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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Emerald Connections Weatherization Plus Health Pilot Program

The Emerald Connections Weatherization Plus Health Pilot Program (Healthy Homes Pilot or the pilot), delivered 97 comprehensive energy retrofits to low-income households in two underserved communities: Lynn, Massachusetts (57) and the Beacon Hill neighborhood in Seattle, Washington (40). Designed by Emerald Cities Collaborative (ECC) and funded via a U.S. Department of Energy (DOE) Weatherization Assistance Program (WAP) Enhancement and Innovation (E&I) grant, ECC created the pilot to expand the reach and range of services typically available to participating WAP households.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Reducing Deferrals by Integrating Health Homes with Weatherization

The U.S. Department of Energy’s Weatherization Assistance Program (WAP) improves energy efficiency and household health for low-income families, yet a substantial number of otherwise eligible homes are deferred from due to health and safety concerns in their homes, including mold, moisture damage, or structural deficiencies. These deferred homes are often occupied by marginalized or otherwise vulnerable residents who may be exposed to elevated indoor air pollutant concentration. Integrating Healthy Homes (HH) interventions with weatherization has been proposed as a strategy to reduce deferrals, address environmental justice concerns, and improve health outcomes. However, limited data on the health and economic implications of such integration exist. This study aimed to assess the potential health benefits and savings-to-investment ratio (SIR) associated with integrating Healthy Homes interventions into weatherization programs for homes typically deferred from WAP services. We collected indoor air pollutant data from homes undergoing health home renovations, including fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), carbon monoxide (CO), and formaldehyde, with sampling times up to one month. Except for fomaldehyde, which was measured using passive UMEx badges, the other metrics were measured using the airQ Pro indoor air quality monitor.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1994

Ice sheet topography from retracked ERS-1 altimetry

An objective of the ERS-1 radar altimeter is to measure the surface topography of the polar ice sheets to a precision on the order of a meter. ERS-1 Waveform Altimeter Product (WAP) data was corrected for several processing errors. A range correction from the WAP waveforms, using the multiparameter retracking algorithm to account for range tracking limitations inherent to radar altimetry, was derived. From crossover analysis, the resulting precision is shown to be about 2.1 m in ocean mode and 2.2 m in ice mode. A topography map, produced with 23 days of corrected data, shows details of the western part of west Antarctic ice sheet and part of the Ross ice shelf including ice divides, ice stream boundaries, and ice shelf grounding lines.

Zwally, H. Jay↗
NASA NTRSDate not supplied

Wi-Fi Signal Survey of the International Space Station by Autonomous Free-Flying Robot

This paper analyzes Wi-Fi signal propagation inside pressurized modules of the International Space Station (ISS). Various flight datasets were collected by the Astrobee fleet of autonomous free-flying robots developed by the NASA Ames Research Center (ARC). The enclosed module spaces of the ISS pose unique challenges for Wi-Fi signal propagation, and understanding these challenges is crucial for optimizing connectivity in such environments. The survey data presented are valuable for optimizing wireless access point (WAP) locations and conditions. A computational method is developed to analyze the wireless communication system, RF coverage, and module compositions. The method is both rigorous and practical for assessing the ISS wireless system performance. The computational tools in this paper serve as a complementary approach to direct, on-orbit measurements, which is a complicated and expensive task. In some operational scenarios, ground measurements may be intractable due to the size of the spacecraft. Results from this research will aid future space missions and commercial spacecraft, providing insights into optimal WAP placements and robust wireless communication systems.

Astrobee↗
NASA NTRSDate not supplied

Wi-Fi Signal Survey of the International Space Station by Autonomous Free-Flying Robot

This paper analyzes Wi-Fi signal propagation inside pressurized modules of the International Space Station (ISS). Various flight datasets were collected by the Astrobee fleet of autonomous free-flying robots developed by the NASA Ames Research Center (ARC). The enclosed module spaces of the ISS pose unique challenges for Wi-Fi signal propagation, and understanding these challenges is crucial for optimizing connectivity in such environments. The survey data presented are valuable for optimizing wireless access point (WAP) locations and conditions. A computational method is developed to analyze the wireless communication system, RF coverage, and module compositions. The method is both rigorous and practical for assessing the ISS wireless system performance. The computational tools in this paper serve as a complementary approach to direct, on-orbit measurements, which is a complicated and expensive task. In some operational scenarios, ground measurements may be intractable due to the size of the spacecraft. Results from this research will aid future space missions and commercial spacecraft, providing insights into optimal WAP placements and robust wireless communication systems.

International Space Station↗
DOE OSTI2023

Building for Growth: Weatherization Updates from NREL

Our NREL team (Jal Desai, Juliana Williams, and Cory Chovanec) will discuss recent and future projects at the National Renewable Energy Laboratory in support to the U.S Department of Energy's Weatherization Assistance Program (WAP). NREL staff will provide updates on several initiatives, including worker credentials, Standard Work Specifications, visualization resources, and more! Be prepared to provide feedback and share new ideas in pursuit of continuous improvement within WAP.

continuous improvement↗
DOE OSTI2024

New Pathways for Equitable Solar Adoption in Texas

As part of the SEIN Round 3 program, a diverse group of energy stakeholders in Texas set out to develop and pilot new pathways to increase rooftop solar adoption at no upfront cost to lowincome households. One potentially promising pathway we identified involved combining funding from existing utility and federal programs promoting weatherization and energy efficiency. Our objective was to demonstrate pilot projects that equitably deployed rooftop solar to properties owned or rented by families in disadvantaged communities. Our goal was to create a clear path for lowincome households to achieve electricity bill relief and to access clean energy by leveraging existing utility energy efficiency programs with existing federal resources, such as the U.S. Department of Health and Human Services (HHS) Low-Income Home Energy Assistance Program (LIHEAP) and/or U.S. Department of Energy (DOE) Weatherization Assistance Program (WAP) funding in Texas. This has been attempted in a few other states with varying degrees of success, but not yet in Texas.

14 SOLAR ENERGY↗
DOE OSTI2024

Determination of Reportable Radionuclides for Defense Waste Processing Facility (DWPF) Sludge Batch 10 (Macrobatch 12)

Savannah River National Laboratory (SRNL) was tasked with the radionuclide characterization of the Sludge Batch 10 (SB10) Tank 40 sample (HTF-40-23-24) in accordance with requirements for reporting the Waste Acceptance Product Specifications (WAPS). The Defense Waste Processing Facility (DWPF) is required to report all radionuclides with half-lives greater than ten years and which comprise greater than 0.05% of the total activity inventory for a given waste form at certain specified “index years”. DWPF complies with the requirements by considering the half-life requirement (t1/2 > 10 years) and radionuclides with concentrations greater than 0.01% of the total inventory from the approximate time of production through 1,100 years.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Characterization of Precipitate Reactor Feed Tank (PRFT) Batches 15, 22, and 26 from the Defense Waste Processing Facility (DWPF)

The Savannah River Site (SRS) Defense Waste Processing Facility (DWPF) processes a Monosodium Titanate/Sludge Solids (MST/SS) waste stream received from the Salt Waste Processing Facility (SWPF) via the Precipitate Reactor Feed Tank (PRFT). During processing, DWPF is required to provide evidence of compliance with the Waste Acceptance Product Specifications (WAPS) to ensure acceptance of their vitrified high-level waste (HLW) into the Civilian Radioactive Waste Management System. Production Records must document the constituents of the MST/SS material in the PRFT from each salt batch (StB) processed at SWPF. Savannah River Mission Completion (SRMC) has requested Savannah River National Laboratory (SRNL) to analyze PRFT samples representing each SWPF salt batch for thirty-two radionuclides. Additionally, elemental analysis of PRFT slurry and MST/SS solids was performed to aid SRMC in further refinement of the inputs and assumptions used in future frit development and Material Tracking Program calculations. The analyses of PRFT Batches 15, 22, and 26, which corresponds to material from the processing of StB4, StB5, and StB7, respectively, are reported herein. The unwashed dried solids of the PRFT batches were found to be 86-87% MST. Additionally, the total sulfur values are well below the assumed 982 mg of sulfate/kg of PRFT slurry used in Material Tracking Program calculations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Characterization of Precipitate Reactor Feed Tank (PRFT) Batches 44 and 49 from the Defense Waste Processing Facility (DWPF)

The Savannah River Site (SRS) Defense Waste Processing Facility (DWPF) processes a Monosodium Titanate/Sludge Solids (MST/SS) waste stream received from the Salt Waste Processing Facility (SWPF) via the Precipitate Reactor Feed Tank (PRFT). During processing, DWPF is required to provide evidence of compliance with the Waste Acceptance Product Specifications (WAPS). Savannah River Mission Completion (SRMC) has requested Savannah River National Laboratory (SRNL) to analyze PRFT samples representing each SWPF salt batch for thirty-two radionuclides. Additionally, elemental analysis of PRFT slurry and MST/SS solids was performed to aid SRMC in further refinement of the inputs and assumptions used in future frit development and Material Tracking Program calculations. The analyses of PRFT Batches 44 and 49, which correspond to material from the processing of Salt Batches (StB) 12 and 11, respectively, are reported herein. The unwashed dried solids of the PRFT Batches 44 and 49 are predominately MST, ~63-59% MST. The two batches have a much higher amount of Fe, Mn, and Ni compared to all previous batches. For Batch 44 this appears to be due to the use of a sludge simulant filter aid during processing of StB 12 and for Batch 49, it is possibly due to the larger amount of insoluble solids for StB 11 in comparison to all previous salt batches. Like previous PRFT batches, a significant amount of the unwashed dried solids are alkaline earth metals. The total sulfate, in mg/kg of slurry, for PRFT Batches 44 and 49 is 119 and 139, respectively, which is well below the current sulfate concentration used in Material Tracking Program calculations and is in agreement with DWPF laboratory sulfate measurements.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

A Novel Architecture for Attack-Resilient Wide-Area Protection and Control System in Smart Grid

Wide-area protection and control (WAPAC) systems are widely applied in the energy management system (EMS) that rely on a wide-area communication network to maintain system stability, security, and reliability. As technology and grid infrastructure evolve to develop more advanced WAPAC applications, however, so do the attack surfaces in the grid infrastructure. This paper presents an attack-resilient system (ARS) for the WAPAC cybersecurity by seamlessly integrating the network intrusion detection system (NIDS) with intrusion mitigation and prevention system (IMPS). In particular, the proposed NIDS utilizes signature and behavior-based rules to detect attack reconnaissance, communication failure, and data integrity attacks. Further, the proposed IMPS applies state transition-based mitigation and prevention strategies to quickly restore the normal grid operation after cyberattacks. As a proof of concept, we validate the proposed generic architecture of ARS by performing experimental case study for wide-area protection scheme (WAPS), one of the critical WAPAC applications, and evaluate the proposed NIDS and IMPS components of ARS in a cyber-physical testbed environment. Our experimental results reveal a promising performance in detecting and mitigating different classes of cyberattacks while supporting an alert visualization dashboard to provide an accurate situational awareness in real-time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

A Cyber-Physical Anomaly Detection for Wide-Area Protection Using Machine Learning

Wide-area protection scheme (WAPS) provides system-wide protection by detecting and mitigating small and large-scale disturbances that are difficult to resolve using local protection schemes. As this protection scheme is evolving from a substation-based distributed remedial action scheme (DRAS) to the control center-based centralized RAS (CRAS), it presents severe challenges to their cybersecurity because of its heavy reliance on an insecure grid communication, and its compromise would lead to system failure. This article presents an architecture and methodology for developing a cyber-physical anomaly detection system (CPADS) that utilizes synchrophasor measurements and properties of network packets to detect data integrity and communication failure attacks on measurement and control signals in CRAS. The proposed machine leaning-based methodology applies a rules-based approach to select relevant input features, utilizes variational mode decomposition (VMD) and decision tree (DT) algorithms to develop multiple classification models, and performs final event identification using a rules-based decision logic. Here, we have evaluated the proposed methodology of CPADS using the IEEE 39 bus system for several performance measures (accuracy, recall, precision, and F-measure) in a cyber-physical testbed environment. Furthermore, our experimental results reveal that the proposed algorithm (VMD-DT) of CPADS outperforms the existing machine learning classifiers during noisy and noise-free measurements while incurring an acceptable processing overhead.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Analysis Of The Sludge Batch 7b (Macrobatch 9) DWPF Pour Stream Glass Sample (Rev. 1)

The Defense Waste Processing Facility (DWPF) began processing Sludge Batch 7b (SB7b), also referred to as Macrobatch 9 (MB9), in January 2012. SB7b is a blend of the heel of Tank 40 from Sludge Batch 7a (SB7a) and the SB7b material that was transferred to Tank 40 from Tank 51. SB7b was processed using Frit 418. During processing of each sludge batch, the DWPF is required to take at least one glass sample to meet the objectives of the Glass Product Control Program (GPCP), which is governed by the DWPF Waste Form Compliance Plan, and to complete the necessary Production Records so that the final glass product may be disposed of at a Federal Repository. Two pour stream glass samples were collected while processing SB7b. The samples were transferred to the Savannah River National Laboratory (SRNL) where one was analyzed and the other was archived. The following conclusions were drawn from the analytical results provided in this report: The sum of oxides for the official SB7b pour stream glass is within the Product Composition Control System (PCCS) limits (95-105 wt%); The average calculated Waste Dilution Factor (WDF) for SB7b is 2.3. In general, the measured radionuclide content of the official SB7b pour stream glass is in good agreement with the calculated values from the Tank 40 dried sludge results from the SB7b Waste Acceptance Program Specification (WAPS) sample; As in previous pour stream samples, ruthenium and rhodium inclusions were detected by Scanning Electron Microscopy-Electron Dispersive Spectroscopy (SEM-EDS) in the SB7b pour stream sample; The Product Consistency Test (PCT) results indicate that the official SB7b pour stream glass meets the waste acceptance criteria for durability with a normalized boron release of 0.8 g/L, which is an order of magnitude less than the Environmental Assessment (EA) glass; The measured density of the SB7b pour stream glass was 2.70 g/cm 3 ; The Fe 2+ /ΣFe ratio of the SB7b pour stream samples was 0.07.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Multifamily Building Stock Modeling: Cooperative Research and Development Final Report, CRADA Number CRD-17-00701

U.S. multifamily buildings house 35 million households, consuming 4 quads of source energy and spending $48 billion on utility bills every year. Almost all of these households live in urban areas, where cities are taking the lead on setting aggressive energy goals. Cities currently do not have the data and tools necessary to identify and target opportunities to save energy in their building stock. Building on the open-source, OpenStudio-based ResStock platform, this project will extend the publicly-available ResStock modeling capabilities to the multifamily sector, enabling Radiant Labs, and others, to partner with cities to market and strategically deploy cost-effective, energy efficiency (EE) upgrades directly to high-priority households. Radiant Labs has been successful in using ResStock's single-family capabilities to provide value to the City of Boulder, Colorado. However, lack of multifamily capabilities in ResStock is a roadblock for Radiant Labs working with New York City, San Francisco, Washington, D.C., and other cities that have expressed significant interest in working with them. In addition, other cities, companies, and utilities can use these open-source capabilities to grow their EE portfolios, thereby multiplying the impact of this project. This work also enables national-scale analysis of EE potential in multifamily buildings, which is of strong interest to a variety of stakeholders, including the U.S. Department of Energy (DOE) Office of Energy Policy and Systems Analysis (EPSA), DOE Weatherization Assistance Program (WAP), U.S. Department of Housing and Urban Development (HUD), and the Bonneville Power Administration (BPA).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Analysis of the sludge batch 9 (Macrobatch 10) DWPF pour stream glass sample

A pour stream (PS) sample taken during processing of Sludge Batch 8 (SB8, Macrobatch 10) was analyzed by Savannah River National Laboratory (SRNL) to verify compliance with the Defense Waste Processing Facility (DWPF) Glass Product Control Program. The following conclusions were drawn from these analyses; The sum of oxides for the SB8 PS glass (97.41 wt%) is within the Product Composition Control System (PCCS) limits (100 ± 5 wt%); The average Waste Dilution Factor (WDF) calculated from the Tank 40 dried sludge analysis results for SB8 is 1.9 ± 0.1. In general, the radionuclide concentration of the SB8 PS glass sample calculated using this WDF is in good agreement with the measured radionuclide content; The Product Consistency Test (PCT) results indicate that the SB8 PS glass meets the Waste Acceptance Product Specifications (WAPS) for durability, with normalized release rates for boron, lithium and sodium all at least two standard deviations lower than those of the Environmental Assessment (EA) glass; The average measured density of the SB8 PS glass is 2.72 g/cm 3 , consistent with previous PS samples; and, The average measured Fe 2+ /ΣFe ratio of the SB8 PS glass is 0.15, within the target range of 0.09- 0.33, and closely resembling the predicted REDOX value of 0.15.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Remote Handled Hot Cell Facility and Other Research Transuranic Waste (Debris)

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 Sandia National Laboratories/New Mexico (SNL/NM) in Albuquerque, New Mexico. The waste described in this report was predominately generated in the SNL/NM Hot Cell Facility (HCF) during the removal and packaging of experimental material and decontamination operations in Building 6580 at Technical Area (TA)-V. The waste stream also includes a very small amount of waste (estimated at less than 1 gram of fuel similar to that used for research at the HCF) originating from classified research at TA-I. In addition, the waste also includes secondary waste termed by SNL/NM as process generated waste (PGW), created during repackaging operations for this waste at the Auxiliary Hot Cell Facility (AHCF). The waste has been stored at the Sandia Pulsed Reactor (SPR) Dense Pack Storage Facility within TA-V or the Manzano Bunkers located at Manzano Base within Kirtland Air Force Base. All of the waste is being repackaged at the AHCF. This report was prepared in accordance with CCP-TP-005, CCP Acceptable Knowledge Documentation (Reference 1), to implement the AK requirements of DOE/WIPP-02-3214, Remote-Handled TRU Waste Characterization Program Implementation Plan (WCPIP) (Reference 2); Waste Isolation Pilot Plant Hazardous Waste Facility Permit, Waste Analysis Plan (WIPP-WAP) (Reference 3); and DOE/WIPP-02-3122, Transuranic Waste Acceptance Criteria for the Waste Isolation Pilot Plant (WIPP-WAC) (Reference 4).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗