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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

An Update on the Geothermal Data Repository's Data Standards and Pipelines: Geospatial Data and Distributed Acoustic Sensing Data

The Department of Energy's (DOE) Geothermal Data Repository (GDR) team has implemented or is currently implementing data standards and automated data pipelines for the following geothermal data types: 1) drilling data, 2) geospatial datasets, and 3) Distributed Acoustic Sensing (DAS) data. These data standards and pipelines are intended to improve the real-world applicability of geothermal machine learning outputs through improving the quality of data. More specifically, through standardizing high-value datasets, the GDR is reducing project-specific data curation requirements, allowing more time to be spent on actual research. By automating this process, the burden of standardization is taken off of the user, overall increasing the availability of standardized data. This paper provides an update on the GDR's transition toward data standardization through automated data pipelines and calls for feedback from the community on how the GDR team can improve this process.

cloud-optimized↗
NASA NTRS1980

An interactive modular design for computerized photometry in spectrochemical analysis

A general functional description of totally automatic photometry of emission spectra is not available for an operating environment in which the sample compositions and analysis procedures are low-volume and non-routine. The advantages of using an interactive approach to computer control in such an operating environment are demonstrated. This approach includes modular subroutines selected at multiple-option, menu-style decision points. This style of programming is used to trace elemental determinations, including the automated reading of spectrographic plates produced by a 3.4 m Ebert mount spectrograph using a dc-arc in an argon atmosphere. The simplified control logic and modular subroutine approach facilitates innovative research and program development, yet is easily adapted to routine tasks. Operator confidence and control are increased by the built-in options including degree of automation, amount of intermediate data printed out, amount of user prompting, and multidirectional decision points.

Bair, V. L.↗
DOE OSTI2025

Automated RF Phase Adjustment for Beam Stabilization in the Fermilab Linac

The Fermilab Linac experiences longitudinal beam phase drift, leading to increased particle loss, conventionally corrected through labor-intensive manual RF adjustments. This project explores machine learning-based automation for drift correction, employing a prototype-based classification approach. Our model utilizes a 34-dimensional feature set (RF settings and BPM readings) and leverages a 7x27 response matrix for system modeling. To overcome limited real-world data, we generate synthetic data, enhancing model training and generalizability. Custom loss functions, including a surrogate energy-consistent loss and a temporal smoothness constraint, ensure physically plausible drift predictions. The goal is a robust system for autonomous phase adjustments, ensuring stable beam acceleration and reduced manual intervention.

Chichili, R. R. [Illinois U., Chicago]↗
NASA NTRS1997

Designing Automation to Reduce Operator Errors

Advanced automation has been accompanied, particularly in aircraft, with a proliferation of modes, where modes define mutually exclusive sets of system behavior. The new mode-rich systems provide flexibility and enhanced capabilities, but they also increase the need for and difficulty of maintaining mode awareness. While automation has eliminated some types of operator mode-awareness errors, it has also created the potential for new types of mode-related problems.

Leveson, Nancy G.↗
NASA NTRS2022

UAV Path Planning for Wildfires - Sustainably Fighting Wildfires with Automated Path Planning for UAVs

As the severity and frequency of wildfires increase, infrastructure, properties, national parks, animal habitats, and human lives (civilians and firefighters) are put at greater risk. This paper examines the possible application of algorithmic path planning for UAV reconnaissance to reduce damage and safety risks, as aforementioned. When the location of a wildfire is known, UAVs are immediately dispatched from an operating base to fly to the fire and support the firefighters as quickly as possible. Then, the algorithm incrementally analyzes different environmental factors to create a path for the UAV to follow. This work focuses on generating a path for the UAV to follow given a set of polygons representing obstacles. The most important features of this algorithm are its fast response time and obstacle maneuverability. The use of an efficient path planning algorithm could potentially save lives, infrastructure, and acres of forest destruction.

UAV↗
NASA NTRS1991

Automated power management and control

A comprehensive automation design is being developed for Space Station Freedom's electric power system. A joint effort between NASA's Office of Aeronautics and Exploration Technology and NASA's Office of Space Station Freedom, it strives to increase station productivity by applying expert systems and conventional algorithms to automate power system operation. The initial station operation will use ground-based dispatches to perform the necessary command and control tasks. These tasks constitute planning and decision-making activities that strive to eliminate unplanned outages. We perceive an opportunity to help these dispatchers make fast and consistent on-line decisions by automating three key tasks: failure detection and diagnosis, resource scheduling, and security analysis. Expert systems will be used for the diagnostics and for the security analysis; conventional algorithms will be used for the resource scheduling.

Dolce, James L.↗
DOE OSTI2024

Modeling and Automation Framework for High IBR Integration in Large-Scale Power Systems

The increasing prevalence of power electronics- interfaced renewable generation sources is leading to a gradual replacement of traditional thermal generation-based synchronous machines. In this context, the modeling of a large-scale power grid that incorporates a significant number of inverter-based resources is crucial for understanding the dynamics and effects of these resources on the power system. This study investigates the positive sequence model of grid-following and grid-forming inverters. Additionally, this work explores the integration of distributed energy resources using population as an indicator of their relative geographic locations. To address challenge to integrate these inverter based resources into a realistic grid of the US Western interconnection, automation scripts are developed to streamline the process of replacing conventional generators with grid-following and grid-forming inverters, as well as allocating distributed energy resources. Different penetration levels of these inverters are considered, and their frequency regulation support following a disturbance is compared through dynamic simulations.

Lyu, Xue↗
DOE OSTI2024

KLOKKOS: Automated test generation for performance-portable programs

SAND2024-13830O The KLOKKOS project provides a suite of test generation and validation tools to increase maintainability and portability of Kokkos programs. KLOKKOS, a portmanteau of Klee and Kokkos, is developing an automated test generation for performance-portable programs using Clang/low-level virtual machine (LLVM) and formal methods. KLOKKOS is based on several topics in computer science: the development of symbolic and concolic analysis of LLVM and C++ codes, formal semantics and type theory, C++ templates and language features, LLVM compiler infrastructure, and data parallel primitives. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525

SciDAC↗
DOE OSTI2025

Automated RF Phase Adjustment for Beam Stabilization in the Fermilab Linac

The Fermilab Linac experiences longitudinal beam phase drift, leading to increased particle loss, conventionally cor- rected through labor-intensive manual RF adjustments. This project explores machine learning-based automation for drift correction, employing a prototype-based classification approach. Our model utilizes a 34-dimensional feature set (RF settings and BPM readings) and leverages a 7x27 response matrix for system modeling. To overcome limited real-world data, we generate synthetic data, enhancing model training and generalizability. Custom loss functions, including a sur- rogate energy-consistent loss and a temporal smoothness constraint, ensure physically plausible drift predictions. The goal is a robust system for autonomous phase adjustments, ensuring stable beam acceleration and reduced manual intervention.

Chichili, R. R. [U. Illinois, Chicago]↗
NASA NTRS1993

Using machine learning techniques to automate sky survey catalog generation

We describe the application of machine classification techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Palomar Observatory Sky Survey provides comprehensive photographic coverage of the northern celestial hemisphere. The photographic plates are being digitized into images containing on the order of 10(exp 7) galaxies and 10(exp 8) stars. Since the size of this data set precludes manual analysis and classification of objects, our approach is to develop a software system which integrates independently developed techniques for image processing and data classification. Image processing routines are applied to identify and measure features of sky objects. Selected features are used to determine the classification of each object. GID3* and O-BTree, two inductive learning techniques, are used to automatically learn classification decision trees from examples. We describe the techniques used, the details of our specific application, and the initial encouraging results which indicate that our approach is well-suited to the problem. The benefits of the approach are increased data reduction throughput, consistency of classification, and the automated derivation of classification rules that will form an objective, examinable basis for classifying sky objects. Furthermore, astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems given automatically cataloged data.

Fayyad, Usama M.↗
NASA NTRS1993

OMP-26 - An interactive scheduling tool for the 26 meter subnetwork

Operations Mission Planner for the 26 Meter (26M) Antenna Subnetwork (OMP-26) is an interactive scheduling tool developed by the Jet Propulsion Laboratory (JPL) to assist in allocating the Deep Space Network (DSN) 26M antennas to support Earth-orbiting Spacecraft (SC). Prior to integrating OMP-26 into the 26M scheduling arena, the text-based, labor-intensive task lacked the sufficient means to support the 1992 mission support increase. Therefore, JPL developed the OMP-26 interactive scheduling tool to automate the time consuming tasks of the existing, manual scheduling process. OMP-26 has addressed the scheduling dilemma by assisting schedulers to identify and resolve conflicts more quickly through its graphical display features and constraint-checking editing capability. Although OMP-26 has reduced the scheduler's existing workload by easing the identification and resolution of conflicts, it will not meet the needs of another mission support increase to occur by 1995. Therefore, future plans for OMP-26 involve transitioning from a solely interactive scheduling tool to one that is highly automated and more powerful.

Rosas, Jody L.↗
NASA NTRS1985

On orbit mission planning using the shuttle trajectory and launch window expert system

With the Space Transportation System (STS) entering the operational era, the need for standardized, automated, mission planning computer tools has become apparent. In order to support an increased flight rate without an increase in manpower, quicker and more efficient methods are needed to perform standard tasks. The Shuttle Trajectory and Launch Window Expert System (STALEX) was developed to automate many aspects of early mission planning for space shuttle missions carrying geosynchronous communications satellites. Most of the commercial Shuttle missions planned for the next 3 years will carry at least one of this type of satellite. The applications of STALEX include payload deployment scheduling, launch window analysis, orbital trajectory determination, and landing opportunity selection.

Ahlf, P. R.↗
NASA NTRS1993

Ice thickness measurement system for the icing research tunnel calibration

To measure icing patterns across a test section of the Icing Research Tunnel, an automated rotating bar measurement system was developed at NASA LeRC. In comparison with the previously used manual measurement system, this system provides a number of improvements: increased accuracy and repeatability, increased number of data points, reduced tunnel operating time, and improved documentation. The automated system uses a linear variable differential transformer (LVDT) to measure ice accretion. This instrument is driven along the bar by means of an intelligent stepper motor which also controls data recording. This paper describes the rotating bar calibration measurement system.

Gibson, Theresa L.↗
NASA NTRS1997

Development of an Automated Reader for Analysis and Storage of Personnel Dosimeter Badge Data

The collection and archiving of data from personnel dosimeters has become increasingly important in light of the lowered Threshold Limit Values (TLV) for HydraZine (HZ), MonoMethylHydrazine (MMH), and Unsymmetrical DiMethylHydrazine (UDMH). The American Conference of Government Industrial Hygienists (ACGIH) lowered the TLV from 100 parts per billion (ppb) to IO ppb and has caused increased concern over long term exposures of personnel to trace levels of these hypergols and other potentially harmful chemicals. An automated system of reading the exposure levels of personnel dosimeters and storing exposure data for subsequent evaluation has been developed. The reading of personnel dosimeter badges for exposure to potentially harmful vapor concentrations of hydrazines or other chemicals is performed visually by comparing the color developed by the badge with a calibrated color comparator. The result obtained using visual comparisons of the developed badge color with the comparator may vary widely from user to user. The automated badge reader takes the variability out of the dosimeter reading by accurately comparing the reflectance obtained from a colored spot on the badge with a reading on the same spot prior to any exposure to chemical vapors. The observed difference between the reflectance values is used as part of a calculation of the dose value for the badge based on a stored calibration curve. The badge reader also stores bar-code data unique to each badge, as well as bar-code information on the user, as part of the permanent badge record. The start and stop exposure times for each badge are recorded and can be used as part of the calculated concentration, in ppm, for each badge logged during a recording period. The badge reader is equipped with a number of badge holders, each of which is unique to a specific type of personnel dosimeter badge. This gives the reader maximum flexibility to allow for the reading of several different types of badges. Test results of the badge reader for several different types of personnel dosimeter badges are presented within the body of this paper.

Meneghelli, B. J.↗
NASA NTRS1997

Development of an Automated Reader for Analysis and Storage of Personnel Dosimeter Badge Data

The collection and archiving of data from personnel dosimeters has become increasingly important in light of the lowered threshold limit values (TLV) for hydrazine (HZ), monomethylhydrazine (MMH), and unsymmetrical dimethylhydrazine (UDMH). The American Conference of Government Industrial Hygienists (ACGIH) lowered the TLV from 100 parts per billion (ppb) to 10 ppb and has caused increased concern over long term exposures of personnel to trace levels of these hypergols and other potentially harmful chemicals. An automated system of reading the exposure levels of personnel dosimeters and storing exposure data for subsequent evaluation has been developed. The reading of personnel dosimeter badges for exposure lo potentially harmful vapor concentrations of hydrazines or other chemicals is performed visually by comparing the color developed by the badge with a calibrated color comparator. The result obtained using visual comparisons of the developed badge color with the comparator may vary widely from user to user. The automated badge reader takes the variability out of the dosimeter reading by accurately comparing the reflectance obtained from a colored spot on the badge with a reading on the same spot prior to any exposure to chemical vapors. The observed difference between the reflectance values is used as part of a calculation of the dose value for the badge based on a stored calibration curve. The badge reader also stores bar-code data unique to each badge, as well as bar-code information on the user, as part of the permanent badge record. The start and stop exposure times for each badge are recorded and can be used as part of the calculated concentration, in ppm, for each badge logged during a recording period. The badge reader is equipped with a number of badge holders, each of which is unique to a specific type of personnel dosimeter badge. This gives the reader maximum flexibility to allow for the reading of several different types of badges. Test results of the badge reader for several different types of personnel dosimeter badges are presented within the body of this paper.

Meneghelli, B. J.↗
NASA NTRS2012

Human-Automation Integration: Principle and Method for Design and Evaluation

Future space missions will increasingly depend on integration of complex engineered systems with their human operators. It is important to ensure that the systems that are designed and developed do a good job of supporting the needs of the work domain. Our research investigates methods for needs analysis. We included analysis of work products (plans for regulation of the space station) as well as work processes (tasks using current software), in a case study of Attitude Determination and Control Officers (ADCO) planning work. This allows comparing how well different designs match the structure of the work to be supported. Redesigned planning software that better matches the structure of work was developed and experimentally assessed. The new prototype enabled substantially faster and more accurate performance in plan revision tasks. This success suggests the approach to needs assessment and use in design and evaluation is promising, and merits investigatation in future research.

human-automation integration↗
DOE OSTI2023

Automated Air Sealing Demonstration: Denver Federal Center Building 40

This project aimed to demonstrate building airtightness achieved by automated air sealing in a commercial building setting. The automated air sealing demonstrated in this project uses a modified blower door to pressurize and distribute the sealing aerosol to achieve the required building airtightness. To demonstrate this technology, Building 40 at the Denver Federal Center, a federally owned campus under the jurisdiction, custody and control of the U.S. General Services Administration (GSA), was selected for testing (Figure 2). This building is currently undergoing several retrofit projects, including increasing insulation, installing high-performance windows, and adding advanced equipment, control systems, and automated air sealing. This demonstration project involved installing automated air sealing and measuring the improvements in the building's airtightness. The automated air sealing was installed over two days by AeroBarrier, the vendor. An external blower door test contractor measured the airtightness of the demonstration space before and after air sealing. The new airtightness value and the percentage increase in airtightness were used to evaluate the energy savings potential of automated air sealing. These airtightness values were used to compute the energy savings and CO 2 emissions reduction for different climate zones, building types, and initial airtightness conditions. In addition, the heating, ventilation and air conditioning (HVAC) load reduction attributable to the reduced building air leakage was studied. This study included research to determine the cost and time reduction of automated air sealing. Finally, the automated air sealing performance was evaluated qualitatively using a focus group discussion that included GSA and Bristol, the general contractor. The installation has shown the demonstration site, with a floor size of 4,462 ft 2 , air leakage has reduced by more than 50% in less than 7 hours, including preparation, site sealing, and cleanup. The performance objectives were classified as quantitative or qualitative based on the evaluation metrics used to assess the project’s success. The key performance objectives for this project were the level of airtightness achieved, the time and cost required to perform the sealing, and the HVAC load reduction attributable to air sealing. Table 1 shows the quantitative performance objectives.

42 ENGINEERING↗
NASA NTRS1994

Models of Human Information Requirements: "When Reasonable Aiding Systems Disagree"

Aircraft flight management and Air Traffic Control (ATC) automation are under development to maximize the economy of flight and to increase the capacity of the terminal area airspace while maintaining levels of flight safety equal to or better than current system performance. These goals are being realized by the introduction of flight management automation aiding and operations support systems on the flight deck and by new developments of ATC aiding systems that seek to optimize scheduling of aircraft while potentially reducing required separation and accounting for weather and wake vortex turbulence. Aiding systems on both the flight deck and the ground operate through algorithmic functions on models of the aircraft and of the airspace. These models may differ from each other as a result of variations in their models of the immediate environment. The resultant flight operations or ATC commands may differ in their response requirements (e.g. different preferred descent speeds or descent initiation points). The human operators in the system must then interact with the automation to reconcile differences and resolve conflicts. We have developed a model of human performance including cognitive functions (decision-making, rule-based reasoning, procedural interruption recovery and forgetting) that supports analysis of the information requirements for resolution of flight aiding and ATC conflicts. The model represents multiple individuals in the flight crew and in ATC. The model is supported in simulation on a Silicon Graphics' workstation using Allegro Lisp. Design guidelines for aviation automation aiding systems have been developed using the model's specification of information and team procedural requirements. Empirical data on flight deck operations from full-mission flight simulation are provided to support the model's predictions. The paper describes the model, its development and implementation, the simulation test of the model predictions, and the empirical validation process. The model and its supporting data provide a generalizable tool that is being expanded to include air/ground compatibility and ATC crew interactions in air traffic management.

Corker, Kevin↗