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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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12 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Space Shuttle main engine powerhead structural modeling, stress and fatigue life analysis. Volume 3: Stress summay of blades and nozzles at FPL and 115 percent RPL loads. SSME HPFTP and HPOTP blades and nozzles

Gasdynamic environments applied to the turbine blades and nozzles of the HPFTP and HPOTP were analyzed. Centrifugal loads were applied to blades to account for the pump rotation of FPL and 115 percent RPL. The computer models used in the blade analysis with results presented in the form of temperature and stress contour plots are described. Similar information is given for the nozzles.

Hammett, J. C.↗
DOE OSTI2025

Floatable Protective Layers: a Strategy to Minimize Solid Electrolyte Interphase Growth and Maximize the Lithium Utilization

Abstract Maximizing lithium (Li) utilization is crucial for enhancing the long‐term stability of Li‐based batteries. In anode‐free Li batteries (AFLBs), although the initial formation of solid electrolyte interphase (SEI) is beneficial on limiting further reaction between Li and electrolyte, large volume change of Li metal anode (LMA) during cycling often leads to continuous breakdown and re‐formation of SEI and formation of inactive Li, hindering its efficiency. In this study, a novel strategy is presented to protect Li metal by applying a floatable protection layer (FPL) on a copper substrate, enabling large Li particles to be primarily deposited below FPL, but SEI to be primarily formed above FPL. This approach effectively minimizes the direct contact between electrolyte and freshly deposited Li, therefore mitigating the continuous side reactions and early failure of AFLBs. As a result, Li consumption is minimized, and the overall stability of the battery is significantly enhanced. Further development of this approach can also be used to improve the performance of other Li‐based batteries for large‐scale applications.

Lim, Hyung‐Seok [Energy and Environment Directorat↗
NASA NTRS2011

Validation of Methods to Predict Vibration of a Panel in the Near Field of a Hot Supersonic Rocket Plume

This paper describes the measurement and analysis of surface fluctuating pressure level (FPL) data and vibration data from a plume impingement aero-acoustic and vibration (PIAAV) test to validate NASA s physics-based modeling methods for prediction of panel vibration in the near field of a hot supersonic rocket plume. For this test - reported more fully in a companion paper by Osterholt & Knox at 26th Aerospace Testing Seminar, 2011 - the flexible panel was located 2.4 nozzle diameters from the plume centerline and 4.3 nozzle diameters downstream from the nozzle exit. The FPL loading is analyzed in terms of its auto spectrum, its cross spectrum, its spatial correlation parameters and its statistical properties. The panel vibration data is used to estimate the in-situ damping under plume FPL loading conditions and to validate both finite element analysis (FEA) and statistical energy analysis (SEA) methods for prediction of panel response. An assessment is also made of the effects of non-linearity in the panel elasticity.

Bremner, P. G.↗
DOE OSTI2026

Study the Protection Improvements for a Weak Grid Area With High IBRs

NLR is collaborating with Florida Power & Light (FPL) and GE to investigate power system stability and protection reliability challenges in a weak-grid region with high penetration of inverter-based resources (IBRs). This presentation will primarily focus on the protection aspects of the study. We will share key insights from this real-world project, including best practices for developing high-fidelity fault study models, establishing a controller-hardware-in-the-loop (CHIL) platform for testing physical relays, identifying system-level protection challenges, and designing enhanced protection schemes to address those issues. Through this discussion, the audience will gain practical understanding of protection studies in IBR-dominated systems, the emerging challenges associated with reduced fault current and altered transient behavior, and effective mitigation strategies. In particular, we will highlight the critical importance of IBR compliance with IEEE 2800-2022 to ensure dependable and secure protection relay operation in modern transmission systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1985

Fuel and oxidizer turbine loss analysis

The turbine losses for the fuel and oxidizer turbines at the FPL condition were assessed by a quasi-3D loss analysis method. This loss analysis method uses two flow codes - MERIDL and TSONIC - to calculate the flow velocities along the blade surfaces and endwalls. The velocities are then used as input to the boundary layer code - BLAYER - to calculate the friction losses due to incidence, secondary flow, and tip clearance. The loss analysis for the fuel turbine indicated an overall two-stage efficiency of about 90%. The largest loss was due to rotor tip clearance. The loss analysis for the oxidizer turbine is nearly completed. Results for the first stage of the two-stage design indicates an efficiency of about 80%, with high losses due to rotor incidence and blade and endwall friction.

Haas, J. E.↗
NASA NTRS1985

Redistribution of the inlet temperature profile through the SSME fuel turbine

A three-dimensional Euler code was used to predict radial inlet temperature profile redistribution through the two-stage fuel turbopump turbine. The calculation was made at the FPL condition using a turbine inlet radial temperature profile. This same calculation was made earlier on single-stage turbine. There was a redistribution of the temperature profile such that the hotter gas that originated at the midspan region at the turbine inlet was shifted to the hub and tip regions on the blade pressure surface at the rotor exit. For the SSME fuel turbine, however, there was no redistribution of the inlet temperature profile. No strong secondary flow patterns were identified. It is indicated that this trend is attributed to the high solidity SSME blading.

Schwab, J. R.↗
NASA NTRS1985

Analytical study of flow phenomena in SSME turnaround duct geometries

The SSME fuel turbopump hot gas manifold was identified as a source of loss and flow distortion which significantly affects the performance and durability of both the drive turbine and the LOX injector area of the main combustion chamber. Two current SSME geometries were studied, the full power level (FPL) and the first manned orbital flight (FMOF) configuration. The effects of turnaround duct geometry on flow losses and distortions, by varying wall curvature and flow area variation in the 180 deg turnaround region were examined. The effects of the duct inlet flow phenomena such as the radial distortion of the inlet flow and inlet swirl level on turnaround duct performance were also investigated. It is shown that of the two current geometries, the FMOF configuration had lower pressure losses and generated less flow distortion, but had a small flow separation bubble at the 180 deg turnaround exit. It is found that by optimizing wall curvature and flow diffusion in the turnaround, improved duct performance can be achieved.

Mclallin, K. L.↗
NASA NTRS1989

Space Shuttle Main Engine structural analysis and data reduction/evaluation. Volume 7: High pressure fuel turbo-pump third stage impeller analysis

This volume summarizes the analysis used to assess the structural life of the Space Shuttle Main Engine (SSME) High Pressure Fuel Turbo-Pump (HPFTP) Third Stage Impeller. This analysis was performed in three phases, all using the DIAL finite element code. The first phase was a static stress analysis to determine the mean (non-varying) stress and static margin of safety for the part. The loads involved were steady state pressure and centrifugal force due to spinning. The second phase of the analysis was a modal survey to determine the vibrational modes and natural frequencies of the impeller. The third phase was a dynamic response analysis to determine the alternating component of the stress due to time varying pressure impulses at the outlet (diffuser) side of the impeller. The results of the three phases of the analysis show that the Third Stage Impeller operates very near the upper limits of its capability at full power level (FPL) loading. The static loading alone creates stresses in some areas of the shroud which exceed the yield point of the material. Additional cyclic loading due to the dynamic force could lead to a significant reduction in the life of this part. The cyclic stresses determined in the dynamic response phase of this study are based on an assumption regarding the magnitude of the forcing function.

Pool, Kirby V.↗
NASA NTRS1989

SSME structural dynamic model development

The high pressure fuel turbopump (HPFTP) is a major component of the Space Shuttle Main Engine (SSME) powerhead. The device is a three stage centrifugal pump that is directly driven by a two stage hot gas turbine. The purpose of the pump is to deliver fuel (liquid hydrogen) from the low pressure fuel turbopump (LPFTP) through the main fuel valve (MFV) to the thrust chamber coolant circuits. In doing so, the pump pressurizes the fuel from an inlet pressure of approximately 178 psi to a discharge pressure of over 6000 psi. At full power level (FPL), the pump rotates at a speed of over 37,000 rpm while generating approximately 77,000 horsepower. Obviously, a pump failure at these speeds and power levels could jeopardize the mission. Results are summarized for work in which the solutions obtained from analytical models of the fuel turbopump impellers are compared with the results obtained from dynamic tests.

Foley, Michael J.↗
DOE OSTI2025

Analysis of a Disturbance Event with Inverter-Based Resources Using EMT Simulations

Increasing penetration of inverter-based resources (IBRs) necessitates newer methods of planning and analysis of disturbances. The existing phasor-domain transient stability (TS) analysis may not capture the dynamics of IBRs during fault events. Here, in this paper, electromagnetic transient (EMT) simulations using high-fidelity detailed model of power grid and one of the affected photovoltaic (PV) plants during the Angeles Forest disturbance in 2018 are performed. In these simulations, the processes to develop EMT models of power grid from traditional phasor-domain TS data and PV plant from collected data are described. Thereafter, using these simulations, the response of the PV plant during the fault event in 2018 is replicated and a sensitivity analysis is performed. The sensitivity analysis consists of making changes to the components within the PV plant and in the power grid to evaluate the impact they have on the response observed by the PV plant during the fault event. This analysis provides an understanding of the components that impact the operation of a PV plant during fault events and provide guidance to system planners on the studies that need to be performed to maintain a reliable power grid as new IBR plants are integrated.

42 ENGINEERING↗
DOE OSTI2020

Low-Income Energy Affordability Data - LEAD Tool - 2018 Update

The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low- and moderate-income (LMI) communities they serve. The LEAD Tool provides estimated LMI household energy data based on income, energy expenditures, fuel type, housing type, and geography, which stakeholders can use to make data-driven decisions when planning for their energy goals. From the LEAD Tool website, users can also create and download customized heat-maps and charts for various geographies, housing, and energy characteristics. Datasets are available for 50 states plus Puerto Rico and Washington D.C., along with their cities, counties, and census tracts. The file below, "1. Description of Files," provides a list of all files included in this dataset. A description of the abbreviations and units used in the LEAD Tool data can be found in the file below titled "2. Data Dictionary 2018". The Low-Income Energy Affordability Data comes primarily from the 2018 U.S. Census American Community Survey 5-Year Public Use Microdata Samples and is calibrated to 2018 U.S. Energy Information Administration electric utility (Survey Form-861) and natural gas utility (Survey Form-176) data. The methodology for the LEAD Tool can viewed below (3. Methodology Document). For more information, and to access the interactive LEAD Tool platform, please visit: https://www.energy.gov/eere/slsc/low-income-energy-affordability-data-lead-tool For more information on the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA), visit: https://betterbuildingsinitiative.energy.gov/accelerators/clean-energy-low-income-communities

affordability↗
DOE OSTI2024

Low-Income Energy Affordability Data - LEAD Tool - 2022 Update

The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low- and moderate-income (LMI) communities they serve. The LEAD Tool provides estimated LMI household energy data based on income, energy expenditures, fuel type, housing type, and geography, which stakeholders can use to make data-driven decisions when planning for their energy goals. From the LEAD Tool website, users can also create and download customized heat-maps and charts for various geographies, housing, energy characteristics, and population demographics and educational attainment. Datasets are available for 50 states plus Puerto Rico and Washington D.C., along with their cities, counties, and census tracts, as well as tribal areas. The file below, "01. Description of Files," provides a list of all files included in this dataset. A description of the abbreviations and units used in the LEAD Tool data can be found in the file below titled "02. Data Dictionary 2022". A list of geographic regions used in the LEAD Tool can be found in files 04-11. The Low-Income Energy Affordability Data comes primarily from the 2022 U.S. Census American Community Survey 5-Year Public Use Microdata Samples and is calibrated to 2022 U.S. Energy Information Administration electric utility (Survey Form-861) and natural gas utility (Survey Form-176) data. The methodology for the LEAD Tool can viewed below (3. Methodology Document). For more information, and to access the interactive LEAD Tool platform, please visit the "10. LEAD Tool Platform" resource link below. For more information on the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA), please visit the "11. CELICA Website" resource below.

AMI↗