Numerical Simulation Model Research Articles

Gas Fire Coupling Control of Goaf Based on Numerical Simulation

ABSTRACT In response to the problem that traditional gas control methods such as water injection and inert gas fire extinguishing are not effective and have a high level of risk in goaf, this study uses COMSOL software to establish a three-dimensional numerical simulation model of goaf, and combines air leakage intensity, oxygen concentration, and floating coal thickness to calculate the gas fire hazard area, in order to achieve effective control. The results show that the deviation between the data obtained from the numerical simulation and the actual measurement value is about 7 m, which proves that the given solution is reliable. The gas concentration of the wind lane and the upper corner is controlled below 1%, which proves that this method ensures the safety of the working environment. The above results show that the design method realizes the effective control of gas fire in the goaf, and provides reference for mine safety management and gas disaster control.

Experimental study on the cushioning energy absorption characteristics of polymer materials resistant to seawater erosion in seismic damping layers

AbstractPolymer materials exhibit vibration damping properties, yet scant research exists on their applicability to submarine tunnels. This study investigates the dynamic characteristics of Polymer Materials Resistant to Seawater Erosion (hereafter referred to as PMRSE) under varying conditions of density, confining pressure, strain rate, and erosion duration through dynamic triaxial tests. The results reveal an increase in material strength with a rise in density; enhanced strength and ductility with increasing confining pressure; and augmented strength and yield stress in correspondence with heightened strain rates. As confining pressure ascends, the equivalent damping ratio of PMRSE gradually diminishes. SEM and EDS indicate a porous structure for PMRSE, with a molded surface skin formed post‐manufacturing to thwart seawater erosion. The strain energy storage and energy absorption evaluation of PMRSE demonstrate its excellence as an energy‐absorbing material. Eventually, employing a numerical simulation model for a specific submarine tunnel reveals that the presence of a damping layer absorbs seismic energy and enhances the stress conditions of the secondary lining. PMRSE manifests as a strain‐rate sensitive material unaffected by seawater corrosion, which exhibits deformation characteristics of low yield strength and long yield stage. Accordingly, PMRSE proves suitable for vibration damping in submarine tunnels.

Analysis on numerical simulation and fracture mechanics model of water inrush of floor with hidden faults under dynamic and static loads

The mining activation of hidden faults under dynamic and static loads is an important reason for the occurrence of floor water inrush disasters in deep coal seam mining. The formation and evolution mechanism of water inrush channel caused by mining on the floor of hidden faults were analyzed through numerical simulation, from the perspective of fracture mechanics, a model was constructed to explore the influence of combined dynamic and static loads on the propagation of water with cracks. A conclusion was drawn that the effects of mining stress and confined water have led to rapid expansion of hidden fault cracks and significant improvement in permeability, at the same time, the confined water in the hidden fault also has a scouring and expansion effect on the cracks, accelerating their development speed. There are spatial and temporal differences in the penetration patterns of hidden faults at different positions of floor, and the closer it is to the goaf, the more likely it is to experience activation of hidden faults and water inrush. When there are multiple hidden small faults in the floor, there is an alternating change between the water inrush growth area and the flow stable area with similar cyclic characteristics. The effect of dynamic load will increase the pore pressure in cracks, and increase the stress intensity factor at the crack tip, and more easily induce crack expansion and penetration failure. The critical water pressure calculation equation for crack propagation and failure under dynamic and static loads was derived, and the calculation method for the minimum safe thickness of the floor was further analyzed, the influence of water pressure, crack length, inclination angle, and mining depth on it was discussed. The effect of dynamic load will increase the pore pressure in cracks, and increase the stress intensity factor at the crack tip, and more easily induce crack expansion and penetration failure. Finally, the theoretical analysis results were verified by an engineering examples. The research results can provide theoretical basis for predicting and preventing water inrush from the mining floor, which is beneficial for the safe and sustainable mining of coal mines.

Numerical prediction of ground-borne vibrations due to continuous vibratory driving of circular closed-ended piles

Various types of pile driving work may induce high-intensity ground-borne vibrations. Predicting vibration intensity before adopting mitigation measures is vital for minimizing the impact of vibration on nearby structures and occupants. Vibratory pile driving is a commonly applied foundation construction method. However, numerical simulation models for ground vibrations during a complete process of vibratory driving have rarely been studied. This study introduces an axisymmetric finite element model that utilizes the arbitrary Lagrangian-Eulerian technique to simulate the continuous vibratory driving of a circular closed-ended pile penetrating from the ground surface to a target depth. The model validity was confirmed by assessing the calculated ground vibrations against the findings documented in earlier research. The results showed that the critical penetration depth of piles, at which the maximum peak particle velocity (PPV) occurs, varied with the radial distance and depth of points of interest, contradicting a common preconception. Moreover, the maximum PPV did not always occur on the ground surface across all radial distances. Parametric analysis revealed that an increase in the soil cohesion strength, pile diameter, or soil-pile friction, or a decrease in the driving frequency or soil damping ratio would increase ground vibrations due to vibratory pile driving.

Efficient Model Updating of a Prefabricated Tall Building by a DNN Method.

The significance of model updating methods is becoming increasingly evident as the demand for greater precision in numerical models rises. In recent years, with the advancement of deep learning technology, model updating methods based on various deep learning algorithms have begun to emerge. These methods tend to be complicated in terms of methodological architectures and mathematical processes. This paper introduces an innovative model updating approach using a deep learning model: the deep neural network (DNN). This approach diverges from conventional methods by streamlining the process, directly utilizing the results of modal analysis and numerical model simulations as deep learning input, bypassing any additional complex mathematical calculations. Moreover, with a minimalist neural network architecture, a model updating method has been developed that achieves both accuracy and efficiency. This distinctive application of DNN has seldom been applied previously to model updating. Furthermore, this research investigates the impact of prefabricated partition walls on the overall stiffness of buildings, a field that has received limited attention in the previous studies. The main finding was that the deep neural network method achieved a Modal Assurance Criterion (MAC) value exceeding 0.99 for model updating in the minimally disturbed 1st and 2nd order modes when compared to actual measurements. Additionally, it was discovered that prefabricated partitions exhibited a stiffness ratio of about 0.2-0.3 compared to shear walls of the same material and thickness, emphasizing their role in structural behavior.

Advanced cyclic constitutive model and parameter calibration method for austenitic stainless steel

Austenitic stainless steel is recognized for its potential in improving structural seismic resistance due to its exceptional ductility. This study seeks to analyse the material characteristics and cyclic constitutive model of austenitic stainless steel under cyclic loading using a combination of experiments and numerical studies. The primary goal is to enhance the precision of numerical simulations predicting the seismic performance of stainless steel and to minimize the costs associated with calibrating the parameters of the cyclic constitutive model. By conducting cyclic loading experiments on stainless steel with different plate thicknesses, the hysteresis curves under different loading protocols were obtained. The loading protocol significantly influences the cyclic hardening behaviour of stainless steel. To calibrate material parameters in the Chaboche model more effectively, a new parameter calibration method based on genetic algorithm optimization is proposed. Additionally, a method is proposed to calibrate the material parameters of the Hu model by utilizing the monotonic tensile stress-strain curve of austenitic stainless steel, which provides a new material model option for the numerical simulation of stainless steel seismic performance. The applicability of the Chaboche model and the Hu model in numerical simulations of stainless steel members is then verified and compared using existing seismic performance test results. The findings indicate that the Hu model offers more accurate numerical simulations of cyclic loading on austenitic stainless steel members compared to the Chaboche model.

Predictive numerical model for simulation of fiber-reinforced concrete beams in bending and inverse parametric analysis

Determining material parameters is essential for understanding the physical properties of fiber-reinforced concrete (FRC), enhancing the design process, and optimizing costs. This paper presents a deterministic numerical model of FRC beams under three-point bending tests (TPBT), with an emphasis on the failure analysis. This model aims to replicate TPBT and address the challenge that comes with direct measurements of FRC parameters, especially in the context of failure mechanisms. It integrates analytical solutions and explicit parameters to describe the bending and failure behavior, while mitigating computational demands in parameter identification due to the complex heterogeneous nature of the material. Laboratory tests were conducted to record key parameters and served as a foundation for the model development and validation of its predictive capabilities. The generated simulated data from the predictive numerical model were then utilized as input for an inverse analysis based on the Levenberg–Marquardt method. The inverse analysis demonstrated high accuracy, with parameter convergence typically within 3 to 7 iterations and errors reduced to less than 2%. Model verification was performed by comparing the results obtained from the inverse analysis with the data obtained from laboratory tests, confirming the model’s effectiveness in accurately predicting FRC failure behavior.

Application of Numerical Modeling and Finite Element Analysis in Fused Filament Fabrication: A Review.

Additive manufacturing (AM) is not necessarily a new process but an advanced method for manufacturing complex three-dimensional (3D) parts. Among the several advantages of AM are the affordable cost, capability of building objects with complex structures for small-batch production, and raw material versatility. There are several sub-categories of AM, among which is fused filament fabrication (FFF), also commonly known as fused deposition modeling (FDM). FFF has been one of the most widely used additive manufacturing techniques due to its cost-efficiency, simplicity, and widespread availability. The FFF process is mainly used to create 3D parts made of thermoplastic polymers, and complex physical phenomena such as melt flow, heat transfer, solidification, crystallization, etc. are involved in the FFF process. Different techniques have been developed and employed to analyze these phenomena, including experimental, analytical, numerical, and finite element analysis (FEA). This study specifically aims to provide a comprehensive review of the developed numerical models and simulation tools used to analyze melt flow behavior, heat transfer, crystallization and solidification kinetics, structural analysis, and the material characterization of polymeric components in the FFF process. The strengths and weaknesses of these numerical models are discussed, simplifications and assumptions are highlighted, and an outlook on future work in the numerical modeling and FE simulation of FFF is provided.

Study on the combustion characteristics and reaction mechanism of aluminum/alcohol-based nanofluid fuel

Enhancing the volumetric energy density of fuels is a crucial approach in the exploration of efficient energy sources. As a commonly used high-energy additive, Aluminum nanoparticles (Al NPs) holds broad application prospects. This study delves into the effects of Al NPs on the combustion characteristics of methanol and ethanol fuels through in-depth analysis of single droplet combustion and spray combustion experiments involving alcohol-based nanofluid fuels. The experiments revealed that adding Al NPs significantly enhances fuel combustion efficiency, shortening both the combustion life and ignition delay time. Spray combustion tests demonstrated that adding 2 wt% Al NPs increased the maximum and average flame propagation speeds of ethanol fuel spray by 48.93 % and 47.94 %, respectively, while the maximum explosion pressure rose from 0.66MPa to 0.83MPa, with a reduced time to reach peak explosion pressure by 106ms. Based on the SEM and XRD characterization results of the combustion residues and the analysis of flame morphology, a physical model of the alcohol-based nanofluid fuel spray combustion flame was established. Numerical simulations of the gas-phase kinetics model showed that the generation rates of radicals such as H, O, and OH were significantly increased with the addition of Al NPs, intensifying the combustion reaction. The findings provide a theoretical basis for future fuel design and combustion performance optimization.

Analysis of SIS epidemic model in bi-uniform hypernetworks

To describe the dynamics of epidemic spread with multiple individuals interacting with each other, we develop a susceptible-infected-susceptible (SIS) spread model with collective and individual contagion in general hypernetworks with higher-order interactions. The constructed model is applied to a bi-uniform hypernetwork to obtain a mean-field model for the SIS model. The threshold value at which an epidemic can spread in the bi-uniform hypernetwork is obtained and analyzed dynamically. By analysis, the model leads to bistability, in which a disease-free equilibrium and an endemic equilibrium coexist. Finally, numerical simulations of the developed model are carried out to give the effect of the proportion of individual contagion hyperedges on the spread of an epidemic.

Study on the influence of the hydrogen–oxygen stoichiometric ratio on the power performance improvement in a large-scale PEMFC stack

This study aims to determine the optimized hydrogen–oxygen stoichiometric ratio for power performance improvement in a large-scale proton exchange membrane fuel cell (PEMFC) stack by analyzing the characteristics of internal heat and mass distributions. The power performance of a large-scale PEMFC stack consisting of the designed stack cells with the counter flow directions of hydrogen and oxygen and a coolant flow channel was experimentally evaluated. Temperatures in the central stack cell were monitored. The coupled numerical simulation model was built to analyze the power performance as well as heat and mass distribution characteristics inside a stack cell. It was found that the greatest power performance of the PEMFC stack occurred at a specific hydrogen–oxygen stoichiometric ratio, and this performance had good uniformities of the temperature and water mass fraction distributions at the proton exchange membrane (PEM). The distribution characteristics of the hydrogen and oxygen mass fractions at the interfaces between the gas diffusion layer (GDL) and the catalytic layer (CL) due to the diffusion effect were analyzed. The mechanism of enhancing power performance from an electrochemical reaction was revealed by the greater gas distribution uniformities. Furthermore, a parameter of energy conversion ratio was employed to quantify the hydrogen utilization degree.

Integer quantum Hall transition: An S -matrix approach to random networks

In this paper we propose an S-matrix approach to numerical simulations of network models and apply it to random networks that we proposed in a previous work [I. A. Gruzberg, A. Klümper, W. Nuding, and A. Sedrakyan, ]. Random networks are modifications of the Chalker-Coddington (CC) model for the integer quantum Hall transition that more faithfully captures the physics of electrons moving in a strong magnetic field and a smooth disorder potential. This method has considerable advantages compared to the transfer matrix approach and gives the value ν≈2.4 for the critical exponent of the localization length in a random network. This finding confirms our previous result and is surprisingly close to the experimental value νexpt≈2.38 observed at the integer quantum Hall transition but substantially different from the CC value νCC≈2.6. Published by the American Physical Society 2024

Numerical Investigation of the Effects of Aspect Ratio on the Hydrodynamic Performance of a Semi-Planing Catamaran

Abstract A semi-planing catamaran is a type of marine craft that benefits from high speed, in conjunction with the its inherent characteristics such as a large deck and high transverse stability. The aspect ratio, length over the beam of a demi-hull, significantly affects the hydrodynamic performance of this vessel. In this study, the effects of the aspect ratio on the hydrodynamic performance of a semi-planing catamaran in calm water and waves are investigated using numerical simulations. The numerical simulation of the AUT-SEM00 model itself is validated by its model test results. The results show that increasing the aspect ratio significantly increases the wetted surface, and that the increase in resistance in calm water is negligible. In addition, increasing the aspect ratio radically reduces the amplitude of vertical acceleration in waves at the center of gravity by up to 85%. Consequently, the seakeeping performance is considerably improved, and the risk to crew and equipment is reduced.

Aerodynamic simulation on roof-mounted intelligent awareness system of intelligent vehicle

With the rapid development of intelligent driving technology, it is urgent to conduct research on the distribution and motion characteristics of snow particles in the area of the intelligent vehicle awareness system under harsh snow and wind conditions. In this paper, the Unsteady Reynolds-Averaged Navier-Stokes (URANS) was first used to conduct 1:12 scaled aerodynamic simulation of the intelligent vehicle. It is found that the error of aerodynamic drag coefficient between simulation and test is 5.6%, indicating that the current numerical simulation model can predict the aerodynamic characteristics of intelligent vehicle accurately. Based on this, URANS was used coupled with Lagrangian Multiphase Model (LMP) to investigate the snow accumulation near the roof-mounted intelligent awareness system under different vehicle speeds and snowfall intensities. The study found that with the increase of snowfall intensity from moderate to heavy and vehicle speed at 40 km/h, the incidence of snow particles on various components significantly increases, and the number of adhered particles also increased accordingly. The particle adhesion rate of the awareness system has decreased by 1.24%, while the number of adhered snow particles increased significantly at the back of the roof-mounted intelligent awareness system and the wake window. Under moderate snow condition, as the vehicle speed increased from 40 to 60 km/h, the number of incident particles and adhered particles in the awareness system have significantly decreased by 24,592 and 317,019, respectively, but the particle adhesion rate has increased by a significant 2.88%. Compared to the same snowfall intensity but low speed, the range of particle distribution is significantly reduced and more scattered.

Characterization of damage behavior and failure mechanisms of the bonded‐bolted hybrid three‐bolt joint in composite laminates

AbstractIn this paper, the mechanical properties, damage modes, and bolt load distribution of the bonded‐bolted hybrid three‐bolt joint were investigated by a combination of experiments and numerical simulations. Acoustic emission (AE) was used to monitor the tensile process of the connection in real time, and the K‐means clustering algorithm was used to realize the cluster analysis of the damage modes. A numerical simulation model of the tensile process of the joint was established using ABAQUS simulation software. The progressive damage evolution of composite laminates, and adhesive layer was characterized by using the VUMAT subroutine, the B‐K failure criterion, and cohesive element with zero thickness, respectively. The results show that four main damage modes occur in composite laminates during tension: matrix cracking, delamination, fiber pull‐out, and fiber breakage, with corresponding peak frequency ranges of (0–80 kHz), (80–210 kHz), (210–330 kHz), and (330–375 kHz), respectively. The adhesive layer between the laminates mainly exhibits peeling failure because of the secondary bending effect. In the load‐bearing process, the adhesive layer was loaded first and failed, and the bolt loading was delayed. Meanwhile, the results of bolt load distribution showed that the bolts and the adhesive layer at both ends carried greater loads.Highlights Damage modes and damage evolution of the bonded‐bolted hybrid joint in tension were analyzed by combining acoustic emission technology and numerical simulation. The simulation of delamination damage in composite laminates was carried out by inserting zero‐thickness cohesive elements into the laminates, and the delamination damage between the carbon fiber layup and the adjacent glass fiber layup was analyzed. The effect of the inclusion of the adhesive layer on the mechanical properties of the joint and the distribution of the bolt load was analyzed.

Research on the water flooding front based on dynamic and static data inversion – a case study

To clarify the movement of the water flooding front in fluvial reservoirs, this research takes the BZ oilfield as an example. By considering the equivalent flow resistance theory for oil–water two-phase flow, the horizontal micro-element equivalent method and the strong heterogeneity of fluvial facies reservoir comprehensively, a calculation model for a non-piston water flooding front in a horizontal well pattern was established. First, five horizontal injection–production well groups in the BZ oilfield were taken as examples to calculate the water breakthrough time for the oil wells. The calculation results are in good agreement with the actual production performance. In detail, the advancing speed of the water flooding front in the high-permeability strip was 0.8–1.6 m/day, and the speed in the low-permeability strip was 0.12–0.35 m/day. When water is seen in the oil well, the advancing speed in the low-permeability strip is reduced, resulting in uneven displacement and the formation of non-dominant potential areas. In addition, the water flooding front advancing distance was simulated to be 300–450 m by establishing a reservoir numerical simulation model, which is close to the result of the proposed model, indicating that the calculation method is reliable. This research is of great significance for predicting the water breakthrough time of horizontal production wells, judging the weak affected area on the mainstream line, and optimizing water injection and tapping reservoir potential in good time.

Numerical simulation of sulfur particle agglomeration at bends of high sulfur natural gas gathering pipelines based on Euler–PBM coupling

Sulfur deposition can result in an increase in the wall thickness of high-sulfur natural gas gathering pipelines, leading to issues like unstable pipeline flow. It is crucial to reveal the aggregation of sulfur particles at key locations of high-sulfur natural gas gathering pipelines to predict the location and amount of sulfur deposition in the pipelines. In this paper, the Euler–PBM (Population balance model) coupling is used to establish a numerical simulation model of gas–solid two-phase pipe flow accompanied by sulfur particle agglomeration in the pipe bends, focusing on the influence of sulfur particle volume fraction, pipe inclination angle and inlet flow velocity on sulfur particles agglomeration behavior. The results show that the sulfur particles have a significant agglomeration effect at the bend of the collecting pipeline, and the agglomeration growth occurs to different degrees throughout the bend, and the main area of sulfur particles agglomeration is near the top wall of the pipeline, followed by other areas near the wall of the pipeline. When the inlet volume fraction of sulfur particles was increased from 0.05 to 0.25%, and the inclination angle of the pipe was increased from 30° to 90°, the distribution range of sulfur particle size after agglomeration became wider, and the maximum size of sulfur particles was 187.56 μm, and the effect of sulfur particle agglomeration was enhanced; the inlet flow rate was increased from 3.0 to 9.0 m/s, and the reduction range of sulfur particle size after agglomeration was 5.68–9.87 μm. The maximum particle size of sulfur particles also decreased, and the effect of sulfur particle agglomeration was weakened.

Diurnal cycles of rain storms over South China during the presummer rainy season

The variation characteristics of rain storms (RSs) are closely related to complex internal physical processes and external dynamic and thermodynamic conditions. Using a 17-year observational rainfall dataset from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), the diurnal cycles of various RS characteristics and their responses to the South China Sea Summer Monsoon (SCSSM) are investigated in South China (SC) during the presummer rainy season (PSRS). Before SCSSM outbreaks, the RSs in the western inland region of SC (WSC) have stronger precipitation intensities and convective features due to orographic lifting, especially at night, while those in the eastern inland region of SC (ESC) have higher RS occurrence frequencies with higher moisture transport, especially in the afternoon. The onset of the SCSSM leads to abundant moisture and sufficient convective available potential energy over the entire SC area, resulting in significant increases in the occurrence frequency, convective fraction, and precipitation top height of RSs. In the WSC, the weakened upward motion and smaller convective inhibition limit RS development, resulting in weaker rainfall intensity. In the ESC, a particularly unstable atmosphere and enhanced low-level moisture transport in the afternoon lead to a larger three-dimensional size, more active convection, and greater precipitation intensity in the RSs. These results offer fresh insight into the diurnal variation in rainfall during the PSRS and can be effectively used to evaluate numerical model simulations.

Electromagnetic wave scattering simulation from precision grinding SiC surface under the influence of suspended micro-particles

ABSTRACT In a precision machining environment, suspended particles in the air have a non-negligible effect on visual roughness measurement results. To address this issue, this paper analyzes the influence of particles on the visual roughness measurement from theoretical derivation and numerical simulation, respectively. Firstly, based on the Lambert-Beer and the light scattering principles, the propagation equation of incident light under the joint action of suspended particles and rough surfaces is derived. Then, a numerical simulation model is designed, and the theoretical equations are verified by simulation experiments. The influence of particle material, particle size (D), particle concentration (N), light wavelength (λ), and SiC surface roughness (R a ) on the average electric field magnitude of the energy-acquisition boundary are analysed based on the simulation experiments. The theoretical derivation shows that the average electric field magnitude of the energy-acquisition boundary is mainly influenced by particle state and rough surface state. The simulation experiment results show that both the particle parameters and the rough surface parameters are consistent with the theoretical derivation. As R a increases, the effect of N on the measurement results decreases. The results reveal the influence mechanism of suspended particles on the visual roughness measurement results and provide a basis for improving visual roughness measurement accuracy.

Effect of vascular compression and drug injection time on thrombolytic therapy: Numerical simulation and validation

Venous thromboembolism (VTE) has been occurring frequently in human society. There is an urgent need to study the influence of several factors on thrombolytic therapy, such as the effects of vascular pressure levels (VPL) and the drug injection time (DIT). Considering blood as a non-Newtonian fluid, valve as a hyperelastic material, and thrombus as a porous medium, a new numerical simulation model of biofluid mechanics incorporating fluid–solid coupling phenomena and biochemical substance reactions is established based on the N-S equations and the convection–diffusion reaction equations. Then, a unique in vitro experimental platform is established to verify the correctness of the constructed mathematical model. The results showed that vascular compression resulted in significant differences in blood flow status localized within the vessel. Vascular compression causes the blood boosting index to fluctuate and the valve displacement values are 135% and 158% greater than the lower VPL, respectively. At the same time, vascular compression weakened vortex intensity, accelerated material transport and response, and improved the treatment. Compared with low VPL, the therapeutic efficacy increased by 7% and 15%, respectively. In addition, when the dose of the drug is high, different injection times can increase the therapeutic effect to different degrees, with a maximum difference of 12%. Our in vitro experiments are similar to the results obtained by numerical simulation, which can verify the reliability of numerical simulation. The computational model proposed and the experimental platform designed in this study have the potential to assist in clinical medication prediction in different venous thromboembolism patients.