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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Assessment of Core Physics Characteristics of Extended Enrichment and Higher Burnup LWR Fuels using the Polaris/PARCS Two-Step Approach (Vol. 2: BWR Fuel)

Nuclear fuel vendors and utilities are currently investigating changes to fuel contents and fuel designs for more economical and safer reactor operations. Extending cycle lengths beyond 18-month cycles for pressurized water reactors (PWRs) and 24-month cycles for boiling water reactors (BWRs) requires extending fuel enrichments beyond the current 5 wt % 235U limit. Therefore, low-enriched uranium plus (LEU+) fuel is expected to be used in current light-water reactor fleets in the near term. LEU+ is a subset of high-assay low-enriched uranium (HALEU) and is a term to describe fuel enrichments above 5% up to 10%. A series of studies were conducted at Oak Ridge National Laboratory (ORNL) to compare low-enriched uranium (LEU) with LEU+ fuel with respect to isotopic fuel content, lattice parameters, and core physics to identify any challenges in operation, storage, and transportation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

BSM Sensitivity Analysis and Meta-Modeling Next Steps [Slides]

We performed a global sensitivity analysis of the Bioenergy Scenario Model (BSM), using Elementary Effects analysis to identify potentially influential factors, with a focus on sustainable aviation fuel (SAF) production. The process was iterative and informed key model changes and updates over the course of the study in addition to identifying the key model inputs that affect the cumulative production of SAF from the present through 2050. More work will be performed to gain deeper insight into the sensitivity of individual pathways as part of our larger efforts to develop a reduced-form version of the BSM.

09 BIOMASS FUELS↗
DOE OSTI2024

Perspectives on Next Steps in Arms Control and Non-Proliferation

Much has happened in arms control over the last year as this chapter has been in development. The prospects for arms control as a viable national security tool have, if anything, grown darker. Russia has falsely equated tearing down the remaining arms control edifice with creating potential leverage vis-à-vis its actions in Ukraine. China has failed to update its talking points on being a responsible arms control actor with its massive nuclear force expansion. The United States has stated clearly that it is open for business on arms control and risk reduction, but it unfortunately has no customers in Russia and China. It remains unclear what specifically the United States is selling in terms of what it wants in a potential agreement. Competitive dynamics and an atmosphere of great power competition are driving all parties further away from the table.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Process Intensification by One-Step, Plasma-Assisted Catalytic Synthesis of Liquid Chemicals from Light Hydrocarbons

In this project, we present a plasma-assisted, catalytic process that can handle variations in production rates and gas compositions of producing wells and reliably converts the hydrocarbons to gas phase olefins, high molecular weight alkanes, and liquid chemicals. The low-temperature plasma serves as a reactive chemical environment that activates and converts the light hydrocarbons to these valuable products. We present results from the integration of a catalyst into the low-temperature plasma zone to improve reaction efficiency and product selectivity. We show that the gas composition, bulk gas temperature, and input power of the plasma, with and without catalysts, influence the production rates of liquids from natural gas feeds.

03 NATURAL GAS↗
DOE OSTI2024

Navigating Options for Transportation Electrification and Solar Charging: Steps and Lessons Learned in Montana Communities

This document is intended to assist communities who are considering investing in electric transportation. It can assist communities engage stakeholders, prioritize community goals, assess electric transportation options, and navigate complex decisions about deploying zero emission electric transportation in their community. It covers technological, economic and environmental aspects of the transition to electric vehicles (EV), and highlights the specific considerations related to the deployment of renewable energy technologies (e.g., distributed solar) in combination with EV supply equipment (EVSE, e.g., charging stations). There are many important decisions to make and questions for communities to ask themselves as they consider electric vehicle types, charging infrastructure, and electricity generation options. This guide will help communities assess: (1) Which stage in the decision-making process they are in with respect to EV deployment; (2) Questions they can explore to guide their decisions about EV deployment; (3) How to engage key stakeholders on EV deployment options; (4) Tradeoffs and benefits of various electric transportation options and; (5) Synergies of pairing electric vehicle charging and renewable energy generation technologies. The analysis and lessons learned presented in this roadmap are intended to serve as a template and guide for similarly situated communities across the country who want to prepare for and play a role in the electrified transportation future.

14 SOLAR ENERGY↗
DOE OSTI2023

Freeform thermoelectrics in single-step manufacturing: additive manufacturing of bismuth-telluride thermoelectrics

The project succeeded in producing crack-free Bismuth Telluride thermoelectric parts with density exceeding 98% through laser powder bed fusion (LPBF) additive manufacturing (AM). This greatly exceeded the highest previously reported density of 88% and is the highest among all semiconducting materials processed by LPBF. The additively manufactured material shows comparable Seebeck coefficient as conventional form and can be made into complex geometries with reduced material loss. On the other hand, measured properties are dramatically sensitive to the AM process parameters used, such that with identical composition, the Seebeck coefficient can be controllably tuned from +120 µV/K to -207 µV/K, which means the material switches between an n-type to a p-type semiconductor depending on processing. These changes are accompanied by significant differences in the as-processed microstructure due to rapid solidification. A machine learning protocol was developed and greatly reduced the experimental burden of the project, reducing the typical process optimization period of 2 years to 6 months. The project was fully successful in the objective of producing defect-free, complex geometry of bismuth-telluride parts through LPBF, but only partially successful in achieving performance goals. First, cost reduction of manufacturing, as measured by material waste, was successfully reduced by up to 70% compared to conventional manufacturing methods. This exceeded the proposed 30% reduction in materials waste needed to reach the 20% cost reduction goal of the project. On the other hand, the device performance, as measured by Seebeck coefficient, failed to reach the 40% improvement in efficiency. Rather, we observe comparable Seebeck coefficient between AM samples and conventionally processed counterparts. The device-level efficiency improvement does exceed 40% for complex geometry samples due to shape-induced increase in temperature gradients, but this was not the originally proposed metric. The machine learning approach developed in this project greatly accelerated the process optimization and can be adopted for fast development of AM processing parameters for other brittle and otherwise difficult-to-print materials. For the public, we deliver an efficient and widely adoptable process for incorporating waste-heat harvesting thermoelectric devices in both industrial and commercial heat exchangers. The geometric flexibility allows the capturing device to conform to the shape of the heat source to improve the system-level conversion efficiency. The technique can be deployed on any commercial LBPF systems with zero modifications, thus poses minimal adoption barrier for any manufacturer that already employed AM technology. Beyond bismuth-telluride, the machine-learning guided optimization protocol can be used in the future to reduce both the time and cost of process development for AM of other energy conversion and harvesting materials.

36 MATERIALS SCIENCE↗