18 research outputs found

    Modeling of Nitrogen Monoxide Formation and Radiation in Nonequilibrium Hypersonic Flows

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    The interaction between nitrogen vibrational-translational relaxation with different chemistrymodels in a hypersonic shock is studied. The vibrational-translational transition models considered include the Larsen–Borgnakke, Schwartz- Slawsky-Herzfeld, and forced harmonic oscillator models; and the nitrogen monoxide formation reaction was studied using the total collision energy chemistry model and reaction cross sections obtained from quasi-classical trajectory simulations. Using direct simulation Monte Carlo solutions that incorporate these models, improved nitrogen monoxide spectral radiation modeling was performed by employing quenching rates from recent experiments. Comparisons of electronic state populations and the corresponding radiative spectra for the different vibrational-translational and chemistry models are presented, and it is shown that the vibronic spectral structure of the nitrogen monoxide radiation could provide a way to test the fidelity of the internal energy transfer and chemistry models

    Supercomputing Modeling & simulation

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    Efficiency Enhancement of PIC-MCC Modeling for Magnetron Sputtering Simulations Using GPU Parallel

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    A particle-in-cell Monte Carlo collision (PIC-MCC) model is presented, parallelized to be suitable for magnetron sputtering simulations ongeneral purpose graphics processing units (GPGPUs). To reduce the large computation time generally required to calculate particleelectromagneticfield interactions, a numerical algorithm is optimized to obtain the best performance with GPGPU parallelization. Theefficiency and accuracy of the GPGPU parallelized PIC-MCC model are examined by comparing the calculated results and the correspondingcomputational time with analytical solutions and the computation time of the serial code, respectively. The erosion and deposition ratesduring sputtering predicted using this model are in good agreement with experimental results. The newly developed PIC-MCC model withGPGPU parallelization is thereby shown to be both efficient and accurate

    Supercomputing

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