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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A divergence-free constrained magnetic field interpolation method for scattered data

An interpolation method to evaluate magnetic fields, given its unstructured and scattered magnetic data, is presented. The method is based on the reconstruction of the global magnetic field using a superposition of orthogonal functions. The coefficients of the expansion are obtained by minimizing a cost function defined as the L2 norm of the difference between the ground truth and the reconstructed magnetic field evaluated on the training data. The divergence-free condition is incorporated as a constraint in the cost function, allowing the method to achieve arbitrarily small errors in the magnetic field divergence. An exponential decay of the approximation error is observed and compared with the less favorable algebraic decay of local splines. Compared to local methods involving computationally expensive search algorithms, the proposed method exhibits a significant reduction of the computational complexity of the field evaluation, while maintaining a small error in the divergence even in the presence of magnetic islands and stochasticity. Finally, applications to the computation of Poincaré sections using data obtained from numerical solutions of the magnetohydrodynamic equations in toroidal geometry are presented and compared with local methods currently in use.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Future bioenergy expansion could alter carbon sequestration potential and exacerbate water stress in the United States

The maximum future projected bioenergy expansion potential, in scenarios limiting warming to 2°C or below, is equivalent to half of present-day croplands. We quantify the impacts of large-scale bioenergy expansion against re/afforestation, which remain elusive, using an integrated human-natural system modeling framework with explicit representation of perennial bioenergy crops. The end-of-century net carbon sequestration due to bioenergy deployment coupled with carbon capture and storage largely depends on fossil fuel displacement types, ranging from 11.4 to 31.2 PgC over the conterminous United States. These net carbon sequestration benefits are inclusive of a 10 PgC carbon release due to land use conversions and a 2.4 PgC loss of additional carbon sink capacity associated with bioenergy-driven deforestation. Moreover, nearly one-fourth of U.S. land areas will suffer severe water stress by 2100 due to either reduced availability or deteriorated quality. These broader impacts of bioenergy expansion should be weighed against the costs and benefits of re/afforestation-based strategies.

09 BIOMASS FUELS↗
NASA NTRS1981

Integral glass encapsulation for solar arrays

Electrostatic bonding technology, an encapsulation technique for terrestrial solar array was developed. The process produces full integral, hermetic bonds with no adhesives or pottants. Panels of six solar cells on a simple glass superstrate were produced. Electrostatic bonding for making the cell front contact was also developed. A metal mesh is trapped into contact with the cell front during the bonding process. Six cell panels using the bonded mesh as the only cell front contact were produced. The possibility of using lower cost glass, with a higher thermal expansion mismatch to silicon, by making lower temperature bonds is developed. However, this requires a planar surface cell.

Landis, G. A.↗
NASA NTRS1983

The economics of data acquisition computers for ST and MST radars

Some low cost options for data acquisition computers for ST (stratosphere, troposphere) and MST (mesosphere, stratosphere, troposphere) are presented. The particular equipment discussed reflects choices made by the University of Alaska group but of course many other options exist. The low cost microprocessor and array processor approach presented here has several advantages because of its modularity. An inexpensive system may be configured for a minimum performance ST radar, whereas a multiprocessor and/or a multiarray processor system may be used for a higher performance MST radar. This modularity is important for a network of radars because the initial cost is minimized while future upgrades will still be possible at minimal expense. This modularity also aids in lowering the cost of software development because system expansions should rquire little software changes. The functions of the radar computer will be to obtain Doppler spectra in near real time with some minor analysis such as vector wind determination.

Watkins, B. J.↗
NASA NTRS1992

ULTRA-SHARP solution of the Smith-Hutton problem

Highly convective scalar transport involving near-discontinuities and strong streamline curvature was addressed in a paper by Smith and Hutton in 1982, comparing several different convection schemes applied to a specially devised test problem. First order methods showed significant artificial diffusion, whereas higher order methods gave less smearing but had a tendency to overshoot and oscillate. Perhaps because unphysical oscillations are more obvious than unphysical smearing, the intervening period has seen a rise in popularity of low order artificially diffusive schemes, especially in the numerical heat transfer industry. The present paper describes an alternate strategy of using non-artificially diffusive high order methods, while maintaining strictly monotonic transitions through the use of simple flux limited constraints. Limited third order upwinding is usually found to be the most cost effective basic convection scheme. Tighter resolution of discontinuities can be obtained at little additional cost by using automatic adaptive stencil expansion to higher order in local regions, as needed.

Leonard, B. P.↗
NASA NTRS2021

Financial feasibility of water conservation in agriculture

Global water use for food production needs to be reduced to remain within planetary boundaries, yet the financial feasibility of crucial measures to reduce water use is poorly quantified. Here, we introduce a novel method to compare the costs of water conservation measures with the added value that reallocation of water savings might generate if used for expansion of irrigation. Based on detailed water accounting through the use of a high-resolution hydrology-crop model, we modify the traditional cost curve approach with an improved estimation of demand, increasing marginal cost per water conservation measure combination and add a correction to control for impacts on downstream water availability. We apply the method to three major river basins in the Indo-Gangetic plain (Indus, Ganges and Brahmaputra), a major global food producing region but increasingly water stressed. Our analysis shows that at basin level only about 10% (Brahmaputra) to just over 20% (Indus and Ganges) of potential water savings would be realised; the equilibrium price for water is too low to make the majority of water conservation measures cost effective. The associated expansion of irrigated area is moderate, about 7% in the Indus basin, 5% in the Ganges and negligible in the Brahmaputra, but farmers' gross profit increases more substantially, by 11%. Increasing the volumetric cost of irrigation water influences supply and demand in a similar way and has little influence on water reallocation. Controlling for the impact on return flows is important and more than halves the amount of water available for reallocation.

Geography / Land Utilization↗
DOE OSTI2021

Providencia Island High-Level Power System Capacity Expansion Analyses [Slides]

Results of a high level cost-benefit analysis using HOMER Pro software are presented for Providencia Island, Colombia. The analysis focuses on integrating solar photovoltaics (PV) and a battery energy storage system (BESS) into an existing diesel-only remote power system. The analysis uses fuel costs and discount rates provided by the stakeholders and NREL-derived capital cost estimates.

14 SOLAR ENERGY↗
DOE OSTI2024

Representative Period Selection for Robust Capacity Expansion Planning in Low-carbon Grids

With the increasing urgency to decarbonize power systems, while mitigating extreme events, capacity expansion models can play a vital role in reliably planning the expansion of power systems and facilitating the integration of renewable energy sources. Optimizing capacity expansion generally involves selecting surrogate representative days from forecasts of load and the generation profiles of variable renewable energy resources. To properly select those representative days, we propose a novel input-based approach in combination with the k-means clustering algorithm that utilize three unique operational inputs: load shedding, renewable curtailment, and transmission congestion. The proposed method allows for more robust and cost-effective capacity planning. The method is validated using a capacity expansion model and a production cost model based on California Independent System Operator (CAISO)'s decarbonization goals, and results in reduced costs and drastically lower load shedding.

Anderson, Osten P.↗
DOE OSTI2024

Representing Carbon Dioxide Transport and Storage Network Investments within Power System Planning Models

Carbon dioxide (CO 2 ) capture and storage (CCS) is frequently identified as a potential component to achieving a decarbonized power system at least cost; however, power system models frequently lack detailed representation of CO 2 transportation, injection, and storage (CTS) infrastructure. In this paper, we present a novel approach to explicitly represent CO 2 storage potential and CTS infrastructure costs and constraints within a continental-scale power system capacity expansion model. In addition, we evaluate the sensitivity of the results to assumptions about the future costs and performance of CTS components and carbon capture technologies. We find that the quantity of CO 2 captured within the power sector is relatively insensitive to the range of CTS costs explored, suggesting that the cost of CO 2 capture retrofits is a more important driver of CCS implementation than the costs of transportation and storage. Finally, we demonstrate that storage and injection costs account for the predominant share of total costs associated with CTS investment and operation, suggesting that pipeline infrastructure costs have limited influence on the competitiveness of CCS.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Joint Expansion Planning of Power and Water Distribution Networks

This research considers the joint expansion planning of power and water distribution networks, which are interdependent at various levels. We consider the dependency arising through the power consumption of pumps and develop models for integrating new components into existing networks. Then, we formulate the joint expansion planning as a Mixed Integer Nonlinear Program (MINLP). Applying this MINLP to a small-scale test network, we illustrate the advantages offered by joint expansion planning, such as increased flexibility and reduced costs and redundancy, over independently expanding power and water distribution networks.

expansion planning↗
DOE OSTI2023

Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications

To better understand the heat production, electricity generation performance, and economic viability of closed-loop geothermal systems in hot-dry rock, the Closed-Loop Geothermal Working Group -- a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed-loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and supercritical CO2) while varying seven continuous independent parameters of interest (mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying Python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the techno-economic analysis script are provided. This data submission will contain results from the Closed Loop Geothermal Working Group study that are within the public domain, including publications, simulation results, databases, and computer codes. GeoCLUSTER is a Python-based web application created using Dash, an open-source framework built on top of Flask that streamlines the building of data dashboards. GeoCLUSTER provides users with a collection of interactive methods for streamlining the exploration and visualization of an HDF5 dataset. The GeoCluster app and database are contained in the compressed file geocluster_vx.zip, where the "x" refers to the version number. For example, geocluster_v1.zip is Version 1 of the app. This zip file also contains installation instructions. **To use the GeoCLUSTER app in the cloud, click the link to "GeoCLUSTER on AWS" in the Resources section below. To use the GeoCLUSTER app locally, download the geocluster_vx.zip to your computer and uncompress this file. When uncompressed this file comprises two directories and the geocluster_installation.pdf file. The geo-data app contains the HDF5 database in condensed format, and the GeoCLUSTER directory contains the GeoCLUSTER app in the subdirectory dash_app, as app.py. The geocluster_installation.pdf file provides instructions on installing Python, the needed Python modules, and then executing the app.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Tabulated Database of Closed-Loop Geothermal Systems Performance for Cloud-Based Technical and Economic Modeling of Heat Production and Electricity Generation: Preprint

To better understand the heat production, electricity generation performance and economic viability of closed loop geothermal systems in hot-dry-rock, the Closed Loop Geothermal Group, a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and super-critical CO2) while varying seven continuous independent parameters of interest (i.e., mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an Organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the TEA (techno-economic analysis) script are provided.

co-axial↗
DOE OSTI2024

Techno-economic and life-cycle analysis of strategies for improving operability and biomass quality in catalytic fast pyrolysis of forest residues

Many of the challenges faced by the first commercial biorefineries were associated with feedstock handling, quality, and cost. Strategies are needed to enable further expansion of biorefineries and meet the growing demand for bio-based fuels and products. Here, we examine 2 key feedstock challenges and mitigation strategies in the context of a catalytic fast pyrolysis (CFP) biorefinery: (1) the operability of the feed system, which may be improved by modifying the minimum particle size fed to the reactor, and (2) the quality of the biomass, which may be improved by employing air classification to remove undesirable material and increase fuel yields. We conduct techno-economic analysis (TEA) and life-cycle analysis for these strategies, employing a discrete event simulation model for biomass preprocessing combined with a series of correlations developed from literature data and a rigorous CFP conversion model. Our results highlight the importance of balancing increased cost and material losses from preprocessing against improved operability and fuel yields. Economics and sustainability were optimized when operating at the lowest minimum particle size, emphasizing the importance of minimizing material losses while maintaining the operability of the process. Economically, additional costs and material losses from air classification could be acceptable due to improved biomass conversion, and an optimum air classification speed was identified; however, the fuel GHG emissions were minimized when air classification was not used. Valorizing material removed during preprocessing as a coproduct could improve economics and sustainability, decreasing the burden of material losses.

09 - BIOMASS FUELS↗
DOE OSTI2021

5.5 Hybrid Additively Manufactured Tooling for Large Composite Structures

This program sought to lower tooling costs for tightly toleranced, large composite aerostructures by using large format additive manufacturing (LFAM). LFAM tooling has the potential to lower tooling costs, but the large and unpredictable thermal expansion of polymer-based tooling did not previously allow for the production of large structures made with high performance resins requiring 350 deg F cures. Geometric tolerance issues and demolding concerns continued to arise. The proposed approach for this work was to print a thin shell via additive manufacturing that would be used as a scaffold for a conventional tooling prepreg. The prepreg would be laminated and cured onto both sides of the shell, creating a tool with a sandwich construction. The cured prepreg would then be machined and serve as the tooling surface. In addition to providing a clean, pit-free surface, the prepreg stiffness and low thermal expansion would physically restrain the AM shell and prevent it from expanding during thermal cycling, thus preventing any geometric mismatch between the nominal and actual part dimensions. A stair-step approach was taken to prove out this approach. Coupon level testing was done to ensure a good bond was possible between the AM shell and the tooling prepreg. These samples were also used to determine the amount of prepreg needed to achieve the desired coefficient of thermal expansion (CTE). The project team than progressed to a subscale tool measuring two feet in length. The geometry used was a C-section spar from Airbus’ Wing of Tomorrow program. A hybrid tool, using the AM shell and tooling prepreg, was made, and a composite part was fabricated with the tool. Dimensional scans of the tool and part indicated that the desired CTE was achieved with the tool. A second tooling approach was taken to reduce risk. In this approach, a subscale tool of the same geometry as previously mentioned was created, but the tool was entirely constructed of the tooling prepreg. AM was used to print a “master” that was then used to fabricate the tool by creating a splash off of the master using tooling prepreg. The innovation was that the master was not machined, but rather, was used right off the printer after a small amount of surface preparation. Removing this machining step was thought to make this approach economically viable when compared to conventional master fabrication. As before, the tool was used to fabricate a part and tested for dimensional accuracy. For the conclusion of the program, a ten-foot tool was created using the hybrid tool approach. The geometry also came from the Airbus C-section spar previously mentioned. Some difficulty arose in accurately predicting the geometry of the tool after laminating the tooling prepreg, resulting in multiple material additions and a tool geometry change. A part was fabricated in an autoclave using the tool. A cost savings of almost 50% was achieved on the subscale tool in both the hybrid and master-style tool, but the savings dropped considerably as the tool length increased in the full-scale tool. Given the less than expected cost savings and added complexity of the tool construction, it is suggested that the master-style tool is best for immediate commercialization for larger tools (although it may be appropriate for smaller, table-top size tools). Since its construction is very similar to conventionally made composite tooling, there already exists a broad supply chain for building the tool, and project partner Additive Engineering Solutions (AES) is well acquainted with the design and build of the AM master needed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

cerf: A Python package to evaluate the feasibility and costs of power plant siting for alternative futures

Long-term electric power sector planning and capacity expansion is a key area of interest to stakeholders across a wide range of organizations because it helps in making informed decisions about investments in infrastructure within the context of potential future vulnerabilities under various natural and human stressors. Future power plant siting costs will depend on a number of factors including the characteristics of the electricity capacity expansion and electricity demand (e.g., fuel mix of future electric power capacity, and the magnitude and geographic distribution of electricity demand growth) as well as the geographic location of power plants. Electricity technology capacity expansion plans modeled to represent alternate future conditions meeting a set of scenario assumptions are traditionally compared against historical trends which may not be consistent with current and future conditions. We present the `cerf` Python package (a.k.a., the Capacity Expansion Regional Feasibility model) which helps evaluate the feasibility and structure of future, scenario-driven electricity capacity expansion plans by siting power plants in areas that have been deemed the least cost option while considering dynamic future conditions. We can use `cerf` to gain insight to research topics such as: 1) under what conditions future projected electricity expansion plans from models such as GCAM-USA are possible to achieve, 2) where and which on-the-ground barriers to siting (e.g., protected areas, cooling water availability) may influence our ability to achieve certain expansions, and 3) how electricity infrastructure build-outs and value may evolve into the future when considering locational marginal pricing (LMP) based on the supply and demand of electricity from a grid operations model.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1979

Evaluation of cellular glasses for solar mirror panel applications

An analytic technique was developed to compare the structural and environmental performance of various materials considered for backing of second surface glass solar mirrors. Cellular glass was determined to be a prime candidate due to its low cost, high stiffness-to-weight ratio, thermal expansion match to mirror glass, evident minimal environmental impact and chemical and dimensional stability under conditions of use. The current state of the art and anticipated developments in cellular glass technology are discussed; material properties are correlated to design requirements. A mathematical model is presented which suggests a design approach which allows minimization of life cost; and, a mechanical and environmental testing program is outlined, designed to provide a material property basis for development of cellular glass hardware, together with methodology for collecting lifetime predictive data. Preliminary material property data from measurements are given. Microstructure of several cellular materials is shown, and sensitivity of cellular glass to freeze-thaw degradation and to slow crack growth is discussed. The effect of surface coating is addressed.

Giovan, M.↗
DOE OSTI2023

Uncertainty-aware molecular dynamics from Bayesian active learning for phase transformations and thermal transport in SiC

Abstract Machine learning interatomic force fields are promising for combining high computational efficiency and accuracy in modeling quantum interactions and simulating atomistic dynamics. Active learning methods have been recently developed to train force fields efficiently and automatically. Among them, Bayesian active learning utilizes principled uncertainty quantification to make data acquisition decisions. In this work, we present a general Bayesian active learning workflow, where the force field is constructed from a sparse Gaussian process regression model based on atomic cluster expansion descriptors. To circumvent the high computational cost of the sparse Gaussian process uncertainty calculation, we formulate a high-performance approximate mapping of the uncertainty and demonstrate a speedup of several orders of magnitude. We demonstrate the autonomous active learning workflow by training a Bayesian force field model for silicon carbide (SiC) polymorphs in only a few days of computer time and show that pressure-induced phase transformations are accurately captured. The resulting model exhibits close agreement with both ab initio calculations and experimental measurements, and outperforms existing empirical models on vibrational and thermal properties. The active learning workflow readily generalizes to a wide range of material systems and accelerates their computational understanding.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Innovative rail transport of a supersized land-based wind turbine blade

Wind turbine blade logistic providers are being challenged with escalating costs and routing complexities as one-piece blade approach lengths of 75 m in various regions of the U.S. land-based market. New lower cost solutions are needed to enable further reductions in the levelized cost of energy (LCOE) and continued market expansion. In this paper, a novel method of using existing U.S. rail infrastructure to deploy 100-m, one-piece blades to U.S. land-based wind sites is numerically investigated. The study removes the constraint that blades must be kept rigid during transport, and it allows bending to keep blades within a clearance profile while navigating horizontal and vertical curvatures. Novel system optimization and blade design processes consider blade structural constraints and rail logistic constraints in parallel to develop a highly flexible, rail-transportable blade. Results indicate maximum deployment potential in the Interior region of the United States and limited deployment potential in other regions. The study concludes that innovative rail transportation solutions combined with advanced rotor technologies can provide a feasible alternative to segmentation and support continued LCOE reductions in the U.S. land-based wind energy market.

17 WIND ENERGY↗