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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Life cycle cost modeling of conceptual space vehicles

This paper documents progress to date by the University of Dayton on the development of a life cycle cost model for use during the conceptual design of new launch vehicles and spacecraft. This research is being conducted under NASA Research Grant NAG-1-1327. This research effort changes the focus from that of the first two years in which a reliability and maintainability model was developed to the initial development of a life cycle cost model. Cost categories are initially patterned after NASA's three axis work breakdown structure consisting of a configuration axis (vehicle), a function axis, and a cost axis. The focus will be on operations and maintenance costs and other recurring costs. Secondary tasks performed concurrent with the development of the life cycle costing model include continual support and upgrade of the R&M model. The primary result of the completed research will be a methodology and a computer implementation of the methodology to provide for timely cost analysis in support of the conceptual design activities. The major objectives of this research are: to obtain and to develop improved methods for estimating manpower, spares, software and hardware costs, facilities costs, and other cost categories as identified by NASA personnel; to construct a life cycle cost model of a space transportation system for budget exercises and performance-cost trade-off analysis during the conceptual and development stages; to continue to support modifications and enhancements to the R&M model; and to continue to assist in the development of a simulation model to provide an integrated view of the operations and support of the proposed system.

Ebeling, Charles↗
NASA NTRS1993

Space transfer vehicle concepts and requirements. Volume 4: Summary of special studies

Our final report for Phase 1 addressed the future space transportation needs and requirements based on the current assets, at the time, and their evolution through technology/advanced development using a path and schedule that supported the world leadership role of the United States in a responsible and realistic financial forecast. Always, and foremost, the recommendations placed high values on the safety and success of missions both manned and unmanned through a total quality management philosophy at Martin Marietta. The second phase of the STV contract involved the use of Technical Directives (TD) to provide short-term support for specialized tasks as required by the COTR. Three of these tasks were performed in parallel with Phase 1. These tasks were the Liquid Acquisition Experiment (LACE), Liquid Reorientation Experiment (LIRE), and Expert System for Design, Operation, and Technology Studies (ESDOTS). The results of these TD's were reported in conjunction with the Phase 1 Final Report. Cost analysis of existing launch systems has demonstrated a need for a new upper stage that will increase America's competitiveness in the global launch services market. To provide a growth path of future exploration class STV's, near-term low-cost upper stages featuring modularity, portability, scalability, and evolvability must be developed. These recommendations define a program that: leverages ongoing activities to establish a new development environment, develop technologies that benefit the entire life cycle of a system, and result in a scalable hardware platform that provides a growth path to future upper stages.

Source record↗
NASA NTRS1994

Advanced support systems development and supporting technologies for Controlled Ecological Life Support Systems (CELSS)

A methyl acetate reactor was developed to perform a subscale kinetic investigation in the design and optimization of a full-scale metabolic simulator for long term testing of life support systems. Other tasks in support of the closed ecological life support system test program included: (1) heating, ventilation and air conditioning analysis of a variable pressure growth chamber, (2) experimental design for statistical analysis of plant crops, (3) resource recovery for closed life support systems, and (4) development of data acquisition software for automating an environmental growth chamber.

Simon, William E.↗
NASA NTRS1994

The meteorological monitoring system for the Kennedy Space Center/Cape Canaveral Air Station

The Kennedy Space Center (KSC) and Cape Canaveral Air Station (CCAS) are involved in many weather-sensitive operations. Manned and unmanned vehicle launches, which occur several times each year, are obvious example of operations whose success and safety are dependent upon favorable meteorological conditions. Other operations involving NASA, Air Force, and contractor personnel, including daily operations to maintain facilities, refurbish launch structures, prepare vehicles for launch, and handle hazardous materials, are less publicized but are no less weather-sensitive. The Meteorological Monitoring System (MMS) is a computer network which acquires, processes, disseminates, and monitors near real-time and forecast meteorological information to assist operational personnel and weather forecasters with the task of minimizing the risk to personnel, materials, and the surrounding population. CLIPS has been integrated into the MMS to provide quality control analysis and data monitoring. This paper describes aspects of the MMS relevant to CLIPS including requirements, actual implementation details, and results of performance testing.

Dianic, Allan V.↗
NASA NTRS2009

Applied Meteorology Unit (AMU) Quarterly Report - Fourth Quarter FY-09

This report summarizes the Applied Meteorology Unit (AMU) activities for the fourth quarter of Fiscal Year 2009 (July - September 2009). Tasks reports include: (1) Peak Wind Tool for User Launch Commit Criteria (LCC), (2) Objective Lightning Probability Tool. Phase III, (3) Peak Wind Tool for General Forecasting. Phase II, (4) Update and Maintain Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS), (5) Verify MesoNAM Performance (6) develop a Graphical User Interface to update selected parameters for the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLlT)

Bauman, William↗
NASA NTRS2021

Mass Inferencing Model Creation And Deployment To Lunar Excavation Robot, RASSOR

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a teleoperated mobile robotic platform with a unique space regolith excavation capability. This research project developed functionality for inferencing regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete ISRU missions. Radio wave propagation time to the Moon and back is ~2.56 seconds. Though teleoperation is possible with this delay, autonomous capability that enables RASSOR to plan and execute excavation missions intelligently and efficiently is preferred. To teleoperate or run autonomously, it is crucial for the quantity of regolith mass ingested by RASSOR to be available as a system state for efficient operation (e.g. knowledge of whether drums are full informs the task of highest priority, whether it be continuing to dig, or returning to a processing plant to offload regolith). A configurable data reduction and analysis pipeline was created to allow for straightforward incorporation of new data, such as that from lunar excavation, to improve model performance in new environments. Four distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR. All four models take in system states and output a mass prediction for each set of the robot’s bucket drums. Initial results from deployment to RASSOR and testing in a simulated lunar environment show that the models have <10% mean error during robot operation. Future work includes refinement of a model that estimates regolith mass in real-time during excavation as well as further testing of the developed models on the hardware.

ROS↗
DOE OSTI2016

Building America Case Study: Quantifying the Financial Benefits of Multifamily Retrofits, Chicago, Illinois

Increasing the adoption of energy efficient building practices will require the energy sector to increase their understanding of the way that retrofits affect multifamily financial performance as well as how those indicators are interpreted by the lending and appraisal industries. This project analyzed building, energy, and financial program data as well as other public and private data to examine the relationship between energy efficiency retrofits and financial performance on three levels: building, city, and community. The project goals were to increase the data and analysis in the growing body of multifamily financial benefits work as well provide a framework for other geographies to produce similar characterization. The goals are accomplished through three tasks: Task one: A pre- and post-retrofit analysis of thirteen Chicago multifamily buildings. Task two: A comparison of Chicago income and expenses to two national datasets. Task three: An in-depth look at multifamily market sales data and the subsequent impact of buildings that undergo retrofits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Results of FY 2023 Alloy 617 and Alloy 709 High-Temperature Crack-Growth Testing

This report summarizes the work performed at Idaho National Laboratory under the “Creep, fatigue and creep-fatigue crack growth tests” task of the “Long-Term VHTR Material Qualification – INL” work package. Work was performed this year to validate the crack growth monitoring setup used with the test frames against both continuous crack length monitoring using an optical camera, as well as post-mortem analysis of marker bands on the fracture surface. Delays prevented the use of a gauge to measure load-line displacement for early tests, and so the creep-fatigue crack growth setup was evaluated using the actuator displacement for a load-line displacement setup. While not ideal, this allowed examination of the shortcomings with the current software setup that was originally designed for performing stress corrosion crack growth rate studies. The method for data collection was modified to link the crack growth monitoring software with Instron’s Wave Matrix software. Once the load-line displacement gauge arrived, the crack growth equipment was successfully modified to permit continuous monitoring of both load-line displacement and crack length. This is critical for creep-fatigue and creep crack growth rate studies for ductile material, as it permits the C* and Ct analyses. Test results are shown for Alloy 617 fatigue and creep-fatigue (without the gauge for load-line displacement measurements), as well as creep-fatigue of Alloy 709, which was performed with the completed test setup, allowing for crack length and load-line displacement monitoring.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Can Large Language Models Understand Intermediate Representations?

Intermediate Representations (IRs) are essential in compiler design and program analysis, yet their comprehension by Large Language Models (LLMs) remains underexplored. This paper presents a pioneering empirical study to investigate the capabilities of LLMs, including GPT-4, GPT-3, Gemma 2, LLaMA 3.1, and Code Llama, in understanding IRs. We analyze their performance across four tasks: Control Flow Graph (CFG) reconstruction, decompilation, code summarization, and execution reasoning. Our results indicate that while LLMs demonstrate competence in parsing IR syntax and recognizing high-level structures, they struggle with control flow reasoning, execution semantics, and loop handling. Specifically, they often misinterpret branching instructions, omit critical IR operations, and rely on heuristic-based reasoning, leading to errors in CFG reconstruction, IR decompilation, and execution reasoning. The study underscores the necessity for IR-specific enhancements in LLMs, recommending fine-tuning on structured IR datasets and integration of explicit control flow models to augment their comprehension and handling of IR-related tasks.

Jiang, Hailong↗
NASA NTRSDate not supplied

IMPACT 1.0—Task Impairment: A Novel Approach for Assessing Impairment during Exploration-Class Missions

Exploration-class and International Space Station (ISS) missions have significantly different levels of associated medical risk for crewmembers. The Integrated Medical Model (IMM), the probabilistic risk assessment tool used for ISS medical trade-space analyses, uses a Functional Impairment (FI) metric to determine quality time lost should a crewmember be afflicted with a medical condition. While IMM-based FI has been successful for ISS operations, it has limitations when applied to exploration-class missions. As the National Aeronautics and Space Administration (NASA) looks ahead to Gateway, Artemis, and Martian missions, a novel, dynamic, and mission-appropriate impairment paradigm is necessary for accurate contingency planning. This paradigm, Task Impairment (TI), fulfills that need by utilizing mission-specific tasks. TI will allow future capability for a loss of mission metric, previously not available with IMM. TI serves as a replacement metric for FI within IMPACT, the next-generation trade-space analysis tool suite created to replace the IMM. IMPACT significantly increases the fidelity of probabilistic risk assessment for exploration-class missions. The Human Exploration of Mars Preliminary List of Crew Tasks (MTL, a source of 1100+ exploration-class mission-specific tasks for crewmembers) was used to calculate TI. Using the Task List, 18 individual Human System Categories were identified as being required to perform each task (e.g., Cardiopulmonary, Cognitive, etc.). Each of the 1200+ tasks were mapped to the Human System categories listed in the Task List. The total number of tasks in each category were tallied to determine how many tasks required each Human System. Lastly, each of the 120 medical conditions from the IMPACT condition list were mapped to the Human System categories to complete the TI calculation. NASA subject matter experts across five medical specialties established consensus for the mapping of each condition. The resulting total tasks impaired by each condition were used to calculate discrete TI values. This process was repeated for each of the four severity/resource utilization variants of each condition, and for each of the three phases of clinical care. Through this process, discrete TI values were calculated for each of the 120 IMPACT medical conditions and their variants. The Task Impairment metric provides higher fidelity, dynamic utility, and quicker analysis of medical impairment compared to the previous Functional Impairment metric used for the Integrated Medical Model. TI will be used for higher fidelity medical impairment analysis and contingency planning during Lunar, Martian, and other long-term exploration-class missions.

William L Fernandez↗
NASA NTRS2015

Modeling and Analysis of Chill and Fill Processes for the EDU Tank

NASA's future missions may require long-term storage and transfer of cryogenic propellants. The Engineering Development Unit (EDU), a NASA in-house effort supported by both Marshall Space Flight Center (MSFC) and Glenn Research Center (GRC), is a Cryogenic Fluid Management (CFM) test article that primarily serves as a manufacturing pathfinder and a risk reduction task for a future CFM payload. The EDU test article, comprises a flight like tank, internal components, insulation, and attachment struts. The EDU is designed to perform integrated passive thermal control performance testing with liquid hydrogen in a space-like vacuum environment. A series of tests, with liquid hydrogen as a testing fluid, was conducted at Test Stand 300 at MSFC during summer of 2014. The objective of this effort was to develop a thermal/fluid model for evaluating the thermodynamic behavior of the EDU tank during the chill and fill processes. Generalized Fluid System Simulation Program (GFSSP), an MSFC in-house general-purpose computer program for flow network analysis, was utilized to model and simulate the chill and fill portion of the testing. The model contained the liquid hydrogen supply source, feed system, EDU tank, and vent system. The modeling description and comparison of model predictions with the test data will be presented in the final paper.

Hedayat, A.↗
NASA NTRS1995

Structural Damage Prediction and Analysis for Hypervelocity Impact

It is necessary to integrate a wide variety of technical disciplines to provide an analysis of structural damage to a spacecraft due to hypervelocity impact. There are many uncertainties, and more detailed investigation is warranted, in each technical discipline. However, a total picture of the debris and meteoroid hazard is required to support manned spaceflight in general, and the international Space Station in particular. In the performance of this contract, besides producing a handbook, research and development was conducted in several different areas. The contract was broken into six separate tasks. Each task objectives and accomplishments will be reviewed in the following sections. The Handbook and separate task reports are contained as attachments to the final report. The final section summarizes all of the recommendations coming out of this study. The analyses and comments are general design guidelines and not necessarily applicable to final Space Station designs since several configuration and detailed design changes were being made during the course of this contract. Rather, the analyses and comments may indicate either a point-in-time concept analysis, available test data, or desirable protection goals, not hindered by the design and operation constraints faced by Space Station designers.

Elfer, Norman↗
DOE OSTI2021

Scalable, In-situ Data Clustering Data Analysis for Extreme Scale Scientific Computing (Final Report)

The objective of this project is to address challenges in the design and development of scalable in-situ data clustering and analytics algorithms and software. Our goal is to develop parallel software consisting of a set of spatio-temporal data clustering and anomaly detection functions, both of which are very important for large-scale analysis and have wide applicability for in-situ runs as well as post-processing analysis. Our design principles for in-situ analysis consider the following: (1) identify parts of the computation can be done close to the data within the nodes, while it is still in memory; (2) extract analysis components can (and should) be performed in remote staging and analysis nodes; (3) develop error-bound approximation methods for applications tolerable for small errors; (4) identify the type of derived distributions and statistics, for spatio-temporal data, that can be kept locally in order to both accelerate computations and meet energy constraints in subsequent iterations and phases; (5) use a self-describing data format so that data can be consistent and understood among local storage (memory and SSDs) and at staging and analysis nodes, thereby providing portability and flexibility; (6) develop service-oriented functions that can schedule in-situ and post-hoc analysis tasks based on the dynamic requirements of applications. Our development focus is to produce the parallel data analysis software/library that will be scalable, reusable, extensible, and generic for applications in different disciplines. The software will be able to run in-situ with the simulations as well as post-hoc analysis. This approach will satisfy many synergistic requirements for data intensive applications executed on data coming from instruments and experiments. In particular, the proposed multilevel approach is directly applicable to perform design tradeoffs for running part of the algorithms near the instruments and the rest on remote (analysis) systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Design-Technology Co-Optimization for NVM-based Neuromorphic Processing Elements

An emerging use-case of machine learning (ML) is to train a model on a high-performance system and deploy the trained model on energy-constrained embedded systems. Neuromorphic hardware platforms, which operate on principles of the biological brain, can significantly lower the energy overhead of a machine learning inference task, making these platforms an attractive solution for embedded ML systems. In this paper, we present a design-technology tradeoff analysis to implement such inference tasks on the processing elements (PEs) of a Non-Volatile Memory (NVM)-based neuromorphic hardware. Through detailed circuit-level simulations at scaled process technology nodes, we show the negative impact of technology scaling on the information-processing latency, which impacts the quality-of-service (QoS) of an embedded ML system. At a finer granularity, the latency inside a PE depends on 1) the delay introduced by parasitic components on its current paths, and 2) the varying delay to sense different resistance states of its NVM cells. Based on these two observations, we make the following three contributions. First, on the technology front, we propose an optimization scheme where the NVM resistance state that takes the longest time to sense is set on current paths having the least delay, and vice versa, reducing the average PE latency, which improves the QoS. Second, on the architecture front, we introduce isolation transistors within each PE to partition it into regions that can be individually power-gated, reducing both latency and energy. Finally, on the system-software front, we propose a mechanism to leverage the proposed technological and architectural enhancements when implementing a machine-learning inference task on neuromorphic PEs of the hardware. Evaluations with a recent neuromorphic hardware architecture show that our proposed design-technology co-optimization approach improves both performance and energy efficiency of machine-learning inference tasks without incurring high cost-per-bit.

42 ENGINEERING↗
NASA NTRS2000

Mass Storage Performance Information System

The purpose of this task is to develop a data warehouse to enable system administrators and their managers to gather information by querying the data logs of the MDSDS. Currently detailed logs capture the activity of the MDSDS internal to the different systems. The elements to be included in the data warehouse are requirements analysis, data cleansing, database design, database population, hardware/software acquisition, data transformation, query and report generation, and data mining.

Scheuermann, Peter↗
DOE OSTI2019

In‐depth comparative analysis of Illumina ® MiSeq run metrics: Development of a wet‐lab quality assessment tool

Abstract Whole genome sequencing of bacterial isolates has become a daily task in many laboratories, generating incredible amounts of data. However, data acquisition is not an end in itself; the goal is to acquire high‐quality data useful for understanding genetic relationships. Having a method that could rapidly determine which of the many available run metrics are the most important indicators of overall run quality and having a way to monitor these during a given sequencing run would be extremely helpful to this effect. Therefore, we compared various run metrics across 486 MiSeq runs, from five different machines. By performing a statistical analysis using principal components analysis and a K ‐means clustering algorithm of the metrics, we were able to validate metric comparisons among instruments, allowing for the development of a predictive algorithm, which permits one to observe whether a given MiSeq run has performed adequately. This algorithm is available in an Excel spreadsheet: that is, MiSeq Instrument & Run (In‐Run) Forecast. Our tool can help verify that the quantity/quality of the generated sequencing data consistently meets or exceeds recommended manufacturer expectations. Patterns of deviation from those expectations can be used to assess potential run problems and plan preventative maintenance, which can save valuable time and funding resources.

Kastanis, George John↗
DOE OSTI2014

Office of Electricity Delivery and Energy Reliability (OE) National Energy Technology Laboratory (NETL) American Recovery and Reinvestment Act 2009 United States Department of Energy

The purpose of this project was for Seeo to deliver the first ever large-scale or grid-scale prototype of a new class of advanced lithium-ion rechargeable batteries. The technology combines unprecedented energy density, lifetime, safety, and cost. The goal was to demonstrate Seeo’s entirely new class of lithium-based batteries based on Seeo’s proprietary nanostructured polymer electrolyte. This technology can enable the widespread deployment in Smart Grid applications and was demonstrated through the development and testing of a 10 kilowatt-hour (kWh) prototype battery system. This development effort, supported by the United States Department of Energy (DOE) enabled Seeo to pursue and validate the transformational performance advantages of its technology for use in grid-tied energy storage applications. The focus of this project and Seeo’s goal as demonstrated through the efforts made under this project is to address the utility market needs for energy storage systems applications, especially for residential and commercial customers tied to solar photovoltaic installations. In addition to grid energy storage opportunities Seeo’s technology has been tested with automotive drive cycles and is seen as equally applicable for battery packs for electric vehicles. The goals of the project were outlined and achieved through a series of specific tasks, which encompassed materials development, scaling up of cells, demonstrating the performance of the cells, designing, building and demonstrating a pack prototype, and providing an economic and environmental assessment. Nearly all of the tasks were achieved over the duration of the program, with only the full demonstration of the battery system and a complete economic and environmental analysis not able to be fully completed. A timeline over the duration of the program is shown in figure 1.

25 ENERGY STORAGE↗
DOE OSTI2018

Development and Characterization of High Performance and Robust Mixed Conducting Cathodes Supportive of Lower Cost Solid Oxide Fuel Cells (Final Report)

The objective of the proposed research is to advance an existing partnership between the University of South Carolina (USC) and LG Fuel Cell Systems, Inc. (LGFCS) to research and develop mixed electronic and ionic conducting cathode materials for durable and robust low-cost solid oxide fuel cells (SOFCs). The first task is to develop mixed ionic and electronic conducting doped (Pr,Nd)NiO 4 (PNNO)-based cathodes. This task is built on a prior collaborative work with LG Fuel Cell System, which showed that doped PNNO could exhibit phase stability at high temperatures. The initial focus will be on investigating the durability and endurance of its electrochemical performance and the temporal evolution of microstructures. In-situ high temperature neutron diffraction and x-ray diffraction will be used to study the structures of these phase stable compounds. PNNO doped with Ca and transition metal elements will be synthesized. Physical properties of these materials with respect to coefficient of thermal expansion, electrical conductivity, diffusion coefficient, and nonstoichiometry will be measured. The benefits of dense versus porous barriers will be studied and the role of barrier layer will be identified and a guideline will be provided to choose the maximum porosity for durable and robust cathode performance with co-doped PNNO as the cathodes. LSCF6428 will be used to compare its power density with that of co-doped PNNO in the absence of Cr, but some studies comparing Cr tolerance will be performed towards the end of the project. The conditions at which preferred nickelate phases are stable will be defined, including sintering temperature, operating temperature, and composition range. The second task will focus on the investigation of the location of degradation by using differential relaxation time (DRT) analysis, coupled with least squares fitting and systematical post analyses. DRT analysis can provide (1) a direct access to the kinetic parameters of the underlying processes in both cathode and anode, and (2) a clearer picture of SOFC operation, which allows loss factors to the changes of microstructures or activities of either electrode to be distinguished, and a better target fuel cell development to be enabled. The third task aims at applying the accelerated testing protocol to investigate the microstructural evolution of the cathode candidates identified in this research. Technical approaches will be developed to mitigate and improve the durability of cathode materials by choosing the right chemistry and tuning cathode microstructures.

36 MATERIALS SCIENCE↗