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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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X-ray computed tomography analysis of pore deformation in IN718 made with directed energy deposition
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Transient heat and mass transfer analysis in a porous ceria structure of a novel solar redox reactor
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Temperature transient analysis for bounded oil reservoir under depletion drive
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Numerical modeling and analysis of Transport Membrane Condensers for waste heat and water recovery from flue gas
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Techno-economic analysis of supercritical extraction of rare earth elements from coal ash
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Life cycle analysis of polylactic acids from different wet waste feedstocks
Producing a valuable chemical product through diversion of wet wastes can simultaneously resolve the problems associated with increasing wastes and greenhouse gas emissions from conventional chemical production processes. In this work, we investigated the life-cycle greenhouse gas emissions, water, and fossil-fuel consumption for waste-derived polylactic acids (PLA) from three different waste feedstocks, namely wastewater sludge, food waste, and swine manure, using the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) model. The decarbonization potential of replacing fossil-based resins with the waste-derived polymer was also investigated. The results show that swine manure-to-PLA pathway was the least carbon intensive (—1.4 kgCO 2 e/kg) among the three waste-to-PLA pathways on a cradle-to-grave basis, followed by the food waste case (—1.3 kgCO 2 e/kg) and then by the wastewater sludge case (0.6 kgCO 2 e/kg). In the baseline scenario, all three waste-to-PLA pathways were less carbon intensive than both fossil-based PET and HDPE on a cradle-to-grave basis: 66% (vs. PET) and 56% (vs. HDPE), 171 and 192%, 181 and 205% reduction in GHG emissions for wastewater sludge-, food waste-, and swine manure-to-PLA pathway, respectively. For all sensitivity cases investigated, the food waste- and swine manure-to-PLA pathways were significantly less carbon intensive than their fossil-counterparts. In terms of the annual decarbonization potential of replacing fossil-based PET or HDPE, the wastewater sludge- and food waste-pathway showed higher mitigation potential than the swine manure-pathway: i) 18–28 kilotons CO 2 e-reduction per year for wastewater sludge pathway; ii) 23–26 kTCO 2 e-reduction/yr for food waste pathway; and iii) about 5 kTCO 2 e-reduction/yr for swine manure pathway depending on the type of conventional resin replaced. However, given the abundant availability of the swine manure feedstocks across the United States, the decarbonization potential of swine manure-based pathway can also increase as the plant capacity or the number of plants grow.
Chromatographic analysis of the acidity-salinity transport system
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Techno-economic analysis and life cycle analysis of e-fuel production using nuclear energy
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Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies
Sampling orthogonal polynomial bases via Monte Carlo is of interest for uncertainty quantification of models with random inputs, using Polynomial Chaos (PC) expansions. It is known that bounding a probabilistic parameter, referred to as coherence, yields a bound on the number of samples necessary to identify coefficients in a sparse PC expansion via solution to an ℓ{sub 1}-minimization problem. Utilizing results for orthogonal polynomials, we bound the coherence parameter for polynomials of Hermite and Legendre type under their respective natural sampling distribution. In both polynomial bases we identify an importance sampling distribution which yields a bound with weaker dependence on the order of the approximation. For more general orthonormal bases, we propose the coherence-optimal sampling: a Markov Chain Monte Carlo sampling, which directly uses the basis functions under consideration to achieve a statistical optimality among all sampling schemes with identical support. We demonstrate these different sampling strategies numerically in both high-order and high-dimensional, manufactured PC expansions. In addition, the quality of each sampling method is compared in the identification of solutions to two differential equations, one with a high-dimensional random input and the other with a high-order PC expansion. In both cases, the coherence-optimal sampling scheme leads to similar or considerably improved accuracy.
Analysis of channel confined selective area growth in evolutionary growth of GaN on SiO2
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