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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Systems Engineering and Integration for Advanced Life Support System and HST

Systems engineering (SE) discipline has revolutionized the way engineers and managers think about solving issues related to design of complex systems: With continued development of state-of-the-art technologies, systems are becoming more complex and therefore, a systematic approach is essential to control and manage their integrated design and development. This complexity is driven from integration issues. In this case, subsystems must interact with one another in order to achieve integration objectives, and also achieve the overall system's required performance. Systems engineering process addresses these issues at multiple levels. It is a technology and management process dedicated to controlling all aspects of system life cycle to assure integration at all levels. The Advanced Integration Matrix (AIM) project serves as the systems engineering and integration function for the Human Support Technology (HST) program. AIM provides means for integrated test facilities and personnel for performance trade studies, analyses, integrated models, test results, and validated requirements of the integration of HST. The goal of AIM is to address systems-level integration issues for exploration missions. It will use an incremental systems integration approach to yield technologies, baselines for further development, and possible breakthrough concepts in the areas of technological and organizational interfaces, total information flow, system wide controls, technical synergism, mission operations protocols and procedures, and human-machine interfaces.

Kamarani, Ali K.↗
DOE OSTI2024

A New Reduced Order Model For The Mechanistic Creep Behavior Of UO 2

This manuscript describes an ongoing NEAMS effort to better determine the performance of advanced nuclear fuels, in particular the creep behavior of doped UO$_2$ for light water reactors. In our previous work, we outlined a method to utilize data generated from lower length scale simulations and implement it into the engineering scale fuel performance analysis. This process has been further refined, and in addition, new data has been used to train the surrogate model which has also been substantially improved since the previous iteration. The new model is compared against the current empirical model used in BISON using both scoping calculations to define the performance over the parameter space and using integral instrumented fuel assessment cases to determine the impact of these models on the overall fuel performance. Suggestions and guidance for future improvements to this method are provided to ensure the model covers relevant parameter space and phenomena.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1987

Non-equilibrium freezing of water-ice in sandy basaltic regoliths and implications for fluidized debris flows on Mars

Many geomorphic features on Mars were attributed to Earth-analogous, cold-climate processes involving movement of water or ice lubricated debris. Clearly, knowledge of the behavior of water in regolith materials under Martian conditions is essential to understanding the postulated geomorphic processes. Experiments were performed with sand-sized samples of natural basaltic regoliths in order to further elucidate how water/regolith interactions depend upon grain size and mineralogy. The data reveal important contrasts with data for clay-mineral substrates and suggest that the microphysics of water/mineral interactions might affect Martian geomorphic processes in ways that are not fully appreciated. Sand and silt sized fractions of two soils from the summit of Mauna Kea were used as Mars-analogous regolith materials. Temperatures were measured for water/ice phase transitions as wet slurries of individual soil fractions which were cooled or heated at controlled rates under a carbon dioxide atmosphere. Freezing and melting of ice was studied as a function of water/soil mass ratio, soil particle size, and thermal-cycle rate. Comparison tests were done under the same conditions with U.S. Geological Survey standard rock powders.

Gooding, J. L.↗
DOE OSTI2025

Multiscale Mechanisms of Twisted Carbon Nanotube Yarns Probed In Situ by Soft X-rays during Tensile Loading

Piecing together carbon nanotubes (CNTs) into assemblies has so far failed to achieve the same elite strength performance metrics as individual CNTs, highlighting a critical deficiency in understanding the effects that the processing of individual nanostructures have on the performance of their derived macroscale assemblies, thereby hindering the development of a process-structure-performance map for these materials. Here, in this work, we propose a method to decouple the distribution orientation of nanoscale tortuosity and the microscale twist of CNT dry-spun yarns under applied loads via in situ soft X-ray probing at high energy (1200 eV) and low energy (280 eV), respectively. With this decoupling enabled by in situ soft X-ray scattering, we acquired a deeper understanding of the deformation mechanisms of these yarns. We found that for untreated yarns, the twist angle of collective CNT bundles at the macroscale is more sensitive to applied stress than the nanoscale alignment distribution. We also found that increasing nominal twist densities of yarns as well as increased strengthening via plasma treatments and polymer infiltration act to decrease the yarns’ sensitivity to realignment at the nanoscale and prevent failure by the slip mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Modeling Single-Crystal Battery Materials: From Fundamental Understanding to Performance Evaluation

The performance of rechargeable batteries is fundamentally influenced by the physicochemical properties and microstructural features of their key material components. Recent experimental advancements have highlighted the potential of single-crystal (SC) morphologies to address inherent limitations of polycrystalline (PC) electrodes and solid-state electrolytes, offering tunable charge transport kinetics and improved cell cycling performance. Here, this review examines how state-of-the-art computational modeling, from atomistic and mesoscale to continuum-level approaches, including machine learning methodologies, has been utilized to investigate the critical factors governing the electrochemical behavior of SC battery materials. We explore how predictive modeling can elucidate the processing–structure–property–performance relationships of SC cathodes, anodes, and solid-state electrolytes, with a focus on unique SC characteristics such as crystallographic anisotropy, size effects, and facet-dependent properties. Additionally, we identify limitations in commonly used modeling techniques and discuss strategies to address these challenges. By integrating high-fidelity simulations with experimental insights, this review aims to outline a clear path for the rational design and optimization of SC battery components, paving the way for accelerated advancements in energy storage technologies.

Materials science↗
DOE OSTI2025

A co-registered in-situ and ex-situ dataset from wire arc additive manufacturing process

Recent progress in sensing techniques and data analytics tools have significantly accelerated the development of Wire Arc Additive Manufacturing (WAAM) systems. This data-centric approach emphasizes leveraging sensor data available throughout the production process to optimize performance. Integration of extensive data analysis provides opportunities for improving precision, reducing waste, and enhancing the quality of produced parts. This method relies on AI/ML models and optimization techniques, which are developed using the data collected from various sources, including in-situ sensors, ex-situ imaging, and manufacturing process parameters. The quality and diversity of this data, along with the alignment between different data streams (achieved through spatiotemporal registration) are critical for the successful development of AI/ML and optimization models. In this work, we present a spatiotemporally registered dataset generated during the WAAM process of deposition of a rectangular block. The dataset includes a comprehensive description of the deposition process, process parameters, welding characteristics and acoustic data collected in-situ, and X-Ray Computed Tomography data of the build.

42 ENGINEERING↗
NASA NTRS1975

M-DAS: System for multispectral data analysis

M-DAS is a ground data processing system designed for analysis of multispectral data. M-DAS operates on multispectral data from LANDSAT, S-192, M2S and other sources in CCT form. Interactive training by operator-investigators using a variable cursor on a color display was used to derive optimum processing coefficients and data on cluster separability. An advanced multivariate normal-maximum likelihood processing algorithm was used to produce output in various formats: color-coded film images, geometrically corrected map overlays, moving displays of scene sections, coverage tabulations and categorized CCTs. The analysis procedure for M-DAS involves three phases: (1) screening and training, (2) analysis of training data to compute performance predictions and processing coefficients, and (3) processing of multichannel input data into categorized results. Typical M-DAS applications involve iteration between each of these phases. A series of photographs of the M-DAS display are used to illustrate M-DAS operation.

Johnson, R. H.↗
DOE OSTI2018

Establishing Building-Level Energy Goals in Procurement Documents: Lessons Learned from Pilot Utility and Portfolio Projects: Preprint

Encouraging commercial building owners to set measurable energy goals before design begins can drive design and contractor teams to develop innovative energy efficiency solutions within conventional building budgets. A federal building owner piloted this technique and created a large-scale zero energy office building on a budget comparable to local market construction rates. The successes and lessons learned from this performance-based procurement project formed the basis of an expanded program using utilities as the outreach channel to replicate the approach. The utilities delivered incentive-based offerings to focus building owners on the whole building rather than on individual building components and systems. In addition, a ripple effect was evident, with individual building owners as well as owners of multiple-building portfolios adopting the techniques, sometimes with variations, but always maintaining the same core principles. The original performance-based procurement process and its successful implementation in a federal building project informed all these efforts. Those successes and lessons learned demonstrate that the approach can be adapted to utility programs with some variation and is a powerful tool for engaging building owners as they make critical design decisions that impact energy performance over the life of the building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Establishing Building-Level Energy Goals in Procurement Documents: Lessons Learned from Pilot Utility and Portfolio Projects

Encouraging commercial building owners to set measurable energy goals before design begins can drive design and contractor teams to develop innovative energy efficiency solutions within conventional building budgets. A federal building owner piloted this technique and created a large-scale zero energy office building on a budget comparable to local market construction rates. The successes and lessons learned from this performance-based procurement project formed the basis of an expanded program using utilities as the outreach channel to replicate the approach. The utilities delivered incentive-based offerings to focus building owners on the whole building rather than on individual building components and systems. In addition, a ripple effect was evident, with individual building owners as well as owners of multiple-building portfolios adopting the techniques, sometimes with variations, but always maintaining the same core principles. The original performance-based procurement process and its successful implementation in a federal building project informed all these efforts. Those successes and lessons learned demonstrate that the approach can be adapted to utility programs with some variation and is a powerful tool for engaging building owners as they make critical design decisions that impact energy performance over the life of the building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Balancing Manufacturability with Performance: Achieving Extrudable, High Thermal Conductivity, and Dielectrically Robust Thermoplastic Composites

Improved thermal management solutions for electrical insulation systems are a priority for increasing efficiency. Although polymeric electrical insulation is ubiquitous, it generally exhibits low thermal conductivities (κ ; 0.1 – 0.3 W/mK). High κ electrical insulation systems are desirable for several reasons including improved heat wicking. Polymer-ceramic composites offer a viable path towards increasing κ of electrical insulation systems. However, processing-induced anisotropic particle orientation can result in prohibitively high concentrations of high κ particles being required to achieve impactful improvements. This work evaluates the effectiveness of a double percolation approach and its impacts on extruded polymer composite insulation κ using polyimide (PI), polyphenylsulfone (PPSU), and hexagonal boron nitride (hBN). Thermoplastic composite blends of PI/PPSU exhibited a 15% improvement in composite κ at comparable loading levels of hBN relative to mono-polymer material systems. On the other hand, PI/PPSU/hBN composites exhibited lower dielectric strengths than either neat polymer/hBN composite. A trade-off between maximizing material κ and resultant processing and dielectric performances may exist when using a double percolation approach for thermoplastic composites.

Witold K. Fuchs↗
DOE OSTI2021

Combustion Performance and Emissions Optimization through Integration of Miniaturized High Temperature Multi Process Monitoring System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of coal-fired utility boilers in this project but can be applied to many other industries and applications as well. The new sensor design, leveraging the existing electrochemical noise-based monitoring system, is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data can be transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, five mMPMS were installed at a full-scale pulverized coal-fired plant, Basin Electric Power Cooperative’s Leland Olds Unit 1. The systems were demonstrated over a 6-week period during typical operation. Sensor measurements of deposit thickness were validated during the demonstration and subsequently leveraged to determine sensor-based boiler cleaning strategies. These strategies have the benefit of reduced thermal stresses on boiler tubes from over-cleaning and improved boiler water management. At the end of the project, continued development of the sensor technology was carried out at PacifiCorp’s Hunter Station. REI leveraged the permanent installation of the mMPMS in Unit 3 made possible by DOE funding on a separate program. The work at Hunter Plant focused on application of machine learning and artificial intelligence-based models for integration of sensor signals into control and optimization of Hunter Unit 3 processes.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗
DOE OSTI2024

A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process

Recent progress in sensing techniques and data analytics tools have significantly accelerated the development of Wire Arc Additive Manufacturing (WAAM) systems. This data centric approach emphasizes leveraging available data throughout the production process to optimize performance. Integration of extensive data analysis provides the opportunity to improve precision, reduce waste, and enhance the quality of produced parts. This method relies on AI/ML models and optimization techniques, which are developed using the data collected from various sources, including in-situ sensors, ex-situ imaging, and manufacturing process parameters. The quality and diversity of this data, along with the alignment between different data streams (achieved through spatiotemporal registration) are critical for the successful development of AI/ML and optimization models. In this work, we present a spatiotemporally registered dataset generated during the WAAM process of deposition of a rectangular block. The dataset includes the comprehensive description of deposition process, process parameters, in-situ collected welding characteristics, acoustic data, and X-Ray Computed Tomography analysis data for the build. Dataset A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process has arisen under UT-Battelle, LLC’s Prime Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy (DOE) to manage and operate the Oak Ridge National Laboratory. UT-Battelle, LLC will not assert any rights under United States law or under the Prime Contract it has in the dataset against any user of the dataset, including any copyrights or patent rights. UT-Battelle, LLC requests that attribution to the dataset is provided as academically appropriate.

42 ENGINEERING↗
NASA NTRS2016

Testing of Synthetic Biological Membranes for Forward Osmosis Applications

Commercially available forward osmosis membranes have been extensively tested for human space flight wastewater treatment. Despite the improvements achieved in the last decades, there is still a challenge to produce reliable membranes with anti-fouling properties, chemical resistance, and high flux and selectivity. Synthetic biological membranes that mimic the ones present in nature, which underwent millions of years of evolution, represent a potential solution for further development and progress in membrane technology. Biomimetic forward osmosis membranes based on a polymeric support filter and coated with surfactant multilayers have been engineered to investigate how different manufacturing processes impact the performance and structure of the membrane. However, initial results of the first generation prototype membranes tests reveal a high scatter in the data, due to the current testing apparatus set up. The testing apparatus has been upgraded to improve data collection, reduce errors, and to allow higher control of the testing process.

Forward osmosis↗
NASA NTRS1993

Design of a water electrolysis flight experiment

Supply of oxygen (O2) and hydrogen (H2) by electolyzing water in space will play an important role in meeting the National Aeronautics and Space Administration's (NASA's) needs and goals for future space missios. Both O2 and H2 are envisioned to be used in a variety of processes including crew life support, spacecraft propulsion, extravehicular activity, electrical power generation/storage as well as in scientific experiment and manufacturing processes. The Electrolysis Performance Improvement Concept Study (EPICS) flight experiment described herein is sponsored by NASA Headquarters as a part of the In-Space Technology Experiment Program (IN-STEP). The objective of the EPICS is to further contribute to the improvement of the SEF technology, specifially by demonstrating and validating the SFE electromechanical process in microgravity as well as investigating perrformance improvements projected possible in a microgravity environment. This paper defines the experiment objective and presents the results of the preliminary design of the EPICS. The experiment will include testing three subscale self-contained SFE units: one containing baseline components, and two units having variations in key component materials. Tests will be conducted at varying current and thermal condition.

Lee, M. Gene↗
DOE OSTI2022

Corrosion of Stainless and Carbon Steel in Aqueous Piperazine for CO2 Capture

Current obstacles that prevent commercial implementation of amine-scrubbing CO2 capture are the high costs. Reducing capital costs by appropriate selection of construction materials, which requires knowledge of material corrosion performance for the process, will improve the economic feasibility of this technology. Corrosion was evaluated in three pilot plant campaigns using aqueous piperazine with the Advanced Stripper (PZAS). 316L stainless steel (SS) experienced higher corrosion than 304 SS and 2205 duplex SS, and the corrosion rate showed strong dependence on the temperature. 304 and 2205 performed well at all locations and should be good construction materials for PZAS. Degraded PZ exacerbated 316L corrosion, and removal of PZ degradation products using a carbon adsorption bed significantly reduced corrosion. Carbon steel (CS) corrosion showed a weak temperature effect because the corrosion was more dependent on the protective siderite film. The protectiveness of the films was related to fluid velocity. Ni-based alloys corroded in PZ, and the rate increased with temperature. Corrosion of C1010 CS and SS (304, 316L, 430) was measured at absorber and water wash conditions on the bench-scale. Corrosion rate decreases with increasing PZ. 8 With more than 0.003 m PZ in solution, CS has acceptable corrosion performance. Corrosion of CS increases with increasing partial pressure of CO2, suggesting loading is another dominant parameter for carbon steel corrosion. Temperature has a less significant effect than PZ concentration and loading. CS corrosion increases with increasing flow velocity at both absorber and water wash conditions. SS had little corrosion at this lower temperature. Performance of siderite (FeCO3) protective films on CS was studied at representative stripper conditions on the bench-scale. Siderite films can deposit on the surface of CS in CO2-loaded PZ solution at temperatures >100 °C and protect CS from corrosion. The protection may fail in degraded PZ. Ethylenediamine (EDA) is one of the major contributors for the loss of film protectiveness or can be the surrogate for the effect of PZ degradation on siderite film protection. A link between protectiveness and the apparent density of siderite films was discovered. The apparent density of siderite films decreases with increasing flow velocity and decreasing CO2 loading, resulting in higher corrosion of CS.

Liu, Ching-Ting↗
DOE OSTI2023

Vision-based localization for cooperative robot-CNC hybrid manufacturing

Wire and arc additive manufacturing (WAAM) has shown promise in recent years for producing large-scale parts with higher deposition rates than other additive processes. WAAM is often combined with subtractive machining to form a hybrid manufacturing process. This hybrid process can be realized by retrofitting computer numerical control (CNC) machines with deposition heads, adding spindles and deposition heads to robots, or developing part localization methods to transfer parts from an additive cell to a CNC machine. Here, a novel, robot-CNC hybrid configuration is introduced where a maneuverable robot is placed in front of a CNC machine to deposit material within the machine envelop. Furthermore, this method removes the need for part localization and the extensive machine modifications required for retrofitting; however, the problem of robot localization is also added. In this work, the effects of error in vision-based, contactless robot localization on machining parameters in a robot-machine hybrid process were studied. Performance was characterized on an implementation of this system using classical computer vision techniques. In addition, machining simulations were conducted to evaluate the effects of image-induced error on chip thickness, material removal rate, and machining allowance. Initial tests show that computer vision could adequately locate a robot for the hybrid WAAM process within .5 mm.

Hybrid manufacturing↗
DOE OSTI2025

Unsupervised Process Anomaly Detection and Identification Using the Leave-One-Variable-Out Approach

Automated anomaly detection and identification can signal equipment issues and pinpoint causes in large-scale industrial systems. For systems with limited failure history, unsupervised machine learning methods can be utilized as they do not require past failures. This study introduces the leave-one-variable-out (LOVO) model, which masks one variable at a time to predict the others, learning underlying process correlations. Detection performance was assessed with synthetic and experimental data, while identification performance used only synthetic data due to its ability to generate labeled anomaly types. For detection using synthetic data, the LOVO model generally outperformed comparative models; while using experimental data, the comparative methods outperformed the LOVO model. However, the comparative methods required selecting a latent size, and these conclusions pertain to using the optimal size. In practice, it would not be feasible to always select the optimal value, and incorrect selections impacted performance. In contrast, the LOVO model does not require a latent space. For identification using synthetic data, the LOVO model was slightly outperformed in interpretability and repeatability but still demonstrated impressive results. These outcomes suggest that the LOVO model is an effective model and may be more easily implemented without the challenging tuning process of selecting a latent size.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1981

Underground coal mining section data

A set of tables which display the allocation of time for ten personnel and eight pieces of underground coal mining equipment to ten function categories is provided. Data from 125 full shift time studies contained in the KETRON database was utilized as the primary source data. The KETRON activity and delay codes were mapped onto JPL equipment, personnel and function categories. Computer processing was then performed to aggregate the shift level data and generate the matrices. Additional, documented time study data were analyzed and used to supplement the KETRON databased. The source data including the number of shifts are described. Specific parameters of the mines from which there data were extracted are presented. The result of the data processing including the required JPL matrices is presented. A brief comparison with a time study analysis of continuous mining systems is presented. The procedures used for processing the source data are described.

Gabrill, C. P.↗