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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

New Insights into the Heterogeneity of the Tagish Lake Meteorite: Soluble Organic Compositions of Variously Altered Specimens

The Tagish Lake carbonaceous chondrite exhibits a unique compositional heterogeneity that may be attributed to varying degrees of aqueous alteration within the parent body asteroid. Previous analyses of soluble organic compounds from four Tagish Lake meteorite specimens (TL5b, TL11h, TL11i, TL11v) identified distinct distributions and isotopic compositions that appeared to be linked to their degree of parent body processing (Herd et al. 2011; Glavin et al. 2012; Hilts et al. 2014). In the present study, we build upon these initial observations and evaluate the molecular distribution of amino acids, aldehydes and ketones, monocarboxylic acids, and aliphatic and aromatic hydrocarbons, including compound‐specific δ13C compositions, for three additional Tagish Lake specimens: TL1, TL4, and TL10a. TL1 contains relatively high abundances of soluble organics and appears to be a moderately altered specimen, similar to the previously analyzed TL5b and TL11h lithologies. In contrast, specimens TL4 and TL10a both contain relatively low abundances of all of the soluble organic compound classes measured, similar to TL11i and TL11v. The organic‐depleted composition of TL4 appears to have resulted from a relatively low degree of parent body aqueous alteration. In the case of TL10a, some unusual properties (e.g., the lack of detection of intrinsic monocarboxylic acids and aliphatic and aromatic hydrocarbons) suggest that it has experienced extensive alteration and/or a distinct organic‐depleted alteration history. Collectively, these varying compositions provide valuable new insights into the relationships between asteroidal aqueous alteration and the synthesis and preservation of soluble organic compounds.

Tagish Lake↗
NASA NTRS2000

Martian Chronology: Goals for Investigations from a Recent Multidisciplinary Workshop

The absolute chronology of Martian rocks and events is based mainly on crater statistics and remains highly uncertain. Martian chronology will be critical to building a time scale comparable to Earth's to address questions about the early evolution of the planets and their ecosystems. In order to address issues and strategies specific to Martian chronology, a workshop was held, 4-7 June 2000, with invited participants from the planetary, geochronology, geochemistry, and astrobiology communities. The workshop focused on identifying: a) key scientific questions of Martian chronology; b) chronological techniques applicable to Mars; c) unique processes on Mars that could be exploited to obtain rates, fluxes, ages; and d) sampling issues for these techniques. This is an overview of the workshop findings and recommendations.

Nyquist, L.↗
DOE OSTI2023

Adaptive learning-driven high-throughput synthesis of oxygen reduction reaction Fe–N–C electrocatalysts

Reducing human reliance on inefficient energy systems and fossil fuels has become more urgent due to the consequences of global climate change. However, traditional trial-and-error approaches have hampered our ability to accelerate the discovery and implementation of functional materials for efficient energy conversion devices, such as polymer electrolyte fuel cells (PEFCs). To address this, we develop an adaptive learning framework that integrates machine learning and state-of-the-art capabilities in high-throughput synthesis to achieve expedited optimization of iron-nitrogen-carbon PEFC oxygen reduction reaction (ORR) electrocatalysts. We use statistical inference, uncertainty quantification, and global optimization to build a computational design-of-experiment tool that identifies the optimum compositions to be investigated next to reduce the demands placed on experimental materials discovery. We benchmark the ability of the proposed strategy to discover optimum catalyst synthesis conditions in a six-dimensional search space when starting with a thirty-six-sample database. By following the adaptive learning strategy, we synthesize fourteen new catalysts from approximately ten billion unique compositions and discover four catalysts that outperform all original samples. The best machine learning-optimized catalyst is 33% more active than the highest-performing one in the initial database, showing an ORR activity seven times larger than those typically reported for the same class of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Machine learning prediction of incidence of Alzheimer’s disease using large-scale administrative health data

Nationwide population-based cohort provides a new opportunity to build an automated risk prediction model based on individuals’ history of health and healthcare beyond existing risk prediction models. We tested the possibility of machine learning models to predict future incidence of Alzheimer’s disease (AD) using large-scale administrative health data. From the Korean National Health Insurance Service database between 2002 and 2010, we obtained de-identified health data in elders above 65 years (N = 40,736) containing 4,894 unique clinical features including ICD-10 codes, medication codes, laboratory values, history of personal and family illness and socio-demographics. To define incident AD we considered two operational definitions: “definite AD” with diagnostic codes and dementia medication (n = 614) and “probable AD” with only diagnosis (n = 2026). We trained and validated random forest, support vector machine and logistic regression to predict incident AD in 1, 2, 3, and 4 subsequent years. For predicting future incidence of AD in balanced samples (bootstrapping), the machine learning models showed reasonable performance in 1-year prediction with AUC of 0.775 and 0.759, based on “definite AD” and “probable AD” outcomes, respectively; in 2-year, 0.730 and 0.693; in 3-year, 0.677 and 0.644; in 4-year, 0.725 and 0.683. The results were similar when the entire (unbalanced) samples were used. Important clinical features selected in logistic regression included hemoglobin level, age and urine protein level. This study may shed a light on the utility of the data-driven machine learning model based on large-scale administrative health data in AD risk prediction, which may enable better selection of individuals at risk for AD in clinical trials or early detection in clinical settings.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2010

Principal Components Analysis of Reflectance Spectra Returned by the Mars Exploration Rover Opportunity

The Mars Exploration Rover Opportunity has spent over six years exploring the Martian surface near its landing site at Meridiani Planum. Meridiani bedrock observed by the rover is largely characterized by sulfate-rich sandstones and hematite spherules, recording evidence of ancient aqueous environments [1]. The region is a deflationary surface, allowing hematite spherules, fragments of bedrock, and "cobbles" of foreign origin to collect loosely on the surface. These cobbles may be meteorites (e.g., Barberton, Heat Shield Rock, Santa Catarina) [2], or rock fragments of exotic composition derived from adjacent terranes or from the subsurface and delivered to Meridiani Planum as impact ejecta [3]. The cobbles provide a way to better understand Martian meteorites and the lithologic diversity of Meridiani Planum by examining the various rock types located there. In the summer of 2007, a global dust storm on Mars effectively disabled Opportunity's Miniature Thermal Emission Spectrometer (Mini-TES), which served as the Athena Science Team s primary tool for remotely identifying rocks of interest on a tactical timescale for efficient rover planning. While efforts are ongoing to recover use of the Mini-TES, the team is currently limited to identifying rocks of interest by visual inspection of images returned from Opportunity's Panoramic Camera (Pancam). This study builds off of previous efforts to characterize cobbles at Meridiani Planum using a database of reflectance spectra extracted from Pancam 13-Filter (13F) images [3]. We analyzed the variability of rock spectra in this database and identified physical characteristics of Martian rocks that could potentially account for the observed variance. By understanding such trends, we may be able to distinguish between rock types at Meridiani Planum and regain the capability to remotely identify locally unique rocks.

Mercer, C. M.↗
DOE OSTI2022

Integrating Embodied Carbon Knowledge for Design Decisions: Preprint

Measuring energy consumption of buildings is well established, and techniques to evaluate the carbon associated with operating buildings are improving. Embodied carbon of buildings is more complex as it considers the release of carbon throughout the building material supply chain and building material end of life fate. Decisions made early during the design and construction of the building can influence and potentially reduce the embodied carbon of buildings. The design and construction communities are uniquely positioned to make decisions that reduce embodied carbon. The objective of this project is to understand barriers to low carbon design and delivery and to point the design and construction communities to useful resources that will result in decisions that reduce embodied carbon. The outcomes of this work include educational resources that familiarize designers and contractors with embodied carbon and life cycle assessments (LCA), case studies that focus on design changes from LCA results, an overview of LCA tools, and examples of readily available, cost-effective design and construction steps to lower embodied carbon. We present an evaluation of existing resources, organized in a decision tree guidance, and identify gaps for further resource development. Through this evaluation process we investigated ways to streamline the process of identifying barriers to implementing solutions quickly.

design professional decisions↗
DOE OSTI2023

Building an Equation of State Density Ladder

The confluence of major theoretical, experimental, and observational advances are providing a unique perspective on the equation of state of dense neutron-rich matter—particularly its symmetry energy—and its imprint on the mass-radius relation for neutron stars. In this contribution, we organize these developments in an equation of the state density ladder. Of particular relevance to this discussion are the impact of the various rungs on the equation of state and the identification of possible discrepancies among the various methods. A preliminary analysis identifies possible tension between laboratory measurements and gravitational-wave detections that could indicate the emergence of a phase transition in the stellar core.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Achieving 50% Energy Savings in Chicago Homes: A Case Study for Advancing Equity and Climate Goals

Since 2019, the National Renewable Energy Laboratory (NREL) and Elevate have collaborated to identify pathways to deep energy retrofits in Chicago's housing stock, document equity implications and co-benefits of this transition, and validate the findings by implementing retrofits in real Chicago homes. This document summarizes our analysis process to model advanced retrofit packages that lead to greater than 50% energy savings in Chicago homes. Based on these findings, we have also developed a roadmap with the City to guide implementation, and are deploying the recommended retrofit packages in real Chicago homes to realize these energy savings. This work was developed in collaboration with two key stakeholders - the City of Chicago and Commonwealth Edison (ComEd) - and funded by the U.S. Department of Energy (DOE). NREL's Residential Buildings team maintains the best-in-class ResStock™ energy model of the U.S. residential building stock. For this work, we calibrated ResStock to Chicago's unique local housing stock to accurately simulate energy use in Chicago homes both for current conditions and with various retrofit scenarios. We simulated a wide range of potential building retrofits covering all aspects of residential energy use and then grouped these into packages based on energy and utility bill savings. ResStock can model diverse building types and housing characteristics, so we're able to observe the range of outcomes that might occur when these upgrades are deployed across the entire housing stock. We can then estimate potential energy savings from an advanced retrofit program on Chicago's housing stock by comparing the modeled energy use before versus after a retrofit. This novel version of ResStock, calibrated to Chicago with data from Elevate, can help City officials, ComEd, and other partners plan for community-scale decarbonization via residential retrofits. Specifically, this work contributes the following project goals: Develop a building retrofit prioritization strategy for Chicago single-family and 2- to 4-unit buildings; Identify neighborhoods and home types that have the highest potential for savings from electrification; and Assess the impact of advanced building retrofits on energy use, utility bills, and CO2 emissions at the city and building level. Although this study is specific to Chicago, its methods and learnings are applicable across the United States. These findings are especially notable for heat pumps and electrification retrofits in cold climates.

building energy modeling↗
DOE OSTI2023

Nuclear Criticality Experiments Research Center Futures: A Report of a Workshop held September 6-9, 2022, Los Alamos, NM, November, 2022

Experiments and training with critical assemblies and fissionable material (at or near the critical state) that explore reactivity phenomena are central to a number of national security challenges. From fission energy to nuclear weapons to a broad suite of scientific challenges, it is clear that additional capacity and capability are needed. The National Criticality Experiments Research Center (NCERC) marked 10 years of operations in 2021. This anniversary was an opportune time to celebrate our successes and progress, and to evaluate the remaining and emergent challenges. Against this backdrop, a workshop of approximately 140 national and international leaders in nuclear research was convened in Los Alamos, New Mexico to explore “NCERC Futures.” Therefore, the present workshop focused specifically on needed capabilities and tools to meet the research challenges in eight topical mission areas served by NCERC. As each Topical Group summarized their discussions in the out brief, it was recognized that key challenges could be met through enabling infrastructure investments and new critical assemblies. Enabling infrastructure includes staffing, additional space/buildings, developing an agile bounding safety basis, the ability to keep pace with technological advances in detectors and data acquisition systems (allowing use of those with Bluetooth™ and similar technologies), an expanded set of materials options (especially plutonium), a “Plug and Play” design and implementation mindset, and a facility that enabled free-field measurements. The new critical assemblies that were identified as having the most impact were a bare plutonium (Pu) Critical Assembly, a Horizontal Split Table (HST), a Super Comet, and a Uranium Solution Burst Assembly. NECRC is a unique, one-of-a-kind facility in the United States. If all the improvements were to be made, NCERC would enable the United States and its partners to address many important research questions related to criticality. These include but are not limited to: (1) Covering the entire neutron energy spectrum for both highly enriched uranium (HEU) and Pu in configurations for virtually all conceivable applications; (2) Performing multi-physics solution experiments and irradiations with a Uranium Solution Burst Assembly, which more closely resembles actual criticality accidents; (3) Conducting free-field experiments to make basic fission physics measurements and much cleaner benchmarks with various experimental observables; and (4) Providing more training classes and more experiments annually at greater cost efficiency enabled by additional buildings and machines and an agile, bounding, risk-balanced Safety Basis. In the end, workshop attendees enthusiastically concluded that NCERC Futures are bright and the workshop helped to identify a roadmap of capability gaps that need to be addressed. This report documents the results of those efforts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Parallel Simulation of Quantum Networks with Distributed Quantum State Management

Quantum network simulators offer the opportunity to cost-efficiently investigate potential avenues for building networks that scale with the number of users, communication distance, and application demands by simulating alternative hardware designs and control protocols. Several quantum network simulators have been recently developed with these goals in mind. As the size of the simulated networks increases, however, sequential execution becomes time-consuming. Parallel execution presents a suitable method for scalable simulations of large-scale quantum networks, but the unique attributes of quantum information create unexpected challenges. In this work, we identify requirements for parallel simulation of quantum networks and develop the first parallel discrete-event quantum network simulator by modifying the existing serial simulator SeQUeNCe. Our contributions include the design and development of a quantum state manager (QSM) that maintains shared quantum information distributed across multiple processes. We also optimize our parallel code by minimizing the overhead of the QSM and decreasing the amount of synchronization needed among processes. Using these techniques, we observe a speedup of 2 to 25 times when simulating a 1,024-node linear network topology using 2 to 128 processes. We also observe an efficiency greater than 0.5 for up to 32 processes in a linear network topology of the same size and with the same workload. We repeat this evaluation with a randomized workload on a caveman network. We also introduce several methods for partitioning networks by mapping them to different parallel simulation processes. We have released the parallel SeQUeNCe simulator as an open source tool alongside the existing sequential version.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Acceptable Knowledge Summary Report for REMOTE-HANDLED DEPLETED URANIUM INGOTS FROM MATERIALS AND FUELS COMPLEX

This Acceptable Knowledge (AK) Summary Report has been prepared for the Central Characterization Program (CCP) for remote-handled (RH) transuranic (TRU) waste generated and managed by the Materials and Fuels Complex (MFC), formerly Argonne National Laboratory-West (ANL-W) and part of the Idaho National Laboratory (INL). The waste described in this report, depleted uranium ingots (waste stream ID-MFC-DU-INGOT), was historically generated in Building 765, the Fuel Conditioning Facility (FCF), formerly, Hot Fuel Examination Facility (HFEF)-South. This AK Summary Report, along with the referenced supporting documents, provides a defensible and auditable record of AK for the designated waste stream, depleted uranium ingots, produced from the FCF electrorefining process. The references and AK source documents used to prepare this report are listed in Sections 8.0 and 9.0 respectively. The source documents cited throughout this report are identified by alphanumeric designations corresponding to a unique Source Document Tracking Number (e.g., AKA01, C001, CCE01, DR001, M001, P001, and U001).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2021

Identifying molecules as biosignatures with assembly theory and mass spectrometry

The search for alien life is hard because we do not know what signatures are unique to life. We show why complex molecules found in high abundance are universal biosignatures and demonstrate the first intrinsic experimentally tractable measure of molecular complexity, called the molecular assembly index (MA). To do this we calculate the complexity of several million molecules and validate that their complexity can be experimentally determined by mass spectrometry. This approach allows us to identify molecular biosignatures from a set of diverse samples from around the world, outer space, and the laboratory, demonstrating it is possible to build a life detection experiment based on MA that could be deployed to extraterrestrial locations, and used as a complexity scale to quantify constraints needed to direct prebiotically plausible processes in the laboratory. Such an approach is vital for finding life elsewhere in the universe or creating de-novo life in the lab.

Stuart M. Marshall↗
DOE OSTI2021

Analysis of basic airflow configurations for separate sensible and latent cooling systems with indoor air recirculation

Separate sensible and latent cooling (SSLC) is a technology with efficiency and comfort advantages over conventional cooling systems used for space conditioning of buildings. Using multiple cooling processes at different temperatures allows SSLC to save energy by raising the evaporation temperature of the sensible cooling process. In this paper, all possible airflow configurations of SSLC systems are enumerated under the following constraints: exactly two heat exchangers are used, and air is recirculated to the conditioned space (no exhaust or outdoor air treatment). Seven designs are identified, with varying free operating variables, and each is modeled. Analysis reveals that several configurations are equivalent, and there is only one unique basic airflow SSLC configuration: the one with the sensible and latent heat exchangers placed in series. The efficiency of the SSLC system is compared against that of the conventional system. Under standard conditions, an SSLC system can improve the coefficient of performance by 14.8%. In addition to the numerical simulation, the optimal operating condition of the basic air configuration of the SSLC system is derived analytically. The basic SSLC system is shown to offer the highest performance improvement when the outdoor temperature is relatively cool and the space sensible heat ratio is high.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Development of Directed Energy Deposited NASA HR-1 to Optimize Properties for Liquid Rocket Engine Applications

Metal additive manufacturing (AM) processes have been demonstrated to be effective at reducing costs and lead times associated with fabrication of complex propulsion component designs. Laser powder directed energy deposition (LP-DED) and laser powder bed fusion (L-PBF) are metal AM technologies that have effectively been used to produce a variety of parts for space applications. These technologies have enabled new designs and materials for these applications. The National Aeronautics and Space Administration (NASA) has identified the need to develop and advance new materials in unique space applications such as high-pressure hydrogen environments. One such metal alloy being developed for these applications is NASA HR-1. A high-strength Fe-Ni based superalloy, NASA HR-1 was designed to resist high pressure hydrogen environment embrittlement, oxidation, and corrosion. AM technologies have enabled the manufacturing of NASA HR-1 to be a feasible material for components in hydrogen environments. Development efforts for NASA HR-1 have completed build and heat treatment optimization, material characterization, thermophysical property testing, and mechanical testing in air and hydrogen environments to mature the understanding of the material. This poster will summarize the development of NASA HR-1 for AM including composition and heat treatment optimization, microstructure characterization, and results of mechanical testing in air and high pressure hydrogen.

NASA HR-1↗
NASA NTRSDate not supplied

Development and Optimization of Additively Manufactured NASA HR-1 for Space Applications

Metal additive manufacturing (AM) processes have been demonstrated to be effective at reducing costs and lead times associated with fabrication of complex propulsion component designs. Laser powder directed energy deposition (LP-DED) and laser powder bed fusion (L-PBF) are metal AM technologies that have effectively been used to produce a variety of parts for space applications. These technologies have enabled new designs and materials for these applications. The National Aeronautics and Space Administration (NASA) has identified the need to develop and advance new materials in unique space applications such as high-pressure hydrogen environments. One such metal alloy being developed for these applications is NASA HR-1. A high-strength Fe-Ni based superalloy, NASA HR-1 was designed to resist high pressure hydrogen environment embrittlement, oxidation, and corrosion. AM technologies have enabled the manufacturing of NASA HR-1 to be a feasible material for components in hydrogen environments. Development efforts for NASA HR-1 have completed build and heat treatment optimization, material characterization, thermophysical property testing, and mechanical testing in air and hydrogen environments to mature the understanding of the material. This presentation will summarize the development of NASA HR-1 for AM including composition and heat treatment optimization, microstructure characterization, and results of mechanical testing in air and high pressure hydrogen.

Additive Manufacturing↗
DOE OSTI2021

Codes and Standards Assessment for Hydrogen Blends into the Natural Gas Infrastructure

Energy utilities are evaluating emerging energy technologies to reduce reliance on carbon as an energy carrier. Hydrogen has been identified as a potential substitute for carbon-based fuels that can be blended into other gaseous energy carriers, such as natural gas. However, hydrogen blending into natural gas has important implications on safety which need to be evaluated. Designers and installers of systems that utilize hydrogen gas blending into natural gas distribution systems need to adhere to local building codes and engage with the authority having jurisdiction (AHJ) for safety and permitting approvals. These codes and standards must be considered to understand where safety gaps might be apparent when injecting hydrogen into the natural gas infrastructure. This report generates a list of relevant codes and standards for hydrogen blending on existing, upgraded, or new pipelines. Additionally, a preliminary assessment was made to identify the codes and standards that need to be modified to enable this technology as well as potential gaps due to the unique nature and safety concerns of gaseous hydrogen.

03 NATURAL GAS↗
NASA NTRS2003

A National Virtual Specimen Database for Early Cancer Detection

Access to biospecimens is essential for enabling cancer biomarker discovery. The National Cancer Institute's (NCI) Early Detection Research Network (EDRN) comprises and integrates a large number of laboratories into a network in order to establish a collaborative scientific environment to discover and validate disease markers. The diversity of both the institutions and the collaborative focus has created the need for establishing cross-disciplinary teams focused on integrating expertise in biomedical research, computational and biostatistics, and computer science. Given the collaborative design of the network, the EDRN needed an informatics infrastructure. The Fred Hutchinson Cancer Research Center, the National Cancer Institute,and NASA's Jet Propulsion Laboratory (JPL) teamed up to build an informatics infrastructure creating a collaborative, science-driven research environment despite the geographic and morphology differences of the information systems that existed within the diverse network. EDRN investigators identified the need to share biospecimen data captured across the country managed in disparate databases. As a result, the informatics team initiated an effort to create a virtual tissue database whereby scientists could search and locate details about specimens located at collaborating laboratories. Each database, however, was locally implemented and integrated into collection processes and methods unique to each institution. This meant that efforts to integrate databases needed to be done in a manner that did not require redesign or re-implementation of existing system

distributed↗
DOE OSTI2023

Accurate Prediction of Algal Biomass Lipid, Protein, and Carbohydrate Composition with Machine Learning Regression Modelling of Near-IR Spectra

During large scale algal biomass cultivation, it is difficult to reliably control relative composition to target levels. Rapid determination of chemical composition is feasible by using near infrared (NIR) spectral data. We sought to build and improve on reliable high-throughput screening prediction method based on partial least squares regression (PLSR) by the application of artificial neural networks (ANN) and associated optimization strategies. The algal biomass sample set was designed and created in an iterative process of culturing in physiologically diverse conditions at the GAI field site, followed by compositional analyses at NREL. The workflow allowed us to identify gaps in compositional space for informing the subsequent cultivation and sampling efforts and generated a high quality set of 210 unique samples with chemical analysis results, spectral scanning data, and cultivation metadata. We observed a significant improvement in the performance of carbohydrate content predictions using an optimized ANN model compared to PLSR, with > 16% reduction in mean absolute percent error (MAPE) when tested on the same set of reserved data. The optimized ANN models for FAME and protein prediction performed exceptionally well with 5.99% and 5.09% MAPE, respectively. Application of these methods to detection and quantification of minor biomass constituents that are relevant to certain product streams has shown positive preliminary results, opening the possibility for extensions to the outputs of this powerful data type. All models are accompanied by prediction uncertainties and unsupervised spectral outlier detection to alert an operator to unreliable spectral data. These tools can be deployed for rapid determination of algal culture status, and cultivation and biomass quality improvement.

algal biofuels↗