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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Application of the Metabolic Modeling Pipeline in KBase to Categorize Reactions, Predict Essential Genes, and Predict Pathways in an Isolate Genome

The DOE Systems Biology Knowledgebase (KBase) platform offers a range of powerful tools for the reconstruction, refinement, and analysis of genome-scale metabolic models built from microbial isolate genomes. In this chapter, we describe and demonstrate these tools in action with an analysis of isoprene production in the Bacillus subtilis DSM genome. Two different methods are applied to build initial metabolic models for the DSM genome, then the models are gapfilled in three different growth conditions. Next, flux balance analysis (FBA) and flux variability analysis (FVA) techniques are applied to both study the growth of these models in minimal media and classify reactions within each model based on essentiality and functionality. The models are applied with the FBA method to predict essential genes, which are then compared to an updated list of essential genes obtained for B. subtilis 168, a very similar strain to the DSM isolate. The models are also applied to simulate Biolog growth conditions, and these results are compared with Biolog data collected for B. subtilis 168. Finally, the DSM metabolic models are applied to explore the pathways and genes responsible for producing isoprene in this strain. These studies demonstrate the accuracy and utility of models generated from the KBase pipelines, as well as exploring the tools available for analyzing these models.

Allen, Benjamin↗
DOE OSTI2023

Application of Interparticle Spacing Model to Maximize Filler Content in Cementitious Pastes

One of the most impactful ways to reduce embodied carbon of concrete in the near term is by partially replacing Portland cement with supplementary cementitious materials and/or fillers. This article describes an approach to reduce cement content in concrete through the development of high filler, low water (HFLW) cementitious pastes. Pastes with cement content as low as 50% (% weight of fines) were designed by applying models that maximize the packing density of the granular system and that consider the characteristics of the materials to calculate interparticle spacing (IPS), thereby allowing to obtain pastes with higher solids concentration and lower water demand. Strong correlations were found between IPS, the consistency index of the Herschel-Bulkley rheological model, and cement hydration kinetic parameters of binary and ternary pastes containing a Portland limestone cement and up to two different types of ground limestone. The approach showed to be feasible for the design of HFLW concrete paste fraction.

Antunes da Silva, Denise↗
DOE OSTI2024

Application of Process Chemical Modeling to Optimize Radioactive Waste Disposal at the Savannah River Site – 24242

The Liquid Waste Program (LWP) managed by Savannah River Mission Completion (SRMC) is responsible for the treatment and disposal of waste at the Savannah River Site (SRS). Radioactive waste at SRS is stored and processed at four key facilities – each with their respective functions to store, blend, grout, or vitrify waste. The tank farm, where waste is stored, consists primarily of legacy waste with new material incoming from the Accelerated Basin De-inventory program (ABD), which is managed by Savannah River Nuclear Solutions (SRNS). System planning is done by SRNS and SRMC to optimize ABD and LWP operations, respectively.

Georgiou, Andreas↗
DOE OSTI2024

Ageing Studies of Mega Battery Packs for Grid Storage Applications Using Physics Based Modeling

The lower Levelized Cost of Electricity (LCOE) from wind and solar photovoltaics has enabled for greater integration of variable energy resources with energy storage tech-nologies such as larger centralized lithium-ion battery megapacks (with 1MWh total energy and 500V rating) to provide utility-scale services to grid operators. The daily cycling of standalone lithium-ion grid storage will reduce the battery cells' capacity due to several degradation mechanisms. A comprehensive physics-based Python tm framework called Liionpack was developed to estimate these megapacks' remaining life and ageing. The study includes various degradation mechanisms coupled to the electrochemical-thermal model at the pack level. The effect of the inhomogeneities from cell-to-cell thermodynamic and kinetic properties for different working conditions including temperature and charge/discharge protocols on the ageing of a megapack are presented here.

Karra, Vikrant↗