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Results for “dynamics simulation”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Enabling molecular dynamics simulations of helium bubble formation in tritium-containing austenitic stainless steels: An Fe-Ni-Cr-H-He potential
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Scalability study of molecular dynamics simulation on Godson-T many-core architecture
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A critical review of the developments in molecular dynamics simulations to study femtosecond laser ablation
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Dislocation dynamics simulations of precipitation-strengthened Ni- and Co-based superalloys
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Electronic structure and tight-binding molecular dynamics simulations for calcium and strontium
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Radiation effect on BCC Fe nanoparticle with varying radiation energy by molecular dynamics simulation
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SHarD: A beam dynamics simulation code for dielectric laser accelerators based on spatial harmonic field expansion
In order to demonstrate acceleration of electrons to relativistic scales by an on chip dielectric laser accelerator (DLA), a ponderomotive focusing scheme capable of capturing and transporting electrons through nanometer-scale apertures over extended interaction lengths has been proposed. Here we present a Matlab-based numerical code (SHarD) utilizing a spatial harmonic expansion of the fields within the dielectric structure to simulate the evolution of the beam phase space distribution in this scheme. The code can be used to optimize key-parameters for the accelerator performance such as the final energy, transverse spot size evolution and total number of electrons accelerated through currently fabricated structures. Eventually, the simulation model will be applied to inform the phase mask profile to be added to a pulse front tilt drive laser pulse using a liquid crystal mask in the experimental setup being assembled at UCLA Pegasus Laboratory.
Threshold displacement energies and primary radiation damage in AlN from molecular dynamics simulations
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A dissipation-based method for improving the accuracy of computational fluid dynamics simulations of high level non-Newtonian wastes
Here this paper investigates a new viscosity model for laminar, transitional, and turbulent pipe flow simulations of a non-Newtonian slurry using the Star-CCM+ software. Herschel-Bulkley (HB) rheology equation was used in its original and modified forms to model the fluid viscosity. The realizable k-ε model was used for modeling of turbulence. It was observed that simulations using the HB model predicted inaccurate profiles of U (mean velocity) and U + (mean velocity in wall units). Therefore, we developed alternative values of viscosity obtained directly from non-linearity of stress–strain variation (α) in each iteration. The developed method, “Alpha method”, applied changes in places where dissipation rate of turbulent kinetic energy occurred and was designed based on local or global dissipation rate values. Inverse values of α were used to test effects of more viscosity reduction for all flow regimes. In prediction of the mean velocities, significant improvements were obtained through global adjustment of viscosity in inverse form during simulation of the laminar and turbulent flow cases. For the transitional flow, obtaining improvements in prediction of U and U + from the same model version faced challenges. While the global adjustments in direct form were found significantly effective in improving the prediction of U, they failed to predict the U + accurately. For this purpose, Local viscosity adjustments were found significantly effective.
A point kinetics model for dynamic simulations of next generation nuclear reactor
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Data trustworthiness signatures for nuclear reactor dynamics simulation
With the increased reliance on digitization in industrial control systems, the need for effective monitoring techniques has risen dramatically. Specifically, there is now a growing concern about the so-called false data injection (FDI) attacks. These attacks aim to alter the raw sensors’ data to cause malicious outcomes. Any serious FDI algorithm is based on an intimate knowledge of the system and its associated physics models, which renders conventional outlier/anomaly detection techniques almost obsolete in the face of such attacks. Thus, a critical need has emerged to develop a new class of defense methods that are capable of detecting FDI attacks under the assumption that the attacker has a strong familiarity with the system and its physics modeling. This class of defense methods are denoted by model-based defenses which are premised on the assumption that the attacker, while having a good understanding of the system, does not have full privileged access to all proprietary data and historical records of operation. However, (s)he is assumed to be capable of learning system behavior using self-learning techniques during an initial lie-in-wait period. To defend against this scenario, we propose a new model-based randomized window algorithm that searches time-series data for signatures that can serve as classifiers between normal and FDI scenarios. The classifiers are based on the correlations between the dominant degrees of freedom (DOFs) and the less-dominant DOFs (expected to be very sensitive to the system details that are unknown to the attacker). For demonstration, RELAP5 models are employed to calculate representative nuclear reactor behavior during a number of transient scenarios. Finally, falsified data are injected into the RELAP5-simulated behavior, and the proposed signature-identification algorithm is employed to detect the injected data.
Investigation of thermomechanical behaviors of acrylate-based shape memory polymers by molecular dynamics simulation
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Cavitation in crosslinked polymers: Molecular dynamics simulations of network formation
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