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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

The Solid Rocket Motor Slag Population: Results of a Radar-based Regressive Statistical Evaluation

Solid rocket motor (SRM) slag has been identified as a significant source of man-made orbital debris. The propensity of SRMs to generate particles of 100 m and larger has caused concern regarding their contribution to the debris environment. Radar observation, rather than in-situ gathered evidence, is currently the only measurable source for the NASA/ODPO model of the on-orbit slag population. This simulated model includes the time evolution of the resultant orbital populations using a historical database of SRM launches, propellant masses, and estimated locations and times of tail-off. However, due to the small amount of observational evidence, there can be no direct comparison to check the validity of this model. Rather than using the assumed population developed from purely historical and physical assumptions, a regressional approach was used which utilized the populations observed by the Haystack radar from 1996 to present. The estimated trajectories from the historical model of slag sources, and the corresponding plausible detections by the Haystack radar, were identified. Comparisons with observational data from the ensuing years were made, and the SRM model was altered with respect to size and mass production of slag particles to reflect the historical data obtained. The result is a model SRM population that fits within the bounds of the observed environment.

Horstman, Matthew F.↗
DOE OSTI2022

Opportunities and data requirements for data-driven prognostics and health management in liquid hydrogen storage systems

During the past decade, Prognostics and Health Management (PHM) has become an important set of tools in various areas of industry and academic reliability engineering. PHM consists of a variety of mathematical and computational methods used to support data-driven decision-making to increase the safety, availability, and reliability of complex engineering systems. In particular, PHM can provide crucial insight into reliability and safety design improvements for developing technologies where historical performance and failure data are limited. This is the case of hydrogen fueling and storage technologies. This work presents a high-level approach for designing data-driven PHM applications for bulk liquid hydrogen (LH 2 ) storage systems for hydrogen fueling stations. This paper addresses core aspects of the design, development, and implementation of data-driven PHM applications that can improve the reliability assessment of hydrogen components. The analysis focuses on the relationship between data availability and diagnostic/prognostic capabilities; potential challenges; and integration schemes for current risk mitigation measures. We identify potential condition-monitoring data sources for key components in an LH 2 storage system, including storage tanks, piping, and pumps. Further, we determine that the short-term goals for the implementation of data-driven models in PHM frameworks in hydrogen systems should focus on developing adequate data collection and analysis strategies, as well as exploring the effect on reliability, safety, and regulations for hydrogen systems.

08 HYDROGEN↗
NASA NTRS1997

The Development of Si and SiGe Technologies for Microwave and Millimeter-Wave Integrated Circuits

Historically, microwave technology was developed by military and space agencies from around the world to satisfy their unique radar, communication, and science applications. Throughout this development phase, the sole goal was to improve the performance of the microwave circuits and components comprising the systems. For example, power amplifiers with output powers of several watts over broad bandwidths, low noise amplifiers with noise figures as low as 3 dB at 94 GHz, stable oscillators with low noise characteristics and high output power, and electronically steerable antennas were required. In addition, the reliability of the systems had to be increased because of the high monetary and human cost if a failure occurred. To achieve these goals, industry, academia and the government agencies supporting them chose to develop technologies with the greatest possibility of surpassing the state of the art performance. Thus, Si, which was already widely used for digital circuits but had material characteristics that were perceived to limit its high frequency performance, was bypassed for a progression of devices starting with GaAs Metal Semiconductor Field Effect Transistors (MESFETs) and ending with InP Pseudomorphic High Electron Mobility Transistors (PHEMTs). For each new material or device structure, the electron mobility increased, and therefore, the high frequency characteristics of the device were improved. In addition, ultra small geometry lithographic processes were developed to reduce the gate length to 0.1 pm which further increases the cutoff frequency. The resulting devices had excellent performance through the millimeter-wave spectrum.

Ponchak, George E.↗
DOE OSTI2024

Joint Management and Optimization of Residential Natural Gas and Electricity Distribution Networks Coupled via Fuel Cells

The attractive features of natural gas as well as the growing electric power demand worldwide have created increasing interest in natural-gas-based distributed generation applications for electric distribution networks. Here, this paper investigates the interdependency between a residential natural gas network and an electric distribution network that are linked together via fuel cells. The modeling of the natural gas network is introduced first, and then the algorithm for gas flow study is presented. The optimal placement and sizing of fuel cell based distributed generation systems are formulated to minimize the losses in both the natural gas network and the electric distribution grid, subject to the constraints imposed by both networks. In addition, a probabilistic model for both gas and electricity demands is developed based on historical electricity and natural gas demand data. A K-means clustering method is used to determine the hourly load states to solve the joint probabilistic optimization problem. Simulation studies are carried out on an integrated system consisting of the IEEE 69-bus distribution network and a radial 27-node natural gas network to verify the developed optimization model and the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A Guide to Engaging Underserved Communities in Commercial Energy Efficiency Field Validations

Underserved communities in the United States often experience the negative impacts of climate change and environmental degradation but enjoy few of the benefits of technological and environmental advances. The White House has addressed this inequity through the Justice40 initiative, which requires 40% of the benefits of select federal investments to be directed to underserved communities (The White House, 2022). Clean energy and energy efficiency are two highlighted investment categories, so the U.S. Department of Energy will guide implementation of the Justice40 initiative by, among other things, decreasing energy burdens, increasing parity in clean energy technology access and adoption, and increasing energy resiliency. A strategy for reaching these goals is to evaluate and validate new energy efficiency technologies in commercial buildings in underserved communities, where buildings may be older, smaller, and have deferred maintenance due to historical underinvestment. This paper develops guidance for researchers pursuing field validations with underserved communities. Historical redlining and past negative experiences with government and large institutions may make residents wary of participating in these field validations. Researchers, therefore, may need to spend more time building relationships and matching technologies to buildings. In this paper, we analyzed technical reports to identify common field validation building characteristics and conducted semi-structured expert conversations to identify key stages and major themes of engaging underserved communities. Results indicate there may be flexibility in site selection and there are steps researchers can take to support collaboration with communities. Results also suggest benefits to both the community and energy efficiency research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2017

Research and Development History of Glass Bubbles Bulk-Fill Thermal Insulation Systems for Large-Scale Cryogenic Liquid Hydrogen Storage Tanks

Based on the published literature record, this document provides an overview of the research and development of glass bubbles bulk-fill thermal insulation systems for cryogenic equipment in general and, in particular, for large-scale cryogenic liquid hydrogen (LH2) storage spheres. Glass bubbles (also known as hollow glass microspheres) are used in place of perlite powder which began use in double-wall cryogenic tanks in the 1930s. Included in this overview is a historical summary, a development timeline, a selected publications list, and the key technical points from those publications.

Cryogenic storage tanks↗
NASA NTRS1994

Vehicle development of Lunar/Mars exploration

The author of this paper presents a historical discussion of robotic vehicle development of lunar and Martian exploration. The discussion begins by comparing and contrasting the transportation, environmental, and operational requirements of the two planets. This is followed by a historical summary of what has been done to date, including some recently released information on the Soviet rovers sent to Mars and Phobos in the early 1970s. Finally, current proposed missions, vehicles, operational requirements, and development status are discussed.

Purvis, James W.↗
NASA NTRSDate not supplied

Continued Environmental Microbiology Monitoring of The International Space Station (ISS) Veggie Unit Used for In-Flight, Crop-Based Food Systems

The International Space Station is a closed environment where rotating sets of Crewmembers live and work. This environment is monitored to ensure occupants’ health and safety during their spaceflight residency by routine Environmental Health System (EHS) collection of microbial samples including air, surface, and water. The microbial samples are collected, enumerated, and analyzed quarterly to monitor on-board system contamination and potential risks to crew health. Quarterly monitoring of the microorganisms in the ISS environment supports crew safety and contributes to a large set of microbial concentration and diversity data. The current in-inflight microbial requirements were developed using this historical data collected by the routine environmental monitoring. These in-flight microbial requirements have been established to maintain the health and safety of the spacecraft environment. This study leverages quarterly operational EHS sampling by collecting additional microbial samples from the surface of the Veggie plant production system on ISS. These samples will yield microbial concentration and diversity that can be compared and analyzed with nominal surface samples from the vehicle. The data collected in this study will aid in the development of requirements for spaceflight-based food production systems. Continued surface sampling of the internal and external surfaces of the Veggie system, along with collaboration from both Johnson Space Center (JSC) & Kennedy Space Center (KSC) scientists studying the microbiome of the veggie-crop systems, will be implemented as part of the future development of crop-based food system requirements for the ISS and beyond.

Christian Mena↗
NASA NTRS2020

Reply to “A Comment on ‘an Evolutionary System of Mineralogy: Proposal for A Classification of Planetary Materials Based on Natural Kind Clustering’”

I welcome the “Comment” from Hatert et al. (2021) related to the proposal for an “Evolutionary system of mineralogy” (Hazen 2019) and thank them for their historically informed, conceptually nuanced, and consistently constructive contribution. They offer corrections related to two facets of my paper that seemed unfairly to criticize aspects of the International Mineralogical Association’s Commission on New Minerals, Nomenclature and Classification (IMA-CNMNC) protocols for classifying minerals. First, they note an unfortunate inferred ambivalence with respect to the relationship between the IMA system and the new evolutionary system. If I was once ambivalent, that view has changed. Having spent the past two years in an ongoing effort to develop this new historical approach, I am struck every day by the power of the IMA-CNMNC system of species classification and nomenclature, which is fundamental and indispensable to the science of mineralogy. As Hatert et al. suggest, any new approach to organizing natural solids, including one focused on planetary evolution, must rest on the foundation provided by the IMA-CNMNC and its many volunteers who selflessly bring order to the mineral kingdom. In the best scenario, the evolutionary system may one day emerge as one of several useful approaches that complement and amplify but in no way replace this core IMA-CNMNC foundation, as clearly stated in the abstract of Hazen (2019). Second, Hatert et al. (2021) offer corrections regarding the IMA-CNMNC approach to classification, in particular a mischaracterization of the formal process to incorporate amorphous phases, poorly crystalline materials, and loosely defined “mineraloids.” I am grateful for the clarifications, as well as the implication that IMA protocols may facilitate the embrace of additional such phases in the future. Finally, I welcome the chance to explore further the emerging concept of “natural kinds” as applied to the mineral kingdom. Here, our thoughts differ. I suggest that minerals, considered in their information-rich, idiosyncratic, paragenetic contexts (in contrast to IMA-CNMNC species), have the potential to represent quintessential examples of “natural kinds.” Furthermore, when viewed in their evolutionary context, minerals offer an intriguing opportunity to expand the concept of “historical natural kinds” beyond its present limited and, at times, controversial use in biology, into the realm of the co-evolving geosphere and biosphere.

Philosophy of mineralogy↗
NASA NTRS1993

MSFC orbital spacecraft development emphases for this decade

Historically, the Marshall Space Flight Center (MSFC) has been responsible for significant accomplishments in the area of developing both manned and unmanned spacecraft. MSFC is presently involved in many of NASA's largest and most prominent programs, with some operational, others being readied for flight, and still others in various stages of design and development. Examples of MSFC programs being designed or developed are Space Station Freedom (S.S. Freedom), the Advanced X-Ray Astrophysics Facility (AXAF) which includes imaging and spectroscopy facilities, the Laser Atmospheric Wind Sounder (LAWS), and the Lunar Ultraviolet Telescope Experiment (LUTE), with Spacelab and Tethered Satellite System (TSS) as examples of current operational MSFC spacecraft. The information obtained from the Long Duration Exposure Facility (LDEF) will aid the design process and life predictions for these and all future spacecraft. A second LDEF is presently being considered. All of these projects will be briefly described in this paper.

Schwinghamer, Robert J.↗
NASA NTRS2017

Synthetic Scenarios from CMIP5 Model Simulations for Climate Change Impact Assessments in Managed Ecosystems and Water Resources: Case Study in South Asian Countries

Increasing population, urbanization, and associated demand for food production compounded by climate change and variability have important implications for the managed ecosystems and water resources of a region. This is particularly true for south Asia, which supports one quarter of the global population, half of whom live below the poverty line. This region is largely dependent on monsoon precipitation for water. Given the limited resources of the developing countries in this region, the objective of our study was to empirically explore climate change in south Asia up to the year 2099 using monthly simulations from 35 global climate models (GCMs) participating in the fifth phase of the Climate Model Inter-comparison Project (CMIP5) for two future emission scenarios (representative concentration pathways RCP4.5 and RCP8.5) and provide a wide range of potential climate change outcomes. This was carried out using a three-step procedure: calculating the mean annual, monsoon, and non-monsoon precipitation and temperatures; estimating the percent change from historical conditions; and developing scenario funnels and synthetic scenarios. This methodology was applied for the entire south Asia region; however, the percent change information generated at 1.5deg grid scale can be used to generate scenarios at finer spatial scales. Our results showed a high variability in the future change in precipitation (-23% to 52%, maximum in the non-monsoon season) and temperature (0.8% to 2.1%) in the region. Temperatures in the region consistently increased, especially in the Himalayan region, which could have impacts including a faster retreat of glaciers and increased floods. It could also change rivers from perennial to seasonal, leading to significant challenges in water management. Increasing temperatures could further stress groundwater reservoirs, leading to withdrawal rates that become even more unsustainable. The high precipitation variability (with higher propensity for localized intense rainfall events) observed in the region can be a key factor for managed ecosystems and water management and could also lead to more incidence of severe urban flooding. The results could be used to assess both mitigation and adaptation alternatives to reduce vulnerabilities in managed ecosystems (agricultural and urban) and water resources.

agriculture↗
DOE OSTI2021

Robust Distributed State Estimator for Interconnected Transmission and Distribution Networks (Final Report RPPR-1)

This project’s objective is to develop a combined transmission and distribution state estimator which accounts for very large system size and model complexity (by way of distributing the computations) and large number of solar PV units connected to the distribution system on multiple feeders. The project not only provides a robust formulation and solution to this problem but also tests the solution by implementing it on a well-established large utility system. It introduces several improvements with respect to the state of the art in existing state estimation software: (a) The developed state estimator (SE) allows robust and accurate monitoring of bidirectional flows in distribution systems which result due to the distributed energy sources which are not observable and thus not incorporated in generation dispatch; (b) Large utility systems with tens of thousands of transmission buses and hundreds of thousands of distribution nodes are difficult to model as a single integrated system. This shortcoming is addressed by developing a “scalable distributed computational framework” which allows splitting the ultra large system models into several small subsystems and coordinating their solution by a robust and practical state estimation formulation; (c) Measurement errors irrespective of their locations are detected and removed by the developed state estimator. Historically, transmission and distribution systems were analyzed and operated as two independent systems. Given the non-transposed short feeder sections, unevenly loaded phases, strictly radial configuration and unidirectional power flows in the absence of remote generation, distribution system analysis was customized to account for these characteristics. However, some of these assumptions are no longer valid (non-radial configuration, bidirectional power flows) and thus distribution system analysis should be revisited. Furthermore, in the past, the interaction between the transmission and distribution systems was quite passive, where distribution substations were modeled as lumped loads in the transmission system model. With substantial generation injected by renewable generation located in the distribution systems, such modeling will no longer be accurate. The developed state estimator facilitates proper monitoring of the interactions between the transmission and distribution systems and enables smart dispatch of these units which are made observable by the state estimator.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Carbonate clumped isotope analysis (Δ 47 ) of 21 carbonate standards determined via gas‐source isotope‐ratio mass spectrometry on four instrumental configurations using carbonate‐based standardization and multiyear data sets

Rationale Clumped isotope geochemistry examines the pairing or clumping of heavy isotopes in molecules and provides information about the thermodynamic and kinetic controls on their formation. The first clumped isotope measurements of carbonate minerals were first published 15 years ago, and since then, interlaboratory offsets have been observed, and laboratory and community practices for measurement, data analysis, and instrumentation have evolved. Here we briefly review historical and recent developments for measurements, share Tripati Lab practices for four different instrument configurations, test a recently published proposal for carbonate‐based standardization on multiple instruments using multi‐year data sets, and report values for 21 different carbonate standards that allow for recalculations of previously published data sets. Methods We examine data from 4628 standard measurements on Thermo MAT 253 and Nu Perspective IS mass spectrometers, using a common acid bath (90°C) and small‐sample (70°C) individual reaction vessels. Each configuration was investigated by treating some standards as anchors (working standards) and the remainder as unknowns (consistency standards). Results We show that different acid digestion systems and mass spectrometer models yield indistinguishable results when instrument drift is well characterized. For linearity correction, mixed gas‐and‐carbonate standardization or carbonate‐only standardization yields similar results. No difference is observed in the use of three or eight working standards for the construction of transfer functions. Conclusions We show that all configurations yield similar results if instrument drift is robustly characterized and validate a recent proposal for carbonate‐based standardization using large multiyear data sets. Δ 47 values are reported for 21 carbonate standards on both the absolute reference frame (ARF; also refered to as the Carbon Dioxide Equilibrated Scale or CDES) and the new InterCarb‐Carbon Dioxide Equilibrium Scale (I‐CDES) reference frame, facilitating intercomparison of data from a diversity of labs and instrument configurations and restandardization of a broad range of sample sets between 2006, when the first carbonate measurements were published, and the present.

58 GEOSCIENCES↗
DOE OSTI2022

Recurrent neural networks for short-term and long-term prediction of geothermal reservoirs

Accurate prediction of geothermal reservoir responses to alternative energy production scenarios is critical for optimizing the development of the underlying resources. While the conventional physics-based models offer a comprehensive prediction tool, data-driven models provide an efficient alternative to build fit-for-purpose predictive models by extracting and using the statistical patterns in the collected data to make predictions. The recurrent neural network (RNN) is a data-driven model that is commonly applied to predict time series sequences. This paper presents a variant of RNN that also utilizes the efficiency of convolutional neural networks (CNN) for the prediction of energy production from geothermal reservoirs. Specifically, a CNN–RNN architecture is developed that takes historical well controls as input (features) and their corresponding production response data as output (labels) to learn an input-output mapping that can predict the future well production responses/performance for any given future well control inputs. The model is paired with a labeling scheme to handle real field disturbances that create data gaps. In addition to the model structure, we introduce a thorough workflow for applying the model, which includes data pre-processing, feature selection, as well as different training strategies for short-term and long-term prediction. Finally, the performance and accuracy of the model are evaluated by applying it to multiple datasets, including a field reservoir model.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

A Comparative Study of Physics‐Informed and Data‐Driven Neural Networks for Compound Flood Simulation at River‐Ocean Interfaces: A Case Study of Hurricane Irene

Simulating compound flooding (CF) at the river-ocean interface within large-scale Earth System Models (ESMs) presents significant challenges due to complex interactions between river discharge, storm surge, and tides. This study assesses the comparative advantages of physics-informed and data-driven machine learning (ML) approaches for enhancing local ESM performance. We systematically compare data-driven neural network models (i.e., CNNs, U-Net, Long Short-Term Memory (LSTM), Gated Recurrent Unit), and physics-informed neural network (PINN) models, including vanilla PINN and a finite-difference-based PINN (FD-PINN). Specifically, FD-PINN is introduced to enhance computational efficiency, accelerating vanilla PINNs by ∼6.5 times while improving accuracy. To enhance data-driven model training, a new data-generation approach is developed to sample historical fluvial and coastal flood events, which ensures a robust data set for extreme event prediction. The models are evaluated using a realistic one-dimensional river domain extracted from an ESM's river mesh and the Hurricane Irene event as an independent test case. Results show that FD-PINN achieves accurate predictions with significantly reduced computational costs relative to vanilla PINNs. Among data-driven models, the best overall performance is achieved by a CNN-LSTM hybrid, which balances accuracy and efficiency. While a fully connected CNN (CNN-FC) provides the best accuracy, it incurs high computational cost. Architectures lacking strong temporal modeling tend to underperform on unseen events. These findings highlight the importance of sequence-aware designs for robust generalization. This study reveals the trade-offs between physics-informed and data-driven models and proposes an adaptive hybrid framework for integrating ML into ESMs to enhance local flood simulations.

Earth Systems Modeling↗
DOE OSTI2024

A Stochastic Framework for Estimating Load Profiles at EV Fast Charging Stations

This paper formulates a methodology for estimating the average daily load profiles of EV fast charging stations over a planning horizon of five to ten years. The developed methodology uses historic vehicle registration data, state-level EV adoption targets, seasonal driving patterns, local demographics, competition, and traffic volume information to predict average station usage. Through Monte Carlo simulations, an average daily load profile is obtained for each month in the planning horizon, and prediction uncertainty is quantified. The proposed framework will facilitate the accurate estimation of energy and demand costs incurred by the charging station over the planning period, thereby informing return-on-investment calculations.

Biswas, Shuchismita↗
DOE OSTI2022

Characterization and Understanding of Thermal Transport in Stationary and Moving Particle Beds for Concentrating Solar Power

Concentrating solar power (CSP) coupled with thermal energy storage (TES) is being considered as an appealing solution to deliver stable, dispatchable, and inexpensive electricity generation from renewable solar energy. The heat from the HTF is stored in a TES system that is significantly less expensive and more scalable than electrochemical storage, enabling electricity generation when the sunlight is unavailable. The general concentrating solar thermal technologies are being pushed to higher temperature for higher efficiency and lower cost in a diverse range application in electricity generation (in CSP), industrial heating, and thermochemical fuel productions. Inert and abundant solid particles are becoming increasingly more important for these emerging applications. Heat transfer in both stationary and moving particle beds have been studied for many decades, revealing a great deal of insights on the mechanisms. Yet, there are still several unresolved problems from both fundamental understanding and technological applications points of view. In this Chapter, we will attempt to provide an up-to-date picture of thermal transport in stationary and moving particle beds. In both cases, we will review historical and contemporary developments in the theoretical, computational, and experimental aspects of heat transfer and related behaviors in particle beds. Here, we will discuss both the advancements and limitations of the existing studies and point to future developments towards deeper fundamental understandings and better engineering applications.

14 SOLAR ENERGY↗