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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Architectural and Operational Considerations Emerging from Hybrid RF-Optical Network Loading Simulations

We have the technical capability to model hybrid deep-space RF and Optical communications networks, but we have little guidance on how the missions and ground architectures will be designed and operated. We exposed several issues that must be resolved before an optimal solution can be reached. With future studies, we may be able to determine solutions to these issues, and perform more precise loading performance analyses to arrive at the most optimal RF and optical ground assets combinations for meeting the projected future demand. The results will then help inform NASA as it plans for infrastructure development to prepare for human/robotic missions in the coming decades.

Chen, Yijiang↗
NASA NTRS2019

Completeness Index for Earthquake-Induced Landslide Inventories

Understanding the global relation between Earthquake-Induced Landslides (EQILs) and the factors contributing to their initiation is still an open topic within the geomorphological community. Accessing EQIL inventories and analyzing them concerning their potential causes is the key to explore such relation. However, each of the existing EQIL inventories has its level of completeness and associated uncertainty which makes any unified relationship which is challenging to obtain. So far, the completeness of EQIL inventories has never been clearly defined. As a result, it has never been accounted for in global EQIL predictive models. In this technical note, we propose a simple definition for the completeness of EQIL inventories. We analyze 30 digital EQIL for 21 earthquakes and develop a semi-quantitative method to estimate the completeness level, which we refer to as Completeness Index (CI). The CI results from a combination of topographic factors, ground shaking parameters, and a measure derived from landslide size statistics. The proposed CI consists of Low, Moderate, and High completeness classes which can be used to evaluate any landslide inventory. We made the whole procedure to compute the CI accessible in an ArcGIS toolbox together with a test dataset.

Hakan Tanyas↗
DOE OSTI2018

Sequential Design of Experiments to Maximize Learning from Carbon Capture Pilot Plant Testing

Pilot plant test campaigns can be expensive and time-consuming. Therefore, it is of interest to maximize the amount of learning and the efficiency of the test campaign given the limited number of experiments that can be conducted. This work investigates the use of sequential design of experiments (SDOE) to overcome these challenges by demonstrating its usefulness for a recent solvent-based CO2 capture plant test campaign. Unlike traditional design of experiments methods, SDOE regularly uses information from ongoing experiments to determine the optimum locations in the design space for subsequent runs within the same experiment. However, there are challenges that need to be addressed, including reducing the high computational burden to efficiently update the model, and the need to incorporate the methodology into a computational tool. We address these challenges by applying SDOE in combination with a software tool, the Framework for Optimization, Quantification of Uncertainty and Surrogates (FOQUS) (Miller et al., 2014a, 2016, 2017). The results of applying SDOE on a pilot plant test campaign for CO2 capture suggests that relative to traditional design of experiments methods, SDOE can more effectively reduce the uncertainty of the model, thus decreasing technical risk. Future work includes integrating SDOE into FOQUS and using SDOE to support additional large-scale pilot plant test campaigns.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

BETO 2021 Peer Review - Algal Biofuels Techno-Economic Analysis 1.3.5.200

The objective of NREL's Algal Biofuel Techno-Economic Analysis (TEA) project is to provide process modeling and analysis to support Algae Program activities, utilizing TEA models to relate key process parameters with overall economics for cultivation, processing, and conversion of algal biomass to fuels and coproducts. By quantifying economic implications of key process metrics, TEA models highlight the technical requirements to achieve future program cost goals as well as enabling a means to track progress towards these goals. This project provides high impact and relevance though generation of critical cost data tied to funded research, with our analyses subsequently exercised by BETO to guide program plans, FOA priorities, and other directives. This includes costs for both algal biomass production and downstream conversion, most notably to support BETO's fuel cost targets below $2.5/GGE by 2030. To mitigate a key risk/challenge in constraining our work to academic analyses rooted only in future projections, our work also seeks to provide near-term value to today's algae industry through frequent industry engagement, while maintaining close ties with other BETO collaborators. This project has made numerous accomplishments since the 2019 peer review, including a continued focus on opportunities for value-added products, with related analyses for new pathway opportunities to achieve BETO cost goals and notable State-of-Technology (SOT) improvements over prior cost benchmarks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

NuScale Systems Engineering Program Overview and Status

NuScale systems engineering program overview, including technical data management and model-based engineering, product structures, architecture views, and model-based systems engineering. Includes a discussion on technical risk and opportunity management and technical readiness levels, as well as risk-informed performance-based principles and methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Hypothesis testing via AI: Generating physically interpretable models of scientific data with machine learning (Full Technical Report)

Deep learning has demonstrated an exceptional ability to solve complex tasks (an engineering success); however, it has done so at the expense of the ability to generate new knowledge (a scientific failure). We propose an alternative framework—entitled Deep Symbolic Regression (DSR)—in which artificial neural networks (NNs) rapidly generate hypotheses about physical relationships among inputs. This framework bypasses the need to interpret an NN altogether, while still leveraging the representational power of deep learning. The resulting models are tractable mathematical expressions, which are inherently and readily human interpretable and can provide insights into underlying physical phenomena. Further, we fold this methodology into the scientific process by allowing the scientist to directly integrate a priori knowledge and beliefs to accelerate learning. We demonstrate this methodology on symbolic regression—the problem of rediscovering underlying expressions describing a dataset—and achieve state-of-the-art performance across a wide variety of symbolic regression problems. Further, we generalize our DSR framework to apply to the more general class of symbolic optimization problems, in which one seeks to optimize a sequence of symbols or “tokens” under a black-box reward function. Examples of other symbolic optimization problems include neural architecture search and computational antibody design. Our generalized tool, Deep Symbolic Optimization (DSO), has been demonstrated on the task of learning symbolic control policies for reinforcement learning environments, and has been adopted as an enabling capability for computational antibody design.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Decision-Model Supported Algal Cultivation Process Enhancement (DMSACPE) (Final Technical Report)

This project was proposed in response to the FY19 Bioenergy Technologies Office Multi-Topic Funding Opportunity Announcement DE-FOA-0002029, Area of Interest Subtopic 1 (AOI1): Cultivation Intensification Processes for Algae. The main challenge identified by the FOA was “in translating results between laboratory research systems and larger-scale outdoor (or mass culture) systems. These difficulties limit reliable experimental durations, adequate and representative experimental volumes of material, and results that can be reproduced reliably. By overcoming the challenge in translating results between laboratory and mass cultures, the objective of AOI 1 is to increase the harvest yield, robustness, and quality of algae cultivation for biofuels and bioproducts”. This report marks the final technical deliverable of this project and reviews all the major findings of the research program.

09 BIOMASS FUELS↗
NASA NTRS2024

Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications

This technical report presents Prithvi-EO-2.0, a new geospatial foundation model that offers significant improvements over its predecessor, Prithvi-EO-1.0. Trained on 4.2M global time series samples from NASA’s Harmonized Landsat and Sentinel-2 data archive at 30m resolution, the new 300M and 600M parameter models incorporate temporal and location embeddings for enhanced performance across various geospatial tasks. Through extensive benchmarking with GEOBench, the 600M version outperforms the previous Prithvi-EO model by 8% across a range of tasks. It also outperforms six other geospatial foundation models when benchmarked on remote sensing tasks from different domains and resolutions (i.e. from 0.1m to 15m). The results demonstrate the versatility of the model in both classical earth observation and high-resolution applications. Early involvement of end-users and subject matter experts (SMEs) are among the key factors that contributed to the project’s success. In particular, SME involvement allowed for constant feedback on model and dataset design, as well as successful customization for diverse SME-led applications in disaster response, land use and crop mapping, and ecosystem dynamics monitoring. Prithvi-EO-2.0 is available on Hugging Face and IBM terratorch, with additional resources on GitHub. The project exemplifies the Trusted Open Science approach embraced by all involved organizations.

Daniela Szwarcman↗
DOE OSTI2020

Adiabatic Cooling System Spreadsheet Model for sCO 2

The attached cost and performance spreadsheet model is for an adiabatic cooling system, one of four cooling system models developed for use in optimizing indirectly-heated supercritical CO 2 (sCO 2 ) power cycles. Running the model requires that the user has REFPROP version 9 or below installed, as well as the Microsoft Excel REFPROP Add-In. Upon opening, use Excel’s Edit Links feature to link to the user’s installed REFPROP.xla or REFPROP.xlam file. For the spreadsheet model compatible with REFPROP version 10 and above, contact Nathan Weiland at nathan.weiland@netl.doe.gov. Technical documentation for the model can be found here: https://www.netl.doe.gov/energy-analysis/details?id=3199.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Direct Dry Cooling System Spreadsheet Model for sCO 2

The attached cost and performance spreadsheet model is for a direct dry cooling system, one of four cooling system models developed for use in optimizing indirectly-heated supercritical CO 2 (sCO 2 ) power cycles. Running the model requires that the user has REFPROP version 9 or below installed, as well as the Microsoft Excel REFPROP Add-In. Upon opening, use Excel’s Edit Links feature to link to the user’s installed REFPROP.xla or REFPROP.xlam file. For the spreadsheet model compatible with REFPROP version 10 and above, contact Nathan Weiland at nathan.weiland@netl.doe.gov. Technical documentation for the model can be found here: https://www.netl.doe.gov/energy-analysis/details?id=3199.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Indirect Dry Cooling System Spreadsheet Model for sCO2

The attached cost and performance spreadsheet model is for an indirect dry cooling system, one of four cooling system models developed for use in optimizing indirectly-heated supercritical CO2 (sCO2) power cycles. Running the model requires that the user has REFPROP version 9 or below installed, as well as the Microsoft Excel REFPROP Add-In. Upon opening, use Excel’s Edit Links feature to link to the user’s installed REFPROP.xla or REFPROP.xlam file. For the spreadsheet model compatible with REFPROP version 10 and above, contact Nathan Weiland at nathan.weiland@netl.doe.gov. Technical documentation for the model can be found here: https://www.netl.doe.gov/energy-analysis/details?id=3199.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Wet Cooling Tower Cooling System Spreadsheet Model for sCO2

The attached cost and performance spreadsheet model is for a wet cooling tower system, one of four cooling system models developed for use in optimizing indirectly-heated supercritical CO2 (sCO2) power cycles. Running the model requires that the user has REFPROP version 9 or below installed, as well as the Microsoft Excel REFPROP Add-In. Upon opening, use Excel’s Edit Links feature to link to the user’s installed REFPROP.xla or REFPROP.xlam file. For the spreadsheet model compatible with REFPROP version 10 and above, contact Nathan Weiland at nathan.weiland@netl.doe.gov. Technical documentation for the model can be found here: https://www.netl.doe.gov/energy-analysis/details?id=3199.

30 DIRECT ENERGY CONVERSION↗
NASA NTRS2007

Numerical Modeling of Propellant Boiloff in Cryogenic Storage Tank

This Technical Memorandum (TM) describes the thermal modeling effort undertaken at Marshall Space Flight Center to support the Cryogenic Test Laboratory at Kennedy Space Center (KSC) for a study of insulation materials for cryogenic tanks in order to reduce propellant boiloff during long-term storage. The Generalized Fluid System Simulation program has been used to model boiloff in 1,000-L demonstration tanks built for testing the thermal performance of glass bubbles and perlite insulation. Numerical predictions of boiloff rate and ullage temperature have been compared with the measured data from the testing of demonstration tanks. A satisfactory comparison between measured and predicted data has been observed for both liquid nitrogen and hydrogen tests. Based on the experience gained with the modeling of the demonstration tanks, a numerical model of the liquid hydrogen storage tank at launch complex 39 at KSC was built. The predicted boiloff rate of hydrogen has been found to be in good agreement with observed field data. This TM describes three different models that have been developed during this period of study (March 2005 to June 2006), comparisons with test data, and results of parametric studies.

Majumdar, A. K.↗
DOE OSTI2026

Technoeconomic Opportunity Analysis for Local Power Generation in Falls City, Nebraska

Falls City is a small community in Nebraska interested in understanding how energy from local energy systems could support the community's economic development planning. To address the current community needs and address the future energy demand technical assistance conducted through the Communities Local Energy Action Program (Communities LEAP) assessed the technical and economic opportunities of adding energy technologies to Falls City's municipally owned and operated electric utility system. The modeling performed considered the technical and economic feasibility of technologies using the System Advisor Model (SAM). The modeling explored three technology configurations using multiple years of historical weather and wholesale cost data (2015-2022 & a typical meteorological year), and two different wholesale escalation rates (0.3% and 2.5%). Wholesale energy prices were based on the Southwest Power Pool's (SPP) real-time energy market and the annual escalation rates of these rates based on historical SPP wholesale and national retail electricity price trends. Results from the modeling showed that at current CAPEX costs and SPP wholesale electricity costs no technology combination averaged across the scenarios run provide a positive net present value (NPV). External financial support, changes in market conditions, and additional revenue streams would help create more economically favorable projects. As conditions change re-evaluation may be necessary.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Functional characterization and regulatory modeling of lignocellulose deconstruction in the saprophytic bacterium Cellvibrio japonicus (Final Technical Report)

The goal of this project was to establish a fundamental systems-level model of lignocellulose deconstruction by saprophytic soil bacteria while simultaneously identifying and characterizing novel enzymes that can be used for applied bioenergy technologies. This project was significant because it elevated our mechanistic and regulatory understanding of bacterial plant biomass degradation and led to technologies to enable bottlenecks in biofuel production R&D. Furthermore, the completed work was novel because it integrated in vivo, in vitro, and in silico approaches with bioenergy-relevant substrates. We identified the required enzymes for lignocellulose degradation and mechanisms of regulation through a combination of transcriptomic profiling (RNAseq), enzymatic analysis, the functional characterization of mutants, and modeling of the regulatory networks used to detect and degrade lignocellulose. This project employed the lignocellulose-degrading bacterium Cellvibrio japonicus to dissect the functional properties and underlying regulatory networks saprophytic bacteria use to depolymerize and utilize lignocellulose. There were four Objectives to this project, the specific metrics of which are summarized in this report.

09 BIOMASS FUELS↗
DOE OSTI2018

Final Report for Project 13-4791: New Mechanistic Models of Creep-Fatigue Crack Growth Interactions for Advanced High Temperature Reactor Components

This project developed and validated a novel, multi-scale, mechanism-based model to quantitatively predict creep-fatigue crack growth and failure for Ni-based Alloy 617 at 800°C. Alloy 617 is a target material for intermediate heat exchangers in Generation IV very high temperature reactor designs, and it is envisioned that this model will aid in the design of safe, long lasting nuclear power plants. The technical effectiveness of the model was shown by demonstrating that experimentally observed crack growth rates can be predicted under both steady state and overload crack growth conditions. Feasibility was considered by incorporating our model into a commercially available finite element method code, ABAQUS, that is commonly used by design engineers. While the focus of the project was specifically on an alloy targeted for Generation IV nuclear reactors, the benefits to the public are expected to be wide reaching. Indeed, creep-fatigue failure is a design consideration for a wide range of high temperature mechanical systems that rely on Ni-based alloys, including industrial gas power turbines, advanced ultra-super critical steam turbines, and aerospace turbine engines. It is envisioned that this new model can be adapted to a wide range of engineering applications.

36 MATERIALS SCIENCE↗
NASA NTRS1996

Numerical Modeling of the Global Atmosphere

Under this grant, we continued development and evaluation of the updraft downdraft model for cumulus parameterization. The model includes the mass, rainwater and vertical momentum budget equations for both updrafts and downdrafts. The rainwater generated in an updraft falls partly inside and partly outside the updraft. Two types of stationary solutions are identified for the coupled rainwater budget and vertical momentum equations: (1) solutions for small tilting angles, which are unstable; (2) solutions for large tilting angles, which are stable. In practical applications, we select the smallest stable tilting angle as an optimum value. The model has been incorporated into the Arakawa-Schubert (A-S) cumulus parameterization. The results of semi-prognostic and single-column prognostic tests of the revised A-S parameterization show drastic improvement in predicting the humidity field. Cheng and Arakawa presents the rationale and basic design of the updraft-downdraft model, together with these test results. Cheng and Arakawa, on the other hand gives technical details of the model as implemented in current version of the UCLA GCM.

Arakawa, Akio↗
DOE OSTI2025

Techno-Economic Viability of Flexible Dispatch of Unconventional Geothermal Systems

Flexible geothermal operations could boost project returns through the allocation of improved power purchase agreements and/or exploitation of power price arbitrage opportunities. In this study, we investigated the techno-economic feasibility of variable flow rate control and time-of-day pricing in closed-loop geothermal systems. We considered U-shaped multilateral system configurations and modeled a variety of technical system parameters. These designs were simulated using a slender-body theory (SBT) model for transient heat transfer and fluid flow. This subsurface model was integrated into the flexible geothermal economic model (FGEM) tool to evaluate the overall flexible geothermal system techno-economics. Future hourly ambient temperature conditions were based on the Sup3rCC dataset. Published datasets were used for future hourly wholesale electricity prices. We analyzed four operating strategies: 1) baseload operation, 2) seasonal dispatch (high flow rate during summer and nominal flow rate during the rest of the year), 3) net generation maximization by varying flow rate to maximize net power output, and 4) revenue maximization by varying flow rate to maximize revenue. We ran all four scenarios for a multiloop configuration with 12 lateral passes, 7-km vertical depth and 87-km total drilling length. Furthermore, we assumed a 60 degrees C/km geothermal gradient and ambient temperature and wholesale electricity prices for New Mexico as a typical state location. The nominal flow rate was set to 80 kg/s. When considering drilling costs of $1,000/m and a discount rate of 7%, the generation maximization scenario resulted in the lowest levelized cost of electricity (LCOE) of ~$150/MWh. When considering project return on investment (ROI), defined as lifetime net income divided by upfront capital costs, all flexible operation scenarios performed better than the base case scenario. The highest ROI of 80% was obtained with the revenue maximization scenario. With drilling costs of $200/m and a discount rate of 5%, the generation maximization scenario resulted in LCOE of $49/MWh.

flexible geothermal↗