Publications

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An analysis was performed to determine whether a hydrogen jet flame impinging on a tunnel ceiling composed of multiple prestressed steel reinforced concrete box beams could result in permanent damage to the tunnel. The lower layer of the concrete box beam was modeled to determine whether heat reaches the steel reinforcing bars and whether spalling could occur. Heat transfer analysis shows that the temperature remains constant at the location of the steel reinforcing bars after 1.3 minutes of impingement and reaches a maximum of 130°C after 5 minutes. However, assuming a constant impingement for 5 minutes is an over estimation due the existing fire model which includes conservative assumptions. Explosive spalling may occur at a thin layer (~0.05 in. at 50 seconds, 0.1 in. at 5 minutes) at the bottom surface of the concrete box beam, but the steel reinforcing bars will not be exposed to the hydrogen flame.

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Recent evaluations of counter-based periodic testing strategies for fault detection in Microprocessor(μP) have shown that only a small set of counters is needed to provide complete coverage of severe faults. Severe faults are defined as faults that leak sensitive information, e.g., an encryption key on the output of a serial port. Alternatively, fault detection can be accomplished by executing instructions that periodically test the control and functional units of the μP. In this paper, we propose a fault detection method that utilizes an ’engineered’ executable program combined with a small set of strategically placed counters in pursuit of a hardware Periodic Built-In-Self-Test (PBIST). We analyze two distinct methods for generating such a binary; the first uses an Automatic Test Generation Pattern (ATPG)-based methodology, and the second uses a process whereby existing counter-based node-monitoring infrastructure is utilized. We show that complete fault coverage of all leakage faults is possible using relatively small binaries with low latency to fault detection and by utilizing only a few strategically placed counters in the μP.

Monte Carlo simulations are at the heart of many high-fidelity simulations and analyses for radiation transport systems. As is the case with any complex computational model, it is important to propagate sources of input uncertainty and characterize how they affect model output. Unfortunately, uncertainty quantification (UQ) is made difficult by the stochastic variability that Monte Carlo transport solvers introduce. The standard method to avoid corrupting the UQ statistics with the transport solver noise is to increase the number of particle histories, resulting in very high computational costs. In this contribution, we propose and analyze a sampling estimator based on the law of total variance to compute UQ variance even in the presence of residual noise from Monte Carlo transport calculations. We rigorously derive the statistical properties of the new variance estimator, compare its performance to that of the standard method, and demonstrate its use on neutral particle transport model problems involving both attenuation and scattering physics. We illustrate, both analytically and numerically, the estimator's statistical performance as a function of available computational budget and the distribution of that budget between UQ samples and particle histories. We show analytically and corroborate numerically that the new estimator is unbiased, unlike the standard approach, and is more accurate and precise than the standard estimator for the same computational budget.

Shock-driven implosions with 100% deuterium (D2) gas fill compared to implosions with 50:50 nitrogen-deuterium (N2D2) gas fill have been performed at the OMEGA laser facility to test the impact of the added mid-Z fill gas on implosion performance. Ion temperature (Tion) as inferred from the width of measured DD-neutron spectra is seen to be 34%±6% higher for the N2D2 implosions than for the D2-only case, while the DD-neutron yield from the D2-only implosion is 7.2±0.5 times higher than from the N2D2 gas fill. The Tion enhancement for N2D2 is observed in spite of the higher Z, which might be expected to lead to higher radiative loss, and higher shock strength for the D2-only versus N2D2 implosions due to lower mass, and is understood in terms of increased shock heating of N compared to D, heat transfer from N to D prior to burn, and limited amount of ion-electron-equilibration-mediated additional radiative loss due to the added higher-Z material. This picture is supported by interspecies equilibration timescales for these implosions, constrained by experimental observables. The one-dimensional (1D) kinetic Vlasov-Fokker-Planck code ifp and the radiation hydrodynamic simulation codes hyades (1D) and xrage [1D, two-dimensional (2D)] are brought to bear to understand the observed yield ratio. Comparing measurements and simulations, the yield loss in the N2D2 implosions relative to the pure D2-fill implosion is determined to result from the reduced amount of D2 in the fill (fourfold effect on yield) combined with a lower fraction of the D2 fuel being hot enough to burn in the N2D2 case. The experimental yield and Tion ratio observations are relatively well matched by the kinetic simulations, which suggest interspecies diffusion is responsible for the lower fraction of hot D2 in the N2D2 relative to the D2-only case. The simulated absolute yields are higher than measured; a comparison of 1D versus 2D xrage simulations suggest that this can be explained by dimensional effects. The hydrodynamic simulations suggest that radiative losses primarily impact the implosion edges, with ion-electron equilibration times being too long in the implosion cores. The observations of increased Tion and limited additional yield loss (on top of the fourfold expected from the difference in D content) for the N2D2 versus D2-only fill suggest it is feasible to develop the platform for studying CNO-cycle-relevant nuclear reactions in a plasma environment.

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ARMA conference poster for a year-round grad intern from CSM

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