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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 1,351 records · Page 75

Spacecraft Trajectory Analysis and Mission Planning Simulation (STAMPS) Software

STAMPS simulates either three- or six-degree-of-freedom cases for all spacecraft flight phases using translated HAL flight software or generic GN&C models. Single or multiple trajectories can be simulated for use in optimization and dispersion analysis. It includes math models for the vehicle and environment, and currently features a "C" version of shuttle onboard flight software. The STAMPS software is used for mission planning and analysis within ascent/descent, rendezvous, proximity operations, and navigation flight design areas.

Puckett, Nancy↗

Preliminary MIPCC Enhanced F-4 and F-15 Preformance Characteristics for a First Stage Reusable Launch Vehicle

Performance increases in turbojet engines can theoretically be achieved through Mass Injection Pre-Compressor Cooling (MIPCC), a process involving injecting water or oxidizer or both into an afterburning turbojet engine. The injection of water results in pre-compressor cooling, allowing the propulsion system to operate at high altitudes and Mach numbers. In this way, a MIPCC-enhanced turbojet engine could be used to power the first stage of a reusable launch vehicle or be integrated into an existing aircraft that could launch a 100-lbm payload to a reference 100-nm altitude orbit at 28 deg inclination. The two possible candidates for MIPCC flight demonstration that are evaluated in this study are the F-4 Phantom II airplane and the F-15 Eagle airplane (both of McDonnell Douglas, now The Boeing Company, Chicago, Illinois), powered by two General Electric Company (Fairfield, Connecticut) J79 engines and two Pratt & Whitney (East Hartford, Connecticut) F100-PW-100 engines, respectively. This paper presents a conceptual discussion of the theoretical performance of each of these aircraft using MIPCC propulsion techniques. Trajectory studies were completed with the Optimal Trajectories by Implicit Simulation (OTIS) software (NASA Glenn Research Center, Cleveland, Ohio) for a standard F-4 airplane and a standard F-15 airplane. Standard aircraft simulation models were constructed, and the thrust in each was altered in accordance with estimated MIPCC performance characteristics. The MIPCC and production aircraft model results were then reviewed to assess the feasibility of a MIPCC-enhanced propulsion system for use as a first-stage reusable launch vehicle; it was determined that the MIPCC-enhanced F-15 model showed a significant performance advantage over the MIPCC-enhanced F-4 model.

Air Breathing Launch Systems↗

Preliminary MIPCC Enhanced F-4 and F-15 Performance Characteristics for a First Stage Reusable Launch Vehicle

Performance increases in turbojet engines can theoretically be achieved through Mass Injection Pre-Compressor Cooling (MIPCC), a process involving injecting water or oxidizer or both into an afterburning turbojet engine. The injection of water results in pre-compressor cooling, allowing the propulsion system to operate at high altitudes and Mach numbers. In this way, a MIPCC-enhanced turbojet engine could be used to power the first stage of a reusable launch vehicle or be integrated into an existing aircraft that could launch a 100-lbm payload to a reference 100-nm altitude orbit at 28 deg inclination. The two possible candidates for MIPCC flight demonstration that are evaluated in this study are the F-4 Phantom II airplane and the F-15 Eagle airplane (both of McDonnell Douglas, now The Boeing Company, Chicago, Illinois), powered by two General Electric Company (Fairfield, Connecticut) J79 engines and two Pratt & Whitney (East Hartford, Connecticut) F100-PW-100 engines, respectively. This paper presents a conceptual discussion of the theoretical performance of each of these aircraft using MIPCC propulsion techniques. Trajectory studies were completed with the Optimal Trajectories by Implicit Simulation (OTIS) software (NASA Glenn Research Center, Cleveland, Ohio) for a standard F-4 airplane and a standard F-15 airplane. Standard aircraft simulation models were constructed, and the thrust in each was altered in accordance with estimated MIPCC performance characteristics. The MIPCC and production aircraft model results were then reviewed to assess the feasibility of a MIPCC-enhanced propulsion system for use as a first-stage reusable launch vehicle; it was determined that the MIPCC-enhanced F-15 model showed a significant performance advantage over the MIPCC-enhanced F-4 model.

MIPCC Reusable Launch Vehicle↗

Designing, Modeling, Constructing, and Testing a Flat Panel Speaker and Sound Diffuser for a Simulator

The goal of this project was to design, model, build, and test a flat panel speaker and frame for a spherical dome structure being made into a simulator. The simulator will be a test bed for evaluating an immersive environment for human interfaces. This project focused on the loud speakers and a sound diffuser for the dome. The rest of the team worked on an Ambisonics 3D sound system, video projection system, and multi-direction treadmill to create the most realistic scene possible. The main programs utilized in this project, were Pro-E and COMSOL. Pro-E was used for creating detailed figures for the fabrication of a frame that held a flat panel loud speaker. The loud speaker was made from a thin sheet of Plexiglas and 4 acoustic exciters. COMSOL, a multiphysics finite analysis simulator, was used to model and evaluate all stages of the loud speaker, frame, and sound diffuser. Acoustical testing measurements were utilized to create polar plots from the working prototype which were then compared to the COMSOL simulations to select the optimal design for the dome. The final goal of the project was to install the flat panel loud speaker design in addition to a sound diffuser on to the wall of the dome. After running tests in COMSOL on various speaker configurations, including a warped Plexiglas version, the optimal speaker design included a flat piece of Plexiglas with a rounded frame to match the curvature of the dome. Eight of these loud speakers will be mounted into an inch and a half of high performance acoustic insulation, or Thinsulate, that will cover the inside of the dome. The following technical paper discusses these projects and explains the engineering processes used, knowledge gained, and the projected future goals of this project

Dillon, Christina↗

Full System Modeling and Validation of the Carbon Dioxide Removal Assembly

The Atmosphere Revitalization Recovery and Environmental Monitoring (ARREM) project was initiated in September of 2011 as part of the Advanced Exploration Systems (AES) program. Under the ARREM project, testing of sub-scale and full-scale systems has been combined with multiphysics computer simulations for evaluation and optimization of subsystem approaches. In particular, this paper describes the testing and modeling of various subsystems of the carbon dioxide removal assembly (CDRA). The goal is a full system predictive model of CDRA to guide system optimization and development. The development of the CO2 removal and associated air-drying subsystem hardware under the ARREM project is discussed in a companion paper.

Coker, Robert↗

Modeling of Revitalization of Atmospheric Water

The Atmosphere Revitalization Recovery and Environmental Monitoring (ARREM) project was initiated in September of 2011 as part of the Advanced Exploration Systems (AES) program. Under the ARREM project, testing of sub-scale and full-scale systems has been combined with multiphysics computer simulations for evaluation and optimization of subsystem approaches. In particular, this paper describes the testing and modeling of the water desiccant subsystem of the carbon dioxide removal assembly (CDRA). The goal is a full system predictive model of CDRA to guide system optimization and development.

Coker, Robert↗

Computer Simulation and Modeling of CO2 Removal Systems for Exploration 2013-2014

The Atmosphere Revitalization Recovery and Environmental Monitoring (ARREM) project was initiated in September of 2011 as part of the Advanced Exploration Systems (AES) program. Under the ARREM project and the follow-on Life Support Systems (LSS) project, testing of sub-scale and full-scale systems has been combined with multiphysics computer simulations for evaluation and optimization of subsystem approaches. In particular, this paper will describes the testing and 1-D modeling of the combined water desiccant and carbon dioxide sorbent subsystems of the carbon dioxide removal assembly (CDRA). The goal is a full system predictive model of CDRA to guide system optimization and development.

Coker, R.↗

Evaluation and Validation of Organic Materials for Advanced Stirling Convertors (ASCs): Overview

Various organic materials are used as essential parts in Stirling Convertors for their unique properties and functionalities such as bonding, potting, sealing, thread locking, insulation, and lubrication. More efficient Advanced Stirling Convertors (ASC) are being developed for future space applications especially with a long mission cycle, sometimes up to 17 years, such as deep space exploration or lunar surface power or Mars rovers, and others. Thus, performance, durability, and reliability of those organics should be critically evaluated in every possible material-process-fabrication-service environment relations based on their mission specifications. In general, thermal stability, radiation hardness, outgassing, and material compatibility of the selected organics have been systematically evaluated while their process and fabrication conditions and procedures were being optimized. Service environment-simulated long term aging tests up to 4 years were performed as a function of temperature for durability assessment of the most critical organic material systems.

Validation↗

A Singular Value Decomposition Framework for Retrievals with Vertical Distribution Information from Greenhouse Gas Column Absorption Spectroscopy Measurements

We describe a variation of the Optimal Estimation (OE) method for greenhouse gas remote sensing retrievals using a singular value decomposition (SVD) and an uninformative prior. The SVD method is capable of discerning vertical information in column integrated absorption measurements. While traditional Bayesian optimal estimation (OE) assumes a prior distribution in order to regularize the inversion problem, the SVD approach identifies principal components that can be retrieved from the measurement without explicitly specifying a prior mean and prior covariance matrix. We discuss the method, illustrate its use on an integrated path differential absorption CO2 lidar measurement model, and compare it to traditional optimal estimation using numerical simulations. In the absence of forward model error, the mathematics behind the SVD method guarantee it to be bias-free, which is confirmed by the numerical simulations. In contrast, traditional OE retrievals exhibit bias when the prior mean used in the retrieval differs from the true mean. While the SVD approach can be used for most trace gas retrievals, it is particularly useful for situations where prior knowledge of the trace gas profile is poor. The SVD analysis is also useful in illustrating how vertical information is treated by the traditional OE approach.

Ramanathan, Anand K.↗

A Singular Value Decomposition Framework for Retrievals with Vertical Distribution Information from Greenhouse Gas Column Absorption Spectroscopy Measurements

We review the singular value decomposition (SVD) framework and use it for quantifying and discerning vertical information in greenhouse gas retrievals from column integrated absorption measurements. While the commonly used traditional Bayesian optimal estimation (OE) assumes a prior distribution in order to regularize the inversion problem, the SVD approach identifies principal components that can be retrieved from the measurement without explicitly specifying a prior mean and prior covariance matrix. We review the SVD method, explicitly recognize the use of an uninformative prior and show it to incur no bias from the choice of the prior. We also make the connection between the SVD method and the pseudo-inverse, which makes it more intuitive and easy to understand. We illustrate the use of the SVD method on an integrated path differential absorption CO2 lidar measurement model and verify our derivations and bias-free properties versus optimal estimation using numerical simulations. In contrast, traditional OE retrievals exhibit bias when the prior mean used in the retrieval differs from the true mean. Hence, the SVD method is particularly useful for situations in which knowledge of the prior mean and prior covariance of the true state (e.g., greenhouse gas profiles) is inadequate.

Ramanathan, Anand K.↗

NASA GeneLab Platform Utilized for Space Radiation Dosimetry Biological Response Compared to Radiation Ground Studies

Ionizing radiation from Galactic Cosmic Rays (GCR) is one of the major risk factors factor that will impact health of astronauts on extended missions outside the protective effects of the Earth's magnetic field. Currently there are gaps in our knowledge of the health risks associated with chronic low dose, low dose rate ionizing radiation, specifically ions associated with high (H) atomic number (Z) and energy (E). The NASA GeneLab project (genelab.nasa.gov) aims to provide a detailed library of Omics datasets associated with biological samples exposed to HZE. The GeneLab Data System (GLDS) includes datasets from both spaceflight and ground-based studies, a majority of which involved exposure to ionizing radiation. Recently GeneLab has also assessed radiation dosimetry data with omics datasets associated with samples flown to the International Space Station (ISS). The combination of the detailed information on radiation exposure for ground-based studies and curated dosimetry information for spaceflight experiments allows GeneLab to be the first comprehensive Omics database for space related research from which an investigator can generate hypotheses to direct future experiments utilizing both ground and space biological radiation data. We demonstrate the usefulness of these datasets by analyzing multiple GeneLab datasets associated with both radiation ground-based studies and spaceflight studies. The radiation ground based studies we analyzed includes both in vivo and in vitro work with a range ions from protons to iron particles with doses from 0.1Gy to 2Gy. These datasets were compared to both in vivo and in vitro datasets from samples flown to the ISS and on shorter shuttle missions with total doses of 0.1 mGy to 30 mGys. From this analysis we were able to associate distinct biological signatures associating specific ions to specific biological response to radiation exposure in space. For example, we discovered radiation biological response related to cardiovascular effects from proton ground studies are the dominating response for samples related to cardiovascular effects on the ISS. With this work we will provide a summary of how different ions will impact different biological response in space and how this can be used in future studies to assess optimal ground experiments to simulate space radiation.

Beheshti, Afshin↗

System Identification for eVTOL Aircraft Using Simulated Flight Data

This paper describes a system identification method for electric vertical takeoff and landing (eVTOL) aircraft. The approach merges fixed-wing and rotary-wing modeling techniques with new strategies to develop a modeling method for eVTOL vehicles using flight test data. The eVTOL aircraft system identification approach is demonstrated through application to the NASA LA-8 tandem tilt-wing, distributed electric propulsion aircraft using a high-fidelity flight dynamics simulation. Orthogonal phase-optimized multisine inputs are applied to each control surface and propulsor at numerous flight conditions throughout the flight envelope to collect informative flight data. An aero-propulsive model is identified at each flight condition using the equation-error method in the frequency domain. The local model parameters are then blended to create a global model across the nominal flight envelope. Parameter estimation results are shown to provide a good fit to modeling data and have good prediction capability. The methodology is developed with a discussion of unique eVTOL vehicle aerodynamic characteristics and practical strategies intended to inform future flight-based system identification efforts for eVTOL aircraft.

system identification↗

Assessment of Quantum ML Applicability for Climate Actions: Comparison of the Variational Quantum Classifier and the Quantum Support Vector Classifier with Classical ML Models

Climate change refers to significant and long-term alterations in the Earth’s climate patterns, typically resulting from human activities that increase greenhouse gas emissions. Addressing climate change is not merely an option but a necessity, demanding creative solutions and efforts from individuals, researchers, communities, and governments. Despite the capabilities of machine learning (ML) with data-driven solutions promising to combat climate change-related problems, they face challenges stemming from traditional computational methods and prolonged training times, impeding their practical utility. Recent strides in quantum computing have permeated diverse domains, spanning from manufacturing engineering and pharmaceutical discovery to the latest frontier of detecting climate anomalies. With the potential to substantially reduce time and computational complexity, quantum computing shows promise in addressing climate change impacts. Its distinctive features will enable the concurrent exploration of expansive solution spaces, making it well-suited for analyzing extensive climate datasets, simulating intricate climate models, optimizing resource allocation, and discerning patterns in climate data for mitigation and adaptation endeavors. This study explores the potential of using Quantum machine learning (QML) techniques on climate and weather data obtained from NASA Giovannis. We used two QML algorithms, the Quantum Support Vector Classifier (QSVC) and the Variational Quantum Classifier (VQC) models, using the IBM Qiskit ML 0.7.2 ecosystem. We used an actual 127-Qubit IBM Quantum Computer (IBM 127-qubit Eagle) in this study. The methodology and results sections describe the experiences gained from applying and evaluating quantum ML results on climate and weather data obtained from NASA satellites as a novel practical application of quantum computing.

Earth Observational Data↗

An Analysis of Frenkel Defects and Backgrounds Modeling for SuperCDMS Dark Matter Searches

Years of astrophysical observations suggest that dark matter comprises more than $\sim$ 80 % of all matter in the universe. Particle physics theories favor a weakly-interacting particle that could be directly detected in terrestrial experiments. The Super Cryogenic Dark Matter Search (SuperCDMS) Collaboration operates world-leading experiments to directly detect dark matter interacting with ordinary matter. The SuperCDMS Soudan experiment searched for weakly interacting massive particles (WIMPs) via their elastic-scattering interactions with nuclei in low-temperature germanium detectors. During the operation of the SuperCDMS Soudan experiment, $^{210}$Pb sources were installed to study background rejection of the Ge detectors. Data from these sources were used to investigate energy loss associated with Frenkel defect formation in germanium crystals at mK temperatures. The spectrum of $^{206}$Pb nuclear recoils was examined near its expected 103 keV endpoint energy to extract the first experimentally determined average displacement threshold energy of 19.7 $\pm$ 0.5 (stat) $\pm$ 0.1 (syst) eV for germanium. This has implications for the sensitivity of future germanium-based dark matter searches including the SuperCDMS SNOLAB experiment. The SuperCDMS SNOLAB experiment will employ germanium and silicon detectors to improve current WIMP-search results by at least one order of magnitude for masses $\leq$ 10 GeV/c$^2$. This will require substantial shielding against cosmogenic and radiogenic backgrounds. The SuperCDMS SNOLAB passive shield will be permanent for the duration of the experiment so extensive simulations were undertaken to optimize the shield design. This resulted in a design of an outer layer of 60 cm of water, a middle layer of 20 cm of lead, and 30 cm of polyethylene which limits the background rate to that required for the primary physics goals of the experiments. The experiment will begin operations in 2020 and care must be taken during the construction phase to limit exposure to the $\pm$ 135 Bq/m$^3$ radon activity in the laboratory. The daughter products of $^{222}$Rn can attach to nearby surfaces leaving long-lived $^{210}$Pb in place for the duration of the experiment. For non-line-of-sight surfaces of the polyethylene shield, the maximum allowable $^{210}$Pb activity is 10,000 nBq/cm$^2$. A study was conducted to experimentally determine the contamination rate of polyethylene and copper by exposing samples for 83 days at SNOLAB. From the resulting surface activities, obtained from high-sensitivity measurements of alpha emissivity using the XIA UltraLo-1800 spectrometer, the average $^{210}$Pb plate-out rate was determined to be 249 and 423 atoms/day/cm$^2$ for polyethylene and copper, respectively. A time-dependent model of alpha activity was

79 ASTRONOMY AND ASTROPHYSICS↗

Template engine applied to rapid modeling

Modeling complex problems can require a significant effort, be subject to human error, and contain repeated patterns of input. SCALE 6.2 and the Used Nuclear Fuel-Storage, Transportation and Disposal Analysis Resource and Data System (UNF-ST-DARDS) have attempted to mitigate these problems with the use of a template engine and template syntax. The template syntax allows redundant input to be consolidated into its simplest pattern and parameterized on the parts that change, reducing effort and likelihood of errors and encapsulating user experience into a reusable model component. This paper presents a summary of rapid modeling benefits and techniques that are facilitated when using templates. Specifically, this paper will discuss how these are applied in conducting as-loaded spent nuclear fuel canister criticality calculations using UNF-ST-DARDS and model perturbation and sampling using SCALE 6.2. (authors)

42 ENGINEERING↗

Transition core modeling for extended enrichment, accident tolerant fuel using PARCS/Polaris

Current plans and efforts from reactor operators and vendors to include extended enrichment (EE) and accident-tolerant fuel (ATF) in current reactor fleets motivate the study of these changes in reactor physics analysis. This work uses the US Nuclear Regulatory Commission core simulator PARCS to do the core calculation and SCALE Polaris lattice physics code to generate the required homogenized, few-group constants. The lattice model used is based on the GE-14 10x10 assemblies with UO{sub 2} fuels. Both nominal core and transition core are studied in this work, and both cores use GE-14 10x10 assemblies with UO{sub 2} fuel. The nominal core uses regular UO{sub 2} fuel with a maximum enrichment of 5 wt % and ZIRC-2 cladding. The ATF transition core uses FeCrAl cladding and regular UO{sub 2} fuel, while the EE-ATF transition core uses FeCrAl cladding with UO{sub 2} fuel with 8 max wt % enrichment. The accuracy presented in the colorset models verified the capability of the PARCS/Polaris procedures for the transition core analysis. For the whole core calculation, the ATF and EE-ATF transition core models were made in addition to the nominal core model. The core parameters to study are the core power distribution and power peaking factor, doppler temperature coefficients, and control rod worth at cold zero power and hot full power. Comparing the core parameters of the transition cores with the nominal core in PARCS, the results suggest that there is no unexpected outcome for the implementation of ATF and EE fuels. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Design and optimization of higher order mode couplers for the superconducting cavities of the PERLE energy recovery linac

The Powerful Energy Recovery Linac for Experiments (PERLE) is an energy recovery linac (ERL) facility based on superconducting radio-frequency (SRF) technology to be hosted at the Laboratoire de Physique des 2 Infinis Irène Joliot-Curie (IJCLab) in France. With a target beam power of 10 MW, PERLE aims to demonstrate the high-current, continuous wave, multi-pass operation to validate options for future high-energy machines, such as the 50 GeV ERL proposed for the Large Hadron electron Collider (LHeC) and the Future Circular electron-hadron Collider (FCC-eh), and host dedicated particle physics and nuclear experiments. In high-current ERLs, the regenerative Beam Breakup (BBU), emerging from the beam and cavity Higher Order Modes (HOMs) interaction, is a major concern for their stable operation. Beam-induced HOMs can increase the cavity heat load at cryogenic temperature and cause beam instabilities. HOM couplers are installed in the cavity beam pipes to absorb HOM energy and mitigate these effects. This thesis presents the design and optimization of several coaxial HOM couplers for the 5-cell 801.58 MHz elliptical Nb cavities of the 500 MeV PERLE ERL configuration. The RF transmission of the HOM couplers was optimized to enhance the damping of the most dangerous HOMs. The optimized HOM couplers were integrated into endgroups to simulate their damping performance and thermal behavior. The optimized HOM couplers were 3D-printed in epoxy and copper-coated. Low-power RF measurements were conducted on the produced HOM couplers installed in copper PERLE-type cavities to validate their damping performance and propose several endgroups for the PERLE 5-cell cavity to mitigate HOMs below the BBU instability limits.

Barbagallo, Carmelo↗