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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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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Residual Monte Carlo high-order solver for Moment-Based Accelerated Thermal Radiative Transfer equations

In this article we explore the possibility of replacing Standard Monte Carlo (SMC) transport sweeps within a Moment-Based Accelerated Thermal Radiative Transfer (TRT) algorithm with a Residual Monte Carlo (RMC) formulation. Previous Moment-Based Accelerated TRT implementations have encountered trouble when stochastic noise from SMC transport sweeps accumulates over several iterations and pollutes the low-order system. With RMC we hope to significantly lower the build-up of statistical error at a much lower cost. First, we display encouraging results for a zero-dimensional test problem. Then, we demonstrate that we can achieve a lower degree of error in two one-dimensional test problems by employing an RMC transport sweep with multiple orders of magnitude fewer particles per sweep. We find that by reformulating the high-order problem, we can compute more accurate solutions at a fraction of the cost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Moving from residual lignocellulosic biomass into high–value products: Outcomes from a long–term international cooperation

Major progress in the bioprocessing of lignocellulose to fuels and value-added chemicals has created the possibility of a low carbon-footprint economy. However, the current complexity and associated costs of lignocellulose conversion result in a higher price for ethanol than for fossil fuels. The cost of cellulosic ethanol production will be lowered by further progress in development of biorefinery technology that produces both ethanol and high-value chemicals with bio-based products that are beginning to penetrate consumer markets in the USA, Brazil, and worldwide. The cost-effectiveness of low carbon-footprint bioproducts will benefit from advances in supplying large amounts of biomass solids to the biorefinery. We describe here outcomes from a successful long-term international cooperation between the Laboratory of Renewable Resources Engineering (LORRE) at Purdue University in the United States and Brazil's Agricultural Research Corporation (EMBRAPA) and Federal University of Sâo Carlos (UFSCar), which has contributed practical pathways to enhance the biorefinery concept. Furthermore, this paper gives an overview of developments that address fundamental knowledge of lignocellulosic biomass pretreatment hydrolysis under optimized operational conditions and bioreactor configurations, and the science and engineering that contributes to the effective production of fuel and ethanol and value-added products from biomass.

09 BIOMASS FUELS↗
DOE OSTI2023

Residuals-based distributionally robust optimization with covariate information

We consider data-driven approaches that integrate a machine learning prediction model within distributionally robust optimization (DRO) given limited joint observations of uncertain parameters and covariates. Our framework is flexible in the sense that it can accommodate a variety of regression setups and DRO ambiguity sets. We investigate asymptotic and finite sample properties of solutions obtained using Wasserstein, sample robust optimization, and phi-divergence-based ambiguity sets within our DRO formulations, and explore cross-validation approaches for sizing these ambiguity sets. Through numerical experiments, we validate our theoretical results, study the effectiveness of our approaches for sizing ambiguity sets, and illustrate the benefits of our DRO formulations in the limited data regime even when the prediction model is misspecified.

97 MATHEMATICS AND COMPUTING↗