Multi-physics Coupling Research Articles

Numerical Investigation of coupling hazard zone of coal spontaneous combustion and gas in gob for high-gas mines

As coal mining operations continue to deepen, the frequency of coal spontaneous combustion (CSC) and gas explosion disasters in high-gas mines is increasing. Understanding the distribution patterns of CSC and gas compound disaster zones in the gob during the extraction process is crucial for reducing the risks of combustion and explosion. This study focuses on the 201 working face of the Shuanglong Coal Mine, where a multi-physical field coupling model of pressure, temperature, gas seepage, and diffusion was established to investigate the evolution characteristics of compound disaster zones and propose corresponding prevention and control measures. The results demonstrate that the area with the most severe composite hazard is mainly located at the return roadway side, extending to the middle of the gob. With increased ventilation volume and advance rate, the area of the CSC and gas coupling hazard zone expands continuously. By implementing measures such as brattice cloth and nitrogen injection, the areas of spontaneous combustion and CH4 explosion zones were reduced by 53.6 % and 49.5 %, respectively, effectively controlling the extent of the compound disaster zone and eliminating the risk of gas explosions.

Evaluating the effectiveness of the modified multi-scale multi-physics coupled model for solid oxide fuel cells: A comparative analysis

A multi-scale multi-physics coupling numerical model serves as an effective tool to study the performance and improve the efficiency of solid oxide fuel cells (SOFCs) and provides the theory and data support for optimizing SOFC structure and operational strategy. To improve the accuracy and reliability of the model, this work established a modified simulation model that considers the effect of operational, structural, and physical parameters of SOFCs. First, the electrochemical kinetics equation, multi-component diffusion lattice Boltzmann (LB) model, and heat transfer LB model are modified by incorporating the reaction gas molar fraction, gas mixture concentration, temperature, and other parameters. Second, a regional hierarchical modeling strategy is proposed, and the multi-scale coupling model is modified by coupling mass and heat transfer. Third, considering the effect of carbon monoxide molar fraction, temperature difference, concentration change and porosity on electrochemical, mass, and heat transfer processes, the effectiveness of modification model is analyzed and validated. Results demonstrate that the modified model considerably improves the numerical simulation to handle the complex operational conditions of SOFCs. The modified model's predictions show better accuracy compared with experimental data, while maintaining consistency with the trends predicted by the original numerical models.

Establishment of Multi-Physics coupling model and analysis on thermal stress and crack risk in directional growth of TiAl alloys under electromagnetic confinement

The electromagnetic confinement directional solidification (EMCDS) technique is an optimal method for preparing large-size and non-contamination directional TiAl alloy crystals. Despite its advantages, the high temperature gradient inherent to this process induces thermal stress within the ingot, which increases the risk of cracking. To address this challenge, an innovative Integrated Multi-Physics Coupling Model was established to map and study the thermal stress field during EMCDS in this study. It synchronized the computation of the electromagnetic field, temperature field, solute field, flow field, and stress field during the crystal growth of TiAl alloy, and its high accuracy was proved by the micro-indentation experiment. Our analysis reveals that transverse temperature differences are crucial in inducing thermal stresses, and identifies that hot cracks and cold cracks are prone to occur respectively at the area of radial 23R along the sample (X = 23R) and on the sample surface, which aligns with experimental observations impressively. This model can more accurately and efficiently optimize the process parameters of the EMCDS process to avoid cracks and promote its industrial application.

Morphological evolution mechanism of microstructures involved in shaping micro-pillar arrays into microlens arrays on fused silica surfaces by CO2 laser polishing

The periodic micro-pillars on the hard-brittle fused silica surface can be shaped into the smooth and defect-free microlens arrays (MLA) by CO2 laser polishing, which can be applied in imaging and beam-shaping. However, the morphology evolution mechanism of the micro-pillars is not clear during polishing, which seriously affects the rapid preparation of high-quality MLAs. Herein, a multi-physics coupling model is established to investigate the interaction between CO2 lasers and micro-pillars on the fused silica surface, and is verified from the perspectives of temporal and spatial temperature. The steady surface temperature evolution law with laser power and spot radius is explored, based on which, the parameter ‘Window’ for polishing is determined to make the material melt and flow without ablation removal. The morphology evolution of micro-pillars is investigated as well as laser-material interaction. It is found that under laser irradiation, the micro-pillar height first increases and then decreases, and its top curvature radius increases. The surface tension makes the dominant contributions to the melting and flow of the micro-pillar materials, while the Marangoni effect and the gravity have little effect. Furthermore, to fabricate the target MLAs with the specific dimensions, the influence of micro-pillar aspect ratio (φ) on microlens surface morphology is investigated. It is found that there are two critical φ for the target MLAs. For the required MLA with the target period of 200 μm and the target height of 40 μm, when the φ is larger than 5.1, the micro-pillar array fails to be shaped into the target MLA by CO2 laser polishing. As the φ decreases, the junction of micro-pillar and the substrate sags downwards significantly, and the deviation between the shaped- and the ideal spherical contours increases. To successfully prepared the target MLA and guarantee the geometry accuracy, the minimum φ is selected to be 0.71. This work has important theoretical significance for obtaining the smooth and defect-free target fused silica MLAs with the specific dimensions by CO2 laser non-evaporative polishing.

Design of thermomechanical processes for tailored microstructures: Methodology and application to nanocrystalline titanium alloy Ti-13Nb-13Zr (NanoTNZ)

Thermomechanical processes enable tailoring of material properties and microstructures for advanced products. In medical technology, next-generation titanium implants require tailored material properties to improve health and quality of life. However, the interaction correlation between process parameters and material properties poses a major challenge for the design of thermomechanical manufacturing processes.In this paper, we present a methodology for the design of thermomechanical processes to achieve tailored microstructural properties through forming technology and heat treatments. The methodology consists of five systematic steps to address the complexity of multiphysical coupling relationships between temperature, stress, microstructure and alloy composition, and to provide a guideline for effective implementation. It is applied to the production of nanostructured Ti-13Nb-13Zr (NanoTNZ) alloy for dental implants. The designed process of severe plastic deformation, recrystallization treatment and aging lead to nanostructured microstructures smaller than 200 nm. The resulting mechanical properties (UTS > 980 MPa, Young’s modulus of 73 GPa) meet the desired goals for improved biomedical implant-bone interactions. The tailored material properties and microstructures of NanoTNZ are therefore highly promising for use as an implant material.The case study demonstrates the importance of a systematic method to manage the complexity of multiphysical coupling relationships in the design of thermomechanical processes to enable tailored microstructures for advanced materials and products.

Simulation of the pulsed streamer discharge in water considering the effect of hydrostatic pressure

Streamer discharge is a very complex multi-scale and multi-physics coupling process, and there is no accurate model that can describe its development. In this paper, a two-dimensional axisymmetric fluid model is established in COMSOL to simulate and study the effects of the applied voltage amplitude, the discharge gap distance, the rising edge of pulse voltage, and hydrostatic pressure on the development of the positive streamer discharge at a needle-plate electrode in water under a nanosecond pulse voltage. The results show that increasing the voltage amplitude, decreasing the pulse rise time, and narrowing the discharge gap all increase the electric field strength of the streamer, thereby affecting the electron density of the plasma channel, among which changing the discharge gap has the greatest effect on the electron density. And under the gap of 3 mm, the peak electron density can reach 3.76 × 1023 m−3; if the discharge gap is narrowed to 1 mm, the peak electron density is reduced to 1.20 × 1023 m−3. In addition, hydrostatic pressure and water molecule spacing are closely linked. Increasing the hydrostatic pressure decreases the electric field strength and the peak electron density in the plasma channel, and its effect on the peak electron density saturates with increasing hydrostatic pressure.

Multi-physics coupling numerical simulation of variable porosity in reactive melt infiltration process

Abstract The hypersonic craft necessitates significant advancements in thermal shielding to safeguard against the extreme aero-thermal environments encountered during flight at hypersonic speeds in near space or upon reentry from space. Carbon fiber-reinforced ceramic matrix composites (FRCMCs) have attracted increasingly interesting attention as advanced structural materials for application in thermal protection. The reactive melt infiltration (RMI) process is preferred for the preparation of FRCMCs because of its low cost and short processing time. However, the RMI process includes the complex interplay of melt flow, reaction dynamics, and thermal fields, with existing models failing to accurately predict these processes due to their uncoupled nature and neglect of pore structure changes. This study introduces a coupled model that integrates mass transfer flow, chemical reaction, and heat transfer, incorporating variable pore structures to more accurately evaluate the RMI process. This approach allows for a comprehensive assessment of internal pressure, temperature, and porosity changes during silicon infiltration into porous media, marking an improvement over the previous model. The model has been validated for use in predicting the exotherm of RMI processes. In conclusion, this coupled model presents a promising avenue for enhancing the fabrication of FRCMCs, either considering the melt infiltration from multiple locations in the RMI process or adjusting the pore structure at the infiltration location to larger pores.

Gap compensation control method for robotic electrochemical milling machining based on multi-physics field coupling

Gap compensation control method for robotic electrochemical milling machining based on multi-physics field coupling

Structural simulation and performance evaluation of self-priming electrostatic diesel vehicle emission particle sensor

Here is reported a self-priming electrostatic particulate matter (PM) sensor for real-time monitoring of diesel exhaust under different operating conditions. Initially, a multi-physics coupling model for the sensor was established. By varying the exhaust flow and temperature, the emissions of diesel vehicles were simulated to evaluate the sensor. The results showed that within the typical velocities (5 to 60 m/s) and temperature ranges (100 to 500 °C) of diesel exhaust, the sensor outlet pressure was consistently below the inlet pressure, with a maximum differential pressure of 259 Pa, indicating the capability for self-priming sampling of exhaust under different operating conditions. Additionally, the calibration platform was constructed using a miniature inverted soot generator which produced a series of samples to calibrate the relationship between current and mass concentration with a correlation coefficient of 0.99. From 0 to 100 mg/m3, the PM sensor exhibited a relative error between −6.00% and 6.00% with good stability and consistency for samples of different sizes and concentrations, with correlation coefficients exceeding 0.98. The results between the self-developed sensor and a commercial instrument revealed that the former provided high-precision real-time measurement of diesel exhaust.

A finite volume–based thermo-fluid-mechanical model of the LPBF process

The multi-physics coupling feature of the laser powder bed fusion (LPBF) process poses great challenges to numerical models regarding computational fidelity and efficiency. This paper proposed a finite volume–based model for predicting integrated thermo-fluid-mechanical behaviors of the LPBF process. The model directly unifies the heat transfer, fluid flow and solid mechanics simulations within a predefined mesh, enabling simultaneous solutions for the fluid domain under Eulerian description and the solid domain under Lagrangian description. Three benchmark tests accounting for individual problems were conducted to validate the model's accuracy and effectiveness. Track-scale LPBF simulations were performed to unravel the intricate interplay between thermal, fluid and mechanical behaviors. The numerical predictions of surface morphologies, molten pool dynamics and melt track dimensions aligned well with the experimental observations. The spatiotemporal evolution of transient thermal stress was accurately captured and the predicted residual stress field showed consistency with nanoindentation measurements. The proposed model was found robust in simultaneously predicting the temperature distribution, melt flow and residual stress evolutions of the LPBF process, and showed strong potential for addressing other similar multi-physics coupling problems.

Research on the high-performance computing method for the neutron diffusion spatiotemporal kinetics equation based on the convolutional neural network

Due to the uncertainty of computational results and the lack of interpretability of models in solving physical field equations in current deep learning, this paper designs a convolutional neural network that can be used to solve the neutron diffusion spatiotemporal kinetics equation in polar and cylindrical coordinate systems. This algorithm directly utilizes the macroscopic cross-section of the material without using the lattice homogenization method, replaces the finite volume method with the extended matrices, and solves the extended matrices using the convolutional kernels instead of the iterative algorithms. Taking the simplified Tsinghua High Flux Reactor (THFR) as an example, the feasibility of the algorithm is verified on the PyTorch platform and compared with the calculation results of the source iteration method running on the GPU. The calculation results show that when the number of grids in the radial and axial sections of the simplified THFR model is 804,600 and 3,576,000, respectively, and the algorithm is iterated 3000 times, the normalized power of the convolutional neural network and the source iteration method converges to 10−10, and the maximum point by point error of the neutron flux density of the above two algorithms converges to 10−5. The computational time consumed by the convolutional neural network is approximately 880.64 s and 3729.62 s, which reduces the computational time by 4.66% and 5.05% compared to the GPU parallel accelerated source iteration method, and the former consumes 43.75% less memory compared to the latter. The convolutional neural network is mainly used as the virtual physics engine for the THFR digital twin system, in addition to solving the neutron diffusion spatiotemporal kinetics equation and further improving computational speed. The algorithm directly utilizes the neutron macroscopic cross-section of the material to calculate the neutron flux density distribution without using the lattice homogenization, providing theoretical guidance and algorithm support for developing the high-precision multi-physical field coupling model.

Research on performance optimization of electrolytic cell: Non-parameter topology and parameter optimization

The technology of water electrolysis for hydrogen production converts renewable energy into hydrogen, enabling efficient storage and utilization of clean energy. The key to enabling the large-scale development of water electrolysis technology lies in enhancing the performance of electrolytic cells and minimizing energy consumption. The mastoid process structure obviously influences the electrolytic cell's flow and electrochemical performance. Therefore, this paper studied the sensitivity of the mastoid process structure to the optimization target, designed the shape topology and the parameter optimization structure, and further analyzed the influence of the two optimization methods on the flow and electrochemical performance of the electrolytic cell based on the multi-physics coupling model. The results show that under the same deformation area, the pressure drop of the topology and the parameter optimization structure is reduced by 17.17 % and 11.89 % compared with that of the original structure. The electrochemical properties were almost unaffected, and the change value was less than 0.1 %. Topology optimization design can achieve optimal performance within limited deformation constraints, and parameter optimization design is more conducive to industrial processing.

Study on heat and mass transfer behavior of coupled electrochemical reaction in porous structure of proton exchange membrane fuel cell

Proton exchange membrane fuel cell (PEMFC) is widely used in transportation, aviation and energy storage due to its unique advantages. Improving the performance of fuel cells depends largely on effective hydrothermal management. In this work, a multi-physical field coupling model based on the lattice Boltzmann method (LBM) is established to analyze the oxygen transport, liquid water transport, heat transfer and electrochemical reaction, mainly considering the difference between the overpotential of the cell and the surface wettability of the structure. The results show that the overpotential is closely related to the reaction process. The rate of water production is significantly accelerated by increasing the overpotential, and the breakage and merging of water clusters are observed. The increase of overpotential will lead to more energy loss in the form of heat, thus increasing the heat production. Enhancing the hydrophobicity of the structure has a positive effect on the performance of the fuel cell, and the possibility of local hot spots in the low-hydrophobic structure is greater. It is feasible to improve water management and fuel cell performance through wettability design.

Influence of Immersion Orientation on Microstructural Evolution and Deformation Behavior of 40Cr Steel Automobile Front Axle during Oil Quenching.

This study employs the finite element method to investigate the microstructural evolution and deformation behavior of a 40Cr steel automobile front axle during the quenching process. By establishing a multi-physics field coupling model, the study elucidates the variation patterns of the microstructure field in the quenching process of the front axle under different immersion orientations. It is found that along the length direction, the bainite and martensite structures decrease from the center to the edge region, while the ferrite structure shows an increasing trend. Additionally, the influence of immersion orientation on the hardness of the front axle's microstructure and deformation behavior is thoroughly discussed. The results indicate that, firstly, when quenched horizontally, the hardness difference among different regions of the front axle is approximately 8.2 HRC, whereas it reaches 10.3 HRC when quenched vertically. Considering the uniformity of the microstructure, the horizontal immersion method is preferable. Secondly, due to the different immersion sequences in different regions of the front axle leading to varying heat transfer rates, as well as the different amounts of martensite structures obtained in different regions, the deformation decreases along the length direction from the center to the edge region. Horizontal immersion quenching, compared to vertical immersion, results in a reduction of approximately 56.2% and 48.9% in deformation on the representative central cross-section (A-A) and the total length of the front axle, respectively. Therefore, considering aspects such as microstructure uniformity and deformation, the horizontal immersion quenching orientation is more favorable.

Monte Carlo Workflow Unification for Nuclear Reactor Analysis with Metamodel-Driven Modeling

Monte Carlo (MC) transport codes are a cornerstone of nuclear reactor analysis frameworks, providing reference solutions and multigroup cross sections, and even as core components in multiphysics couplings. These applications can be seen in toolkits from the Nuclear Energy Advanced Modeling and Simulation program and the U.S. Nuclear Regulatory Commission’s BlueCRAB (Comprehensive Reactor Analysis Bundle). Contrary to their ubiquitousness in reactor physics modeling and simulation, popular MC codes, such as MCNP, Serpent, and KENO, are still reliant on antiquated textual input formats. These input languages use a plethora of keywords with terse syntax to specify all facets of a model, including its geometry, materials, physics settings, and tally options. This poses a steep learning curve and a poor user experience. Being tied to unique text-based input formats also significantly complicates programmatic input generation or modification that may be desired and/or required within a multiphysics framework. This work demonstrates how the development of programmatic interfaces for MC codes can support model unification and translation activities. Building on the Python application program interface (API) development of MCNPy, similar capabilities are being implemented for Serpent that are able to support model translation. In future work, the Serpent API capabilities will be made more robust and the work will be further expanded to include translations with KENO.

Experimental study and life prediction for aero-engine turbine blade considering creep-fatigue interaction effect

As an important failure form of the turbine blade, creep-fatigue interaction damage affects the safe operation and maintenance strategy of aero-engine, and has been the focus of scientific research and the academic community. Firstly, based on the Kachanov-Rabotnov-Lemaitre continuum damage mechanics theory and the nonlinear symmetry of creep damage and fatigue damage, a creep-fatigue life prediction model is constructed considering the interaction effect in this paper. Then, based on the thermal-fluid–solid multi-physical field coupling numerical simulation of the turbine blade, the equivalent method of creep-fatigue load spectrum was explored according to the equal damage criterion and linear damage rule, and the creep-fatigue interaction test of smooth samples of the blade material was conducted to analyze the creep-fatigue fracture morphology. Finally, the stress term in the creep-fatigue life prediction model of blade material is modified by the correction factor α, and the modified creep-fatigue life prediction model of the turbine blade is constructed considering the interaction effect. The results show that the modified creep-fatigue life prediction model considering the interaction effect has a high life prediction ability with an error of 3.9%. The above research has important scientific research value for the life extension design of turbine blades and the improvement of aero-engine maintenance strategy.

An IGBT coupling structure with a smart service life reliability predictor using active learning

Abstract An effective approach is proposed to evaluate the service life reliability of a multi-physics coupling structure of an insulated gate bipolar transistor (IGBT) module. The node-based smoothed finite element method with stabilization terms is firstly employed to construct an electrical-thermal-mechanical (ETM) coupling structure of the IGBT module, based on which the multi-physics responses can be accurately calculated to predict the service life of the IGBT module. By using the high-quality sample data obtained through the ETM coupling model, a Monte Carlo based active learning Kriging metamodel (AK-MCS) is developed to assess the service life reliability of the IGBT module, which can greatly reduce the computational cost needed by the surrogate model construction and reliability analysis. Numerical results show that the proposed ETM coupling structure can produce high-quality sample data of the IGBT dynamics and the AK-MCS machine learning technique can accurately estimate the service life reliability of the IGBT module.

A Review of Multiphysics Coupling Mechanical Behavior of Titanium-Coated Heterogeneous Wing for Re-entry Hypersonic Vehicle

A Review of Multiphysics Coupling Mechanical Behavior of Titanium-Coated Heterogeneous Wing for Re-entry Hypersonic Vehicle

A quasi-3D SinZZ model-driven multi-field Chebyshev FEM for nonlinear vibration control in multilayer multiferroic composite plates

This paper presents an advanced numerical method for modeling and mitigating nonlinear vibrations in thin multilayered fiber-reinforced multiferroic composite plates, addressing complex multi-physical interactions. The proposed methodology leverages a multi-physical coupling Chebyshev finite element formulation, utilizing high-order shape functions derived from Chebyshev polynomials. By integrating the strengths of spectral element methods and Legendre spectral finite element methods, this approach effectively overcomes challenges such as shear locking and spurious zero energy modes while ensuring high convergence rates in multi-physical problems. A quasi-3D refined model, incorporating the Murakami zig-zag model and sinusoidal shear deformation theory, is employed to accurately capture the nonlinear Von Kármán strain–displacement relationship and the magneto-electro-elastic coupling in multilayer structures with thickness-dependent material properties. To suppress nonlinear vibrations, the study utilizes a closed-loop multiphysical Chebyshev finite element model for time-domain analysis of viscoelastically damped systems, employing the Golla–Hughes–McTavish model. The results underscore the significant influence of multiferroic properties and the strategic distribution of ferroelectric fibers within the substrate on the dynamic behavior of the plate. The numerical validation, supported by rigorous verification, demonstrates the robustness of the proposed method in effectively simulating and controlling multilayer fiber-reinforced multiferroic composite plates. Additionally, this research highlights the potential for significant vibration reduction through semi-active damping mechanisms, offering valuable insights for practical applications in industries where precision and stability are critical.

Multi-physical Field Coupling Analysis of Flat Wire Motor

Multi-physical Field Coupling Analysis of Flat Wire Motor