Institute Of Mechanics,Chinese Academy of Sciences
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An MPM-FDM coupled method for landslide analysis considering surface-subsurface conjugated water flow
No full textThe material point method (MPM) can effectively simulate large deformation problems involving hydromechanical coupling, such as rainfall-induced landslides. Current MPM formulations simulate rainfall boundaries by applying either pore water pressure or velocity boundaries directly. This method does not incorporate the effects of surface water ponding and runoff during heavy rainfall. To address this problem, this study proposes a coupled method that integrates the MPM with the finite difference method (FDM) for hydro-mechanical analysis. Underground water flow is modelled using a two-phase, two-point MPM with the Richards equation, while surface water flow is computed by FDM based on shallow water equations. The two models are coupled: the FDM provides the surface water flow velocity and pore water pressure for subsurface flow simulation in the MPM, while the MPM supplies the surface infiltration rate for surface water flow simulation in the FDM. The new method was validated against existing numerical simulations and centrifuge tests. It was found that the new method can effectively capture the interactions between surface and subsurface flows, as well as the shallow landslide involving surface erosion or washout, which existing MPM codes cannot simulate. Parametric studies further reveal that neglecting the coupling effects of surface-subsurface flow predicts deeper sliding surfaces and longer rainfall durations to failure due to the ignorance of surface ponding and positive pore water pressure at the ground surface. Considering surface water flow tends to shift the failure mode from "slide-to-flow" to "flowlike", especially when slope angle is larger and soil permeability is lower
Investigation of solidification parameters and microstructure evolution in directed energy deposition with laser beam oscillation
No full textLaser beam oscillation offers significant potential to enhance process stability, control solidification parameters, and tailor microstructure in directed energy deposition. A coupled mesoscopic-microcosmic numerical model is utilized in this work to investigate the effect of oscillating laser beam on the solidification parameters and microstructure evolution during the directed energy deposition with laser beam oscillation (DED-LBO) process. The dynamics solidification conditions induced by the oscillating laser beam are considered in the mesoscopic thermal-fluid model. Based on the solidification parameters, the columnar-to-equiaxed transition of the microstructure is discussed, and microstructure evolution is analyzed using the microcosmic phase-field model. The results show that temperature gradient (G) and cooling rate (GR) vary transiently with the position along the laser oscillation trajectory. The microstructure is predominantly characterized by columnar grain growth, with a relative probability exceeding 85.37 %. An increase in oscillation amplitude and frequency effectively reduces both G and GR, resulting in a coarser microstructure. Good agreement is achieved between the simulated and experimental dimensions and microstructural morphologies of the deposited layers, demonstrating the validity of the developed model. The findings of this work provide valuable insight into revealing the dynamic solidification parameters under the oscillating laser beam and elucidating the physical mechanisms governing microstructure evolution under varying oscillation conditions
Direct numerical simulation of Rayleigh-Bénard convection based on physics-informed neural networks with transfer learning
No full textRayleigh-B & eacute;nard (RB) convection, characterized by a fluid layer with bottom heating and top cooling, serves as a fundamental model system in fluid dynamics research, serves as an essential paradigm for studying thermally driven flows, offering fundamental understanding of heat transfer, fluid mixing, and turbulent transition processes that occur widely in nature and industrial systems. This study introduces the application of Physics-Informed Neural Networks (PINNs) augmented with transfer learning techniques. Using transfer learning, our aim is to take advantage of the knowledge gained from training PINNs on a Ra condition to improve predictions for other Ra values. Preliminary results show that transfer learning-enhanced PINNs successfully capture the convective regime while avoiding convergence to steady-state solutions, enabling efficient prediction across varying Rayleigh (Ra) numbers without requiring full retraining. Furthermore, different ways of transferring models are also proposed to explore the feasibility of knowledge transfer across different natural convection configurations, including cases with varying inclination angles and Prandtl (Pr) numbers. The effective incorporation of transfer learning into PINNs have demonstrated promising capabilities for RB convection modeling, suggesting several key areas for future investigation. Further advanced transfer strategies suited to particular physical systems and conditions can be investigated as PINNs develop
Prediction of mechanical properties of cross-linked polymer interface by graph convolution network
No full textMachine learning models have made significant advances in the establishment of structure-property relationships. However, it is still a challenge to predict the mechanical properties of the adhesive interface due to the complexity and randomness of the polymer topologies. In this paper, we employed a graph convolutional network (GCN) model to predict the mechanical properties of a specific cross-linked polymer interfacial system, including yield strength (sigma(y)), ultimate strength (sigma(u)), failure strain (epsilon(u)), and fracture toughness (Gamma) utilizing molecular dynamics simulations. The results showed that the adopted GCN model can predict the mechanical properties with over 88% accuracy. Furthermore, the prediction performances for epsilon(u) and sigma(u) are better than those for Gamma and sigma(y), with R-2 similar to 0.73 for epsilon(u), R-2 similar to 0.64 for sigma(u), R-2 similar to 0.51 for Gamma, and R-2 similar to 0.43 for sigma(y). It is worth noting that the GCN model with the sum aggregator slightly outperforms that with the mean aggregator, and that models with linear regression and fully connected neural network regression provide similar predictions. The influence of input node features on prediction performance was also investigated. It was observed that the node closeness centrality is an important graph parameter in prediction. Specifically, node closeness centrality presents a more significant influence on the global mechanical properties of the adhesive interface, such as epsilon(u), sigma(u), and Gamma. Additionally, sensitivity analysis demonstrated that appropriate hyperparameters can improve computational efficiency without losing accuracy on a restricted set of data. This paper demonstrated the capacity of the GCN model to predict the mechanical properties of the adhesive interface with diverse topologies and provided a possible pathway for improving the mechanical properties of the adhesive interface by tailoring polymer structures in the future
A numerical toolkit for the ignition delay time and ignition probability density predictions based on instantaneous mixing fields in OpenFOAM
No full textThe OpenFOAM built-in chemistry solver, chemFoam, is extended as multiMeshChemFoam to simultaneously calculate the zero-dimensional (0D) ignition processes on the entire computational domain of practical simulations. The instantaneous temperature, pressure, and species mass fractions of a mixing field are input for the ignition calculation. A solver termed idtFoam is then developed to extract the Ignition Delay Time (IDT) on all cells from the 0D calculations. Several ignition criterions including the temperature exceeds a threshold value, the peaks in heat release rate (or equivalently, the time derivative of temperature) and species mass fractions are available. Another solver denoted as ipdFoam is finally compiled to construct the Ignition Probability Density (IPD) on the entire domain for a certain period. A time series of transient data from the mixing field are necessitated for the ignition calculation, IDT extraction, and IPD construction on individual cells. The numerical toolkit is verified with chemFoam for the 0D ignitions of ethylene. It is then applied to the mixing fields of an ethylene-fueled model supersonic combustor. It is computationally-efficient to evaluate the ignition performance of practical combustion systems in the design phase. Furthermore, assessment on the ignition properties can be made prior to any detailed and computationally-expensive simulations on the reactive flow, since only mixing field is required for calculating the IDT and IPD
Synergistic heat transfer modeling of actively cooled lattice structures under high-temperature boundary conditions
No full textThis paper presents an efficient multimodal thermal performance analysis model for predicting the thermal behavior of actively cooled three-dimensional lattice sandwich cylindrical structures in extreme thermal environments, such as those encountered in air and space vehicles. Traditional computational fluid dynamics (CFD) methods are accurate but computationally expensive in predicting conjugate heat transfer. Meanwhile, existing equivalent models are limited by their incomplete heat transfer mechanisms or their applicability only under low-temperature conditions. In contrast, this study develops a coupled prediction model that integrates solid heat conduction, forced convection of the radiation-transparent cooling medium, and interfacial radiation. The model is based on the energy conservation equation and a Newtonian iterative format, enabling the quantification of radiative heat transfer's contribution to overall heat dissipation efficiency in high-temperature environments. The model's predictions of total heat dissipation and the average temperature of the outer wall across a wide temperature range, using air as the cooling medium, are validated against high-fidelity CFD simulations and show excellent agreement with numerical calculations. Furthermore, the computational efficiency is improved by more than 400 times. Additional analysis reveals that, in high-temperature conditions, heat flow competition between the outer wall and lattice rods can cause a reversal in the temperature gradient, underscoring the significant role of radiation-convection dynamic coupling. This study provides a theoretical framework for the optimal design of dynamic thermal management systems in active composite thermal protection, expanding the applicability of conjugate heat transfer mechanisms in extreme thermal environments
Synergistic heat transfer modeling of actively cooled lattice structures under high-temperature boundary conditions
No full textThis paper presents an efficient multimodal thermal performance analysis model for predicting the thermal behavior of actively cooled three-dimensional lattice sandwich cylindrical structures in extreme thermal environments, such as those encountered in air and space vehicles. Traditional computational fluid dynamics (CFD) methods are accurate but computationally expensive in predicting conjugate heat transfer. Meanwhile, existing equivalent models are limited by their incomplete heat transfer mechanisms or their applicability only under low-temperature conditions. In contrast, this study develops a coupled prediction model that integrates solid heat conduction, forced convection of the radiation-transparent cooling medium, and interfacial radiation. The model is based on the energy conservation equation and a Newtonian iterative format, enabling the quantification of radiative heat transfer's contribution to overall heat dissipation efficiency in high-temperature environments. The model's predictions of total heat dissipation and the average temperature of the outer wall across a wide temperature range, using air as the cooling medium, are validated against high-fidelity CFD simulations and show excellent agreement with numerical calculations. Furthermore, the computational efficiency is improved by more than 400 times. Additional analysis reveals that, in high-temperature conditions, heat flow competition between the outer wall and lattice rods can cause a reversal in the temperature gradient, underscoring the significant role of radiation-convection dynamic coupling. This study provides a theoretical framework for the optimal design of dynamic thermal management systems in active composite thermal protection, expanding the applicability of conjugate heat transfer mechanisms in extreme thermal environments
Physical and MPM modelling of sand column collapse with different moisture and density conditions
No full textThe sand column collapse test is a simple but useful experiment for investigating the dynamic behaviour of granular flow, which is an important topic in engineering geology and the validation of numerical models. Previous studies have not adequately considered the influence of soil moisture and density conditions. In this study, a series of sand column collapse tests were conducted, considering five water contents ranging from 0 to 10 % and two relative densities of 40 % and 58 %. Particle Image Velocimetry (PIV) was utilised to post-process the experimental results. A hydro-mechanical coupled Material Point Method (MPM), improved by incorporating a non-linear strain hardening/softening law, was employed to back-analyse the physical model tests. The measured and computed results show that as water content increases, the degree of collapse and post-collapse runout distance initially decrease, consistent with changes in Bishop's stress, affected by suction and interparticle water meniscus. As relative density increases, both the degree of collapse and the post-collapse runout distance decrease due to the greater shear strength and Bishop's stress. The MPM simulations closely matched experimental results, confirming the model's accuracy in simulating large deformations in both dry and unsaturated soils
An arc-melted eutectic medium-entropy alloy with superior strength-ductility synergies at room and cryogenic temperatures
No full textThe cryogenic compressive mechanical properties of eutectic multi-principal alloys have rarely been reported. In this work, the superior fracture strength-fracture strain synergies at room and liquid nitrogen temperatures (RT and LNT) of the arc-melted Cr50Co25Ni25 eutectic medium-entropy alloy were found. These values were 1917 MPa and 39.1 % at RT, along with 1990 MPa and 26.1 % at LNT. The reduction of ductility at LNT was primarily attributed to the inferior deformation capability of the BCC phase containing HCP phase. The fracture mechanisms were dominated by ductile fracture of the FCC phase and brittle fracture of the BCC phase at both temperatures, while dislocation pile-ups and stacking faults were responsible for the deformation mechanisms
Energy dissipation mechanism of high-entropy alloys /CFRP/Al laminates under hypervelocity impact
No full textFiber metal laminates (FMLs) have garnered significant attention due to their high specific stiffness and strength, making them ideal candidates for spacecraft meteoroid/debris shielding in deep-space missions. In this study, an advanced energetic FMLs structure was designed and subjected to hypervelocity impact testing at 3.2 km/s and 5 km/s. The results indicate that, despite experiencing similar shock pressures and shock wave durations upon impact, the energetic FMLs structures with equivalent areal density exhibited superior ballistic performance compared to traditional metal or FMLs structures. These energetic FMLs structures have the ability to split the projectile into smaller parts and scatter the projectile shards over a larger space. Further analysis revealed that the shock heating effect of the energetic FMLs bumper accelerates the oxidation reactions of both projectile and bumper fragment elements due to its unique local plastic deformation characteristics and energy release mechanisms, thereby significantly enhancing the protective capability