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Published in Proceedings of the 2021 11th International Conference on Power, Energy and Electrical Engineering (CPEEE), pp. 272-280, Shiga, Japan, 2021
Moon exploration is an attractive research ofinterest especially along with the development of lunar vehicletechnologies in the past decades. Here, a small lunar vehicleprototype with a foldable mechanism was proposed. It can foldand unfold in the lunar environment, which can reduce the volumeby about 20%. The robotic arm of the lunar rover whichincorporates the camera into its end-effector also helps reduce thenumber of vision sensors and extra energy consumption. Besides,a combination of solar panels and compact nuclear batteries canensure the rover’s endurance of operation on the moon. Inaddition, the folding process of the lunar rover, the ability to gouphill and downhill, and the ability to pass over obstacles aresimulated in SOLIDWORKS MOTION. Accordingly, twooptimization schemes, including adding more suspension systemsand automatic route planning systems, are proposed. With thedevelopment of the foldable lunar vehicle, it became possible forlarge number of lunar vehicles to be sent to the moon in one time,which also provided the basis for the commercialization of themoon landing.
Recommended citation: Rong Jin (2021). "The Conceptional Design and Simulation of a Foldable Lunar Vehicle." In Proceedings of the 2021 11th International Conference on Power, Energy and Electrical Engineering (CPEEE), pp. 272-280. February 26-28, 2021, Shiga, Japan. DOI: 10.1109/CPEEE51686.2021.9383342
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Published in Proceedings of the ASME 2024 International Mechanical Engineering Congress and Exposition, Volume 3, American Society of Mechanical Engineers, Portland, Oregon, USA, 2024
High-velocity impact analysis is crucial in defense, aerospace, and materials science, involving scenarios ranging from projectiles hitting land vehicles to supersonic aircraft traveling in dusty environments. This work presents a detailed computational analysis of high-velocity impacts using the Smoothed Particle Hydrodynamics (SPH) method. Impact events include a stainless steel projectile against a magnesium alloy target plate, with impact velocities ranging from 1.2 km/s to 2.4 km/s. We employ carefully calibrated plasticity, fracture, and equation of state models to characterize the behaviors of both projectile and target over a wide range of strain rates and temperatures. Our simulation results include the evolution of the von-Mises effective stress and temperature fields at different impact velocities. Several key material failure mechanisms are observed, such as spalling and adiabatic shearing. We partition and quantify the dissipation of the impact kinetic energy into the kinetic and internal energies of both the projectile and the target. Finally, we analyze the time histories of the corresponding proportions during the impact events and the distributions of energies across all material points at key time points. We find that at all impact velocities, the target’s kinetic energy peaks when the shock wave reaches the back face and stabilizes after complete penetration. As the impact velocity increases, the kinetic energy of the target and the internal energy of the projectile contribute more significantly to the dissipation of the impact energy, while the contribution of the target internal energy decreases.
Recommended citation: Rong Jin, Xingsheng Sun (2024). "Characterization of Energy Dissipation and Material Failure Mechanisms In High-Velocity Impact of Magnesium Alloys." In Proceedings of the ASME 2024 International Mechanical Engineering Congress and Exposition, Volume 3. American Society of Mechanical Engineers, November 17-21, 2024, Portland, Oregon, USA. DOI: 10.1115/imece2024-141602
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Published in Modelling and Simulation in Materials Science and Engineering, Vol. 32(8), 2024
Phase transitions of metals in hydrogen (H) environments are critically important for applications in energy storage, catalysis, and sensing. Nanostructured metallic particles can lead to faster charging and discharging kinetics, increased lifespan, and enhanced catalytic activities. However, establishing a direct causal link between nanoparticle structure and function remains challenging. In this work, we establish a computational framework to explore the atomic configuration of a metal-hydrogen system when in equilibrium with a H environment. This approach combines Diffusive Molecular Dynamics with an iteration strategy, aiming to minimize the system’s free energy and ensure uniform chemical potential across the system that matches that of the H environment. Applying this framework, we investigate H chemical potential-composition isotherms during the hydrogenation and dehydrogenation of palladium nanoparticles, ranging in size from 3.9 nm to 15.6 nm and featuring various shapes including cube, rhombic dodecahedron, octahedron, and sphere. Our findings reveal an abrupt phase transformation in all examined particles during both H loading and unloading processes, accompanied by a distinct hysteresis gap between absorption and desorption chemical potentials. Notably, as particle size increases, absorption chemical potential rises while desorption chemical potential declines, consequently widening the hysteresis gap across all shapes. Regarding shape effects, we observe that, at a given size, cubic particles exhibit the lowest absorption chemical potentials during H loading, whereas octahedral particles demonstrate the highest. Moreover, octahedral particles also exhibit the highest desorption chemical potentials during H unloading. These size and shape effects are elucidated by statistics of atomic volumetric strains resulting from specific facet orientations and inhomogeneous H distributions. Prior to phase transformation in absorption, a H-rich surface shell induces lattice expansion in the H-poor core, while before phase transformation in desorption, surface stress promotes lattice compression in the H-rich core. The magnitude of the volumetric strains correlates well with the size and shape dependence, underlining their pivotal role in the observed phenomena.
Recommended citation: Xingsheng Sun, Rong Jin (2024). "Size and shape dependence of hydrogen-induced phase transformation and sorption hysteresis in palladium nanoparticles." Modelling and Simulation in Materials Science and Engineering, Vol. 32(8). DOI: 10.1088/1361-651X/ad89e3
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The presentation performed a computational analysis of high-velocity impacts (1.2–2.4 km/s) between stainless steel projectiles and magnesium alloy targets using Smoothed Particle Hydrodynamics (SPH). Simulations reveal principal failure mechanisms, quantify energy dissipation into kinetic and internal energies, and demonstrate velocity-dependent energy partitioning. Results highlight peak kinetic energies at shock-wave arrival and evolving energy distributions during penetration.
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This presentation investigated the mechanisms of material deformation, failure, and energy dissipation in high/hyper-velocity impacts on magnesium alloys impacted by steel projectiles (up to 3 km/s). A high-fidelity Smoothed Particle Hydrodynamics (SPH) model, calibrated with plasticity, fracture, and EOS models, was validated against experimental data. Parametric studies revealed critical insights into energy partitioning and failure mechanisms, guiding protective system design.
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This presentation addressed the calibration challenges in high-velocity impact modeling by applying ensemble-based data assimilation (DA) to Smoothed Particle Hydrodynamics (SPH) simulations. Utilizing the ensemble Kalman filter (EnKF), we iteratively integrated experimental observations and simulation results to enhance accuracy of material model parameters. The resulting improved calibration framework significantly advances reliability and precision in high-strain-rate impact simulations.
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In this work, we employ ensemble-based data assimilation (DA) to calibrate material model parameters under high-velocity impact conditions. DA integrates experimental observations with numerical models. By iteratively updating simulation inputs based on observational data, DA minimizes errors arising from both numerical approximations and experimental inaccuracies. Specifically, we use smoothed particle hydrodynamics (SPH) simulations as the dynamic system. The discrete-time nature of SPH simulations makes them particularly well-suited for sequential DA methods. We apply the ensemble Kalman filter (EnKF), a robust DA technique, to refine material model parameters by reconciling discrepancies between experimental observations and simulation results. This work signifies a substantial progression towards integrating DA techniques into high-strain-rate material modeling and demonstrates the potential of combining experimental data with advanced numerical methods to address challenges in high-velocity impact applications. The expected outcome is an improved methodology for calibrating material models and estimating model parameters, yielding more accurate and reliable high-velocity impact simulations.
Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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