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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Updating the Thermal Vacuum Chambers at the NASA Johnson Space Center

Chambers A and B are two large thermal vacuum chambers at Johnson Space Center which enable space simulation for unmanned and human-rated missions, respectively. With the resurgence in deep space missions for scientific research and various private commercial ventures, these chambers are expected to be used frequently for at least the next decade. For qualifying the James Webb Space Telescope, upgrades to Chamber A were performed which included the addition of a 12.5 kW refrigeration system with helium shrouds capable of simulating deep space environment and an efficient and reliable LN2 natural flow thermosiphon system for the thermal shield. Continuous improvements since then have focused on ensuring operational readiness by modernizing the data acquisition, recording, controls, and visualization systems for both chambers and clean room. These upgrades will be the focus of this paper. Controlling the Cryochambers was enhanced by moving from a 32-bit SCADA system to a 64-bit architected system. Infrastructural changes involved installing redundant power circuits, adding new servers, network switches, and including load balancing with fail-over between servers to minimize downtime. Instead of distributed servers, 3 redundant servers are used to share configurations. Configurations are now kept in a shared SQL instance making it easy to deploy and maintain. During this upgrade process many sub-systems (PLCs and NI PXI interfaces to sensors) were upgraded from the prior OPC-DA to the more secure OPC-UA protocol. Cryo-system PLCs were updated to allow Ganni cycle floating pressure calculations from any cold box to be sent to any compressor. During the project, the team recreated over 70,000 live data points, 50000 historical data points, and 4000 alarms. Finally, the graphical interfaces were upgraded to support HTML 5 in conjunction shared pages were implemented reducing the total number of webpages by over 75%. These system updates reinvigorated the previous SCADA system which had reached its end of life. The same look and feel was maintained while providing operators with an updated interface to control, troubleshoot, and record. The new system architecture is more robust and easier to maintain creating a path forward to address remaining problem points and implement additional features.

Cody Schaefer↗
DOE OSTI2023

The Department of Energy and IDEA team up to document industry best practices

This article describes a collaboration between the U.S. Department of Energy and the International District Energy Association (IDEA) to document best practices in district energy systems. The initiative focuses on analyzing real-world performance data and highlighting effective strategies for improving efficiency, integrating renewable energy, and supporting decarbonization efforts. It highlights case studies from the University of California, Davis, and Princeton University to show how long-term master planning, phased project implementation, and strong financial analysis can drive successful transitions to more sustainable energy systems. U.C. Davis emphasizes incremental, results-driven planning and pilot projects, while Princeton focuses on aligning climate goals with financially viable infrastructure investments and life-cycle cost analysis. Overall, the article demonstrates that combining strategic planning, data-driven decision-making, and financial accountability is essential for advancing sustainable district energy systems.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

Advanced Semi-Supervised Learning With Uncertainty Estimation for Phase Identification in Distribution Systems

The integration of advanced metering infrastructure (AMI) into power distribution networks generates valuable data for tasks such as phase identification; however, the limited and unreliable availability of labeled data in the form of customer phase connectivity presents challenges. To address this issue, we propose a semi-supervised learning (SSL) framework that effectively leverages labeled and unlabeled data. Our approach incorporates self-training, label spreading, and Bayesian neural networks (BNNs) to enhance phase identification with AMI data. Our method uses an ensemble of multilayer perceptron classifiers in a self-training setup, iteratively adding high-confidence pseudo-labels to improve robustness. We also apply label spread to propagate labels based on data similarity, which enhances generalization across diverse distributions. In addition, we employ a BNNs with uncertainty estimation, boosting confidence in predictions and reducing phase identification errors. In our case study, we achieved approximately 98% +/- 0.08 accuracy with uncertainty using minimal and unreliable labeled data from a real U.S. utility, Duquesne Light Company. Our SSL approach, combined with uncertainty estimation, provides an efficient solution for phase identification in AMI data, ultimately improving the reliability of smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Framework for custom event sample augmentations for ATLAS analysis data

For HEP event processing, data is typically stored in column-wise synchronized containers, such as most prominently ROOT’s TTree, which have been used for several decades to store by now over 1 exabyte. These containers can combine row-wise association capabilities needed by most HEP event processing frameworks (e.g. Athena for ATLAS) with column-wise storage, which typically results in better compression and more efficient support for many analysis use-cases. One disadvantage is that these containers, TTree in the HEP use-case, require to contain the same attributes for each entry/row (representing events), which can make extending the list of attributes very costly in storage, even if those are only required for a small subsample of events. Since the initial design, the ATLAS software framework features powerful navigational infrastructure to allow storing custom data extensions for subsamples of events in separate, but synchronized containers. This allows adding event augmentations to ATLAS standard data products (such as DAOD-PHYS or PHYSLITE) avoiding duplication of those core data products, while limiting their size increase. For this functionality, the framework does not rely on any associations made by the I/O technology (i.e. ROOT), however it supports TTree friends and builds the associated index to allow for analysis outside of the ATLAS framework. A prototype based on the Long-Lived Particle search is implemented and preliminary results with this prototype will be presented. At this point, augmented data are stored within the same file as the core data. Storing them in separate files will be investigated in future, as this could provide more flexibility, e.g. certain sites may only want a subset of several augmentations or augmentations can be archived to tape once their analysis is complete.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Experimental Investigation of the Effect of Air-Handling and DME-Propane Blends on the Performance and Emissions of a 4-Cylinder CI Engine

Dimethyl ether (DME) is considered an excellent alternative to diesel because of its higher cetane number and lower carbon content. Additionally, DME can be blended with abundantly available propane with minimal modifications to the propane infrastructure. This paper focuses on an experimental investigation of the effect of air-handling i.e., boost pressure and exhaust gas recirculation (EGR), and DME-propane blends on the combustion and emissions performance of a light-duty, four-cylinder, compression ignition (CI) engine. Here, the boost pressure and EGR sweeps were carried out and showed that higher boost pressures resulted in increased brake thermal efficiencies (BTE) at the expense of higher NOx emissions which could be reduced by an increase in EGR. The fuel sweeps were carried out at 0, 15 and 25% propane (neat, 85% and 75% DME) with 0% and 25% EGR. The fuel sweeps indicated that the ignition delay (ID) increased and burn duration (BD) decreased monotonically when the blend increased to 25% propane/75% DME. The results suggest optimum engine performance with neat DME at 105 kPa boost pressure and 25% EGR with propane addition improving the BTE with negligible increase in emissions. Higher contents of Propane, up to 25%, did not affect the variability of combustion, with standard deviations of burn duration and peak cylinder pressures below 1% for all test cases.

air-handling↗
DOE OSTI2022

Assessment of Offshore Wind Energy Leasing Areas for Humboldt and Morro Bay Wind Energy Areas, California

The National Renewable Energy Laboratory (NREL) is providing scientific and technical services to the Bureau of Ocean Energy Management (BOEM) under an interagency agreement. The purpose of this report is to provide technical assistance in delineating potential lease areas from the California wind energy areas (WEAs) that can be competitively auctioned to wind energy developers. Each wind energy area is presumed to be technically and economically feasible for wind energy development based on the economic cost study performed by NREL in 2020. The subsequent analysis summarized in this report is intended to help BOEM maximize efficient offshore wind energy resource use and ensure fair return to the Government for use of the lease areas, by making recommendations for viable ways to divide the WEAs into auctionable commercial lease areas of approximately equal value. We considered several factors that affect the value of lease areas for wind energy development, including mean wind speeds, water depth, seafloor gradient, seismicity, hard substrate, and access to infrastructure. The largest impact to generating capacity came from the choice of mooring technology and the resulting setback from the lease area boundaries. Based on our setback assumptions, the generating capacity for a wind plant using catenary moorings could be nearly 30% less than with vertical moorings in Humboldt, or approximately 20% less in Morro Bay. The likely range of generating capacity is 1.5 to 3 GW in Humboldt and 3 to 5 GW in Morro Bay.

17 WIND ENERGY↗
NASA NTRS2013

The Tailoring of Traditional Systems Engineering for the Morpheus Project

NASA's Morpheus Project has developed and tested a prototype planetary lander capable of vertical takeoff and landing that is designed to serve as a testbed for advanced spacecraft technologies. The lander vehicle, propelled by a LOX/Methane engine and sized to carry a 500kg payload to the lunar surface, provides a platform for bringing technologies from the laboratory into an integrated flight system at relatively low cost. From the beginning, one of goals for the Morpheus Project was to streamline agency processes and practices. The Morpheus project accepted a challenge to tailor the traditional NASA systems engineering approach in a way that would be appropriate for a lower cost, rapid prototype engineering effort, but retain the essence of the guiding principles. The team has produced innovative ways to create an infrastructure and approach that would challenge existing systems engineering processes while still enabling successful implementation of the current Morpheus Project. This paper describes the tailored systems engineering approach for the Morpheus project, including the processes, tools, and amount of rigor employed over the project's multiple lifecycles since the project began in FY11. Lessons learned from these trials have the potential to be scaled up and improve efficiency on a larger projects or programs.

Devolites, Jennifer L.↗
DOE OSTI2019

Computational Strategies for Scalable Genomics Analysis

The revolution in next-generation DNA sequencing technologies is leading to explosive data growth in genomics, posing a significant challenge to the computing infrastructure and software algorithms for genomics analysis. Various big data technologies have been explored to scale up/out current bioinformatics solutions to mine the big genomics data. In this review, we survey some of these exciting developments in the applications of parallel distributed computing and special hardware to genomics. We comment on the pros and cons of each strategy in the context of ease of development, robustness, scalability, and efficiency. Although this review is written for an audience from the genomics and bioinformatics fields, it may also be informative for the audience of computer science with interests in genomics applications.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2013

Fully Printed, Flexible, Phased Array Antenna for Lunar Surface Communication

NASAs future exploration missions focus on the manned exploration of the Moon, Mars, and beyond, which will rely heavily on the development of a reliable communications infrastructure from planetary surface-to-surface, surface-to-orbit, and back to Earth. Flexible antennas are highly desired in many scenarios. Active phased array antennas (active PAAs) with distributed control and processing electronics at the surface of an antenna aperture offer numerous advantages for radar communications. Large-area active PAAs on flexible substrates are of particular interest in NASA s space radars due to their efficient inflatable package that can be rolled up during transportation and deployed in space. Such an inflatable package significantly reduces stowage volume and mass. Because of these performance and packaging advantages, large-area inflatable active PAAs are highly desired in NASA s surface-to-orbit and surface-to-relay communications. To address the issues of flexible electronics, a room-temperature printing process of active phased-array antennas on a flexible Kapton substrate was developed. Field effect transistors (FETs) based on carbon nanotubes (CNTs), with many unique physical properties, were successfully proved feasible for the PAA system. This innovation is a new type of fully inkjet-printable, two-dimensional, high-frequency PAA on a flexible substrate at room temperature. The designed electronic circuit components, such as the FET switches in the phase shifter, metal interconnection lines, microstrip transmission lines, etc., are all printed using a special inkjet printer. Using the developed technology, entire 1x4, 2x2, and 4x4 PAA systems were developed, packaged, and demonstrated at 5.3 GHz. Several key solutions are addressed in this work to solve the fabrication issues. The source/drain contact is developed using droplets of silver ink printed on the source/drain areas prior to applying CNT thin-film. The wet silver ink droplets allow the silver to wet the CNT thin-film area and enable good contact with the source and drain contact after annealing. A passivation layer to protect the device channel is developed by bonding a thin Kapton film on top of the device channel. This film is also used as the media for transferring the aligned CNT thin-film on the device substrate. A simple and cost-effective technique to form multilayer metal interconnections on flexible substrate is developed and demonstrated. Contact vias are formed on the second substrate prior to bonding on the first substrate. Inkjet printing is used to fill the silver ink into the via structure. The printed silver ink penetrates through the vias to contact with the contact pads on the bottom layer. It is then annealed to form a good connection. One-dimensional and two-dimensional PAAs were fabricated and characterized. In these circuits, multilayer metal interconnects were used to make a complete PAA system.

Subbaraman, Harish↗
NASA NTRSDate not supplied

Bioreactor Development for CO2-Based In Situ Resource Utilization Manufacturing

Sustainable long-duration manned missions on both the Moon and Mars will require in situ resource utilization (ISRU). Carbon dioxide (CO2) has great potential as a harvestable resource, making up 95% of the atmosphere on Mars and being produced as respiratory waste in spacecraft and future planetary habitats. Through ISRU, biomanufacturing has the capability to produce a near limitless array of products from local space resources. Here, a CO2-based ISRU recombinant protein producing bioreactor and associated biomanufacturing organisms were designed to produce a highly stable carbonic anhydrase (CA). Candidate organisms were selected by growth characterization on acetate and formic acid, carbon substrates that are synthesized via electrochemical conversion of CO2. To improve growth on the CO2 producing substrate formic acid and for direct integration of ISRU CO2, a synthetic Calvin-Benson-Bassam cycle was designed for use in Escherichia coli. Multiplex genetic modification in E. coli was facilitated by a tailored CRISPR/Cas9 and λ red recombineering two-vector system. For expression of CA, a blue light regulated T7 promoter was employed for dynamic and small molecule free induction. Efficient bioproduction through a fed-batch exponential feeding strategy was determined via mass balance analysis from ISRU substrates to biomass and CA yield. Flux balance analysis was used to model ISRU substrate metabolism and metabolic pathway engineering in candidate organisms under cultivation strategy conditions for both metabolism reconstruction and pathway design optimization. Finally, a small-scale, disposable bag bioreactor for use in the NASA Bioculture System infrastructure was designed to enable CO2-based CA biomanufacturing in reduced-gravity environments.

biomanufacturing↗
NASA NTRSDate not supplied

Development of a Weather Capability for the Urban Air Mobility Airspace Research Roadmap

Traditionally, the transportation system’s resiliency to the impacts of weather is an area where neglected or incorrect assumptions can lead to difficulties later in the research and development lifecycle. To mitigate this, NASA has ongoing efforts to develop a set of research roadmaps for organizing, integrating, and communicating research into new aviation infrastructure and transportation modalities, within which weather is being addressed early on. An effort has been undertaken to add weather assumptions and requirements to an already-existing roadmap for the Urban Air Mobility (UAM) airspace, seeking to integrate weather requirements early in the system design. This effort addresses the way in which state-of-the art and evolving weather science and technology can enable safe and efficient travel with increasing tempo of UAM operations over time. This paper describes the addition of weather as one of 10 capabilities into the UAM Airspace research roadmap, laying out the anticipated weather technology and information requirements needed to facilitate operations at various UAM Maturity Levels. The process developed and exercised by MIT Lincoln Laboratory researchers produced 41 unique requirements to be satisfied by a Weather capability for the UAM ecosystem, with more than 300 dependencies identified across the system. These requirements cover measurement, analysis, modeling, forecasting, decision support, dissemination, and overarching policy, and are provided with an overview of weather challenges for UAM. The requirements were mainly defined based on subject matter expert review of existing UAM Airspace system requirements, and refined based on iterative feedback with various stakeholders including regulators, academia, and industry. Going forward, this roadmap will help researchers and developers align to a common vision in ensuring that weather is appropriately considered in the UAM ecosystem.

Timothy Bonin↗
NASA NTRSDate not supplied

Development of a Weather Capability for the Urban Air Mobility Airspace Research Roadmap

Traditionally, the transportation system’s resiliency to the impacts of weather is an area where neglected or incorrect assumptions can lead to difficulties later in the research and development lifecycle. To mitigate this, NASA has ongoing efforts to develop a set of research roadmaps for organizing, integrating, and communicating research into new aviation infrastructure and transportation modalities, within which weather is being addressed early on. An effort has been undertaken to add weather assumptions and requirements to an already-existing roadmap for the Urban Air Mobility (UAM) airspace, seeking to integrate weather requirements early in the system design. This effort addresses the way in which state-of-the art and evolving weather science and technology can enable safe and efficient travel with increasing tempo of UAM operations over time. This paper describes the addition of weather as one of 10 capabilities into the UAM Airspace research roadmap, laying out the anticipated weather technology and information requirements needed to facilitate operations at various UAM Maturity Levels. The process developed and exercised by MIT Lincoln Laboratory researchers produced 41 unique requirements to be satisfied by a Weather capability for the UAM ecosystem, with more than 300 dependencies identified across the system. These requirements cover measurement, analysis, modeling, forecasting, decision support, dissemination, and overarching policy, and are provided with an overview of weather challenges for UAM. The requirements were mainly defined based on subject matter expert review of existing UAM Airspace system requirements, and refined based on iterative feedback with various stakeholders including regulators, academia, and industry. Going forward, this roadmap will help researchers and developers align to a common vision in ensuring that weather is appropriately considered in the UAM ecosystem.

research roadmap↗
DOE OSTI2024

ESM data downscaling: a comparison of super-resolution deep learning models

Abstract Climate projections at fine spatial resolutions are required to conduct accurate risk assessment for critical infrastructure and design adaptation planning. Generating these projections using advanced Earth system models (ESM) requires significant computational resources. To address this issue, various statistical downscaling techniques have been introduced to generate fine-resolution data from coarse-resolution simulations. In this study, we evaluate and compare five deep learning-based downscaling techniques, namely, super-resolution convolutional neural networks, fast super-resolution convolutional neural network ESM, efficient sub-pixel convolutional neural network, enhanced deep residual network (EDRN), and super-resolution generative adversarial network (SRGAN). These techniques are applied to a dataset generated by the Energy Exascale Earth System Model (E3SM), focusing on key surface variables such as surface temperature, shortwave heat flux, and longwave heat flux. Models are trained and validated using paired fine-resolution (0.25 $$^{\circ }$$ ∘ ) and coarse-resolution (1 $$^{\circ }$$ ∘ ) monthly data obtained from a 9-year simulation. Next, blind testing is performed using monthly data obtained from two different years outside of the training and validation set. To evaluate the efficiency of each technique, different statistical metrics are used, including mean squared error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and learned perceptual image patch similarity (LPIPS). The results show that EDRN outperforms other algorithms in terms of PSNR, SSIM, and MSE, but struggles to capture fine-scale features in the data. In contrast, SRGAN, a generative model that uses perceptual loss, excels in capturing fine details at boundaries and internal structures, resulting in lower LPIPS than other methods.

Pawar, Nikhil M. (ORCID:0000000211613289)↗
DOE OSTI2022

CASM — A software package for first-principles based study of multicomponent crystalline solids

CASM is a software package that enables first-principles based studies of crystalline materials. It has been designed to treat coupled chemical, mechanical, vibrational, and magnetic degrees of freedom to determine ground state and finite temperature properties of crystals. The symmetry of the underlying parent crystal structure is used to enumerate perturbations of the parent crystal structure and generate derivative structures which can be input to first-principles calculations in order to explore the ground state energy landscape. CASM algorithmically constructs cluster expansions that fully couple discrete and continuous degrees of freedom, and generates highly efficient code to evaluate the cluster expansion basis functions. Widely used machine learning methods are integrated for fitting expansion coefficients to first-principle calculations. The fully parameterized cluster expansions can be combined with (kinetic) Monte Carlo methods to calculate finite temperature thermodynamic and kinetic properties. CASM Alloy Manager identifies distinct parent crystal structures in an alloy system, creating individual projects for each, and integrating the results. The integrated infrastructure facilitates the linkage between first-principles statistical mechanics predictions with higher length scale computational methods, such as phase field simulations. In conclusion, CASM projects are designed to be easy to share in repositories, to re-use, and to extend to include additional chemical species or types of degrees of freedom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Subtle changes in hydrogen bond orientation result in glassification of carbon capture solvents

Water-lean CO 2 capture solvents show promise for more efficient and cost-effective CO 2 capture, although their long-term behavior in operation has yet to be well studied. New observations of extended structure solvent behavior show that some solvent formulations transform into a glass-like phase upon aging at operating temperatures after contact with CO 2 . The glassification of a solvent would be detrimental to a carbon-capture process due to plugging of infrastructure, introducing a critical need to decipher the underlying principles of this phenomenon to prevent it from happening. In this work, we present the first integrated theoretical and experimental study to characterize the nano-structure of metastable and glassy states of an archetypal single-component alkanolguanidine carbon-capture solvent and assess how minute changes in atomic-level interactions convert the solvent between metastable and glass-like states. Small-angle neutron scattering and neutron diffraction coupled with small- and wide-angle X-ray scattering analysis demonstrate that minute structural changes in solution precipitae reversible aggregation of zwitterionic alkylcarbonate clusters in solution. Our findings indicate that our test system, an alkanolguanidine, exhibits a first-order phase transition, similar to a glass transition, at approximately 40 °C—close to the operating absorption temperature for post-combustion CO 2 capture processes. We anticipate that these phenomena are not specific to this system, but are present in other classes of colvents as well. We discuss how molecular-level interactions can have vast implications for solvent-based carbon-capture technologies, concluding that fortunately in this case, glassification of water-lean solvents can be avoided as long as the solvent is run above its glass transition temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Bioreactor Development for CO2-Based In Situ Resource Utilization Manufacturing

Sustainable long-duration manned missions on both the Moon and Mars will require in situ resource utilization (ISRU). Carbon dioxide (CO2) has great potential as a harvestable resource, making up 95% of the atmosphere on Mars and being produced as respiratory waste in spacecraft and future planetary habitats. Through ISRU, biomanufacturing has the capability to produce a near limitless array of products from local space resources, which include pharmaceuticals, bioplastics, chemical feedstocks, and industrial enzymes. Here, a CO2-based ISRU recombinant protein bioreactor and associated biomanufacturing organisms were designed to produce a highly stable carbonic anhydrase (CA). Initial work characterized candidate organisms for growth on acetate and formic acid, carbon substrates that can be synthesized via electrochemical conversion of CO2. To improve growth on the CO2 producing substrate formic acid and for direct integration of ISRU CO2, a synthetic Calvin-Benson-Bassam cycle was designed for use in Cyberlindnera jadinii and Escherichia coli. Genetic modifications in E. coli will be facilitated by a tailored CRISPR/Cas9 and λ red recombineering two-vector system. For expression of CA, a blue light regulated T7 promoter was employed for dynamic and small molecule free induction. Efficient bioproduction through a fed-batch exponential feeding strategy was determined via mass balance calculations from ISRU substrates to biomass and CA yield. Flux balance analysis was used to model ISRU substrate metabolism and metabolic pathway engineering in candidate organisms under cultivation strategy conditions for both metabolism reconstruction and pathway design optimization. Finally, a small-scale, disposable bag bioreactor concept for use in the NASA Bioculture System infrastructure was designed to enable CO2-based CA production in reduced-gravity environments.

Biomanufacturing, Pathway Engineering, Flux Balanc↗
DOE OSTI2025

Practical Implementation of GPU-based Computing at the Grid Edge for Resilience Scenarios

This paper presents a practical implementation of GPU-accelerated computing at the grid edge to enhance power system resilience through next-generation smart meters. Advanced Metering Infrastructure (AMI) systems rely predominantly on centralized processing architectures, which limit real-time response capabilities during grid disturbances. This work proposes the integration of GPU-enabled computational platforms directly within smart meter to enable local execution support for power system analytics, fault detection algorithms, and optimization routines. The proposed framework uses the Julia programming language to leverage highperformance parallel computing capabilities while maintaining code portability and development efficiency. We use two experimental scenarios to benchmark the computational feasibility of this approach: sparse linear system solutions representative of power flow analyses, and multi-stage production cost simulations incorporating unit commitment and economic dispatch operations. Results demonstrate that computationally intensive power system algorithms, such as those supporting resilience scenario calculations, can be effectively executed at the distribution edge using commercially available embedded GPU hardware. Keywords—GPU acceleration, edge computing, smart meters, grid resilience, AMI, resilience.

De Souza, Reubun [School of Electrical Engineering↗