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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Conjunctive Surface and Groundwater Management in Utah. Implications for Oil Shale and Oil Sands Development

Unconventional fuel development will require scarce water resources. In an environment characterized by scarcity, and where most water resources are fully allocated, prospective development will require minimizing water use and seeking to use water resources in the most efficient manner. Conjunctive use of surface and groundwater provides just such an opportunity. Conjunctive use includes two main practices: First, integrating surface water diversions and groundwater withdrawals to maximize efficiency and minimize impacts on other resource users and ecological processes. Second, conjunctive use includes capturing surplus or unused surface water and injecting or infiltrating that water into groundwater aquifers in order to increase recharge rates. Conjunctive management holds promise as a means of addressing some of the West's most intractable problems. Conjunctive management can firm up water supplies by more effectively capturing spring runoff and surplus water, and by integrating its use with groundwater withdrawals; surface and groundwater use can be further integrated with managed aquifer recharge projects. Such integration can maximize water storage and availability, while simultaneously minimizing evaporative loss, reservoir sedimentation, and surface use impacts. Any of these impacts, if left unresolved, could derail commercial-scale unconventional fuel development. Unconventional fuel developers could therefore benefit from incorporating conjunctive use into their development plans. Despite its advantages, conjunctive use is not a panacea. Conjunctive use means using resources in harmony to maximize and stabilize long-term supplies it does not mean maximizing the use of two separate but interrelated resources for unsustainable short-term gains and it cannot resolve all problems or provide water where no unappropriated water exists. Moreover, conjunctive use may pose risks to ecological values forgone when water that would otherwise remain in a stream is diverted for aquifer recharge or other uses. To better understand the rapidly evolving field of conjunctive use, this Topical Report begins with a discussion of Utah water law, with an emphasis on conjunctive use issues. We contrast Utah's approach with efforts undertaken in neighboring states and by the federal government. We then relate conjunctive use to the unconventional fuel industry and discuss how conjunctive use can help address pressing challenges. While conjunctive management cannot create water where none exists, it does hold promise to manage existing resources in a more efficient manner. Moreover, conjunctive management reflects an important trend in western water law that could provide benefit to those contemplating activities that require large-scale water development.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2011

Application of the Split Hopkinson Resonant Bar Test for Seismic Property Characterization of Hydrate-bearing Sand Undergoing Water Saturation

Conventional resonant bar tests allow the measurement of seismic properties of rocks and sediments at low frequencies (several kilohertz). However, the tests require a long, slender sample which is often difficult to obtain from the deep subsurface and weak and fractured formations. We present an alternative low-frequency measurement technique to the conventional resonant bar tests. This technique involves a jacketed core sample placed between a pair of long, metal extension rods with attached seismic source and receiver—the same geometry as the split Hopkinson pressure bar test for large-strain, dynamic impact experiments. Because of the added length and mass to the sample, the resonance frequency of the entire system can be lowered significantly, compared to the sample alone. The proposed “Split Hopkinson Resonant Bar (SHRB)” test is applied in two steps. In the first step, extension and torsion-mode resonance frequencies and attenuation of the system are measured. Then, numerical inversions for the compressional and shear wave velocities and attenuation are performed. We initially applied the SHRB test to synthetic materials (plastics) for testing its accuracy, then used it for measuring the seismic velocities and attenuation of a rock core containing supercritical CO 2 , and a sediment core while methane hydrate formed in the pore space.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Machine Learning for Correlated Intelligence. LDRD SAND Report

The Machine Learning for Correlated Intelligence Laboratory Directed Research & Development (LDRD) Project explored competing a variety of machine learning (ML) classification techniques against a known, open source dataset through the use of a rapid and automated algorithm research & development (RD) infrastructure. This approach relied heavily on creating an infrastructure in which to provide a pipeline for automatic target recognition (ATR) ML algorithm competition. Results are presented for nine ML classifiers against a primary dataset using the pipeline infrastructure developed for this project. New approaches to feature set extraction are presented and discussed as well.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

100% Carbon-Free Electricity for Sandia NM and KAFB Using Concentrating Solar Power (CSP) (SAND Report)

This report provides a design study to produce 100% carbon-free electricity for Sandia NM and Kirtland Air Force Base (KAFB) using concentrating solar power (CSP). Annual electricity requirements for both Sandia and KAFB are presented, along with specific load centers that consume a significant and continuous amount of energy. CSP plant designs of 50 MW and 100 MW are then discussed to meet the needs of Sandia NM and the combined electrical needs of both Sandia NM and KAFB. Probabilistic modeling is performed to evaluate inherent uncertainties in performance and cost parameters on total construction costs and the levelized cost of electricity. Total overnight construction costs are expected to range between ~$300M - $400M for the 50 MW CSP plant and between ~$500M - $800M for the 100 MW plant. Annual operations and maintenance (O&M) costs are estimated together with potential offsets in electrical costs and CO 2 emissions. Other considerations such as interconnections, land use and permitting, funding options, and potential agreements and partnerships with Public Service Company of New Mexico (PNM), Western Area Power Administration (WAPA), and other entities are also discussed.

14 SOLAR ENERGY↗
DOE OSTI2022

Probabilistic Modeling of Climate Change Impacts on Renewable Energy and Storage Requirements for NM's Energy Transition Act (SAND Report)

This report provides a study of the potential impacts of climate change on intermittent renewable energy resources, battery storage, and resource adequacy in Public Service Company of New Mexico’s Integrated Resource Plan for 2020 – 2040. Climate change models and available data were first evaluated to determine uncertainty and potential changes in solar irradiance, temperature, and wind speed in NM in the coming decades. These changes were then implemented in solar and wind energy models to determine impacts on renewable energy resources in NM. Results for the extreme climate-change scenario show that the projected wind power may decrease by ~13% due to projected decreases in wind speed. Projected solar power may decrease by ~4% due to decreases in irradiance and increases in temperature in NM. Uncertainty in these climate-induced changes in wind and solar resources was accommodated in probabilistic models assuming uniform distributions in the annual reductions in solar and wind resources. Uncertainty in battery storage performance was also evaluated based on increased temperature, capacity fade, and degradation in round-trip efficiency. The hourly energy balance was determined throughout the year given uncertainties in the renewable energy resources and energy storage. The loss of load expectation (LOLE) was evaluated for the 2040 No New Combustion portfolio and found to increase from 0 days/year to a median value of ~2 days/year due to potential reductions in renewable energy resources and battery storage performance and capacity. A rank-regression analyses revealed that battery round-trip efficiency was the most significant parameter that impacted LOLE, followed by solar resource, wind resource, and battery fade. An increase in battery storage capacity to ~25,000 – 30,000 MWh from a baseline value of ~14,000 MWh was required to reduce the median value of LOLE to ~0.2 days/year with consideration of potential climate impacts and battery degradation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Gen 3 Particle Pilot Plant (G3P3) Life Cycle Management Plan (SAND report)

The National Solar Thermal Test Facility (NSTTF) at Sandia National Laboratories New Mexico (SNL/NM) developed this Life Cycle Management Plan (LCMP) to document its process for executing, monitoring, controlling and closing-out Phase 3 of the Gen 3 Particle Pilot Plant (G3P3). This plan serves as a resource for stakeholders who wish to be knowledgeable of project objectives and how they will be accomplished.

14 SOLAR ENERGY↗
DOE OSTI2023

Predicting Failure Using Deep Learning SAND Report

Accurate prediction of ductile failure is critical to Sandia’s NW mission, but the models are computationally heavy. The costs of including high-fidelity physics and mechanics that are germane to the failure mechanisms are often too burdensome for analysts either because of the person-hours it requires to input them or because of the additional computational time, or both. In an effort to deliver analysts a tool for representing these phenomena with minimal impact to their existing workflow, our project sought to develop modern data-driven methods that would add microstructural information to business-as-usual calculations and expedite failure predictions. The goal is a tool that receives as input a structural model with stress and strain fields, as well as a machine-learned model, and output predictions of structural response in time, including failure. As such, our project spent substantial time performing high-fidelity, three-dimensional experiments to elucidate materials mechanisms of void nucleation and evolution. We developed crystal-plasticity finite-element models from the experimental observations to enrich the findings with fields not readily measured. We developed engineering length-scale simulations of replicated test specimens to understand how the engineering fields evolve in the presence of fine-scale defects. Finally, we developed deep learning convolutional neural networks, and graph-based neural networks to encode the findings of the experiments and simulations and make forward predictions in time for structural performance. This project demonstrated the power of data-driven methods for model development, which have the potential to vastly increase both the accuracy and speed of failure predictions. These benefits and the methods necessary to develop them are highlighted in this report. However, many challenges remain to implementing these in real applications, and these are discussed along with potential methods for overcoming them.

97 MATHEMATICS AND COMPUTING↗