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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Prospects for silvicultural enhancement of fire resistance in mesic westside forests of the Pacific Northwest

Increasing wildfire activity in mesic, temperate Pacific Northwest forests west of the Cascade Range crest has stimulated interest in understanding whether alternative forest management practices could reduce risk of stand-replacing fire. To explore how management can enhance fire resistance in these forests and assess tradeoffs among resistance enhancement, carbon sequestration and storage, and economic returns, we conducted 40-year simulations of stand development with BioSum, a framework for conducting landscape analysis with the Forest Vegetation Simulator (FVS), utilizing a statistically representative and spatially balanced sample of Forest Inventory and Analysis (FIA) plots. Simulation outcomes under business-as-usual silviculture were contrasted with fire-aware silviculture, and treatment optimization logic was developed and applied to represent landscape-scale outcomes under business-as-usual and fire-focused management scenarios. Simulation results indicate that fire-aware prescriptions and fire-focused management can meaningfully enhance stand- and landscape-scale fire resistance of westside forests under less than extreme fire weather, but at the cost of lower economic returns and reduced net carbon storage and sequestration over the 40-year analysis window. Shifting from business-as-usual regeneration harvests with short rotations to fire-aware, episodic selection harvest improved fire resistance the most, especially in young privately-owned forests, and with only modest tradeoffs in carbon and economic outcomes. While fire-aware treatments generally reduced net present value from forest operations over business-as-usual, most treatments still generated positive net present value and could be implemented without subsidy. Fire-aware prescriptions that removed and utilized non-merchantable harvest residues instead of burning them, via either pile or broadcast burning, partially mitigated carbon emissions associated with fire-aware treatments, with about the same improvement in fire resistance. Given the currently limited institutional and financial capacity to implement fire resistance enhancing treatments at scale, the insights from this analysis may aid managers seeking to elevate fire resistance to prioritize where and how to manage.

Science & Technology - Other Topics↗
NASA NTRS1980

The application of LANDSAT remote sensing technology to natural resources management. Section 1: Introduction to VICAR - Image classification module. Section 2: Forest resource assessment of Humboldt County.

A teaching module on image classification procedures using the VICAR computer software package was developed to optimize the training benefits for users of the VICAR programs. The field test of the module is discussed. An intensive forest land inventory strategy was developed for Humboldt County. The results indicate that LANDSAT data can be computer classified to yield site specific forest resource information with high accuracy (82%). The "Douglas-fir 80%" category was found to cover approximately 21% of the county and "Mixed Conifer 80%" covering about 13%. The "Redwood 80%" resource category, which represented dense old growth trees as well as large second growth, comprised 4.0% of the total vegetation mosaic. Furthermore, the "Brush" and "Brush-Regeneration" categories were found to be a significant part of the vegetative community, with area estimates of 9.4 and 10.0%.

Fox, L., III↗
NASA NTRS2010

An Optimization Model for Scheduling Problems with Two-Dimensional Spatial Resource Constraint

Traditional scheduling problems involve determining temporal assignments for a set of jobs in order to optimize some objective. Some scheduling problems also require the use of limited resources, which adds another dimension of complexity. In this paper we introduce a spatial resource-constrained scheduling problem that can arise in assembly, warehousing, cross-docking, inventory management, and other areas of logistics and supply chain management. This scheduling problem involves a twodimensional rectangular area as a limited resource. Each job, in addition to having temporal requirements, has a width and a height and utilizes a certain amount of space inside the area. We propose an optimization model for scheduling the jobs while respecting all temporal and spatial constraints.

Garcia, Christopher↗
NASA NTRS1986

On the design of classifiers for crop inventories

Crop proportion estimators that use classifications of satellite data to correct, in an additive way, a given estimate acquired from ground observations are discussed. A linear version of these estimators is optimal, in terms of minimum variance, when the regression of the ground observations onto the satellite observations in linear. When this regression is not linear, but the reverse regression (satellite observations onto ground observations) is linear, the estimator is suboptimal but still has certain appealing variance properties. In this paper expressions are derived for those regressions which relate the intercepts and slopes to conditional classification probabilities. These expressions are then used to discuss the question of classifier designs that can lead to low-variance crop proportion estimates. Variance expressions for these estimates in terms of classifier omission and commission errors are also derived.

Heydorn, R. P.↗
DOE OSTI2024

Estimating the influence of field inventory sampling intensity on forest landscape model performance for determining high-severity wildfire risk

Abstract Historically, fire has been essential in Southwestern US forests. However, a century of fire-exclusion and changing climate created forests which are more susceptible to uncharacteristically severe wildfires. Forest managers use a combination of thinning and prescribed burning to reduce forest density to help mitigate the risk of high-severity fires. These treatments are laborious and expensive, therefore optimizing their impact is crucial. Landscape simulation models can be useful in identifying high risk areas and assessing treatment effects, but uncertainties in these models can limit their utility in decision making. In this study we examined underlying uncertainties in the initial vegetation layer by leveraging a previous study from the Santa Fe fireshed and using new inventory plots from 111 stands to interpolate the initial forest conditions. We found that more inventory plots resulted in a different geographic distribution and wider range of the modelled biomass. This changed the location of areas with high probability of high-severity fires, shifting the optimal location for management. The increased range of biomass variability from using a larger number of plots to interpolate the initial vegetation layer also influenced ecosystem carbon dynamics, resulting in simulated forest conditions that had higher rates of carbon uptake. We conclude that the initial forest layer significantly affects fire and carbon dynamics and is dependent on both number of plots, and sufficient representation of the range of forest types and biomass density.

Science & Technology - Other Topics↗
DOE OSTI2023

A Conceptual Design of the Reactor Cavity Cooling System for the Horizontal Compact High Temperature Gas Reactor (HC-HTGR)

Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multi-disciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR in 3 years and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. This report documents the design study to derive a conceptual design study of the RCCS for the HC-HTGR. It includes the identification of the functions and requirements of the HC-HTGR RCCS, design analyses including high-level design consideration and the calculations for optimizing design space of the system with supporting component-level analysis to inform the material selection and performance of the water panel, the description of the conceptual design of the HC-HTGR RCCS derived based on the analyses results, and performance evaluation of the conceptual RCCS for the HC-HTGR. A detailed concept of the RCCS has been identified and high-level system requirements has been developed for the HC-HTGR. Design space focusing on the natural circulation loop portion of the RCCS has been investigated to optimize the system performance. The initial baseline dimensions were firstly derived based on the scoping calculations. A component level design analysis was conducted for the water panel to inform the material selection and to assess its conduction performance. A preliminary system-level performance analysis was performed for the 1/8th of the compartment of the initial baseline design of the RCCS using RELAP5-3D. To improve the system thermal performance, the RCCS design has been updated by exploring various design options by design parametric analyses. Based on the results, the conceptual design of the RCCS for the HC-HTGR has been derived, which satisfies the target performance of ~1 MWt at the elevated vessel wall temperature conditions. Transient simulations were conducted for the conceptual RCCS design for the HC-HTGR under various operation modes and heat load conditions using RELAP5-3D. The system dynamics in different operating states was investigated and the system performance under transients of interest was evaluated. The results demonstrated the overall system feasibility that the RCCS design maintains structures temperatures lower than maximum allowable temperature with sufficient system inventory without any active heat removal in the design process with certain transients addressed. The HC-HTGR RCCS will have additional design updates of subsystems or optimization of the system components during the preliminary and final design phases. Since the entire plant has not been integrated yet, this delivered conceptual design is subject to changes for integration, that require additional conceptual design activities and Quality and Assurance implementation (Q&A). The performance assessment of the RCCS for the HC-HTGR will be then revisited and optimized to finalize the system design, and the RCCS integrated primary system analysis will be utilized to simulate selective accident scenarios of interest where efforts are currently undergoing in the project.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1980

Research in the application of spectral data to crop identification and assessment, volume 2

The development of spectrometry crop development stage models is discussed with emphasis on models for corn and soybeans. One photothermal and four thermal meteorological models are evaluated. Spectral data were investigated as a source of information for crop yield models. Intercepted solar radiation and soil productivity are identified as factors related to yield which can be estimated from spectral data. Several techniques for machine classification of remotely sensed data for crop inventory were evaluated. Early season estimation, training procedures, the relationship of scene characteristics to classification performance, and full frame classification methods were studied. The optimal level for combining area and yield estimates of corn and soybeans is assessed utilizing current technology: digital analysis of LANDSAT MSS data on sample segments to provide area estimates and regression models to provide yield estimates.

Daughtry, C. S. T.↗
NASA NTRSDate not supplied

Slosh-Induced Ullage Collapse Validation by Computational Fluid Dynamics and Application to In-space Propellant Dynamics

Ullage collapse predictions made using Computational Fluid Dynamics (CFD) were validated then made for an in-space cryogenic propellant unsettling application. Ullage collapse is the decrease in propellant tank pressure due to cooling of the ullage gas, which can be significant for cryogenic propulsion systems. Vehicles may be developed that are robust to temperature and pressure changes caused by heat leaks, e.g., propellant tanks with high maximum operation pressures, technologies yielding active thermal conditioning, and systems with ample pressurant for conditioning. These methods are robust because additional mass, cost, and complexity are used to address cryogenic fluid management (CFM). As vehicles are optimized for increased payload capacity, tracking of events such as ullage collapse and self-pressurization in tanks will become increasingly important for propellant inventory calculations. Some ullage collapse events can be studied through ground experimentation, but propellant unsettling in and around in-space coast mission phases must be studied in the absence of an acceleration field. Computational Fluid Dynamics is a powerful tool to address this need, enabling prediction of complex physics prior to flight. Validation of the chosen CFD tool and modeling methodology was done using data from a previously conducted subscale slosh-induced ullage collapse ground test performed in part by the Japan Aerospace Exploration Agency (JAXA). A small tank was partially filled with liquid nitrogen and pressurized with gaseous nitrogen at various temperatures. The tank was oscillated laterally to induce high amplitude slosh dynamics resulting in wave breakup. Successful qualitative validation of slosh wave dynamics and quantitative validation of ullage collapse promoted confidence in extending ullage collapse predictions to a flight application. Mechanisms of ullage collapse caused by main engine cutoff while in-space were identified. Both slosh dynamics leading to engine shutdown and body dynamics following shutdown were shown to contribute to propellant unsettling and ullage collapse.

J M Brodnick↗
NASA NTRS1992

The Automated Logistics Element Planning System (ALEPS)

ALEPS, which is being developed to provide the SSF program with a computer system to automate logistics resupply/return cargo load planning and verification, is presented. ALEPS will make it possible to simultaneously optimize both the resupply flight load plan and the return flight reload plan for any of the logistics carriers. In the verification mode ALEPS will support the carrier's flight readiness reviews and control proper execution of the approved plans. It will also support the SSF inventory management system by providing electronic block updates to the inventory database on the cargo arriving at or departing the station aboard a logistics carrier. A prototype drawer packing algorithm is described which is capable of generating solutions for 3D packing of cargo items into a logistics carrier storage accommodation. It is concluded that ALEPS will provide the capability to generate and modify optimized loading plans for the logistics elements fleet.

Schwaab, Douglas G.↗
DOE OSTI2023

Battery state-of-health diagnostics during fast cycling using physics-informed deep-learning

Rapid, in-situ Li-ion battery state-of-health (SOH) quantification is challenging. Li-ion battery aging can vary significantly with chemistry, operating conditions, cycling demands, electrode design, and operation history. As a cell ages, optimal and safe operating conditions need to be adapted to account for battery degradation by tracking critical aging modes such as loss-of-lithium-inventory (LLI), loss-of-active-material (LAM) in either electrode, and/or impedance rise. This manuscript describes a framework for identifying battery aging modes in-operando using fast-rate voltage charge/discharge responses. The framework uses a physically based Li-ion battery model to produce synthetic high-rate responses at aged states. The aging model is calibrated against experimental data from cells with different electrode loadings and cycled under a variety of fast-charging conditions (1 h, 15 min, 10 min, and 7 min charging). The synthetically generated high-rate responses at aged states are then used to train a deep-learning model to identify real cell state-of-health from fast charge/discharge battery voltage responses. The synthetically trained deep-learning model performance is validated by comparing to standard incremental capacity analysis and half-cell measurements. Finally, the framework demonstrates the benefits of using high-rate physics-based models to generate synthetic data for training deep-learning models.

25 ENERGY STORAGE↗
DOE OSTI2022

Fusion Fuel Cycle Inventory Reduction Studies Using a Processing-Time–Based Discrete-Time Interval Model

Developing a Fusion Pilot Plant (FPP) design that minimizes risks due to tritium in-process inventory (IPI) is an important concern for the operation of commercial devices. This becomes even more of concern since an FPP will be breeding more tritium than is burned in the reactor for sustainability. The IPI is the tritium moving through the system that is not in the storage and delivery subsystem. Here a process model that solves time-dependent differential equations based on processing times was used to investigate the reduction of the IPI of a potential fuel cycle design. The impact of new and more efficient technologies such as direct internal recycling (DIR), metal foil pumps, continuous pumping, improved isotope separation, and hydrogen separating continuous pumps on IPI was investigated by adjusting subsystem processing times and material flow streams. It was shown that any of the insertions of DIR studied in this paper caused a reduction in the total IPI of the system and proved to be the optimal way to reduce the IPI in the system. Fuel cycle modifications near the torus, such as a coupled DIR and improved pumping systems, produced the largest reductions in tritium inventory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1986

Mission analysis flow sequencing optimization

This investigation is an extension of a project dealing with the problem of optimal use of ground resources for future space missions. This problem was formulated as a linear programming problem using an indirect approach. Instead of minimizing the inventory level of needed ground resources, the overlapping periods during which the same types of resources are used by various flights are minimized. The model was built upon the assumption that during the time interval under consideration, the costs of various needed resources remain constant. Under other assumptions concerning costs of resources, the objective function, in general, assumes a non-linear form. In this study, one case where the form of the objective function turns out to be quadratic is considered. Also, disadvantages and limitations of the approach used are briefly discussed.

Scott, M.↗
NASA NTRS1985

A mathematical formulation of the problem of optimal use of ground resources for future space missions

An approximate mathematical formulation for scheduling of future space missions is proposed. The objective is to schedule the flights to efficiently use the available ground resources, to minimize the inventory level of ground resources needed and to minimize the overlapping or conflicting periods during which the same types of resources are used by the various flights. The development of the mathematical formulation of the problem considers the presence of a large number of sequencing and resource constraints: (1) the order in which the flights are to be launched is predetermined; and (2) some types of resources are to be used only by certain flights. A linear objective function based on cost considerations is constructed and this function is minimized subject to the various constraints.

Scott, M.↗
DOE OSTI2022

A toolkit for plant lipid engineering: surveying the efficacies of lipogenic factors for accumulating specialty lipids

Plants produce energy-dense lipids from carbohydrates using energy acquired via photosynthesis, making plant oils an economically and sustainably attractive feedstock for conversion to biofuels and value-added bioproducts. A growing number of strategies have been developed and optimized in model plants, oilseed crops and high-biomass crops to enhance the accumulation of storage lipids (mostly triacylglycerols, TAGs) for bioenergy applications and to produce specialty lipids with increased uses and value for chemical feedstock and nutritional applications. Most successful metabolic engineering strategies involve heterologous expression of lipogenic factors that outperform those from other sources or exhibit specialized functionality. In this review, we summarize recent progress in engineering the accumulation of triacylglycerols containing - specialized fatty acids in various plant species and tissues. We also provide an inventory of specific lipogenic factors derived from a wide variety of organisms, along with their reported efficacy in supporting the accumulation of desired lipids. A review of previously obtained results serves as a foundation to guide future efforts to optimize combinations of factors to achieve further enhancements to the production and accumulation of desired lipids in a variety of plant tissues and species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Simulating fusion alpha heating in a stellarator reactor

Gyrocenter following simulations of fusion born alpha particles in a stellarator reactor are preformed using the BEAMS3D code. The Wendelstein 7-X high mirror configuration is scaled in geometry and magnetic field to reactor relevant parameters. A $2\,\times\,10^{20}m^{-3}$ density plasma with 20 keV core temperatures is assumed and fusion birth rates calculated for various fusion products assuming a 50/50 deuterium-tritium mixture. It is found that energetic He 4 ions comprise the vast majority of the energetic particle inventory. Slowing down simulations of the He4 population suggest plasma heating consistent with scaled energy confinement times for a stellarator reactor. Losses for this configuration appear large suggesting optimization beyond the scope of the W7-X device is key to a future fusion reactor. These first simulations are designed to demonstrate the capability of the BEAMS3D code to provide fusion alpha birth and heating profiles for stellarator reactor designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2001

AMINO ACID ANALYSES OF THE ANTARCTIC CM2 METEORITES ALH 83100 AND LEW 90500 USING LIQUID CHROMATOGRAPHY-TIME OF FLIGHT-MASS SPECTROMETRY

The investigation of organic compounds in primitive carbonaceous meteorites provides a record of the chemical processes that occurred in the early solar system. In particular, amino acids have been shown to be potential indicators in tracing the nature of carbonaceous chondrite parent bodies [ 13. The delivery of amino acids by carbonaceous chondrites to the early Earth could have been any important source of the Earth's prebiotic organic inventory [2]. Over 80 different amino acids have been detected in the Murchison CM2 meteorite, most of them completely non-existent in the terrestrial biosphere [3]. We have optimized a new liquid chromatography-time-of-flight-mass spectrometry (LC-ToF-MS) technique coupled with OPAMAC derivatization in order to detect amino acids in meteorite extracts by UV fluorescence and exact mass simultaneously. The detection limit of the LC-ToF-MS instrument for amino acids is at least 3 orders of magnitude lower than traditional GC-MS techniques. Here we report on the first analyses of amino acids and their enantiomeric abundances in the CM2 carbonaceous meteorites ALH 83100, LEW 90500, and Murchison using this new LC-ToF-MS instrument configuration. Amino acid analyses of any kind for the CM meteorite ALH 83100 have not previously been reported.

Glavin, D. P.↗
DOE OSTI2022

Risk-Informed Operations and Maintenance Decision Making Using Deep Reinforcement Learning

A challenge for operating nuclear power plants is the significant cost of operations and maintenance, at times consuming up to 66% of annual operating costs. This project aims to build a framework for a risk-informed asset-management tool that integrates inspections, repairs, spare-part inventory, supply chain, and business choices to lower overall O&M costs. Our approach uses a combination of data-driven modeling and deep reinforcement learning to create and implement optimal maintenance policies for the existing nuclear fleet, as well as new advanced reactors. The creation of an asset management tool that uses these advanced methods will give operators new capabilities to help reduce the burden of O&M spending in nuclear power plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Assessing the life-cycle environmental impacts of the wood pallet sector in the United States

Wood pallets play a critical role in the movement and storage of goods worldwide. They are an important component in the complex global supply chain and used by almost every industry. It is therefore important to assess the environmental implications of the wood pallet supply chain and identify optimization strategies that can be implemented. In this paper, primary 2018 annual production data collected from U.S. pallet manufacturers were used to develop the first industry-average life-cycle inventory (LCI). A new functional unit was proposed to perform a more refined and accurate environmental life-cycle assessment of the wood pallet supply chain. Using the LCI data developed, a cradle-to-grave industry-average life-cycle impact assessment was performed. This novel approach quantifies environmental impacts of a generic multi-use pallet, including repair and remanufacturing. The total global warming impact was 10.4 kg CO 2 e per 45.4 t of pallet loads of product delivered using wood pallets. The manufacturing stage contributed the most, about 35%, followed by the raw material supply stage. About 41% of total primary energy consumption was from renewable sources, with most sourced from biomass. Fossil fuels comprised about 52% of the total (225 MJ per functional unit) primary energy consumption. Total environmental impact was significantly affected by two main parameters: reference service life and load-bearing capacity. Pallet repair was also found to be an important component of the wood pallet supply chain, which has a low environmental footprint compared with the overall impact of a pallet and enables mitigation of overall impact by extending the reference service life. Finally, at end-of-life, common industry practices demonstrated substantial potential environmental benefits that can minimize overall environmental impact.

54 ENVIRONMENTAL SCIENCES↗