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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

An Analysis of the Strayton Engine, a Brayton and Stirling Cycle Recuperating Engine

This paper explores the novel Strayton engine concept. This engine combines the cycles of a Brayton engine with that of a Stirling engine to create a highly efficient recuperating gas turbine engine. In the explored case, both Brayton cycle and Stirling cycle engines are used to generate electrical power. Additionally, the Stirling engine is used to draw heat out of the Brayton turbine (acting to cool the turbine blades), while also pumping heat into Brayton cycle just before combustion occurs (acting as the mechanism for recuperation). The purpose of this paper is to detail the system level modeling techniques used to generate the simulation, perform a cycle analysis of the combined cycle engine, identify key technologies and challenges associated with the concept, and compare potential performance gains with existing gas turbine engines and internal combustion engines. Topics such as controls, blade cooling effects, engine weight, and heat transfer using heat pipe are also explored. Results from this work show potential architectures that could provide the required heat transfer rates, potential control strategies, and performance benefits, including efficiency gains between 10% and 3% on engines ranging from 200HP to 670HP with the combined cycle engine.

Chapman, Jeffryes W.↗
NASA NTRS2019

An Analysis of the Strayton Engine, a Brayton and Stirling Cycle Recuperating Engine

This paper explores the novel Strayton engine concept. This engine combines the cycles of a Brayton engine with that of a Stirling engine to create a highly efficient recuperating gas turbine engine. In the explored case, both Brayton cycle and Stirling cycle engines are used to generate electrical power. Additionally, the Stirling engine is used to draw heat out of the Brayton turbine (acting to cool the turbine blades), while also pumping heat into Brayton cycle just before combustion occurs (acting as the mechanism for recuperation). The purpose of this paper is to detail the system level modeling techniques used to generate the simulation, perform a cycle analysis of the combined cycle engine, identify key technologies and challenges associated with the concept, and compare potential performance gains with existing gas turbine engines and internal combustion engines. Topics such as controls, blade cooling effects, engine weight, and heat transfer using heat pipe are also explored. Results from this work show potential architectures that could provide the required heat transfer rates, potential control strategies, and performance benefits, including efficiency gains between 10% and 3% on engines ranging from 200HP to 670HP with the combined cycle engine.

Gas turbine engine↗
NASA NTRSDate not supplied

CERES ERBE-like Instantaneous TOA Estimates (ES-8) in HDF (CER_ES8_Terra-FM2_Edition1-CV)

The ES-8 archival data product contains a 24-hour, single-satellite, instantaneous view of scanner fluxes at the top-of-atmosphere (TOA) reduced from spacecraft altitude unfiltered radiances using Earth Radiation Budget Experiment (ERBE) scanner Inversion algorithms and the ERBE shortwave (SW) and longwave (LW) Angular Distribution Models (ADMs). The ES-8 also includes the total (TOT), SW, LW, and window (WN) channel radiometric data; SW, LW, and WN unfiltered radiance values; and the ERBE scene identification for each measurement. These data are organized according to the CERES 3.3-second scan into 6.6-second records. As long as there is one valid scanner measurement within a record, the ES-8 record will be generated. The following CERES ES8 data sets are currently available: CER_ES8_TRMM-PFM_Edition1 CER_ES8_TRMM-PFM_Edition2 CER_ES8_TRMM-PFM_Transient-Ops2 CER_ES8_Terra-FM1_Edition1 CER_ES8_Terra-FM2_Edition1 CER_ES8_Terra-FM1_Edition2 CER_ES8_Terra-FM2_Edition2 CER_ES8_Aqua-FM3_Edition1 CER_ES8_Aqua-FM4_Edition1 CER_ES8_Aqua-FM3_Edition2 CER_ES8_Aqua-FM4_Edition2 CER_ES8_Aqua-FM3_Edition1-CV CER_ES8_Aqua-FM4_Edition1-CV CER_ES8_Terra-FM1_Edition1-CV CER_ES8_Terra-FM1_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2006-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

WINDOW UNFILTERED RADIANCE↗
NASA NTRSDate not supplied

CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Aqua-FM4_Edition1)

The ERBE-like Monthly Geographical Averages (ES-4) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

NET FLUX↗
DOE OSTI2023

Natural Language Processing for Text Based Event Extraction: Identifying Events of Interest Related to Worldwide State-Sponsored Civil Nuclear Power

Beginning in FY20, SRNL was funded by the National Nuclear Security Administration’s Office of Defense Nuclear Non-Proliferation Research and Development to develop a prototype natural language processing/natural language understating machine learning-based modeling and analysis pipeline to extract and forecast events of interest from massive open data sources. The working hypothesis within the approach is that contextual shifts in key words and phrases act as indicators of events of interest over time. Therefore, by identifying points in time where contextual shifts occur, events of interest can be extracted along with explicit and implicit connections of entities and activities. The development of the preliminary prototype pipeline proved successful, meriting further testing of the pipeline on more broad topical domains and in a worldwide data environment. Therefore, SRNL, in collaboration with the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Tech, have continued development with a test case of identifying events of interest related to worldwide state-sponsored civil nuclear power in open data sources. In the first year of this follow-on effort, the team has curated domain-specific data corpuses using an automated scheme and applied the modeling and analysis pipeline. This robust, focused, and efficient approach consists of an ensemble of analyses applied to time dependent word embedding models that are trained on the data corpuses. In this report, the team has demonstrated the capability of the existing pipeline (as development has continued in parallel) by exploring several specific case-studies centered around Rosatom’s international activities regarding the planning, construction, operation, and/or shutdown of nuclear reactors. A basic timeline events has been generated by manually cataloging known “milestone” events that have occurred at reactors in Turkey, Finland, Hungary, and Egypt and compared with the output of the modeling pipeline. In this approach, the team has characterized the lead time using the prototype pipeline, as well as the ability to capture relevant information, which proved 100% successful. A deep dive example of the Akkuyu reactor (Turkey) is presented that shows the breadth of information that can be captured using the approach. In this case study, events were extracted pertaining to the planning/construction of Akkuyu including protests from the population, information campaigns in response to the protests, forged regulatory documents and lawsuits, budgetary/shareholder information, geopolitical tensions, and the various construction milestones. This has demonstrated the pipeline’s utility as a research aid or real-time event extraction tool, where summary-level information and detailed text extractions from millions of articles or Tweets across long time periods can be generated with significantly less effort than current techniques.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

MHD, disruptions and control physics: Chapter 4 of the special issue: on the path to tokamak burning plasma operation

In this chapter, we review the progress in MHD stability, disruptions and control in magnetic fusion research that has occurred over the past (more than) one and a half decades since the publication by Hender et al in 2007 on the same topic as part of the update of ITER Physics Basis. During this period, remarkable progress has been achieved in the understanding of the basic physics and overall control of MHD instabilities through a wide spectrum of dedicated experiments, theory and modeling. The sawtooth activities are probably today one of the best understood of MHD events and very robust control schemes have been developed for reliable operation of tokamaks through core heating. Similarly, significant improvements have been achieved in understanding and control of neoclassical tearing modes, resistive wall modes or locked modes and their control through ECCD or error field control. The field of disruption prediction through application of artificial intelligence, machine learning or deep learning methods, which had already started at the time of the 2007 review, has progressed significantly due to general progress in these fields and application of newer, more sophisticated algorithms. However, although remarkable progress has been achieved in the field of Disruptions, their understanding, prediction, possible avoidance and mitigation still remain probably the most active fields of R&D globally in this field. This is especially because reactor grade machines like ITER and DEMO will be much less tolerant in respect of disruptions and runaway currents, and their occurrences must be either avoided altogether or minimized to an acceptable value without causing any significant hindrance to robust machine operations. This review is intended to present a broad spectrum of the R&D that has occurred in this field in support of ITER, which will also be of immense significance for all future machines, especially reactors like DEMO.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A Strategy for NACS investment in Machine Learning

The Nuclear and Chemical Sciences (NACS) Division furnishes the expertise in the scientific areas of chemical, nuclear and isotopic sciences that are foundational in the Laboratory’s national security missions. This expertise is maintained and advanced through identification, development and application of state-of-the-art theoretical, computational and experimental methods and tools. Recent developments in artificial intelligence and machine learning (AI/ML) techniques enabled by advances in computing capabilities and widespread availability of powerful software implementations have made use of these techniques ubiquitous across both science and industry. While the scope of AI/ML applications is incredibly large and evolves very rapidly, the topics most relevant to NACS missions fall into the general category of detecting, categorizing or identifying features in large, complex datasets using either supervised or unsupervised learning. This covers both basic scientific data analysis and the development of efficient surrogate models of real-life technological systems, experimental detectors, or theoretical models. To remain at the forefront of its core scientific disciplines, NACS must both cultivate ML expertise as well as continuously explore applying this expertise to new problems or utilizing new methods. This document identifies the key areas where this support is critical and provides a strategy for investing in them.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

Wind Plant Flow Physics and Power Performance in Complex Environments: Cooperative Research and Development (Final Report)

Cornell University will partner with NLR on the topic of wind farm wake effects to improve understanding of interactions between complex atmospheric flows, terrain, and wind turbine wakes and plant efficiency. Wind plant flow simulation tools will also be validated. The work performed will help improve wind farm modeling by analyzing data, applying models, designing and performing experiments to acquire additional wind farm data, and develop better models.

17 WIND ENERGY↗
NASA NTRS1974

Simulation of traffic control signal systems

In recent years there has been considerable interest in the development and testing of control strategies for networks of urban traffic signal systems by simulation. Simulation is an inexpensive and timely method for evaluating the effect of these traffic control strategies since traffic phenomena are too complex to be defined by analytical models and since a controlled experiment may be hazardous, expensive, and slow in producing meaningful results. This paper describes the application of an urban traffic corridor program, to evaluate the effectiveness of different traffic control strategies for the Massachusetts Avenue TOPICS Project.

Connolly, P. J.↗
NASA NTRS1978

The Third General Scientific Assembly of the International Association of Geomagnetism and Aeronomy - Special sessions of auroral processes

Methods of timing magnetic substorms, the rapid fluctuations of aurorae, electromagnetic and electrostatic instabilities observed on the field lines of aurorae, the auroral microstructure, and the relationship of currents, electric field and particle precipitation to auroral form are discussed. Attention is given to such topics as D-perturbations as an indicator of substorm onset, the role of the magnetotail in substorms, spectral information derived from imaging data on aurorae, terrestrial kilometric radiation, and the importance of the mirror force in self-consistent models of particle fluxes, currents and potentials on auroral field lines.

Russell, C. T.↗
NASA NTRS1980

Space shuttle base heating analysis

Work performed in support of radiation and convective base heating predictions in developing the space shuttle thermal environment is described. Topics discussed include plume radiation predictions and the development of prediction methods; convective base heating predictions due to both reversed flow and direct plume impingement; and evaluation testing of a gas temperature probe used in short-duration base heating model tests.

Source record↗
NASA NTRS1982

Solidification processing

The solidification processing activities are reported. The following topics are studied: behavior of semisolid metals, purification and strengthening by fractional melting, continuous casting, control of ingot surface quality, and metal matrix composites. Formation of deoxidation products in steels is also investigated. Rapid solidification, crystal growth, experimental and mathematical modeling of solidification processes are explored.

Source record↗
NASA NTRS1987

Quadrennial review of the magnetotail

The findings of research conducted on the magnetotail in the years 1983-1986 are presented. The topics discussed include observations of the distant (between 60 and 220 earth radii) and the near-earth (earthward of 35 earth radii) magnetotail regions by the ISEE l, 2, and 3 and IMP 8 spacecraft, and magnetotail theory and modeling. These studies established the association between substorms and plasmoids in the deep tail and the linkage between the magnetosphere and the ionosphere via field-aligned currents and electric fields.

Huang, C. Y.↗
NASA NTRS1992

Advanced electromagnetic methods for aerospace vehicles

The Advanced Helicopter Electromagnetics (AHE) Industrial Associates Program continues its research on variety of main topics identified and recommended by the Advisory Task Force of the program. The research activities center on issues that advance technology related to helicopter electromagnetics. While most of the topics are a continuation of previous works, special effort has been focused on some of the areas due to recommendations from the last annual conference. The main topics addressed in this report are: composite materials, and antenna technology. The area of composite materials continues getting special attention in this period. The research has focused on: (1) measurements of the electrical properties of low-conductivity materials; (2) modeling of material discontinuity and their effects on the scattering patterns; (3) preliminary analysis on interaction of electromagnetic fields with multi-layered graphite fiberglass plates; and (4) finite difference time domain (FDTD) modeling of fields penetration through composite panels of a helicopter.

Balanis, Constantine A.↗
NASA NTRS1990

Recent developments in learning control and system identification for robots and structures

This paper reviews recent results in learning control and learning system identification, with particular emphasis on discrete-time formulation, and their relation to adaptive theory. Related continuous-time results are also discussed. Among the topics presented are proportional, derivative, and integral learning controllers, time-domain formulation of discrete learning algorithms. Newly developed techniques are described including the concept of the repetition domain, and the repetition domain formulation of learning control by linear feedback, model reference learning control, indirect learning control with parameter estimation, as well as related basic concepts, recursive and non-recursive methods for learning identification.

Phan, M.↗