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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Scheduling algorithms for multiprogramming in a hard-real-time environment.

The problem of multiprogram scheduling on a single processor is studied from the viewpoint of the characteristics peculiar to the program functions that need guaranteed service. It is shown that an optimum fixed priority scheduler possesses an upper bound to processor utilization which may be as low as 70 percent for large task sets. It is also shown that full processor utilization can be achieved by dynamically assigning priorities on the basis of their current deadlines. A combination of these two scheduling techniques is also discussed.

Liu, C. L.↗
DOE OSTI2023

Grid ancillary services using electrolyzer-Based power-to-Gas systems with increasing renewable penetration

Increasing penetrations of renewable-based generation have led to a decrease in the bulk power system inertia and an increase in intermittency and uncertainty in generation. Energy storage is considered to be an important factor to help manage renewable energy generation at greater penetrations. Hydrogen is a viable long-term storage alternative. This paper analyzes and presents use cases for leveraging electrolyzer-based power-to-gas systems for electric grid support. The paper also discusses some grid services that may favor the use of hydrogen-based storage over other forms such as battery energy storage. Real-time controls are developed, implemented and demonstrated using a power-hardware-in-the-loop(PHIL) setup with a 225-kW proton-exchange-membrane electrolyzer stack. These controls demonstrate frequency and voltage support for the grid for different levels of renewable penetration (0%, 25%, and 50%). A comparison of the results shows the changes in respective frequencies and voltages as seen as different buses as a result of support from the electrolyzers and notes the impact on hydrogen production as a result of grid support. Finally, the paper discusses the practical nuances of implementing the tests with physical hardware, such as inverter/electrolyzer efficiency, as well as the related constraints and opportunities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

A cloud computing approach to massively-parallel distributed stochastic optimization with application to geomechanical reservoir characterization

Many search strategies used to optimize parameters during hydrologic model calibration are inherently limited in that simulations must be performed sequentially in order for the algorithm to converge. As a result, the overall time required to reach a solution increases linearly with the number of steps necessary. In contrast, sampling strategies that attempt to approximate the posterior distribution of the parameters do not require the model simulations to be run in sequence and therefore invite the use of a massively parallel approach across heterogeneous computing environments. We apply a cloud computing methodology to this problem where a head node running on Amazon Web Services continuously produces candidate models that are distributed to arbitrary compute environments to run the simulation, in our case Clemson’s Palmetto cluster computer. Thus the time required to obtain a sufficient number of samples to produce an adequate approximation of the posterior distribution of the parameters is limited by the number of available compute sites. Monte Carlo sampling of the posterior space would be duplicative and inefficient, thus we combine Latin hypercube methods with genetic algorithms to ensure that no large regions of the parameter space are left unexplored, and that high probability regions are investigated thoroughly. We independently assess the fit to different types of data sets without the need to construct a single objective function. Sets of Pareto optimal models are particularly valuable when the quality and information content of data is poorly known or conceptual model errors exist in our simulation. We illustrate our approach for a problem where in situ strain data are used to calibrate the parameters of an oil reservoir in the Avant oil field in Oklahoma. We use well injection and shut-in to stress a deep (500m) confined formation, and observe the geomechanical response using borehole strainmeters installed in the shallow subsurface (30m). These data were then used to calibrate the poroelastic properties of the reservoir and caprock along with the geometry of an elliptic channel associated with the formation. Using our approach we are able to identify issues with model error as well as substantial tradeoffs that occur within the parameters.

inversion, stochastic, geomechanics, poroelastic, ↗
NASA NTRS1982

Planning assistance for the NASA 30/20 GHz program. Network control architecture study.

Network Control Architecture for a 30/20 GHz flight experiment system operating in the Time Division Multiple Access (TDMA) was studied. Architecture development, identification of processing functions, and performance requirements for the Master Control Station (MCS), diversity trunking stations, and Customer Premises Service (CPS) stations are covered. Preliminary hardware and software processing requirements as well as budgetary cost estimates for the network control system are given. For the trunking system control, areas covered include on board SS-TDMA switch organization, frame structure, acquisition and synchronization, channel assignment, fade detection and adaptive power control, on board oscillator control, and terrestrial network timing. For the CPS control, they include on board processing and adaptive forward error correction control.

Inukai, T.↗
DOE OSTI2022

Application of the Continuum Damage Mechanics Wilshire-Cano-Stewart (WCS) Model

In this study, the applications of the continuum damage mechanics-based Wilshire-Cano-Stewart (WCS) model are explored to predict rupture time, minimum-creep-strain-rate (MCSR), damage, damage evolution, and creep deformation. Increase knowledge in manufacturing methods has pushed the limit of material science and the development of new materials. Conventional testing is required to qualify materials against creep which according to the ASME B&PV III code, 10,000+ hours of experiments are necessary for each heat before materials are put into service. This process is costly and not feasible for new materials. As an alternative, models have been employed to predict creep behaviors and reduce the amount of time necessary for material qualification. Many models have been developed to predict distinct creep behaviors and the question of which model is best remains. Amongst current models, the WCS model has emerge with the ability to predict multiple behaviors using an explicit analytical approach with the ability to predict long-term creep. In this study the novel continuum damage mechanics WCS is employed in multiple applications. The goals of the study are (a) to discuss and determine the framework of the WCS model and validated it mathematically and using parametric simulations, (b) applied the model to accelerated creep data to show the capabilities of the model with non-conventional data, and (c) applied a novel numerical method, the datum temperature method (DTM) to show the model extrapolations and interpolations capabilities with limited and reduce data sets. To accomplish these goals, data is gathered for alloy P91 and Inconel 718 to develop and post-audit validate the model. The benefits of using the WCS model is that it provides an explicit stress and temperature dependency ideal for extrapolations, the coupled equations are suitable for finite element analysis (FEA) implementation, and it follows an explicit calibration approach. The model also proves that it can be applied to accelerated testing data and using the DTM.

Cano, Jaime A↗
DOE OSTI2020

Use of the Manuela 3D/Radiation Scanning Tool at Nuclear Facilities - 20437

Licensees, facility operators and decommissioning contractors have a need for comprehensive, accurate and precise radiological and topographical data to plan and execute safe and efficient Decontamination and Decommissioning (D and D) projects. Traditional approaches rely greatly upon labor and administratively intensive data collection methods that require considerable time and effort to glean the relevant data to plan and perform work in a radiological work area. Orano Decommissioning Services has developed and utilized at French nuclear facilities a lightweight portable scanning instrument called MANUELA (Mobile Apparatus for Nuclear Expertise Localization Assistance). Recently Orano conducted demonstrations at two United States nuclear facilities using MANUELA that may prove useful in areas of the fuel cycle including: - ALARA (As Low As Reasonably Achievable) planning during facility operations; - Scoping and site characterization during the D and D planning phase; - Remedial action support during active decommissioning work; - Radiation and modeling planning for plant modifications; - Support Final Status Survey and demonstration of 'end state' compliance for license termination. MANUELA is currently being evaluated for use during decommissioning of nuclear facilities and could aide in demonstrating compliance with end state criteria after decommissioning. Of particular interest are decommissioning projects planned for various sites across the United States. Most of these sites present unique challenges and opportunities to safely and efficiently decommission in a regulatory compliant manner. The two demonstration site's current conditions of relatively low radiation levels inside containment proved to be ideal platforms to deploy the MANUELA instrument for evaluation of the complex geometries typically found in a nuclear facility. The MANUELA instrument was able to precisely identify local hot spots of the reactor system's primary equipment and was able to simultaneously overlay the dose information onto the scanned 3D images. Using data like this, a licensee would be able to make informed technical and personnel decisions on methods to remediate, shield or properly dispose of the radioactive source term. MANUELA can be used throughout the decommissioning process to validate progress and continue to refine the work activities to optimize the efforts of the crew which reduces downtime waiting for survey results, whereas traditional survey methodology relies on a physical survey to be performed and the data transcribed onto survey maps that are only two dimensional. The traditional format tends to be inaccurate and difficult to interpret the precise location(s) of hot spots or generalized dose rates. The resultant scan also allows the user to know the exact extent of the survey versus transposing information onto a map with only a portion of the map area scanned. MANUELA also compiles all of the relevant survey data into a downloadable table format which includes the measurement identification number, time stamp, point space location on the XYZ plane, and the dose rate value. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Dynamic data-driven multiscale modeling for predicting the degradation of a 316L stainless steel nuclear cladding material

Here, we have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High-Frequency, Multiclass Nonintrusive Load Monitoring for Grid-Interactive Residential Buildings

Smart buildings with net-load metering and control capabilities can provide valuable flexibility to grid operators. This article develops a novel approach for high-frequency, multiclass nonintrusive load monitoring (NILM) that enables effective net-load monitoring capabilities with minimal additional equipment and cost. Relative to existing NILM work, the proposed solution operates at a faster timescale, providing accurate multiclass state predictions for each 60-Hz ac cycle without relying on event-detection techniques. The approach is validated using a test bed with residential appliances and shown to have high accuracy, good generalization properties, and sufficient response time to support building grid-interactive control at fast timescales relevant to the provision of grid frequency support services.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2016

SU-F-R-12: Prediction of TrueBeam Hardware Issues Using Trajectory Log Analysis

Purpose: To predict potential failures of hardware within the Varian TrueBeam linear accelerator in order to proactively replace parts and decrease machine downtime. Methods: Machine downtime is a problem for all radiation oncology departments and vendors. Most often it is the result of unexpected equipment failure, and increased due to lack of in-house clinical engineering support. Preventative maintenance attempts to assuage downtime, but often is ineffective at preemptively preventing many failure modes such as MLC motor failures, the need to tighten a gantry chain, or the replacement of a jaw motor, among other things. To attempt to alleviate downtime, software was developed in house that determines the maximum value of each axis enumerated in the Truebeam trajectory log files. After patient treatments, this data is stored in a SQL database. Microsoft Power BI is used to plot the average maximum error of each day of each machine as a function of time. The results are then correlated with actual faults that occurred at the machine with the help of Varian service engineers. Results: Over the course of six months, 76,312 trajectory logs have been written into the database and plotted in Power BI. Throughout the course of analysis MLC motors have been replaced on three machines due to the early warning of the trajectory log analysis. The service engineers have also been alerted to possible gantry issues on one occasion due to the aforementioned analysis. Conclusion: Analyzing the trajectory log data is a viable and effective early warning system for potential failures of the TrueBeam linear accelerator. With further analysis and tightening of the tolerance values used to determine a possible imminent failure, it should be possible to pinpoint future issues more thoroughly and for more axes of motion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Preliminary Hyde Memorial State Park Modular Pumped Hydro Energy Storage Sizing Study

Hyde Memorial State Park has lost grid supplied power and has been running on a diesel generator for some time now. The powerline that feeds the park is a state owned, 5 mile underground extension from the PNM service connection point. The line has decayed over the past 30 plus years and due to the location (much of it running under the road) the cost of repair and the logistics of closing the road are not good options. In June 2019 through a state contractor, the State of New Mexico Energy, Minerals and Natural Resources Department completed a renewable energy microgrid feasibility study to see if it was technically and economically feasible to operate the park without future grid power. The study looked at solar plus battery storage and a propane generator as a possible option. New Mexico State Parks Division has indicated their wish to move forward with the microgrid project which will now go out to one of the state’s energy services performance contractors. The contractor will have to finalize the feasibility study and develop a complete list of construction costs. Given, the lack of long-term O&M data on the battery, as part of the next phase of the project the State of New Mexico Energy, Minerals and Natural Resources Department asked Los Alamos National Laboratory to preliminary examine the potential for pumped hydro as an alternative to batteries.

13 HYDRO ENERGY↗
DOE OSTI2022

Dynamic Data-Driven Multiscale Modeling for Predicting Microstructure and Mechanical Properties of 316L Stainless Steel

We have developed a long short-term memory stacked ensemble (LSTM-SE) surrogate modeling approach that can provide rapid predictions of microstructural evolution and the resultant mechanical properties of American Iron and Steel Institute (AISI) 316L series stainless steel (316LSS) fuel cladding under conditions of varying temperature and radiation dose rate. To acquire training data, we developed and implemented a kinetic Monte Carlo (KMC) model to simulate precipitation kinetics of M 23 C 6 , γ', and G phases within SS316L cladding. Experimentally reported precipitation kinetics of SS316L in literature were linked to the kinetic parameters of the simulated precipitation in our KMC model. The model was then used to simulate microstructure evolution under synthetically generated treatments of varying temperature and radiation dose rate, for periods of up to 3000 hours. Changes in volume fraction, number density, and particle size of precipitates were recorded, and particle area fractions were correlated using statistical methods to develop the surrogate model. Simultaneously, the mechanical properties of the simulated microstructures were evaluated using microstructure-based finite element method (FEM) analysis to determine the elastic modulus, yield stress, ultimate tensile strength, and elongation to failure of the aged microstructures. Using this approach, our surrogate model can predict precipitation behavior within 0.25% volume fraction and mechanical properties within 6% relative error from the values predicted by the KMC and FEM models using 50 training simulations as input. The trained recurrent neural network-based model can return estimations of precipitation kinetics and mechanical properties ~1000 times faster than the physics-based codes. This work demonstrates, as a proof of concept, that reactor material service lifetimes under variable service conditions can be predicted for a statistics-based model from a practicably obtainable dataset.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Major Drivers of Long-Term Distribution Transformer Demand

Distribution transformers, used to step-down medium voltage to service-voltage level for end-use electrical consumption, are currently experiencing major shortages. Utilities are experiencing extended lead times for transformers of up to 2 years (a 4x increase on lead times pre-2022) and prices have gone up by as much as 5-6 times in the past 2 years. Current shortages have been attributed to pent-up post-pandemic demand, workforce shortages and low retention rates, component supply chain challenges, and materials shortages (grain-oriented electrical steel, aluminum, and copper). The supply of this equipment is critical for the reliability and growth of the power system, and in meeting administration climate goals in terms of electrification of demand and the growth of renewable energy. This report details some of the initial analysis conducted by the National Renewable Energy Laboratory (NREL), supported by the Department of Energy's Office of Electricity and Office of Policy, in assessing the long-term demand trends for distribution transformers. Expected increased demand is due to a confluence of not only electrification and renewable energy growth, but also in the context of aging electric infrastructure, increased frequency and severity of extreme weather events, and utility-driven investments in reliability and resiliency of the electricity distribution system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Toward Wireless Smart Grid Communications: An Evaluation of Protocol Latencies in an Open-Source 5G Testbed

Fifth-generation networks promise wide availability of wireless communication with inherent security features. The 5G standards also outline access for different applications requiring low latency, machine-to-machine communication, or mobile broadband. These networks can be advantageous to numerous applications that require widespread and diverse communications. One such application is found in smart grids. Smart grid networks, and Operational Technology (OT) networks in general, utilize a variety of communication protocols for low-latency control, data monitoring, and reporting at every level. Transitioning these network communications from wired Wide Area Networks (WANs) to wireless communication through 5G can provide additional benefits to their security and network configurability. However, introducing these wireless capabilities may also result in a degradation of network latency. In this paper, we propose utilizing 5G for smart grid communications, and we evaluate the latency impacts of encapsulating GOOSE, Modbus, and DNP3 for transmission over a 5G network. The OpenAirInterface open-source library is utilized to deploy an in-lab 5G Core Network and gNB for testing with off-the-shelf User Equipment (UE). This creates an effective 5G test platform for experimenting with different OT protocols such as GOOSE. The results are validated by measuring two different Intelligent Electronic Devices’ contact closure times for each network configuration. These tests are also conducted for varying packet sizes in order to isolate different sources of network latency. Our study outlines the latency impact of communication over 5G for time-critical and non-critical applications regarding their transition toward private 5G-based OT network implementations. The conducted experiments illustrate that in the case of GOOSE packets, simple encapsulation may exceed the protocol’s time-critical nature, and, therefore, additional measures must be taken to ensure a viable transition of GOOSE to 5G services. However, non-critical applications are shown to be viable for migration to 5G.

42 ENGINEERING↗
NASA NTRS1972

Photographic summary

The photographic objectives of the Apollo 15 mission were designed to support a wide variety of scientific and operational experiments, to provide high-resolution panoramic photographs and precisely oriented metric photographs of the lunar surface, and to document operational tasks on the lunar surface and in flight. Detailed premission planning integrated the photographic tasks with the other mission objectives to produce a balanced mission that has returned more data than any previous space voyage. The return of photographic data was enhanced by new equipment, the high latitude of the landing site, and greater time in lunar orbit. New camera systems that were mounted in the scientific instrument module (SIM) bay of the service module provided a major photographic capability that was not available on any previous lunar mission, manned or unmanned.

Dietrich, J. W.↗
NASA NTRS1975

Manipulator system performance measurement

Free-flying teleoperator technology for satellite servicing is reported. The rationale for a series of manipulator system tests is presented. Data are reported on movement time in a fine positioning task using two different manipulator systems. The movement time data showed reliable effects of movement direction and index of difficulty. These data were considered to be baseline performance measures for the manipulator system used and modifications to the control and visual systems were suggested for future testing.

Kirkpatrick, M., III↗
NASA NTRS1976

Early results of the ionospheric experiment of the Apollo-Soyuz Test Project

A description is presented of a spacecraft-to-spacecraft Doppler-tracking experiment which was performed by the Smithsonian Astrophysical Observatory on the occasion of the Apollo-Soyuz Test Project (ASTP). The experiment involved the measurement of the relative velocity between the ASTP docking module and the Apollo command service module by a Doppler-tracking method. The objectives of the ionospheric experiment include the measurement of the time changes of the columnar electron content between the two spacecraft. The obtained data can provide a basis for the determination of the horizontal gradients of electron density at the height of 220 km.

Grossi, M. D.↗
NASA NTRS1977

Operational data processing: The first ten years are the hardest

A historical perspective of operational data processing and its development in the National Environmental Satellite Service is presented. The types of sensor data to be used in operational data processing are specified through the time period of the 1980's. Features that are essential for the design and implementation of a good data base system are outlined. Realistic standards for optimal data productions are discussed.

Leese, J. A.↗

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