could be visualized, validating its capability to perform tasks with high precision and efficiency. The results obtained demonstrate the effectiveness of using Simulink and Simscape in the design and simulation of robotic systems, highlighting the importance of these tools for automated development.

3D 의류 시뮬레이션 Z-weave 프로그램을 이용한 실물 소재 비교와 지속 가능한 패션 산업에서의 실현성

This study aims not only to address environmental issues caused by indiscriminate fashion consumption, specifically in the context of Fast Fashion but also to find an alternative and a sustainable solution that is ‘Upcycling’ using the 3D clothing simulation program Z-weave. Upcycling products have limitations in that it is difficult to produce samples since finished products must be produced directly with limited materials and resources like waste clothes. To overcome these limitations, a 3D clothing simulation program is introduced to effectively utilize the limited resources of waste clothing. The purpose of this study is to confirm the similarity between a virtual fabric created through Z-weave and a real fabric, through this, to evaluate the possibility of application in the actual fashion industry. As a research method, surveys and interviews were conducted with related majors on virtual clothing created as similar as possible to actual clothing by adjusting the physical properties within the Z-weave program. This study attempted to describe the impact of digital technology on the fashion industry and how 3D clothing simulation programs can be used in sustainable fashion production.

Dual Domain Decomposition Method for High-Resolution 3D Simulation of Groundwater Flow and Transport

The high-resolution 3D groundwater flow and transport simulation problem requires massive discrete linear systems to be solved, leading to significant computational time and memory requirements. The domain decomposition method is a promising technique that facilitates the parallelization of problems with minimal communication overhead by dividing the computation domain into multiple subdomains. However, directly utilizing a domain decomposition scheme to solve massive linear systems becomes impractical due to the bottleneck in algebraic operations required to coordinate the results of subdomains. In this paper, we propose a two-level domain decomposition method, named dual-domain decomposition, to efficiently solve the massive discrete linear systems in high-resolution 3D groundwater simulations. The first level of domain decomposition partitions the linear system problem into independent linear sub-problems across multiple subdomains, enabling parallel solutions with significantly reduced complexity. The second level introduces a domain decomposition preconditioner to solve the linear system, known as the Schur system, used to coordinate results from subdomains across their boundaries. This additional level of decomposition parallelizes the preconditioning of the Schur system, addressing the bottleneck of the Schur system solution while improving its convergence rates. The dual-domain decomposition method facilitates the partition and distribution of the computation to be solved into independent finely grained computational subdomains, substantially reducing both computational and memory complexity. We demonstrate the scalability of our proposed method through its application to a high-resolution 3D simulation of chromium contaminant transport in groundwater. Our results indicate that our method outperforms both the vanilla domain decomposition method and the algebraic multigrid preconditioned method in terms of runtime, achieving up to 8.617× and 5.515× speedups, respectively, in solving massive problems with approximately 108 million degrees of freedom. Therefore, we recommend its effectiveness and reliability for high-resolution 3D simulations of groundwater flow and transport.

Does 3D simulation impact clinical reasoning for orthodontic treatment planning of impacted maxillary canines?

Clinical reasoning is an essential competence to develop in the diagnosis and treatment planning of impacted maxillary canines to ensure good treatment outcomes. It involves skills of radiographic interpretation and mental visualization. To master these, postgraduate students learn to interpret 2D and 3D X-rays to locate these canines accurately. This process demands the creation of mental models of the impaction and resolving it either by envisioning the canine's movement to its correct position or considering its removal. To facilitate this cognitive exercise, a 3D-printed simulator, derived from Cone Beam Computed Tomography scans, serves as a tool to allow students to experiment with various movement simulations, helping them select the most viable treatment approach.This project aimed to assess the differences in expert and novice orthodontists’ clinical reasoning for impacted maxillary canines, and whether the addition of a 3D simulator would affect their reasoning. Thirteen (13) novices randomly assigned to a control and intervention group and three (3) experts took part in a Think-Aloud exercise to diagnose and treatment plan a case of bilaterally impacted maxillary canines. Experts and intervention group novices had the 3D simulator in addition to standardized patient records. Their responses were recorded and analyzed according to a coding scheme reflecting the clinical reasoning process. While experts demonstrated quick clinical judgment and found the 3D simulator redundant, novices were more uncertain and required additional cues. Novices using the 3D simulator described more elaborate treatment plans and had increased awareness of potential complications as compared to the control group.

A Review of Machine Learning Methods in Turbine Cooling Optimization

In the current design work, turbine performance requirements are getting higher and higher, and turbine blade design needs multiple rounds of iterative optimization. Three-dimensional turbine optimization involves multiple parameters, and 3D simulation takes a long time. Machine learning methods can make full use of historically accumulated data to train high-precision data models, which can greatly reduce turbine blade performance evaluation time and improve optimization efficiency. Based on the data model, the advanced intelligent combinatorial optimization technology can effectively reduce the number of iterations, find the better model faster, and improve the optimization calculation efficiency. Based on the different cooling parts of turbine blades and machine learning, this research explores the potential of implementing different machine learning algorithms in the field of turbine cooling design.

TAAM refinement on high-resolution experimental and simulated 3D ED/MicroED data for organic molecules.

3D electron diffraction (3D ED), or microcrystal electron diffraction (MicroED), has become an alternative technique for determining the high-resolution crystal structures of compounds from sub-micron-sized crystals. Here, we considered L-alanine, α-glycine and urea, which are known to form good-quality crystals, and collected high-resolution 3D ED data on our in-house TEM instrument. In this study, we present a comparison of independent atom model (IAM) and transferable aspherical atom model (TAAM) kinematical refinement against experimental and simulated data. TAAM refinement on both experimental and simulated data clearly improves the model fitting statistics (R factors and residual electrostatic potential) compared to IAM refinement. This shows that TAAM better represents the experimental electrostatic potential of organic crystals than IAM. Furthermore, we compared the geometrical parameters and atomic displacement parameters (ADPs) resulting from the experimental refinements with the simulated refinements, with the periodic density functional theory (DFT) calculations and with published X-ray and neutron crystal structures. The TAAM refinements on the 3D ED data did not improve the accuracy of the bond lengths between the non-H atoms. The experimental 3D ED data provided more accurate H-atom positions than the IAM refinements on the X-ray diffraction data. The IAM refinements against 3D ED data had a tendency to lead to slightly longer X-H bond lengths than TAAM, but the difference was statistically insignificant. Atomic displacement parameters were too large by tens of percent for L-alanine and α-glycine. Most probably, other unmodelled effects were causing this behaviour, such as radiation damage or dynamical scattering.

Analysis of seepage behavior of porous asphalt pavement based on scale test and three-dimensional simulation

This study implemented indoor scaled drainage testing and three-dimensional (3D) finite element simulations to analyze the seepage behavior of ultra-wide cross-section porous asphalt concrete (PAC) pavement with voids of 18 %, 20 % and 22 %. The seepage water level curves under the rainfall intensity of 0.5, 1, 2, 10, 50 and 100 years recurrence intervals were obtained by scaled test. The Seep3D software was used to analyze the seepage state of the ultra-wide cross-section porous pavement. Results indicated that void ratio was the paramount factor affecting the drainage capacity, which decreasing porosity significantly intensifies roadway surface water depth over 25 %. Water level curves obtained in scaled test showed similar trends to pore water pressure curves in 3D simulation. According to the theory of non-uniform gradual seepage, the pore water pressure can be used to effectively characterize the seepage state inside the porous pavement. Implementing cross drain with 10 m spacing maximally alleviated inundation by 23 %. Spacing intervals of 50 m, 30 m, and 20 m proportionately mitigated peak value by 4 %, 7 % and 12 % respectively.

Digital sand patch: Using laser scanning and discrete element simulation for rapider pavement texture depth measurement

The sand patch method is one of the most basic methods for measuring pavement texture depth (TD), which is an important reference index for pavement anti-skid performance evaluation and road maintenance. However, manual sand patch method heavily relies on the experience of the operators. The emergence of laser 3D scanning and simulation has made it possible to conduct digital sand patch. This study introduces a digital sand patch framework based on 3D scanning and discrete element simulation for precise TD measurement. We developed a 3D scanner with an accuracy of 0.04 mm to obtain the pavement texture data, along with algorithms for outlier removal and slope correction in point cloud data. The method of 3D reconstruction of triangular meshes was adopted to transform discrete point clouds into continuous 3D models to build 3D pavement models. In addition, the virtual process of rotation-spreading-measurement of the digital sand patch method was constructed by discrete element simulation with reference to the physical principles of the manual sand patch method. At the same time, an adaptive dynamic feedback control logic was proposed to accurately determine the termination conditions of the sand patching process. To validate our method, we collected 126 samples from over 20 km of pavement surfaces with various gradations. The results demonstrated an average relative error of 2.92 % compared to the manual sand patch method, and a correlation coefficient of 0.9926 with the laser scanning Mean Profile Depth (MPD) algorithm. Stability and accuracy tests, including scanning downsampling and volatility assessments, confirmed the robustness of our method. This innovative technique for rapid and precise TD measurement not only offers immediate practical benefits but also sets the stage for future research on pavement skid resistance.

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.

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.

Response characteristics and detectability of pegmatitic rare-metal deposits using different grounded-wire configurations

The differential electrical dipole (DED) and differentially normalized electromagnetic method (DNME) have a stronger transverse magnetic field than the horizontal electric dipole (HED) and, thus, have been successfully used for resource exploration in conductive ocean environments. However, which of these two is more suitable for the exploration of resistive targets on land, such as pegmatite veins and ore-related mafic and ultramafic intrusions in mineral deposits, remains unknown. Thus, we conduct a comparative study of the DED, DNME, and HED based on forward modeling and application to a field survey. The signal amplitude of the horizontal electric field measured using the DED and DNME is substantially weaker than that obtained via the HED with the same source length and transmitting current. The lateral variation in the horizontal electric field response observed via the DNME reflects the change in the shallow electrical structure, indicating the spatial distribution of pegmatite veins, as verified by the 3D simulation results and data obtained in a field survey of pegmatitic rare-metal deposits in Lushi County, China. The DED and DNME exhibit similar abilities for detecting resistive targets. Both methods show higher detectability than HED based on 3D synthetic modeling. Our results indicate that the DNME, with its higher responses and better lateral resolution, is a better choice in field surveys on land than the DED.

A novel hybrid-stress method using an eight-node solid-shell element for nonlinear thermoelastic analysis of composite laminated thin-walled structures

Composite laminated thin-walled structures, widely used in high-speed aircrafts, undergo a complex thermal–mechanical coupling environment. Geometrical nonlinearities with a thermal effect bring significant challenge to finite element analysis of structures. In this paper, a novel hybrid-stress method based on the solid-shell element is proposed for nonlinear thermoelastic analysis. An eight-node solid-shell element (CSSH8) is developed based on the assumed natural strain method and hybrid-stress formulations to overcome various locking problems and achieve an effective 3D simulation for structures with a large span-thickness ratio. The Green–Lagrange displacement-strain relation is selected to take the geometrical nonlinearities into account. The modified generalized laminate constitutive model is extended to consider both the thermal expansion and temperature-dependent material properties. A temperature variation along the laminate thickness can also be assumed in the constitutive model. Nonlinear thermoelastic equilibrium equations are derived using the Hellinger–Reissner variational principle, in which five different coupling cases for thermal–mechanical loads can be fully involved. Numerical examples demonstrate that the proposed method with CSSH8 element is insensitive to various distorted meshes and numerically robust to pass the buckling point; meanwhile large step sizes can be achieved in the path-following nonlinear thermoelastic analysis.

The response of gut microbiota to arsenic metabolism is involved in arsenic-induced liver injury, which is influenced by the interaction between arsenic and methionine synthase

The drivers of changes in gut microbiota under arsenic exposure and the mechanism by which microbiota affect arsenic metabolism are still unclear. Here, C57BL/6 mice were exposed to 0, 5, or 10 ppm NaAsO2 in drinking water for 6 months. The results showed that arsenic exposure induced liver injury and increased the abundance of folic acid (FA)/vitamin B12 (VB12)- and butyrate-synthesizing microbiota. Statistical analysis and in vitro cultures showed that microbiota were altered to meet the demand for FA/VB12 by arsenic metabolism and to resist the toxicity of unmetabolized arsenic. However, at higher arsenic levels, changes of these microbiota were inconsistent. A 3D molecular simulation showed that arsenic bound to methionine synthase (MTR), which was confirmed by SEC-UV-DAD (1 μM recombinant human MTR was purified with 0 or 2 μM NaAsO2 at room temperature for 1 h) and fluorescence-labeled arsenic co-localization (primary hepatocytes were exposed to 0, 0.5, or 1 μM ReAsH-EDT2 for 24 h) in non-cellular and cellular systems. Mechanistically, the arsenic-MTR interaction in the liver interferes with the utilization of FA/VB12, which increases arsenic retention and thus results in a substantial increase in the abundance of butyrate-synthesizing microbiota compared to FA/VB12-synthesizing microbiota. By exposing C57BL/6J mice to 0 or 10 ppm NaAsO2 with or without FA (6 mg/L) and VB12 (50 μg/L) supplementation in their drinking water for 6 months, we constructed an FA/VB12 intervention mouse model and found that FA/VB12 supplementation blocked the disturbance of gut microbiota, restored MTR levels, promoted arsenic metabolism, and alleviated liver injury. We demonstrate that the change of gut microbiota is a response to arsenic metabolism, a process influenced by the arsenic-MTR interaction. This study provides new insights for understanding the relationship between gut microbiota and arsenic metabolism and present therapeutic targets for arseniasis.

1D analytic and numerical analysis of thin film heat transfer gauges and infra-red cameras in non-planar applications

The impulse response method is widely used for heat transfer analysis in turbomachinery applications. Traditionally, the 1D method assumes a: linear time invariant, isotropic, semi-infinite block with planar surfaces and does not accurately model the true geometric behaviour. This paper evaluates the error introduced by the planar assumption and outlines the required modifications for accurate freeform surface analysis. Adapted cylindrical basis functions are defined for the impulse response method and used to evaluate the impact of the 1D planar assumption. The analytic solutions for both convex and concave surfaces are presented. A penta-diagonal algorithm, for a modified numerical Crank-Nicolson scheme, is also evaluated for fast stable implementation of curved geometry simulation. The scheme shows comparable performance to the impulse response, whilst removing the requirement for linear time invariance. The new methods are demonstrated in the case of aerothermal analysis for heat transfer in a turbine nozzle guide vane. A 3D ANSYS simulation is used as a benchmark and further highlights the importance of the curvature effects. The methods are extended using curvature mapping for infra-red camera data, enabling direct 3D thermal simulation or the fast calculation of freeform curvature. This paper defines the methodology to analyse heat transfer measurements on non-planar geometry.

A Coupling Physics Model for Real-Time 4D Simulation of Cardiac Electromechanics

Cardiac simulators can assist in the diagnosis of heart disease and enhance human understanding of this leading cause of mortality. The coupling of multiphysics, such as electrophysiology and active–passive mechanics, in the simulation of the heart poses challenges in utilizing existing methodologies for real-time applications. The low efficiency of physically-based simulation is mostly caused by the need for electrical-stress conduction to use tiny time steps in order to prevent numerical instability. Additionally, the mechanical simulation experiences sluggish convergence when dealing with significant deformation and stiffness, and there are also concerns regarding volume inversion. We provide a coupling physics model that transforms the active–passive dynamics into multiphysics solving constraints, aiming at boosting the real-time efficiency of the cardiac electromechanical simulation. The multiphysics processes are initially divided into two levels: cell-level electrical stimulation and organ-level electrical-stress diffusion/conduction. This separation is achieved by employing operator splitting in combination with the quasi-steady-state method, which simplifies the system equations. Next, utilizing spatial discretization, we employ the matrix-free conjugate gradient approach to solve the electromechanical model, therefore improving the efficiency of the simulation. The experimental results illustrate that our simulation model is capable of replicating intricate cardiac physiological phenomena, including 3D spiral waves and rhythmic contractions. Moreover, our model achieves a significant advancement in real-time computation while maintaining a comparable level of accuracy to current methods. This improvement is advantageous for interactive medical applications.

Performance of a novel loop heat pipe coupled with micro vapor-driven jet injector – An experimental and numerical study

Loop heat pipe (LHP) is an efficient phase-change heat transfer device which has been widely applied in cooling high-power electronics on ground and in spacecraft. In previous work, a novel LHP coupled with vapor-driven jet injector (VDJI) has been proved to be feasible and shows excellent performance, namely LHPI. However, due to the lack of pressure data during LHP operation, the coupling mechanisms of VDJI and LHP remain unknown. Especially, the heat-mass transfer between high-speed vapor and subcooled liquid inside VDJI, which has great influence on the LHPI, need to be investigated to guide the design of the LHPI. In this paper, the start-up process, steady-state operation characteristic of LHPI and internal flow field of VDJI were investigated experimentally and numerically. By using the pore-forming sintering and integrated sintering method, the bi-porous wick was prepared and embedded on the base plate surface of evaporator, which brought a significant improvement in its performance. The results indicated that the LHPI could operate under a power of 600 W (50.0 W/cm2) without dry-out. Maintaining the heating wall temperature within 85 °C, the minimum thermal resistance of the LHPI with bi-porous and integrated sintered wick was below 0.18, and the maximum heating power can reach up to 404 W, which are 60% lower and 52.5% higher than mono-porous wick, respectively. In addition, four operation modes of VDJI were classified as low-efficiency mode, normal-injection mode, restricted expansion mode and superheated mode. The operation modes of VDJI had great influence on the performance of LHPI. In normal-injection mode, the entrainment ratio of VDJI exceeded 100, which resulted in the lowest thermal resistance of LHPI. For long-term operation of LHPI, the VDJI is suggested keep operating in normal-injection mode. Moreover, by using 3D numerical simulation method, the internal flow structure of the VDJI was obtained to gives an insight into mechanisms of these four operation modes. The numerical results showed the profile of compression waves and confirmed the existence of condensation shock wave in VDJI.

Static Loading Simulation on Temporary Platform and Ladder Absorbent Chamber Design

This study utilizes SolidWorks software to thoroughly examine the structural layout and static load simulation of a temporary platform and ladder in an adsorbent chamber. SolidWorks, a computer-aided design (CAD) and computer-aided engineering (CAE) software, offers robust tools for 3D modeling, simulation, and analysis, making it ideal for this type of structural assessment. Finite element analysis (FEA), a simulation model within SolidWorks, is employed to determine stress distribution and safety factors. The results demonstrate the platform's maximum stress at 198.65 MPa, below the yield strength of ASTM A36 Steel, leading to a safety factor of 1.3. These findings validate the design's safety and reliability for industrial use.