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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Neural network model of neutral beam injection in the EAST tokamak to enable fast transport simulations

The neutral beam injection (NBI) system in EAST produces energetic neutral particles, which collide with electrons and ions in tokamak plasmas and heat the plasmas through Coulomb collisions. Moreover, it drives a non-inductive source of current, due to the charge-exchange collision between neutral particles and ions, and injects toroidal torque, which generates a toroidal rotation of the plasma. The effect caused by the NBI system, such as plasma heating, current drive, total neutron rate, momentum transfer, and shine-through, are modeled by a comprehensive module called NUBEAM. However, NUBEAM is computationally intensive since it relies on Monte Carlo methods. In this work, a neural network model has been developed as a surrogate model for NUBEAM in EAST. The database for neural-network model training, validation and testing is generated by running TRANSP for experimental discharges from recent EAST campaigns (after the latest NBI upgrade) while using the NUBEAM module. Simulation results illustrate that the trained neural network has the capability of replicating the predictions made by NUBEAM while demanding a significantly shorter execution time. Finally, these results indicate that surrogate models like the one proposed in this work could enable fast transport simulations for EAST after integrating them into a control-oriented predictive code such as COTSIM.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Ambient energy for buildings: Beyond energy efficiency

The following Key Messages comprise the salient findings of this study: 1. Ambient energy (from sun, air, ground, and sky) can heat and cool buildings; provide hot water, ventilation and daylighting; dry clothes; and cook food. These services account for about three-quarters of building energy consumption and a third of total US demand. Biophilic design (direct and indirect connections with nature) is an intrinsic adjunct to ambient energy systems, and improves wellness and human performance. 2. The current strategy of electrification and energy efficiency for buildings will not meet our climate goals, because the transition to an all-renewable electric grid is too slow. Widespread adoption of ambient energy is needed. Solar-heated buildings also flatten the seasonal demand for electricity compared to all-electric buildings, reducing required production capacity and long-term energy storage. In addition, ambient-conditioned buildings improve resilience by remaining livable during power outages. 3. National policies, incentives, and marketing should be enacted to promote ambient energy use. Federal administrative priorities should reflect the importance of ambient energy for buildings. Use of ambient energy should be encouraged through existing and new building codes and standards. 4. Ambient energy system design tools are needed for architects, engineers, builders, building scientists, realtors, appraisers, and consumers. PVWatts is used over 100 million times per year for photovoltaic system design. A similar, simple, and accessible tool for ambient design is crucial. 5. Training on ambient energy is needed throughout secondary, post-secondary, and continuing education for workforce development. Currently, only about 10% of colleges teach courses on passive heating and cooling systems. 6. Ambient-conditioned buildings should be demonstrated in all US climate zones. Performance should be monitored and reported, with quantitative case studies made widely available. 7. While current technology is sufficient to build high-performance ambient buildings now, research is needed to develop new technologies to harness ambient energy more effectively and more economically. Such advancements will facilitate adoption of ambient energy technologies in a wider range of buildings, including retrofits. Examples include windows with much lower thermal losses, use of the building shell as thermal storage, alternative light-weight thermal storage systems, sky radiation cooling systems, automated controls for solar gains and passive cooling, and ground coupling.

14 SOLAR ENERGY↗
DOE OSTI2024

Cryo2StructData: A Large Labeled Cryo-EM Density Map Dataset for AI-based Modeling of Protein Structures

The advent of single-particle cryo-electron microscopy (cryo-EM) has brought forth a new era of structural biology, enabling the routine determination of large biological molecules and their complexes at atomic resolution. The high-resolution structures of biological macromolecules and their complexes significantly expedite biomedical research and drug discovery. However, automatically and accurately building atomic models from high-resolution cryo-EM density maps is still time-consuming and challenging when template-based models are unavailable. Artificial intelligence (AI) methods such as deep learning trained on limited amount of labeled cryo-EM density maps generate inaccurate atomic models. To address this issue, we created a dataset called Cryo2StructData consisting of 7,600 preprocessed cryo-EM density maps whose voxels are labelled according to their corresponding known atomic structures for training and testing AI methods to build atomic models from cryo-EM density maps. Cryo2StructData is larger than existing, publicly available datasets for training AI methods to build atomic protein structures from cryo-EM density maps. We trained and tested deep learning models on Cryo2StructData to validate its quality showing that it is ready for being used to train and test AI methods for building atomic models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

miniWeather

The code “miniWeather” solves the 2-D Euler equations with a Finite-Volume method on a regular Cartesian grid with Runge-Kutta time stepping, 4th-order hypervisocisty, and 4th-order spatial accuracy. The code is primarily a parallel programming training mini application in Fortran, C, and C++ with MPI, OpenMP, OpenMP offload, OpenACC, and C++ portability approaches. It can also serve as a mini application for acceptance testing for new machines and compilers for both functionality and performance.

Norman, MatthewR↗
DOE OSTI2023

Machine Learning-Based Regression Models for Ironmaking Blast Furnace Automation

Computational fluid dynamics (CFD)-based simulation has been the traditional way to model complex industrial systems and processes. One very large and complex industrial system that has benefited from CFD-based simulations is the steel blast furnace system. The problem with the CFD-based simulation approach is that it tends to be very slow for generating data. The CFD-only approach may not be fast enough for use in real-time decisionmaking. To address this issue, in this work, the authors propose the use of machine learning techniques to train and test models based on data generated via CFD simulation. Regression models based on neural networks are compared with tree-boosting models. In particular, several areas (tuyere, raceway, and shaft) of the blast furnace are modeled using these approaches. The results of the model training and testing are presented and discussed. The obtained R 2 metrics are, in general, very high. The results appear promising and may help to improve the efficiency of operator and process engineer decisionmaking when running a blast furnace.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1970

An Exercise Prescription Intervention Program with Periodic Ergometric Grading

A long term exercise prescription type of physical conditioning program has been available to executive personnel of the NASA Manned Spacecraft Center for the past two years. Periodic ergometric testing with a heart rate controlled, automatically programmed, bicycle ergometer is used to follow the individual's progress and appropriately alter his exercise prescription from time to time. Such a program appears feasible, and acceptance is excellent, dropout rates small and periodic testing participation good. Subjects training diligently can maintain satisfactory levels of conditioning.

Owen, C. A.↗
NASA NTRS1979

Liquid oxygen/liquid hydrogen auxiliary power system thruster investigation

The design, fabrication, and demonstration of a 111 newton (25 lb) thrust, integrated auxiliary propulsion system (IAPS) thruster for use with LH2/LO2 propellants is described. Hydrogen was supplied at a temperature range of 22 to 33 K (40 to 60 R), and oxygen from 89 to 122 K (160 to 220 R). The thruster was designed to operate in both pulse mode and steady-state modes for vehicle attitude control, space maneuvering, and as an abort backup in the event of failure of the main propulsion system. A dual-sleeve, tri-axial injection system was designed that utilizes a primary injector/combustor where 100 percent of the oxygen and 8 percent of the hydrogen is introduced; a secondary injector/combustor where 45 percent of the hydrogen is introduced to mix with the primary combustor gases; and a boundary layer injector that uses the remaining 45 percent of the hydrogen to cool the thrust throat/nozzle design. Hot-fire evaluation of this thruster with a BLC injection distance of 2.79 cm (1.10 in.) indicated that a specific impulse value of 390 sec can be attained using a coated molybdenum thrust chamber. Pulse mode tests indicated that a chamber pressure buildup to 90 percent thrust can be achieved in a time on the order of 48 msec. Some problems were encountered in achieving ignition of each pulse during pulse trains. This was interpreted to indicate that a higher delivered spark energy level ( 100 mJ) would be required to maintain ignition reliability of the plasma torch ignition system under the extra 'cold' conditions resulting during pulsing.

Eberle, E. E.↗
NASA NTRS1981

Relation of the activities of the IPDF/INPE project (reforestation subproject) during the year 1979

The state of Mato Grosso do Sul was selected as the study area to define the recognizable classes of Eucalyptus spp. and Pinus spp. by visual and automatic analyses. For visual analysis, a preliminary interpretation key and a legend of 6 groups were derived. Based on these six groups, three final classes were defined for analysis: (1) area prepared for reforestation; (2) area reforested with Eucalyptus spp.; and (3) area reforested with Pinus spp. For automatic interpretation the area along the highway from Ribas do Rio Pardo to Agua Clara was classified into the following classes: eucalytus, bare soil, plowed soil, pine and "cerrado". The results of visual analysis show that 67% of the reforested farms have relative differences in area estimate below 5%, 22%, between 5% and 10%; and 11% between 10% and 20%. The reforested eucalyptus area is 17 times greater than the area of reforested pine. Automatic classification of eucalyptus ranged from 73.03% to 92.30% in the training areas.

Dejesusparada, N.↗
NASA NTRS1986

An Ada implementation of the network manager for the advanced information processing system

From an implementation standpoint, the Ada language provided many features which facilitated the data and procedure abstraction process. The language supported a design which was dynamically flexible (despite strong typing), modular, and self-documenting. Adequate training of programmers requires access to an efficient compiler which supports full Ada. When the performance issues for real time processing are finally addressed by more stringent requirements for tasking features and the development of efficient run-time environments for embedded systems, the full power of the language will be realized.

Nagle, Gail A.↗
NASA NTRS1993

Influence of simulated microgravity on the maximal oxygen consumption of nontrained and trained rats

The effects of microgravity and endurance training (TR) on maximal O2 consumption was investigated in trained and nontrained (NT) rats subjected to head-down suspension (HDS) by comparing maximal O2 consumption, treadmill run time (RT), and mechanical efficiency (ME) of treadmill running in HDS rats, both NT and TR, and in respective cage controls. It was found that HDS for 28 days was associated with significant reduction in absolute maximal O2 consumption in both TR and NT rats. Relative maximal O2 consumption, however, was significantly reduced in TR but not NT rats. Reductions in RT and ME occurring in both TR and NT rats after 28 days of HDS were similar. The TR rats exhibited greater diuretic, natriuretic, and kaliuretic responses to HDS than the NT rats.

Woodman, Christopher R.↗
NASA NTRS1994

A distributed computing model for telemetry data processing

We present a new approach to distributing processed telemetry data among spacecraft flight controllers within the control centers at NASA's Johnson Space Center. This approach facilitates the development of application programs which integrate spacecraft-telemetered data and ground-based synthesized data, then distributes this information to flight controllers for analysis and decision-making. The new approach combines various distributed computing models into one hybrid distributed computing model. The model employs both client-server and peer-to-peer distributed computing models cooperating to provide users with information throughout a diverse operations environment. Specifically, it provides an attractive foundation upon which we are building critical real-time monitoring and control applications, while simultaneously lending itself to peripheral applications in playback operations, mission preparations, flight controller training, and program development and verification. We have realized the hybrid distributed computing model through an information sharing protocol. We shall describe the motivations that inspired us to create this protocol, along with a brief conceptual description of the distributed computing models it employs. We describe the protocol design in more detail, discussing many of the program design considerations and techniques we have adopted. Finally, we describe how this model is especially suitable for supporting the implementation of distributed expert system applications.

Barry, Matthew R.↗
NASA NTRS2002

A Scalable, Out-of-Band Diagnostics Architecture for International Space Station Systems Support

The computational infrastructure of the International Space Station (ISS) is a dynamic system that supports multiple vehicle subsystems such as Caution and Warning, Electrical Power Systems and Command and Data Handling (C&DH), as well as scientific payloads of varying size and complexity. The dynamic nature of the ISS configuration coupled with the increased demand for payload support places a significant burden on the inherently resource constrained computational infrastructure of the ISS. Onboard system diagnostics applications are hosted on computers that are elements of the avionics network while ground-based diagnostic applications receive only a subset of available telemetry, down-linked via S-band communications. In this paper we propose a scalable, out-of-band diagnostics architecture for ISS systems support that uses a read-only connection for C&DH data acquisition, which provides a lower cost of deployment and maintenance (versus a higher criticality readwrite connection). The diagnostics processing burden is off-loaded from the avionics network to elements of the on-board LAN that have a lower overall cost of operation and increased computational capacity. A superset of diagnostic data, richer in content than the configured telemetry, is made available to Advanced Diagnostic System (ADS) clients running on wireless handheld devices, affording the crew greater mobility for troubleshooting and providing improved insight into vehicle state. The superset of diagnostic data is made available to the ground in near real-time via an out-of band downlink, providing a high level of fidelity between vehicle state and test, training and operational facilities on the ground.

Fletcher, Daryl P.↗
NASA NTRS2004

Verification and Validation Methodology of Real-Time Adaptive Neural Networks for Aerospace Applications

Recent research has shown that adaptive neural based control systems are very effective in restoring stability and control of an aircraft in the presence of damage or failures. The application of an adaptive neural network with a flight critical control system requires a thorough and proven process to ensure safe and proper flight operation. Unique testing tools have been developed as part of a process to perform verification and validation (V&V) of real time adaptive neural networks used in recent adaptive flight control system, to evaluate the performance of the on line trained neural networks. The tools will help in certification from FAA and will help in the successful deployment of neural network based adaptive controllers in safety-critical applications. The process to perform verification and validation is evaluated against a typical neural adaptive controller and the results are discussed.

Gupta, Pramod↗
NASA NTRS2005

Design, Development, and Innovation of an Interactive Multimedia Training Simulator for Responding to Air Transportation Bomb Threats

This paper describes an interactive multimedia simulator for air transportation bomb threat training. The objective of this project is to improve the air transportation sector s capability to respond to bomb threats received by commercial airports and aircraft. The simulator provides realistic training on receiving and responding to a variety of bomb threats that might not otherwise be possible due to time, cost, or operational constraints. Validation analysis indicates that the use of the simulator resulted in statistically significant increases in individual ability to respond to these types of bomb threats.

Chung, Christopher A.↗
NASA NTRS2009

Image-Capture Devices Extend Medicine's Reach

Johnson Space Center, Henry Ford Hospital in Detroit, and Houston-based Wyle Laboratories collaborated on NASA's Advanced Diagnostic Ultrasound in Microgravity (ADUM) experiment, which developed revolutionary medical ultrasound diagnostic techniques for long-distance use. Mediphan, a Canadian company with U.S. operations in Springfield, New Jersey drew on NASA expertise to create frame-grabber and data archiving technology that enables ultrasound users with minimal training to send diagnostic-quality ultrasound images and video to medical professionals via the Internet in near real time allowing patients as varied as professional athletes, Olympians, and mountain climbers to receive medical attention as soon as it is needed.

Source record↗
NASA NTRS2002

INTEGRITY - Integrated Human Exploration Mission Simulation Facility

It is proposed to develop a high-fidelity ground facility to carry out long-duration human exploration mission simulations. These would not be merely computer simulations - they would in fact comprise a series of actual missions that just happen to stay on earth. These missions would include all elements of an actual mission, using actual technologies that would be used for the real mission. These missions would also include such elements as extravehicular activities, robotic systems, telepresence and teleoperation, surface drilling technology-all using a simulated planetary landscape. A sequence of missions would be defined that get progressively longer and more robust, perhaps a series of five or six missions over a span of 10 to 15 years ranging in duration from 180 days up to 1000 days. This high-fidelity ground facility would operate hand-in-hand with a host of other terrestrial analog sites such as the Antarctic, Haughton Crater, and the Arizona desert. Of course, all of these analog mission simulations will be conducted here on earth in 1-g, and NASA will still need the Shuttle and ISS to carry out all the microgravity and hypogravity science experiments and technology validations. The proposed missions would have sufficient definition such that definitive requirements could be derived from them to serve as direction for all the program elements of the mission. Additionally, specific milestones would be established for the "launch" date of each mission so that R&D programs would have both good requirements and solid milestones from which to .build their implementation plans. Mission aspects that could not be directly incorporated into the ground facility would be simulated via software. New management techniques would be developed for evaluation in this ground test facility program. These new techniques would have embedded metrics which would allow them to be continuously evaluated and adjusted so that by the time the sequence of missions is completed, the best management techniques will have been developed, implemented, and validated. A trained cadre of managers experienced with a large, complex program would then be available.

Henninger, Donald L.↗
NASA NTRS2014

A Semiautomated Multilayer Picking Algorithm for Ice-sheet Radar Echograms Applied to Ground-Based Near-Surface Data

Snow accumulation over an ice sheet is the sole mass input, making it a primary measurement for understanding the past, present, and future mass balance. Near-surface frequency-modulated continuous-wave (FMCW) radars image isochronous firn layers recording accumulation histories. The Semiautomated Multilayer Picking Algorithm (SAMPA) was designed and developed to trace annual accumulation layers in polar firn from both airborne and ground-based radars. The SAMPA algorithm is based on the Radon transform (RT) computed by blocks and angular orientations over a radar echogram. For each echogram's block, the RT maps firn segmented-layer features into peaks, which are picked using amplitude and width threshold parameters of peaks. A backward RT is then computed for each corresponding block, mapping the peaks back into picked segmented-layers. The segmented layers are then connected and smoothed to achieve a final layer pick across the echogram. Once input parameters are trained, SAMPA operates autonomously and can process hundreds of kilometers of radar data picking more than 40 layers. SAMPA final pick results and layer numbering still require a cursory manual adjustment to correct noncontinuous picks, which are likely not annual, and to correct for inconsistency in layer numbering. Despite the manual effort to train and check SAMPA results, it is an efficient tool for picking multiple accumulation layers in polar firn, reducing time over manual digitizing efforts. The trackability of good detected layers is greater than 90%.

Antarctic Ice-Sheet↗
NASA NTRSDate not supplied

Measurement of Material Recession and Shock Standoff in Plasma Windtunnel using Neural Nets

Arcjets are plasma wind tunnels used to test the performance of heatshield materials for spacecraft atmospheric entry. These facilities present an extremely harsh flow environment with heat fluxes up to 109 W/m2 for up to 30 minutes. The plasma is low-temperature (∼1 eV) but high pressure (> 10 kPa) creating high-enthalpy supersonic flows similar to atmospheric entry conditions. Typically, material samples are measured before and after a test to characterize the total recession. However, this does not capture time-dependent effects such as material expansion and non-linear recession. This work will present new analysis of arcjet test videos which measure both the time-dependent 2D recession of the material samples and the shock standoff distance. The results show non-linear time-dependent effects are present for some conditions. The material and shock edges are extracted from the videos by training and applying a convolutional neural network. Due to the consistent camera settings, the machine learning model achieves high accuracy (± 2 px) relative to manually segmented images with only a small number of training frames (80).

Neural network↗