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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Carbon-Based Metal-Free ORR Electrocatalysts for Fuel Cells: Past, Present, and Future

Replacing precious platinum with earth-abundant materials in fuel cells for oxygen reduction reaction (ORR) has been the objective worldwide for several decades. In last ten years, the carbon-based metal-free ORR electrocatalysts is the fastest-growing branch in this area. Great progresses have been made in promoting the performance and understanding the underlying ORR process. This article presents a comprehensive review of this filed by emphasizing on the emerging issues such as the design and controllable construction of porous structures and doping configurations, mechanistic understanding from the model catalysts and the combined experimental and theoretical studies, and more importantly, the performance evaluation in a full cell. Centering these topics, the most up-to-date results are presented, along with the remarks and perspectives for the future development of carbon-based metal-free ORR electrocatalysts.

Yang, Lijun↗
DOE OSTI2017

Evaluating and optimizing the NERSC workload on Knights Landing

NERSC has partnered with 20 representative application teams to evaluate performance on the Xeon-Phi Knights Landing architecture and develop an application-optimization strategy for the greater NERSC workload on the recently installed Cori system. In this article, we present early case studies and summarized results from a subset of the 20 applications highlighting the impact of important architecture differences between the Xeon-Phi and traditional Xeon processors. We summarize the status of the applications and describe the greater optimization strategy that has formed.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2018

Performance and Evaluation of the Global Modeling and Assimilation Office Observing System Simulation Experiment

The National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) has spent more than a decade developing and implementing a global Observing System Simulation Experiment framework for use in evaluting both new observation types as well as the behavior of data assimilation systems. The NASA/GMAO OSSE has constantly evolved to relect changes in the Gridpoint Statistical Interpolation data assimiation system, the Global Earth Observing System model, version 5 (GEOS-5), and the real world observational network. Software and observational datasets for the GMAO OSSE are publicly available, along with a technical report. Substantial modifications have recently been made to the NASA/GMAO OSSE framework, including the character of synthetic observation errors, new instrument types, and more sophisticated atmospheric wind vectors. These improvements will be described, along with the overall performance of the current OSSE. Lessons learned from investigations into correlated errors and model error will be discussed.

OSS↗
DOE OSTI2015

SU-E-T-235: Data Mining for Evaluating Treatment Performances Over a Large Quantity of Data to Monitor and Improve SBRT Workflow

Purpose: To quality assure a large quantity of retrospective treatment cases for treatment performances by randomly sampling is inefficient. Here we provide a method to efficiently monitor and investigate the QA of SBRT workflow over Mosaiq. Methods: The code developed with Microsoft SQL Server Management Studio 2008R2 and VBA was used for retrieving and sorting data from Mosaiq (version 2.3–2.6 during 2012–2015). SBRT patients were filtered by fractional dose over 350cGy and total fraction number less than 6, which SBRT prescriptions were defined. The quality assurance on the SBRT workflow was focused on the treatment deliveries such as patient positioning setup, CBCT indicated offsets and couch shifted corrections. The treatment delivery were done by Varian Truebeam systems and the record/verify by Mosaiq. Results: Total 82 SBRT patients corresponding to 103 courses and 854 CBCT images were found by the retrieval query. Most centers record daily pre-treatment (Pre-Tx: before treatment shift) image-guided shifts along treatment course for inter-fraction motion record, and it is useful to also verify it with post-treatment imaging (Post-Tx: after treatment CBCT verification) to verify intra-fraction motion. Analyzing the details of daily recorded shifts can reveals the information of patient-setup and staff’s record/verify behaviors. 3 examples were provided as solid evidences and on-going rectification for preventing future mistakes. Conclusions: The report gave feasible examples for inspector to verify a large amount of data during site investigation. This program can also be extended to a scheduled data mining with software to periodical analyze the timely records in Mosaiq, for example, a various control charts for different QA purposes. As the current trend of automation in radiation therapy field, the data mining would be a necessary tool in the future, just as the automatic plan quality evaluation has been under development in Eclipse.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1989

Test and validation for robot arm control dynamics simulation

The Flight Telerobotic Servicer (FTS) program will require an ability to develop, in a cost effective manner, many simulation models for design, analysis, performance evaluation, and crew training. Computational speed and the degree of modeling fidelity associated with each simulation must be commensurate with problem objectives. To demonstrate evolving state-of-the-art general purpose multibody modeling capabilities, to validate these by laboratory testing, and to expose their modeling shortcomings, two focus problems at the opposite ends of the simulation spectrum are defined: (1) Coarse Acquisition Control Dynamics. Create a real time man-in-the-control-loop simulator. Provide animated graphical display of robot arm dynamics and tactile feedback sufficient for cueing the operator. Interface simulator software with human operated tactile feedback controller; i.e., the Kraft mini-master. (2) Fine, Precision Mode Control Dynamics. Create a high speed, high fidelity simulation model for the design, analysis, and performance evaluation of autonomous 7 degree-of-freedom (DOF) trajectory control algorithms. This model must contain detail dynamic models for all significant dynamics elements within the robot arm, such as joint drive mechanisms.

Yae, K. Harold↗
NASA NTRS1977

US Search and Rescue Mission Control Center functions

A satellite aided Search and Rescue (SAR) Mission concept consisting of a local coverage bent pipe system, and a global coverage system is described. The SAR instrument is to consist of a Canadian repeater and a French processor for which Canada and France, respectively are to evaluate health and trends. Performance evaluations of each system were provided. The United States and Canada will each have a Search and Rescue Mission Control Center (MCC) and their functions were also examined. A summary of the interface requirements necessary to perform each function was included as well as the information requirements between the USMCC and each of its interfaces. Physical requirements such as location, manning etc. of the USMCC were discussed.

Source record↗
DOE OSTI2022

Continuous fiber malleable thermoset composites with sub-1-minute dwell times; validation of impact performance and evaluation of the efficacy of the compression forming process. CRADA Final Report

Mallinda is developing polyimine malleable thermoset prepreg composite materials which have excellent mechanical properties (100 GPa tensile modulus, 2 GPA tensile strength, 2.4% elongation at break) and high operating temperatures (Tg>200°C). At scale, polyimine resins are commensurate in price with commodity epoxy resins. What distinguishes malleable thermoset prepreg from traditional thermoset prepreg materials, is that they are fully cured during Mallinda’s roll-to-roll production of prepreg laminate. This results in 5 key value-differentiating benefits. First, it simplifies manufacturing logistics by enabling ambient transportation and storage, and by significantly extending out-life and shelf-life almost indefinitely. Second, elimination of autoclave curing reduces the economic and energy costs to the customer. Third, scrap rates can be reduced as malleable thermoset prepreg materials are directly reusable. Fourth, the manufacturing consolidation step can be roughly 10x faster than traditional thermosets, because the resin is already cured. Parts can be made via compression forming by the application of heat and pressure to quickly vitrify and consolidate a multilayer part – easily leading to sub 3-minute cycle times (at lab scale we have demonstrated a 20 second dwell time, with room for further optimization). Finally, the closed-loop cradle-to-cradle solution-based recyclability of malleable thermoset composites can also contribute significantly to the future of sustainable lightweight materials. The focus of this project was the development, optimization and validation of malleable thermoset composite materials which exhibit manufacturing cycle times of 3-minute or less, high speed impact performance on par with incumbent technologies, and defect-free consolidation of 3 dimensional parts.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Spatial profiles of photon chemical potential in near-field thermophotovoltaic cells

Emitted photons stemming from the radiative recombination of electron–hole pairs carry chemical potential in radiative energy converters. This luminescent effect can substantially alter the local net photogeneration in near-field thermophotovoltaic cells. Several assumptions involving the luminescent effect are commonly made in modeling photovoltaic devices; in particular, the photon chemical potential is assumed to be zero or a constant prescribed by the bias voltage. The significance of photon chemical potential depends upon the emitter temperature, the semiconductor properties, and the injection level. Hence, these assumptions are questionable in near-field thermophotovoltaic devices with nanoscale separation distances between the emitter and the cell. In the present work, an iterative solver that combines fluctuational electrodynamics with the drift-diffusion model is developed to tackle the coupled photon and charge transport problem, enabling the determination of the spatial profile of photon chemical potential beyond the detailed balance approach. Here, the difference between the results obtained by allowing the photon chemical potential to vary spatially and by assuming a constant value demonstrates the limitations of the conventional approaches. This study is critically important for performance evaluation of near-field thermophotovoltaic systems with nanoscale vacuum gaps.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2016

Fission gas bubble identification using MATLAB's image processing toolbox

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods. - Highlights: •Automated image processing can aid in the fuel qualification process. •Routines are developed to characterize fission gas bubbles in irradiated U–Mo fuel. •Frequency domain filtration effectively eliminates FIB curtaining artifacts. •Adaptive thresholding proved to be the most accurate segmentation method. •The techniques established are ready to be applied to large scale data extraction testing.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Convolutional Neural Networks for Hydrometeor Classification using Dual Polarization Doppler Radars

Traditional fuzzy logic hydrometeor classification algorithm is a common way to classify precipitation type from dual polarization doppler radar. We propose a deep learning-based method to estimate hydrometeors efficiently using observed radar variables such as horizontal reflectivity (Z H ), differential reflectivity (Z DR ), correlation coefficient (ρ HV ) and specific differential phase (K DP ) from National Weather Service NEXRAD collected at Vance AFB facility at the first elevation angle from January 1st, 2015 to July 31th, 2019. We stack matrices of values from these four polarimetric variables as one 3D array. Samples are preprocessed and divided into training, validation and test set with four target hydrometeor categories (Ice Crystals (IC), Dry Snow (DS), Light and/or Moderate Rain (RA) and Big Drops (rain) (BD)). We developed and optimized five Convolutional Neural Networks (CNNs) architectures and achieved an accuracy of 87.23% and 93.736% respectively using modified ResNet with two different input data selection strategies for hydrometeor classification. Training data selection strategies were important to ensure use of available samples in training for robust performance evaluated by applying the models to novel time period beyond what was use to train the model. Seasonal variation in atmospheric conditions lead to seasonal patterns of liquid vs solid forms of precipitation, that poses challenge for classifier and offer insights into domain specific approaches required for problem of hydrometeor identification. Computationally efficient and scalable approach for classification of hydrometeors offer opportunties to effectively use the large volumes of rich time series of radar observations that are becoming increasingly available.

Lu, Yuping↗
DOE OSTI2015

Transition Analysis of Promising U.S. Future Fuel Cycles Using ORION

The US Department of Energy Office of Fuel Cycle Technologies performed an evaluation and screening (E&S) study of nuclear fuel cycle options to help prioritize future research and development decisions. Previous work for this E&S study focused on establishing equilibrium conditions for analysis examples of 40 nuclear fuel cycle evaluation groups (EGs) and evaluating their performance according to a set of 22 standardized metrics. Following the E&S study, additional studies are being conducted to assess transitioning from the current US fuel cycle to future fuel cycle options identified by the E&S study as being most promising. These studies help inform decisions on how to effectively achieve full transition, estimate the length of time needed to undergo transition from the current fuel cycle, and evaluate performance of nuclear systems and facilities in place during the transition. These studies also help identify any barriers to achieve transition. Oak Ridge National Laboratory (ORNL) Fuel Cycle Options Campaign team used ORION to analyze the transition pathway from the existing US nuclear fuel cycle—the once-through use of low-enriched-uranium (LEU) fuel in thermal-spectrum light water reactors (LWRs) —to a new fuel cycle with continuous recycling of plutonium and uranium in sodium fast reactors (SFRs). This paper discusses the analysis of the transition from an LWR to an SFR fleet using ORION, highlights the role of lifetime extensions of existing LWRs to aid transition, and discusses how a slight delay in SFR deployment can actually reduce the time to achieve an equilibrium fuel cycle.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Evaluating the performance of random forest and iterative random forest based methods when applied to gene expression data

Gene-to-gene networks, such as Gene Regulatory Networks (GRN) and Predictive Expression Networks (PEN) capture relationships between genes and are beneficial for use in downstream biological analyses. There exists multiple network inference tools to produce these gene-to-gene networks from matrices of gene expression data. Random Forest-Leave One Out Prediction (RF-LOOP) is a method that has been shown to be efficient at producing these gene-to-gene networks, frequently known as GEne Network Inference with Ensemble of trees (GENIE3). Random Forest can be replaced in this process by iterative Random Forest (iRF), which performs variable selection and boosting. Here we validate that iterative Random Forest-Leave One Out Prediction (iRF-LOOP) produces higher quality networks than GENIE3 (RF-LOOP). We use both synthetic and empirical networks from the Dialogue for Reverse Engineering Assessment and Methods (DREAM) Challenges by Sage Bionetworks, as well as two additional empirical networks created from Arabidopsis thaliana and Populus trichocarpa expression data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Evaluation of Performance Variables to Accelerate the Deployment of Sustainable Aviation Fuels at a Regional Scale

An increase in jet fuel consumption and its associated emissions across the world have led to the need for alternative technologies to produce sustainable aviation fuels (SAF). One option to produce SAFs is to utilize waste or biomass-based feedstocks that has the potential to reduce greenhouse gas emissions by 50% or more compared to conventional jet fuel. However, there is a lack of understanding of how the synergistic effects of key performance variables could hinder or help the deployment of aviation fuels on a regional scale. Here, we assess the implications of key variables-including type and quantity of waste/biomass feedstock availability near the airport, cost of SAF production, life cycle greenhouse gas (GHG) emissions, policies, and fuel/infrastructure logistics-on the deployment of SAF at Chicago's O'Hare International Airport. We consider three ASTM International-approved SAF technologies (Hydroprocessed Esters and Fatty Acids, Fischer-Tropsch, and Alcohol to Jet) that can be blended up to 50% with petroleum-based jet fuel. Results from our analysis show that woody biomass-based Fischer-Tropsch technology has the lowest fuel production costs ($2.31-$2.81/gallon gasoline equivalent) of all pathways, and it reduces life cycle GHG emissions by 86% compared to conventional jet fuel despite the higher availability of crop residues compared to either woody biomass or fats, oils, and greases. Also, infrastructure is available at O'Hare International Airport to blend SAF with Jet A fuel through three terminals directly connected to the airport via pipelines. Our sensitivity analysis shows renewable fuel incentives and feedstock price to be key performance variables affecting the production cost and deployment of SAF.

alcohol-to-jet↗
DOE OSTI2022

Bio-inspired bistable piezoelectric energy harvester for powering animal telemetry tags: Conceptual design and preliminary experimental validation

Here, this paper presents the conceptual design, preliminary experimental validation, and performance evaluation of a novel bio-inspired bi-stable piezoelectric energy harvester for self-powered animal telemetry tags. The overall conceptual design, which includes a bio-inspired attachment and a bi-stable piezoelectric energy harvester, is introduced firstly with a specific application example of marine fish tracking. The self-powered telemetry tag can be externally deployed on fish (dorsal fin) to monitor fish habitats, population, and underwater environment. Inspired by the Venus flytrap's rapid shape transition, a bi-stable piezoelectric energy harvester is developed to scavenge energy from fish maneuvering and the surrounding fluid flow for a sustainable power supply. The bistability of the harvester is characterized by the measured force-displacement curve and double potential wells. A bluff body is integrated to the free end of the bistable piezoelectric energy harvester to enhance the structure-fluid interaction for the large-amplitude snap-through vibrations and higher voltage output. Controlled laboratory experiments are conducted in a water tank on the bio-inspired bi-stable piezoelectric energy harvester using a servo motor system to simulate fish swing motion at various conditions to evaluate the power generation performance. The preliminary underwater experimental results demonstrated that the proposed bio-inspired bi-stable piezoelectric energy harvester could effectively convert fish swing motions into electricity. The device collected 17.25 mJ of energy over 130 s under a peak-to-peak swing angle of 30° at 1.5 Hz in the capacitor charging experiments.

Animal tracking↗
DOE OSTI2018

Evaluation of performance metrics for the Wave Energy Prize converters tested at 1/20 th scale

It is expected that wave energy technologies will play a future role in providing clean renewable energy and diversifying energy portfolios; however, they are still at an early stage of development compared to other renewables, with varying archetypes proposed. As technologies advance toward commercialization, benchmarking is needed to quantify performance and costs. In this review, experimental datasets of Wave Energy Converter (WEC) devices tested in the final stage of the Wave Energy Prize (WEPrize) are compared and ranked using performance metrics found in the literature and those developed as WEPrize judging metrics at both U.S. and European representative wave climates. Because the WEPrize devices were tested under a set of identical sea states, which ranged from typical operating conditions to extreme storm events, consistent datasets were produced to facilitate comparison. This allows for a rare addition to the open literature on device performance trends. In addition, a reevaluation of trends established in previous power performance benchmarking studies is given. Trends found in previous studies were confirmed, except for the absorbed energy per characteristic mass metric, in which some of the WEPrize devices had higher values. Each of the metrics considered in this study has limitations due to the assumptions in simplifying the economic potential (e.g., power absorbed vs. a proxy to cost). In addition, each of these proxies is limited to the capital cost of a device, unlike the final metric used in the WEPrize, HPQ, which includes limited proxies of operational and capital expenditures, as well as array considerations. Recommendations are given for the use and potential modification of the metrics considered. Specifically, it is recommended that the ACE metric (from the WEPrize) be modified to more accurately include the other important system costs, such as the PTO and mooring, as well as installation, operation and maintenance costs.

16 TIDAL AND WAVE POWER↗