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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 NTRS1987

Information prioritization for control and automation of space operations

The applicability of a real-time information prioritization technique to the development of a decision support system for control and automation of Space Station operations is considered. The steps involved in the technique are described, including the definition of abnormal scenarios and of attributes, measures of individual attributes, formulation and optimization of a cost function, simulation of test cases on the basis of the cost function, and examination of the simulation scenerios. A list is given comparing the intrinsic importances of various Space Station information data.

Ray, Asock↗
NASA NTRS2004

Orbit Optimization and Scattering Coefficient Analysis for the Proposed GLORIA System

This paper investigates the optimization of an orbit for a Low-Earth Orbiting (LEO) satellite for coastal coverage over Antarctic and United States shorelines as part of the Geostationary/Low-Earth Orbiting Radar Image Acquisition (GLORIA) System. Simulations over a range of orbital parameters are performed to determine the optimal orbit. Scattering coefficients are computed for the optimal orbit throughout the day and characterized to compare various scenarios for which link budget comparisons could then be made.

Welch, Bryan↗
NASA NTRS2014

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

Modal Filtering↗
NASA NTRS2016

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

Modal Filtering↗
DOE OSTI2011

Effect of Mixed Working Fluid Composition on Binary Cycle Condenser Heat Transfer Coefficients

Effect of Mixed Working Fluid Composition on Binary Cycle Condenser Heat Transfer Coefficients Dan Wendt, Greg Mines Idaho National Laboratory The use of mixed working fluids in binary power plants can provide significant increases in plant performance, provided the heat exchangers are designed to take advantage of these fluids non-isothermal phase changes. In the 1980's testing was conducted at DOE's Heat Cycle Research Facility (HCRF) where mixtures of different compositions were vaporized at supercritical pressures and then condensed. This testing had focused on using the data collected to verify that Heat Transfer Research Incorporated (HTRI) codes were suitable for the design of heat exchangers that could be used with mixtures. The HCRF data includes mixture compositions varying from 0% to 40% isopentane and condenser tube orientations of 15{sup o}, 60{sup o}, and 90{sup o} from horizontal. Testing was performed over a range of working fluid and cooling fluid conditions. Though the condenser used in this testing was water cooled, the working fluid condensation occurred on the tube-side of the heat exchanger. This tube-side condensation is analogous to that in an air-cooled condenser. Tube-side condensing heat transfer coefficient information gleaned from the HCRF testing is used in this study to assess the suitability of air-cooled condenser designs for use with mixtures. Results of an air-cooled binary plant process model performed with Aspen Plus indicate that that the optimal mixture composition (producing the maximum net power for the scenario considered) is within the range of compositions for which data exist. The HCRF data is used to assess the impact of composition, tube orientation, and process parameters on the condensing heat transfer coefficients. The sensitivity of the condensing coefficients to these factors is evaluated and the suitability of air-cooled condenser designs with mixtures is assessed. This paper summarizes the evaluation of the HCRF data and discusses the next steps in the project evaluation of air-cooled condenser designs that can take advantage of the performance gains possible with these fluids.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Hydrogen Production, Grid Integration, and Scaling for the Future

The Hydrogen Production, Grid Integration, and Scaling for the Future project will inform clean hydrogen production deployment across the planning, procurement, and operation stages of hydrogen production on the grid. Hydrogen production from renewables is a clean source of fuel which is near zero for greenhouse gas emissions and criteria pollutants. The results from this project will inform entities looking to build clean energy projects that produce good paying jobs in manufacturing, installation, maintenance and operation of these facilities. This project provides system characterization examples, multiple configurations, optimizations, and suggested metering and custody transfer points through multiple scenarios and hardware testing of NREL's state-of-the-art 1.25 MW polymer electrolyte membrane (PEM) electrolyzer system to characterize system performance in relevant scenarios. This work also creates a digital twin for emulation in the Advanced Research on Integrated Systems (ARIES) virtual environment and performs hardware-in-the-loop (HIL) testing of pilot-scale, decentralized, and centralized hydrogen systems.

centralized hydrogen production↗
DOE OSTI2013

UP2 400 High Activity Oxide Legacy Waste Retrieval Project Scope and Progress-13048

The High Activity Oxide facility (HAO) reprocessed sheared and dissolved 4500 metric tons of light water reactor fuel the fuel of the emerging light water reactor spent fuel between 1976 and 1998. Over the period, approximately 2200 tons of process waste, composed primarily of sheared hulls, was produced and stored in a vast silo in the first place, and in canisters stored in pools in subsequent years. Upon shutdown of the facility, AREVA D and D Division in La Hague launched a thorough investigation and characterization of the silos and pools content, which then served as input data for the definition of a legacy waste retrieval and reconditioning program. Basic design was conducted between 2005 and 2007, and was followed by an optimization phase which lead to the definition of a final scenario and budget, 12% under the initial estimates. The scenario planned for the construction of a retrieval and reconditioning cell to be built on top of the storage silo. The retrieved waste would then be rinsed and sorted, so that hulls could subsequently be sent to La Hague high activity compacting facility, while resins and sludge would be cemented within the retrieval cell. Detailed design was conducted successfully from 2008 until 2011, while a thorough research and development program was conducted in order to qualify each stage of the retrieval and reconditioning process, and assist in the elaboration of the final waste package specification. This R and D program was defined and conducted as a response and mitigation of the major project risks identified during the basic design process. Procurement and site preparatory works were then launched in 2011. By the end of 2012, R and D is nearly completed, the retrieval and reconditioning process have been secured, the final waste package specification is being completed, the first equipment for the retrieval cell is being delivered on site, while preparation works are allowing to free up space above and around the silo, to allow for construction which is scheduled to being during the first semester of 2013. The elaboration of the final waste package is still undergoing and expected to be completed by then end of 2013, following some final elements of R and D required to demonstrate the full compatibility of the package with deep geological repository. The HAO legacy waste retrieval project is so far the largest such project entering operational phase on the site of La Hague. It is on schedule, under budget, and in conformity with the delivery requirements set by the French Safety Authority, as well as other stakeholders. This project paves the way for the successful completion of AREVA La Hague other legacy waste retrieval projects, which are currently being drafted or already in active R and D phase. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Detecting Unclassified Electromagnetic Signals for Secure Wireless Communication Using Open Set Recognition

We developed multiple machine learning methods for the detection and classification of new wireless communication waveforms, which is critical for targeted attacks in wireless networks and electronic warfare. Our machine learning models are capable of dynamically detecting security threats in near real time through our advanced open set recognition (OSR) approach. This model has demonstrated significant improvements in the detection of unknown waveforms, thereby enhancing the security and reliability of mission critical communications. Our approach to detecting uncertain security threats is novel; we advanced OSR techniques by incorporating domain knowledge of wireless signals. Specifically, we combined time and frequency domain model features to enhance the model’s performance. Utilizing an OSR approach eliminates the need for training data to be distributed similarly to the deployment environment and removes the requirement for the training set to contains all possible threat classes. This is crucial because it is often infeasible to determine and characterize all potential security threats in advance. Our model were trained on simulated data, generated in partnership with the University at Albany, State of New York. The data set contained a diverse array of wireless signals, including those with additive white Gaussian noise and multipath signals, with and without line of sight. This comprehensive training set allowed us to optimize our models to detect unknown waveforms under various challenging scenarios, such as low signal-to-noise ratios. By training on various waveforms, varying signal-to-noise ratio, and different sample sizes under normal conditions, our models were fine tuned to perform effectively in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Predicting Dynamic-to-Static Correction Factor from Petrophysical Data and Chemostratigraphy using Unsupervised Machine Learning

Estimating static mechanical properties of stratigraphic layers is critical for optimizing subsurface engineering applications. To estimate dynamic-to-static correction factor F ds (static-to-dynamic Young’s modulus ratio) across the Caney shale interval in Oklahoma, USA, we integrated triaxial test measurements and petrophysical data, including well logs and X-ray fluorescence (XRF) using unsupervised machine learning (ML). We used a novel workflow that includes principal component analysis (PCA) to reduce data set dimensionality of well logs and XRF data sets—both separately and combined—creating three scenarios, and later applied inverse distance weighting (IDW) to derive F ds profiles for these scenarios. Furthermore, we applied K-means clustering on each scenario to predict depositional facies, and built a stiffness zonation profile through chemostratigraphic analysis of the terrigenous elements to validate the predicted F ds . The predicted F ds profile from each scenario using the PCA-IDW method was compared with the constant F ds approach from our previous study by calculating the root mean square error (RMSE). The combined data sets scenario yielded the lowest RMSE value of 0.113, while the RMSE values for the well logs and XRF scenarios were 0.131 and 0.129, respectively. In addition, the predicted F ds from the XRF scenario well-matched the stiffness zonation from the chemostratigraphic analysis that was built using the optimized K-means clustering of nine clusters for that scenario. These methods and findings offer a valuable tool for refining lithological classification and improving the F ds profile, potentially enhancing drilling and stimulation strategies for subsurface energy engineering applications.

clastic rock↗
NASA NTRS1993

Simulations of satellite Doppler wind observations

This study will involve two objectives: (1) to develop, through computer simulations, optimal satellite-based sensor scanning techniques for direct measurement of tropospheric winds on the meso- and synoptic scales; and (2) to construct simulations of remotely measured wind fields for assessing impact of such fields on the diagnosis and prognosis of atmospheric phenomena through the use of Observing System Simulation Experiments (OSSE). Using the LAWS Simulation Model (LSM), various global coverage scenarios have been investigated as part of an effort to define the optimal orbit, configuration and sampling strategies for observations of winds for use in global circulation models. Simulated data sets have been provided to GSFC, FSU and several LAWS team members. Particular emphasis has been on providing realistic cloud cover, cirrus backscatter, aerosol distribution and wind variance on scales less than 600 km. Progress is currently being made to incorporate other remote sensors (AIRS/AMSU, STIKSCAT) into the global OSSEs.

Emmitt, George D.↗
DOE OSTI2010

Optical emission and nanoparticle generation in Al plasmas using ultrashort laser pulses temporally optimized by real-time spectroscopic feedback

With an interest in pulsed laser deposition and remote spectroscopy techniques, we explore here the potential of laser pulses temporally tailored on ultrafast time scales to control the expansion and the excitation degree of various ablation products including atomic species and nanoparticulates. Taking advantage of automated pulse-shaping techniques, an adaptive procedure based on spectroscopic feedback is applied to regulate the irradiance and enhance the optical emission of monocharged aluminum ions with respect to the neutral signal. This leads to optimized pulses usually consisting in a series of femtosecond peaks distributed on a longer picosecond sequence. The ablation features induced by the optimized pulse are compared with those determined by picosecond pulses generated by imposed second-order dispersion or by double pulse sequences with adjustable picosecond separation. This allows to analyze the influence of fast- and slow-varying envelope features on the material heating and the resulting plasma excitation degree. Using various optimal pulse forms including designed asymmetric shapes, we analyze the establishment of surface pre-excitation that enables conditions of enhanced radiation coupling. Thin films elaborated by unshaped femtosecond laser pulses and by optimized, stretched, or double pulse sequences are compared, indicating that the nanoparticles generation efficiency is strongly influenced by the temporal shaping of the laser irradiation. A thermodynamic scenario involving supercritical heating is proposed to explain enhanced ionization rates and lower particulates density for optimal pulses. Numerical one-dimensional hydrodynamic simulations for the excited matter support the interpretation of the experimental results in terms of relative efficiency of various relaxation paths for excited matter above or below the thermodynamic stability limits. The calculation results underline the role of the temperature and density gradients along the ablated plasma plume which lead to the spatial distinct locations of excited species. Moreover, the nanoparticles sizes are computed based on liquid layer ejection followed by a Rayleigh and Taylor instability decomposition, in good agreement with the experimental findings.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Enhanced grid operation and optimized PV penetration utilizing highly distributed sensor data

This task describes R&D activities to establish methods to cost-effectively achieve very high PV penetration scenarios (well beyond 100% of peak load at the feeder level) by leveraging distributed inverters to increase situational awareness and provide local voltage support. The grid performance and reliability objectives (SI vision) of this proposal were selected to enhance feeder planning models that can better characterize and quantify the electric power system including the secondary system servicing customers. The Communication objective was selected to demonstrate how visibility and control of behind-the-meter systems and distributed storage at large scale can be optimized to address system reliability and variability impacts, and to maximize the value of solar in high PV penetration scenarios. The goal of this project was to achieve enhanced grid operation and optimized PV penetration utilizing highly distributed sensor data via three subtasks 1.1-1.3.

14 SOLAR ENERGY↗
DOE OSTI2018

Meta-Level Design Guidance and Operator Performance Measures for Hybrid Control Rooms

The purpose of this grant was to refine and test methods to evaluate digital human system interfaces (HSI) for existing largely analog nuclear power plant (NPP) control rooms (CRs). We hypothesized that CR operator performance (CROP) in hybrid NPP CRs will be improved if future digital HSI is designed based on: 1) more robust design guidelines for operator situation awareness (SA) and decision-making (DM); 2) enhanced CROP metrics during HSI evaluation; 3) an ontology for selecting simulation scenarios to evaluate digital HSI; and 4) a model to predict optimal HSI design attributes given CROP objectives. The team conducted numerous nuclear power plant site visits (e.g., to Brown’s Ferry, Palo Verde, Sequoyah and Vogtle) to study control room operations and crisis management and 3 visits to the NRC Chattanooga Training Center. We observed research studies at DC Cook and NRC Chattanooga in collaboration with the Halden Reactor Project. We collected operator performance and workload data in one NPP simulator. A comprehensive human (i.e., CROP) performance literature review was published in Applied Ergonomics. We obtained operator team performance data from CAER to produce our data fusion model and a paper delineating the results have been accepted (revision submitted) in Resilience Engineering and System Safety. We analyzed interview data related to scenario ontology development; a manuscript is still in preparation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Enhancing the Survivability of Power Systems With Grid-Edge DERs Against DoS Attacks

Power system survivability, defined as the ability of a system to maintain steady-state functionality under varying operational conditions, reflects its resilience against disturbances. While existing research primarily focuses on physical-layer disturbances, the increasing prevalence of grid-edge DERs, which are primarily used for integrating renewable energy, has significantly expanded the cyber attack surface. As a result, operational disruptions caused by cyber threats are posing significant challenges to system survivability and cannot be overlooked. To fill this gap, we redefine system survivability to incorporate the cyber layer’s status and propose a Distributionally Robust Optimization (DRO) approach to enhance power system survivability against potential cyber-physical threats. In this paper, we first analyze the operational guidelines of systems with a high penetration of DERs under various cyber network conditions and redefine survivability in this context. Next, we focus on the most common cyber threat, Denial-of-Service (DoS) attacks, and develop a corresponding attack model. This model allows for the creation of a kernel-based ambiguity set that captures attack uncertainties using historical data. Finally, we transform the proposed DRO model as a tractable optimization problem, with its solution providing an optimal cyber redundancy plan to enhance system survivability in DoS attack scenarios. Simulation results on the IEEE 13-node and 123-node test feeders demonstrate the effectiveness of our proposed model in improving system survivability. This model can also be expanded to include other types of common attacks and serve as a comprehensive planning tool to improve overall cyber physical survival of the system.

cybersecurity↗
DOE OSTI2022

Maximum power point tracking for a multi-layered piezoelectric heel charger with a levered mechanism toward impact-based energy harvesting

The piezoelectric footstep energy harvester does not always work at its maximum power point when the external load is fixed, as the optimal load changes when the walking excitation alters. Thus, the harvesting efficiency is downgraded largely in real-life scenarios compared to in-lab experiments and theoretical or numerical predictions due to the mismatch between the actual load and the optimal load. To address this issue, the concept of Maximum Power Point Tracking (MPPT) is investigated in this paper and the circuit design is implemented for a multi-layered levered piezoelectric footstep energy harvester (heel charger). The proposed event-driven MPPT circuit interface with a customized buck converter aims to maximize the power gained from daily walking using the heel charger to power a fixed load, such as smart insole or shoes. The MPPT circuit design is conceptually simulated and then tested with the heel charger to further validate if it works at its maximum power point when the frequency of the input excitation alters. Results show that the extracted power from the heel charger connected to a fixed resistance load with MPPT implementation is improved up to 300% compared to the one without MPPT implementation in simulation and up to 180% in the experiment when connected to a fixed load. The difference between simulation and experimental results is due to the optimization of using voltage sources as the heel charger and the control signals (pulse width modulation) from the microcontroller in the simulation.

47 OTHER INSTRUMENTATION↗
NASA NTRS2009

Lunar Outpost Life Support Architecture Study Based on a High Mobility Exploration Scenario

As scenarios for lunar surface exploration and habitation continue to evolve within NASA s Constellation program, so must studies of optimal life support system architectures and technologies. This paper presents results of a life support architecture study based on a 2009 NASA scenario known as Scenario 12. Scenario 12 represents a consolidation of ideas from earlier NASA scenarios and includes an outpost near the Lunar South Pole comprised of three larger fixed surface elements and four attached pressurized rovers. The scenario places a high emphasis on surface mobility, with planning assuming that all four crewmembers spend roughly 50% of the time away from the outpost on 3-14 day excursions in two of the pressurized rovers. Some of the larger elements can also be mobilized for longer duration excursions. This emphasis on mobility poses a significant challenge for a regenerative life support system in terms of cost-effective waste collection and resource recovery across multiple elements, including rovers with very constrained infrastructure resources. The current study considers pressurized rovers as part of a distributed outpost life support architecture in both stand-alone and integrated configurations. A range of architectures are examined reflecting different levels of closure and distributed functionality. Different lander propellant scavenging options are also considered involving either initial conversion of residual oxygen and hydrogen propellants to water or initial direct oxygen scavenging. Monte Carlo simulations are used to assess the sensitivity of results to volatile high-impact mission variables, including the quantity of residual lander propellants available for scavenging, the fraction of crew time away from the outpost on excursions, total extravehicular activity hours, and habitat leakage. Architectures are evaluated by estimating surpluses or deficits of water and oxygen per 180-day mission and differences in fixed and 10-year-total equivalent system mass (ESM) relative to a reference case. Results are presented based on current assumptions for Scenario 12 and based on Monte Carlo simulations with assumed probability distributions for the high-impact mission variables. The calculated probability of no water or oxygen resupply from Monte Carlo simulations provides a quantitative measure of system robustness that can be used for cost/benefit analyses to identify leading architecture candidates. Areas of technology improvement that are likely to have a significant impact are also suggested.

Lange, Kevin E.↗
DOE OSTI2019

Scalable Representation Learning for Long-Term Augmented Reality-Based Information Delivery in Collaborative Human-Robot Perception

Augmented reality (AR)-based information delivery has been attracting an increasing attention in the past few years to improve com- munication in human-robot teaming. In the long-term use of AR systems for collaborative human-robot perception, one of the biggest challenges is to perform place and scene matching under long-term environmental changes, such as dramatic variations in lighting, weather and vegetation across di erent times of the day, months, and seasons. To address this challenge, we introduce a novel representation learning approach that learns a scalable long-term representation model that can be used for place and scene matching in various long-term conditions. Our approach is formulated as a regularized optimization problem, which selects the most representative scene templates in di erent scenarios to construct a scalable representation of the same place that can exhibit signi cant long-term environment changes. Our approach adaptively learns to select a small subset of the templates to construct the representation model, based on a user-de ned representativeness threshold, which makes the learned model highly scalable to the long-term variations in real-world applications. To solve the formulated optimization problem, a new algo- rithmic solver is designed, which is theoretically guaranteed to converge to the global optima. Experiments are conducted using two large-scale benchmark datasets, which have demonstrated the superior performance of our approach for long-term place and scene matching.

42 ENGINEERING↗
DOE OSTI2016

TH-CD-BRA-09: Towards Absolute Dose Measurement in MRI-Linac and Gamma-Knife: Design and Construction of An MR-Compatible Water Calorimeter

Purpose: The purpose of this work is to design and optimize a portable Water Calorimeter (WC) for use in a commercial MRI-linac and Gamma-knife in addition to conventional radiotherapy linacs. Water calorimeters determine absorbed dose to water at a point by measuring radiation-induced temperature rise of the volume (the two are related by the medium specific heat capacity). In this formalism, one important correction factor is heat transfer correction k-ht. It compensates for heat gain/loss due to conductive and convective effects, and is numerically calculated as ratio of temperature rise in the absence of heat loss to that in the presence of heat loss. Operating at 4°C ensures convection is minimal. Methods: A commercial finite element software was used to evaluate several WC designs with different insulation materials and thicknesses; channels allowing coolant to travel around WC (to sustain WC at 4°C) were modeled, and worst-case scenario variation in the temperature of the coolant was simulated for optimization purposes (2.6 mK/s). Additionally, several calorimeter vessel design parameters (front/back glass thickness/separation, diameter) were also simulated and optimized. Optimization is based on minimizing long term calorimeter drift (24h) as well as variation and magnitude of k-ht. Results: The final selected WC design reached a modest drift of 11µK/s after 15h for the worst-case coolant temperature variation. This design consists of coolant channels being encompassed on both sides by cryogel insulation. For the MRI-linac beam, glass thickness plays the largest effect on k-ht with variation of upto 0.6% in the first run for thicknesses ranging between 0.5–1.7mm. Subsequent runs vary only within 0.1% with glass thickness. Other factors such as vessel radius and top/bottom glass separation have sub 0.1% effects on k-ht. Conclusion: An MR-safe 4°C stagnant WC appropriate for dosimetry in MRI-linac and Gamma-Knife was designed, optimized, and construction is nearly completed. NSERC Discovery Grant RGPIN-435608.

07 ISOTOPE AND RADIATION SOURCES↗