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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Ultrafast jet classification at the HL-LHC

Abstract Three machine learning models are used to perform jet origin classification. These models are optimized for deployment on a field-programmable gate array device. In this context, we demonstrate how latency and resource consumption scale with the input size and choice of algorithm. Moreover, the models proposed here are designed to work on the type of data and under the foreseen conditions at the CERN large hadron collider during its high-luminosity phase. Through quantization-aware training and efficient synthetization for a specific field programmable gate array, we show that O ( 100 ) ns inference of complex architectures such as Deep Sets and Interaction Networks is feasible at a relatively low computational resource cost.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Seamless Wireless Communication Platform for Internet of Things Applications

The rapid growth of the Internet of Things (IoT) devices resulted in the proliferation of wireless technologies to cater to their increasing data rate requirements and support multiple applications. However, such ever-increasing wireless technologies present numerous challenges such as incompatible wireless standards, increased energy consumption, and insecure communication. The traditional gateways proposed in the literature suffers from limitations such as computational complexity, resource requirements, increased cost, and device size. We vision an era of seamless wireless communication to alleviate the aforementioned challenges in IoT applications. through three inter-dependent functionalities namely detection and identification of wireless technologies, energy-efficient transmit power control, and secure end-to-end communication. To prove the concept, a new gateway is proposed to achieve these three functionalities with only physical layer measurements so that the different communication protocols in the higher layers can be avoided. Novel schemes are conceptualized for resource-limited seamless IoT applications. Moreover, the conceptual seamless IoT platform is validated through software-based computer simulation and software-defined radio-based testbed implementation. Finally, the preliminary analysis demonstrates that the proposed platform has great potential in advancing seamless IoT applications.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Notional Habitat Science Outfitting for a Lunar Surface Habitat or Mars Transit Habitat

Science outfitting is often given insufficient treatment in the development of early conceptual studies for lunar surface habitats. In some cases, only control masses and volumes are used as placeholders. In others, one science discipline may be given detailed treatment while others are largely ignored. It is not unheard of for science outfitting to be entirely forgotten in initial concept layouts. This is exacerbated by the reality that spacecraft design studies are often initiated long before science objectives have been established for any given human spaceflight destination. When those objectives later emerge, they can be difficult to accommodate if sizing studies did not allocate sufficient resources for them. A notional science outfitting can be created for virtually any human exploration habitat, however, utilizing data created by the International Space Station and Constellation programs. Biology, human research, physics, and geology science laboratories and a general-purpose work area for a lunar surface habitat will be derived using equipment identified by the Constellation-era Optimizing Science and Exploration Working Group (OSEWG) or flown on the International Space Station. Early science outfitting definition and inclusion in surface habitat sizing is critical for developing an exploration architecture that meets science needs. The mass, volume, power, and use cases associated with these notional laboratories impacts all of the habitat subsystems, habitat dimensions, hatch dimensions, logistics operations, launch vehicles and landers.

Lunar Habitat↗
DOE OSTI2026

Addressing the split incentive challenge for rooftop solar PV and battery energy storage in multifamily rental buildings (CRADA 638 Final Report)

This project advances the understanding of how roof solar PV systems and battery energy storage systems (BESS) can be effectively deployed in multifamily residential buildings, a sector that has historically faced barriers due to misaligned incentives between landlords and tenants. By leveraging high-resolution building stock data and simulation tools, the research demonstrates how energy consumption patterns vary across building types, climates, and occupant characteristics, and how these variations influence the optimal sizing and operation of distributed energy resources. A key contribution is the development of a publicly accessible, web-based tool named RESIDE (Residential Energy Systems & Infrastructure Data Evaluation) that allows users to explore building energy use and evaluate solar and battery configurations without requiring specialized expertise. This significantly lowers the barrier to entry for stakeholders such as property owners, utilities, and policymakers. From a technical perspective, the project shows that integrating rooftop solar PV with battery energy storage can substantially reduce electricity costs and peak demand through strategies such as energy arbitrage and peak shaving. The modeling framework incorporates real-world constraints, including time-of-use electricity pricing and battery degradation, providing realistic and actionable insights. Economically, the results indicate that properly sized systems can deliver meaningful cost savings, improving the feasibility of energy investments in multifamily housing. More broadly, the project benefits the public by supporting the transition to affordable and reliable energy, particularly in rental multifamily housing where adoption has traditionally lagged.

14 SOLAR ENERGY↗
DOE OSTI2023

Lipoprotein subfraction patterns throughout gestation in The Gambia: changes in subfraction composition and their relationships with infant birth weights

Lipoprotein subfraction concentrations have been shown to change as gestation progresses in resource-rich settings. The objective of the current study was to evaluate the impact of pregnancy on different-sized lipoprotein particle concentrations and compositions in a resource-poor setting. Samples were collected from pregnant women in rural Gambia at enrollment (8–20 weeks), 20 weeks, and 30 weeks of gestation. Concentrations of different-sized high-density, low-density, and triglyceride-rich lipoprotein particles (HDL, LDL, and TRL, respectively) were measured by nuclear magnetic resonance in 126 pooled plasma samples from a subset of women. HDL was isolated and the HDL proteome evaluated using mass spectroscopy. Subfraction concentrations from women in The Gambia were also compared to concentrations in women in the U.S. in mid gestation. Total lipoprotein particles and all-sized TRL, LDL, and HDL particle concentrations increased during gestation, with the exception of medium-sized LDL and HDL particles which decreased. Subfraction concentrations were not associated with infant birth weights, though relationships were found between some lipoprotein subfraction concentrations in women with normal versus low birth weight infants (< 2500 kg). HDL’s proteome also changed during gestation, showing enrichment in proteins associated with metal ion binding, hemostasis, lipid metabolism, protease inhibitors, proteolysis, and complement activation. Compared to women in the U.S., Gambian women had lower large- and small-sized LDL and HDL concentrations, but similar medium-sized LDL and HDL concentrations. Most lipoprotein subfraction concentrations increase throughout pregnancy in Gambian women and are lower in Gambian vs U.S. women, the exception being medium-sized LDL and HDL particle concentrations which decrease during gestation and are similar in both cohorts of women. The proteomes of HDL also change in ways to support gestation. These changes warrant further study to determine how a lack of change or different changes could impact negative pregnancy outcomes.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2010

A High-Throughput, Adaptive FFT Architecture for FPGA-Based Space-Borne Data Processors

Historically, computationally-intensive data processing for space-borne instruments has heavily relied on ground-based computing resources. But with recent advances in functional densities of Field-Programmable Gate-Arrays (FPGAs), there has been an increasing desire to shift more processing on-board; therefore relaxing the downlink data bandwidth requirements. Fast Fourier Transforms (FFTs) are commonly used building blocks for data processing applications, with a growing need to increase the FFT block size. Many existing FFT architectures have mainly emphasized on low power consumption or resource usage; but as the block size of the FFT grows, the throughput is often compromised first. In addition to power and resource constraints, space-borne digital systems are also limited to a small set of space-qualified memory elements, which typically lag behind the commercially available counterparts in capacity and bandwidth. The bandwidth limitation of the external memory creates a bottleneck for a large, high-throughput FFT design with large block size. In this paper, we present the Multi-Pass Wide Kernel FFT (MPWK-FFT) architecture for a moderately large block size (32K) with considerations to power consumption and resource usage, as well as throughput. We will also show that the architecture can be easily adapted for different FFT block sizes with different throughput and power requirements. The result is completely contained within an FPGA without relying on external memories. Implementation results are summarized.

Nguyen, Kayla↗
NASA NTRS2023

Commercial Low-Earth Orbit Destination (CLD) Capabilities of Interest and Resource Needs

The Commercial Low Earth Orbit (LEO) Development Program team has been working with NASA and the International Space Station (ISS) National Lab (NL) stakeholders to identify capabilities of interest to both conduct research/technology demonstrations and estimate the resources that will be needed from Commercial LEO Destinations (CLDs). Through a series of one-on-one and working group meetings with users/stakeholders, hardware items of interest to the user community were identified and converted into capabilities (e.g., centrifugation, microscope, pressure chamber, etc.). In parallel, resources needed to operate the research equipment (e.g., crew time, number of experiments, volume, etc.) were estimated in order for the CLD providers to better understand NASA’s potential future service requirements. The capabilities and the resources included in this White Paper do not represent NASA requirements. Instead, they constitute a preliminary set of potential capability and resource needs collated to guide CLD providers in appropriately sizing and outfitting their CLD designs. NASA is requesting feedback from industry on how these capabilities and resources align with their own needs as well as those of their non-NASA customers. Information on how the capabilities/resources impact the CLD designs is also requested. After assessing industry’s feedback to this white paper, NASA plans to issue a preliminary set of requirements for review.

International Space Station↗
DOE OSTI2023

Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation

Abstract This study proposes and assesses a methodology to obtain high-quality probabilistic predictions and uncertainty information of near-landfall tropical cyclone–driven (TC-driven) storm tide and inundation with limited time and resources. Forecasts of TC track, intensity, and size are perturbed according to quasi-random Korobov sequences of historical forecast errors with assumed Gaussian and uniform statistical distributions. These perturbations are run in an ensemble of hydrodynamic storm tide model simulations. The resulting set of maximum water surface elevations are dimensionality reduced using Karhunen–Loève expansions and then used as a training set to develop a polynomial chaos (PC) surrogate model from which global sensitivities and probabilistic predictions can be extracted. The maximum water surface elevation is extrapolated over dry points incorporating energy head loss with distance to properly train the surrogate for predicting inundation. We find that the surrogate constructed with third-order PCs using elastic net penalized regression with leave-one-out cross validation provides the most robust fit across training and test sets. Probabilistic predictions of maximum water surface elevation and inundation area by the surrogate model at 48-h lead time for three past U.S. landfalling hurricanes (Irma in 2017, Florence in 2018, and Laura in 2020) are found to be reliable when compared to best track hindcast simulation results, even when trained with as few as 19 samples. The maximum water surface elevation is most sensitive to perpendicular track-offset errors for all three storms. Laura is also highly sensitive to storm size and has the least reliable prediction. Significance Statement The purpose of this study is to develop and evaluate a methodology that can be used to provide high-quality probabilistic predictions of hurricane-induced storm tide and inundation with limited time and resources. This is important for emergency management purposes during or after the landfall of hurricanes. Our results show that sampling forecast errors using quasi-random sequences combined with machine learning techniques that fit polynomial functions to the data are well suited to this task. The polynomial functions also have the benefit of producing exact sensitivity indices of storm tide and inundation to the forecasted hurricane properties such as path, intensity, and size, which can be used for uncertainty estimation. The code implementing the presented methodology is publicly available on GitHub.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Abiotic selection of microbial genome size in the global ocean

Abstract Strong purifying selection is considered a major evolutionary force behind small microbial genomes in the resource-poor photic ocean. However, very little is currently known about how the size of prokaryotic genomes evolves in the global ocean and whether patterns reflect shifts in resource availability in the epipelagic and relatively stable deep-sea environmental conditions. Using 364 marine microbial metagenomes, we investigate how the average genome size of uncultured planktonic prokaryotes varies across the tropical and polar oceans to the hadal realm. We find that genome size is highest in the perennially cold polar ocean, reflecting elongation of coding genes and gene dosage effects due to duplications in the interior ocean microbiome. Moreover, the rate of change in genome size due to temperature is 16-fold higher than with depth up to 200 m. Our results demonstrate how environmental factors can influence marine microbial genome size selection and ecological strategies of the microbiome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Climatic factors and human population changes in Eurasia between the Last Glacial Maximum and the early Holocene

Archaeological records document a significant expansion of populations from the Last Glacial Maximum (LGM, ~23–19 ka) to the early Holocene (EH, ~9 ka) in Eurasia, which is often attributed to the influence of orbital-scale climate changes. Yet, information remains limited concerning the climatic factor(s) which were responsible for conditioning demographic patterns. Here, in this work, we present results from an improved Minimalist Terrestrial Resource Model (MTRM), forced by a transient climate simulation from the LGM to the EH. Simulated potential hunter-gatherer population densities and spatial distributions across Eurasia are supported by observed archaeological sites in Europe and China. In the low latitudes, potential population size change was predominantly controlled by precipitation and its strong influence on plant and animal resources. In the middle-high latitudes, temperature was the dominant driver in influencing potential population size change and animal resource availability. Different regional responses of potential populations to climate change across Eurasia - owing to variations in available food resources between the LGM and EH - provide a better understanding of human dispersal during the Late Pleistocene.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Assessing uncertainty in the timing of energy use during cost-optimal distributed energy technology selection and sizing

This paper empirically derives uncertainty ranges in cost-optimal solar PV and storage sizing by comparing results from the REopt Lite optimization platform from metered data and a set of simulated Department of Energy Commercial Reference Building (CRB) profiles at 65 sites. We find load profile shape alone does not explain a site’s optimal configurations (i.e., PV, Storage, PV and Storage, No System). Still, load profile shape does introduce uncertainty to optimal PV and storage capacities. Across all cases where PV is part of an optimal configuration, we find the average ratio of power capacities derived from metered loads to capacities derived from CRB profiles to be 0.97 (and as high as 1463), where 1 would be a perfect match in system size. For storage, the ratio is 1.6 (and as high as 42). We also assess how, in the absence of complete metered data, a CRB profile can be selected that would be expected to yield the most similar solar PV and storage capacities. From those metrics that can be available from billing data (i.e., peak demand, monthly load totals), we find that uncertainty is most reduced by selecting the CRB’s with an annual peak occurring at the most similar time, or those with the lowest average root mean square error (RMSE) among monthly peak loads. This research can help improve the implementation and interpretation of results derived from simulated load profiles and is an important next step in advancing smart grid solutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Barren Plateaus Preclude Learning Scramblers

Scrambling processes, which rapidly spread entanglement through many-body quantum systems, are difficult to investigate using standard techniques, but are relevant to quantum chaos and thermalization. In this Letter, we ask if quantum machine learning (QML) could be used to investigate such processes. In this study we prove a no-go theorem for learning an unknown scrambling process with QML, showing that it is highly probable for any variational Ansatz to have a barren plateau landscape, i.e., cost gradients that vanish exponentially in the system size. This implies that the required resources scale exponentially even when strategies to avoid such scaling (e.g., from Ansatz -based barren plateaus or no-free-lunch theorems) are employed. Furthermore, we numerically and analytically extend our results to approximate scramblers. Hence, our work places generic limits on the learnability of unitaries when lacking prior information.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

VOLTTRON/volttron-pnnl-aems

The Autonomous Energy Management Software (AEMS) system will continuously optimize the operations of the distributed energy resources in the small and medium size commercial building by minimizing energy consumption and cost, while providing a solution for maximizing decarbonization benefits from electrification of buildings. Initially, AEMS system will manage rooftop air conditioners and heat pumps but it can be extended in the future to manage, hot water heaters, storage (battery and thermal), electric vehicle charging and monitoring solar photovoltaic. AEMS support both energy efficiency and grid service features.

Bleeker, Amelia [Pacific Northwest National Labora↗
DOE OSTI2020

An Eight-County Appraisal of the San Andres Residual Oil Zone (ROZ) 'Fairway' of the Permian Basin

This document assesses the size and distribution of the oil resource in an eight-county portion of the San Andres residual oil zone (ROZ) fairway in the Permian Basin. Using well log analysis, the study divided the ROZ into partitions, developed a database of geologic properties for each partition and estimated the oil in place in each partition. The study then used the FE/NETL CO 2 Prophet Model to estimate the oil that could be produced and CO 2 stored from applying CO 2 EOR to each partition. With the FE/NETL Onshore CO 2 EOR Cost Model, the commercially viable partitions were identified as those that could produce oil and store CO 2 economically at an oil price of $75/STB. The remaining geologically viable partitions could use CO 2 EOR to store CO 2 with production of oil to offset some of the costs. The database used for this study, and a report describing the database is available on NETL's website under the Collection Name Eight-County San Andres ROZ Appraisal.

02 PETROLEUM↗
DOE OSTI2020

A Four-County Appraisal of the San Andres Residual Oil Zone (ROZ) 'Fairway' of the Permian Basin

This document assesses the size and distribution of the oil resource in a four-county portion of the San Andres residual oil zone (ROZ) fairway in the Permian Basin. Using well log analysis, the study divided the ROZ into partitions, developed a database of geologic properties for each partition and estimated the oil in place in each partition. The study then used the FE/NETL CO 2 Prophet Model to estimate the oil that could be produced and CO 2 stored from applying CO 2 EOR to each partition. With the FE/NETL Onshore CO 2 EOR Cost Model, the commercially viable partitions were identified as those that could produce oil and store CO 2 economically at an oil price of $75/STB. The remaining geologically viable partitions could use CO 2 EOR to store CO 2 with production of oil to offset some of the costs. The database used for this study, and a report describing the database is available on NETL's website under the Collection Name: Four-County San Andres ROZ Appraisal.

02 PETROLEUM↗
DOE OSTI2023

Multi-Unit Dwelling Plug-in EV Charging Innovation Pilots (Final Report)

Nearly one-third of residences in the U.S. are multi-unit dwellings (MUDs), e.g., apartments and condominiums, and MUDs with five or more units account for approximately 45% of rental households. While 80% of EV charging takes place at home, less than 5% of home charging takes place at MUDs. With public electric vehicle (EV) charging still underdeveloped, lack of access to reliable home charging is a major barrier to EV adoption for MUD residents. Challenges to siting electric vehicle supply equipment (EVSE) at MUDs include the high upfront cost of EVSE installation, physical and/or electrical infrastructure constraints, a lack of clear incentives for property managers to invest in installing EV charging for tenants, and a limited number of EV charging service providers that offer solutions adapted to the unique needs of MUDs. Through award DE-EE0008473 from the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE), Center for Sustainable Energy (CSE), Energetics, and Forth, along with a diverse team of partners, led a three-year project to address barriers to EV charging at MUDs by developing an online toolkit geared toward residents, homeowner associations (HOAs), and property managers. The project, referred to as Vehicle Charging Innovations – Multi-Unit Dwellings (VCI-MUD project), engaged stakeholders across the country to identify real and perceived barriers to EV charging at MUDs and explored innovative technologies that attempt to alleviate the identified barriers. Over the course of three and a half years, the project conducted 60 interviews with industry stakeholders, compiled findings in an easy-to-use toolkit, and disseminated the toolkit across national, regional, state, and local channels. Key findings and outcomes of the VCI-MUD project include: Identifying six primary barriers to the installation of EV charging at MUDs; Developing five fact sheets and eight case studies highlighting innovative charging solutions to address barriers, including real-world operational and financial data; Developing a user-friendly, online empowerment toolkit with five important points for “making your pitch” to support EV charging to assist residents, property managers, building managers, and HOAs explore options for MUD charging. The VCI-MUD online toolkit was designed with replicability in mind. It includes general tools and guides to evaluate EV charging demand, gauge readiness for EV charging installation, and develop actionable plans. The fact sheets and case studies highlight the diversity of emerging MUD EV charging solutions, featuring different geographic and structural installation scenarios and providing interested parties with a menu of options, rather than prescribing a one-size-fits-all solution. The following resources are included in the toolkit to provide MUD stakeholders with all the information needed to navigate EV charging installation at their MUD location: Empowerment Toolkit – Easy-to-read FAQ overview, stakeholder roles and responsibilities, and additional resources for MUD EV charging installations; Charging Basics – Glossary of terms and descriptions of charging features, installation and operating expenses; EV Charging Survey Templates – Resident-to-Resident, Property Manager-to-Resident and HOA-to-Resident template letters with pre-populated template questions; Technology Selection Tool – Charging barrier fact sheets and case study examples; Installation Checklist – Submittal document requirements for EVSE installations; MUD Building Self-Evaluation Survey – Self-guided evaluation of potential barriers to EV charging installation at MUD locations; Curbside Resources – Case studies and fact sheets for curbside charging options; Find a Certified Electrician – Approved list of certified EV charging installers; “Right-to-Charge” State Legal References – Legal requirements for charging equipment at MUD locations. The online toolkit was promoted extensively in the final six months of the project and will continue to be disseminated by the Clean Cities Coalitions and other partners after the end of the VCI-MUD project to encourage, support, and demonstrate viable solutions for vehicle charging infrastructure in MUDs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

American-Made Solar Prize: Edgeli Enables DER Integration (CRADA 615) (Final Report)

The purpose of this project was to demonstrate how granular time series data and automated data transformation, and impact assessment tools could speed interconnection approvals for distributed energy resource projects of various types and sizes. Types included community solar, rooftop solar, and EV charging projects. Using software routines to automate the transformation of data (e.g. GIS) to a network database and power flow model then applying scenarios to create hourly (8760) hosting capacity values and voltage and thermal impacts for specific projects, we were able to demonstrate the feasibility of quickly assembling and analyzing key utility data sets for interconnection purposes. The outcomes of this effort will become the foundation for future work that will enhance and encapsulate the software components developed as part of this project, into web services (e.g. APIs) that can be integrated into queue management systems and automate interconnection screening processes.

14 SOLAR ENERGY↗