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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 703 records · Page 39

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NASA NTRS1994

Mapping ERS-1 wind fields over north west Atlantic using a variational objective analysis

A variational method is implemented to produce five day mean gridded ERS-1 analyzed wind fields in the north west Atlantic with the aim of providing for wind forcing of basin scale ocean models. The method consists of minimizing a cost functional, designed to measure misfits to prescribed weighted constraints which express a smoothed behavior and the proximity to input data vectors and curl. The weights are empirically determined by comparison with independent ship and buoy data over four five day periods. Root mean square differences between analyzed winds and independent data are thus further decreased: they range from 0.8 up to 1.8 m/s. Some problems present in the initial data remain; they are principally due to incomplete data coverage (instrumental problems), and possibly unresolved ambiguities. The resulting curl fields are smoothed and show coherent patterns. A comparison with the European Center for Medium range Weather Forecasting (ECMWF) analysis is encouraging.

Siefridt, L.↗

NASA NTRS1997

A Case Study of 4 & 5 Cost Effectiveness

This paper looks at the Independent Verification and Validation (IV&V) of NASA's Space Shuttle Day of Launch I-Load Update (DoLILU) project. IV&V is defined. The system's development life cycle is explained. Data collection and analysis are described. DoLILU Issue Tracking Reports (DITRs) authored by IV&V personnel are analyzed to determine the effectiveness of IV&V in finding errors before the code, testing, and integration phase of the software development life cycle. The study's findings are reported along with the limitations of the study and planned future research.

Neal, Ralph D.↗

NASA NTRS1979

Low cost point focus solar concentrator, phase 1

Design concepts and plans for mass-production facilities and equipment, field installation, and maintenance were developed and used for cost analysis of a pneumatically stabilized plastic film point focus solar concentrator which has potential application in conjunction with Brayton cycle engines or supply of thermal energy. A sub-scale reflector was fabricated and optically tested by laser ray tracing to determine focal deviations of the surface slope and best focal plane. These test data were then used for comparisons with theoretical concentrator performance modeling and predictions of full-scale design performance. Results of the economic study indicate the concentrator design will have low cost when mass-produced and has cost/performance parameters that fall within current Jet Propulsion Laboratory goals.

Source record↗

NASA NTRS2015

Aeroelastic Analysis of a Flexible Wing Wind Tunnel Model with Variable Camber Continuous Trailing Edge Flap Design

This paper presents data analysis of a flexible wing wind tunnel model with a variable camber continuous trailing edge flap (VCCTEF) design for drag minimization tested at the University of Washington Aeronautical Laboratory (UWAL). The wind tunnel test was designed to explore the relative merit of the VCCTEF concept for improved cruise efficiency through the use of low-cost aeroelastic model test techniques. The flexible wing model is a 10%-scale model of a typical transport wing and is constructed of woven fabric composites and foam core. The wing structural stiffness in bending is tailored to be half of the stiffness of a Boeing 757-era transport wing while the torsional stiffness is about the same. This stiffness reduction results in a wing tip deflection of about 10% of the wing semi-span. The VCCTEF is a multi-segment flap design having three chordwise camber segments and five spanwise flap sections for a total of 15 individual flap elements. The three chordwise camber segments can be positioned appropriately to create a desired trailing edge camber. Elastomeric material is used to cover the gaps in between the spanwise flap sections, thereby creating a continuous trailing edge. Wind tunnel data analysis conducted previously shows that the VCCTEF can achieve a drag reduction of up to 6.31% and an improvement in the lift-to-drag ratio (L=D) of up to 4.85%. A method for estimating the bending and torsional stiffnesses of the flexible wingUWAL wind tunnel model from static load test data is presented. The resulting estimation indicates that the stiffness of the flexible wing is significantly stiffer in torsion than in bending by as much as 9 to 1. The lift prediction for the flexible wing is computed by a coupled aerodynamic-structural model. The coupled model is developed by coupling a conceptual aerodynamic tool Vorlax with a finite-element model of the flexible wing via an automated geometry deformation tool. Based on the comparison of the lift curve slope, the lift prediction for the rigid wing is in good agreement with the estimated lift coefficients derived from the wind tunnel test data. Due to the movement of the VCCTEF during the wind tunnel test, uncertainty in the lift prediction due to the indicated variations of the VCCTEF deflection is studied. The results show a significant spread in the lift prediction which contradicts the consistency in the aerodynamic measurements, thus suggesting that the indicated variations as measured by the VICON system may not be reliable. The lift prediction of the flexible wing agrees very well with the measured lift curve for the baseline configuration. The computed bending deflection and wash-out twist of the flexible wing also match reasonably well with the aeroelastic deflection measurements. The results demonstrate the validity of the aerodynamic-structural tool for use to analyze aerodynamic performance of flexible wings.

Wind Tunnel↗

DOE OSTI2025

Reweighting simulated events using machine-learning techniques in the CMS experiment

Data analyses in particle physics rely on an accurate simulation of particle collisions and a detailed simulation of detector effects to extract physics knowledge from the recorded data. Event generators together with a GEANT -based simulation of the detectors are used to produce large samples of simulated events for analysis by the LHC experiments. These simulations come at a high computational cost, where the detector simulation and reconstruction algorithms have the largest CPU demands. This article describes how machine-learning (ML) techniques are used to reweight simulated samples obtained with a given set of parameters to samples with different parameters or samples obtained from entirely different simulation programs. The ML reweighting method avoids the need for simulating the detector response multiple times by incorporating the relevant information in a single sample through event weights. Results are presented for reweighting to model variations and higher-order calculations in simulated top quark pair production at the LHC. This ML-based reweighting is an important element of the future computing model of the CMS experiment and will facilitate precision measurements at the High-Luminosity LHC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

Integration of Solid Oxide Fuel Cell Systems Into Artificial Intelligence Data Centers

This report presents the results of a techno-economic analysis (TEA) that evaluates the economic benefits of integrating solid oxide fuel cell (SOFC) systems with artificial intelligence (AI) data centers. The analysis was completed in two phases: a scoping-level analysis was performed to identify impactful integration opportunities, followed by a more detailed TEA. Results show that, due to their modularity, SOFC can meet the 99.999% availability requirement of data centers with minimal additional costs. Heat integration via absorption chillers decreases data center electricity consumption at the tradeoff of increased water consumption. Higher SOFC exhaust temperatures are important for achieving larger electricity savings. Finally, power electronics integration with SOFC direct current electricity can reduce electricity consumption by 9 percent and reduce water consumption by 6.4 percent.

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS1972

DORCA 2 computer program. Volume 1: User's guide

The Dynamic Operational Requirements and Cost Analysis Program (DORCA 2) is described. The computer program provides a top level analysis tool for NASA and relies on a man machine interaction to optimize results based on external criteria. The computer program relies heavily on outside sources to provide cost information and vehicle parameters. Given data describing mission, vehicles, payloads, containers, space facilities, schedules, cost values, and costing procedures, the program computes flight schedules, cargo manifests, vehicle fleet requirements, acquisition schedules, and cost summaries. The program is designed to consider earth orbit, lunar, interplanetary, and automated satellite missions.

Wray, S. T., Jr.↗

NASA NTRS1989

The use of COSMIC NASTRAN in an integrated conceptual design environment

Changes in both software and hardware are rapidly bringing conceptual engineering tools like finite element analysis into mainstream mechanical design. Systems that integrate all phases of the manufacturing process provide the most cost benefits. The application of programming concepts like object oriented programming allow for the encapsulation of intelligent data within the design geometry. This combined with declining cost in per seat hardware bring new alternatives to the user.

White, Gil↗

NASA NTRS1999

Superpolishing and Precision Metrology on a Metal Mandrel and Replicated Segments for Constellation-X

We have superpolished a diamond-turned aluminum mandrel (coated with electroless Ni) to an axial roughness of 6.34 nm rms. The mandrel is made to the Astro-E secondary mirror design for the 81st shell. Precision metrology at 100 mm to submicron scales has established the power spectral density of the mandrel and ultralightweight gold coated replicated segments. Predicted image quality of a set of optimally aligned replicated segments of this and a matching primary is substantially improved as compared to the flight mirrors for Astro-E. This approach using metal mandrels, superpolishing, and replicated ultralightweight foil mirrors, may represent a cost-effective approach to meeting the 15 arcsec half-energy width and weight requirements for the Constellation-X mission. Descriptions of the polishing apparatus, the precision metrology instruments, and the surface data analysis are presented. The general methods described are applicable to precision optics for both normal incidence and grazing incidence optics.

Content, D.↗

NASA NTRS1999

Superpolishing and Precision Metrology on a Metal Mandrel and Replicated Segments for Constellation-X

We have superpolished a diamond-turned aluminum mandrel (coated with electroless Ni) to an axial roughness of 0.34 nm rms. The mandrel is made to the Astro-E secondary mirror design for the 81st shell. Precision metrology at 100 mm to submicron scales has established the power spectral density of the mandrel and ultralightweight gold coated replicated segments. Predicted image quality of a set of optimally aligned replicated segments of this and a matching primary is substantially improved as compared to the flight mirrors for Astro-E. This approach using metal mandrels, superpolishing, and replicated ultralightweight foil mirrors, may represent a cost-effective approach to meeting the 15 arcsec half-energy width and weight requirements for the Constellation-X mission. Descriptions of the polishing apparatus, the precision metrology instruments, and the surface data analysis are presented. The general methods described are applicable to precision optics for both normal incidence and grazing incidence optics.

Content, D.↗

NASA NTRS1999

Superpolishing and Precision Metrology on a Metal Mandrel and Replicated Segments for Constellation-X

Content, D.↗

NASA NTRS2017

Towards the Development of a Global, Satellite-Based, Terrestrial Snow Mission Planning Tool

A global, satellite-based, terrestrial snow mission planning tool is proposed to help inform experimental mission design with relevance to snow depth and snow water equivalent (SWE). The idea leverages the capabilities of NASA's Land Information System (LIS) and the Tradespace Analysis Tool for Constellations (TAT-C) to harness the information content of Earth science mission data across a suite of hypothetical sensor designs, orbital configurations, data assimilation algorithms, and optimization and uncertainty techniques, including cost estimates and risk assessments of each hypothetical permutation. One objective of the proposed observing system simulation experiment (OSSE) is to assess the complementary or perhaps contradictory information content derived from the simultaneous collection of passive microwave (radiometer), active microwave (radar), and LIDAR observations from space-based platforms. The integrated system will enable a true end-to-end OSSE that can help quantify the value of observations based on their utility towards both scientific research and applications as well as to better guide future mission design. Science and mission planning questions addressed as part of this concept include: What observational records are needed (in space and time) to maximize terrestrial snow experimental utility? How might observations be coordinated (in space and time) to maximize this utility? What is the additional utility associated with an additional observation? How can future mission costs be minimized while ensuring Science requirements are fulfilled?

Mission Desig↗

NASA NTRS2018

K-Means Cluster Study for Radiofrequency Propagation Characterization

The objective of this study is to design a simple method for mining radio frequency (RF) propagation data. The study explored the characteristics of a large dataset of propagation experiments conducted over the span of years and using several ground stations around the world. Furthermore, this study developed simple predictive models that can be used for link characterization and overall propagation behavior description, without the need for physical measurements on-site. It is understood that such statistical learning has several drawbacks in terms of accuracy and precision. K-means clustering was used to characterize the data set in a way never explored before in an attempt to create useful tools that reduce cost, time and risk. K-means clustering was used to characterize the data set. Cosine distance was used as a method to determine the optimal number for clustering each feature. Dependence and independence analysis was performed to explore intra and inter-sensitivity between the presented features, with respect to each other and time. Several predicative models were generated and evaluated with respect to a test set to assess a measure of prediction accuracy and precision. A simple method for data analysis was developed and tested as the basis for further studies and future refinement to produce optimal performing models.

Cognitive↗

DOE OSTI2024

Assessing the Viability of Geothermal Microgrid Deployment: A Geospatial Analysis Across the United States

Geothermal microgrids hold a potential of supplying clean and dependable power to communities throughout the United States (US), all while sidestepping the expenses associated with connecting to strained or isolated power grids. Nonetheless, their implementation is still in its early stages in the country. The objective of this analysis is to leverage available data to pinpoint regions across the US that exhibit favorable conditions for the development of geothermal microgrids. Drawing from a variety of sources, including estimates of geothermal resources, the costs associated with geothermal energy generation and electricity transmission, existing microgrid locations, and subsidy programs, we aim to identify promising areas for further exploration. By mapping out the contiguous US, Alaska, and Hawaii, we delineate regions with high relative favorability for geothermal microgrid deployment. Our findings reveal the presence of highly favorable regions across the Western states of the contiguous US, as well as isolated areas in Alaska and Hawaii. Furthermore, we delve into a discussion on state policies and incentive programs, considering their role in fostering favorable conditions or posing barriers to geothermal microgrid development.

Alaska↗

NASA NTRS2005

Discovering System Health Anomalies Using Data Mining Techniques

We present a data mining framework for the analysis and discovery of anomalies in high-dimensional time series of sensor measurements that would be found in an Integrated System Health Monitoring system. We specifically treat the problem of discovering anomalous features in the time series that may be indicative of a system anomaly, or in the case of a manned system, an anomaly due to the human. Identification of these anomalies is crucial to building stable, reusable, and cost-efficient systems. The framework consists of an analysis platform and new algorithms that can scale to thousands of sensor streams to discovers temporal anomalies. We discuss the mathematical framework that underlies the system and also describe in detail how this framework is general enough to encompass both discrete and continuous sensor measurements. We also describe a new set of data mining algorithms based on kernel methods and hidden Markov models that allow for the rapid assimilation, analysis, and discovery of system anomalies. We then describe the performance of the system on a real-world problem in the aircraft domain where we analyze the cockpit data from aircraft as well as data from the aircraft propulsion, control, and guidance systems. These data are discrete and continuous sensor measurements and are dealt with seamlessly in order to discover anomalous flights. We conclude with recommendations that describe the tradeoffs in building an integrated scalable platform for robust anomaly detection in ISHM applications.

Sriastava, Ashok, N.↗

NASA NTRS2018

Using Historical Cost and Schedule Data to Predict Cost Risk for Future NASA X-Planes

Accurate cost estimates help managers understand critical cost-risk information, which improves their perception of the impact project changes have on the budget and schedule. This research project examined buffer reserves, a key aspect of cost estimation. The main focus of this project was to utilize historical data to calculate the extent to which NASA programs typically exceed their original buffers.

cost analysis↗

DOE OSTI2025

Informing Plant Asset Reliability and Availability Through AI-Driven Analysis of Operator Logs

The availability and reliability of nuclear power plant (NPP) structures, systems, and components (SSCs) are critical parameters for NPP safety. Tracking these parameters is necessary but costly and labor-intensive, requiring the collection and evaluation of SSC event data such as shutdowns, startups, and failures. To show how these events are needed for the parameters an example is given: one measure of reliability is based on the number of equipment failure events and the number of run hours (i.e., the time from a startup event to a shutdown event). Here, this work investigates using artificial intelligence (AI) to mine NPP operator log entry texts for SSC event data. Four AI approaches were explored for identifying these events, including natural language processing (NLP) methods, generative AI, generative AI combined with NLP, and topic modeling. A key challenge addressed with all four approaches is the brevity of operator log entries. Among these four a neural network–based NLP method was shown to be the most promising for this application, achieving F1 scores of 86.0% for shutdowns, 92.2% for startups, and 80.4% for failures on a subject-matter-expert-curated dataset from NPP operator logs, compared to a baseline of 66.6% for a random classifier. This shows that NLP methods can perform better than generative AI. Additionally, the NLP methods combined with generative AI were shown to perform better than generative AI alone. Generative AI was most successful at providing the background information for the NLP methods to use. This work demonstrates the potential to use AI to automate parameter collection from NPP operator log entries and other records.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

PDV Methods and Analysis for Surveillance of Explosive Components

The Weapons Evaluation Test Laboratory (WETL) at Sandia is collaborating with Lawrence Livermore National Laboratory (LLNL) to enhance explosive surveillance testing by integrating Photon Doppler Velocimetry (PDV) data. This project has streamlined the testing environment, reducing hardware costs and training needs while improving data collection efficiency and usability for lab technicians.

Kress, Matthew Kip [Sandia National Laboratories (↗