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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Production of Energy Efficient Preform Structures (PEEPS)

Due to its low density, good structural characteristics, excellent fabrication properties, and attractive appearance, aluminum metal and its alloys continue to be widely utilized. The transportation industry continues to be the largest consumer of aluminum products, with aerospace as the principal driver for this use. Boeing has long been the largest single company consumer of heat-treated aluminum in the U.S. The extensive use of aluminum to build aircraft and launch vehicles has been sustained, despite the growing reliance on more structurally efficient carbon fiber reinforced composite materials. The trend in the aerospace industry over the past several decades has been to rely extensively on large, complex, thin-walled, monolithic machined structural components, which are fabricated from heavy billets and thick plate using high speed machining. The use of these high buy-to-fly ratio starting product forms, while currently cost effective, is energy inefficient, with a high environmental impact. The widespread implementation of Solid State Joining (SSJ) technologies, to produce lower buy-to-fly ratio starting forms, tailored to each specific application, offers the potential for a more sustainable manufacturing strategy, which would consume less energy, require less material, and reduce material and manufacturing costs. One objective of this project was to project the energy benefits of using SSJ techniques to produce high-performance aluminum structures if implemented in the production of the world fleet of commercial aircraft. A further objective was to produce an energy consumption prediction model, capable of calculating the total energy consumption, solid waste burden, acidification potential, and CO2 burden in producing a starting product form - whether by conventional or SSJ processes - and machining that to a final part configuration. The model needed to be capable of computing and comparing, on an individual part/geometry basis, multiple possible manufacturing pathways, to identify the best balance of energy consumption and environmental impact. This model has been created and populated with energy consumption data for individual SSJ processes and process platforms. Technology feasibility cases studies were executed, to validate the model, and confirm the ability to create lower buy-to-fly ratio performs and machine these to final configuration aircraft components. This model can now be used as a tool to select manufacturing pathways that offer significant energy savings and, when coupled with a cost model, drive implementation of the SSJ processes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Exploration of Optimization Options for Increasing Performance of a GPU Implementation of a Three-dimensional Bilateral Filter

This report explores using GPUs as a platform for performing high performance medical image data processing, specifically smoothing using a 3D bilateral filter, which performs anisotropic, edge-preserving smoothing. The algorithm consists of a running a specialized 3D convolution kernel over a source volume to produce an output volume. Overall, our objective is to understand what algorithmic design choices and configuration options lead to optimal performance of this algorithm on the GPU. We explore the performance impact of using different memory access patterns, of using different types of device/on-chip memories, of using strictly aligned and unaligned memory, and of varying the size/shape of thread blocks. Our results reveal optimal configuration parameters for our algorithm when executed sample 3D medical data set, and show performance gains ranging from 30x to over 200x as compared to a single-threaded CPU implementation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Initial testing of wave energy powered UV-C LED anti-biofouling system (CRADA 523)

3newable is requesting technical assistance for laboratory testing at the Marine and Coastal Research (MCRL) Laboratory of a UV-C LED anti-biofouling system. Ocean observing sensors provide critical data sources from deployed buoys and other platforms at sea. However, in addition to the availability of reliable power sources, biofouling of sensors and instruments is a limiting factor for operation and maintenance of deployed instruments. In collaboration with the Woods Hole Oceanographic Institute Ocean Observatories Initiative, 3newable has developed a novel solution to overcome these challenges and extend the deployment period of buoy-mounted sensors. The 3newable system co-locates wave energy converters to supply UV-C LED anti-biofouling units on powered buoy arrays. MCRL staff will implement an experiment to evaluate the efficacy of 3newable’s device under test for inhibiting growth of organisms on test coupons in a flow through seawater tank.

42 ENGINEERING↗
DOE OSTI2022

Quantitative Performance Assessment of Proxy Apps and Parents (Report for ECP Proxy App Project Milestone ADCD-504-28)

The ECP Proxy Application Project has an annual milestone to assess the state of ECP proxy applications and their role in the overall ECP ecosystem. Our FY22 March/April milestone (ADCD- 504-28) proposed to: Assess the fidelity of proxy applications compared to their respective parents in terms of kernel and I/O behavior, and predictability. Similarity techniques will be applied for quantitative comparison of proxy/parent kernel behavior. MACSio evaluation will continue and support for OpenPMD backends will be explored. The execution time predictability of proxy apps with respect to their parents will be explored through a carefully designed scaling study and code comparisons. Note that in this FY, we also have quantitative assessment milestones that are due in September and are, therefore, not included in the description above or in this report. Another report on these deliverables will be generated and submitted upon completion of these milestones. To satisfy this milestone, the following specific tasks were completed: Study the ability of MACSio to represent I/O workloads of adaptive mesh codes. Re-define the performance counter groups for contemporary Intel and IBM platforms to better match specific hardware components and to better align across platforms (make cross-platform comparison more accurate). Perform cosine similarity study based on the new performance counter groups on the Intel and IBM P9 platforms. Perform detailed analysis of performance counter data to accurately average and align the data to maintain phases across all executions and develop methods to reduce the set of collected performance counters used in cosine similarity analysis. Apply a quantitative similarity comparison between proxy and parent CPU kernels. Perform scaling studies to understand the accuracy of predictability of the parent performance using its respective proxy application. This report presents highlights of these efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

High-temperature thermal imaging to inform the arc-melt synthesis of nuclear materials

The advancement of nuclear energy technology necessitates the development of novel materials and synthesis methods to produce materials which enable new fuel cycles. Alongside the maturation of R&D scale technologies to produce these materials, there is an ongoing effort to develop in situ monitoring capabilities to reduce the time to the discovery and development of these fuels. Monitoring data can be leveraged in artificial intelligence platforms to detect phenomena which lead to varied macro- and microstructural features which impact the application and performance of samples synthesized. The present study presents early-stage findings of the implementation of high-temperature, high-frame-rate infrared thermal imaging to monitor the arc-melt synthesis of novel fuels and compounds relevant to advanced nuclear reactors. The study illustrates both the challenges and opportunities of this methodology, highlighting the importance of internal standards while determining emissivity and transmission values as well as visualizing volatilization during melt synthesis.

Stone, Jordan↗
DOE OSTI2013

Towards uncovering the roles of switchgrass peroxidases in plant processes

Herbaceous perennial plants selected as potential biofuel feedstocks had been understudied at the genomic and functional genomic levels. Recent investments, primarily by the U.S. Department of Energy, have led to the development of a number of molecular resources for bioenergy grasses, such as the partially annotated genome for switchgrass (Panicum virgatum L.), and some related diploid species. In its current version, the switchgrass genome contains 65,878 gene models arising from the A and B genomes of this tetraploid grass. The availability of these gene sequences provides a framework to exploit transcriptomic data obtained from next-generation sequencing platforms to address questions of biological importance. One such question pertains to discovery of genes and proteins important for biotic and abiotic stress responses, and how these components might affect biomass quality and stress response in plants engineered for a specific end purpose. It can be expected that production of switchgrass on marginal lands will expose plants to diverse stresses, including herbivory by insects. Class III plant peroxidases have been implicated in many developmental responses such as lignification and in the adaptive responses of plants to insect feeding. Here, we have analyzed the class III peroxidases encoded by the switchgrass genome, and have mined available transcriptomic datasets to develop a first understanding of the expression profiles of the class III peroxidases in different plant tissues. Lastly, we have identified switchgrass peroxidases that appear to be orthologs of enzymes shown to play key roles in lignification and plant defense responses to hemipterans.

09 BIOMASS FUELS↗
DOE OSTI2017

RCCI Combustion Regime Transitions in a Single-Cylinder Optical Engine and a Multi-Cylinder Metal Engine

We present that Reactivity Controlled Compression Ignition (RCCI) is an approach to increase engine efficiency and lower engine-out emissions by using in-cylinder stratification of fuels with differing reactivity (i.e., autoignition characteristics) to control combustion phasing. Stratification can be altered by varying the injection timing of the high-reactivity fuel, causing transitions across multiple regimes of combustion. When injection is sufficiently early, combustion approaches a highly-premixed autoignition regime, and when it is sufficiently late it approaches more mixing-controlled, diesel-like conditions. Engine performance, emissions, and control authority over combustion phasing with injection timing are most favorable in between, within the RCCI regime.To study charge preparation phenomena that dictate regime transitions, two different optical diagnostics are applied in a single-cylinder heavy-duty optical engine, and conventional engine diagnostics are applied in a multi-cylinder, light-duty all-metal engine. Both engines are operated with iso-octane and n-heptane as the low- and high-reactivity fuels, respectively. The iso-octane fuel fraction delivers 80% of the total fuel energy, the global equivalence ratio is 0.35, and no exhaust gas recirculation is used. In the optical engine, single-shot, band-pass infrared (IR) imaging of emission near 3.3 microns measures thermal C-H stretch-band emission of hot fuel vapor and intermediate combustion products, providing qualitative information about the fuel-vapor distribution and ignition locations during low-temperature heat release. Additionally, high-speed 7.2 kHz visible-light imaging of natural luminosity, optimized to detect chemiluminescence, indicates the spatial and temporal evolution of high-temperature heat release and combustion. Similar combustion regimes are observed for both engine platforms, allowing an opportunity for optical engine data to provide insight into fundamental phenomena affecting regime ranges and transitions in production engines. Key findings from imaging diagnostics indicate that at the late-injection limit of RCCI control authority, low-temperature ignition occurs when clearly identifiable jet structures are still intact, and during high-temperature combustion there is prevalent and persistent soot incandescence representative of locally mixing-limited (i.e., fuel-rich) combustion. Finally, at the early-injection limit of RCCI control, observed stratification during low-temperature ignition is subtle; however, high-temperature combustion still occurs sequentially from the bowl rim radially inwards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Development of an open-source regional data assimilation system in PEcAn v. 1.7.2: application to carbon cycle reanalysis across the contiguous US using SIPNET

Abstract. The ability to monitor, understand, and predict the dynamics of the terrestrial carbon cycle requires the capacity to robustly and coherently synthesize multiple streams of information that each provide partial information about different pools and fluxes. In this study, we introduce a new terrestrial carbon cycle data assimilation system, built on the PEcAn model–data eco-informatics system, and its application for the development of a proof-of-concept carbon “reanalysis” product that harmonizes carbon pools (leaf, wood, soil) and fluxes (GPP, Ra, Rh, NEE) across the contiguous United States from 1986–2019. We first calibrated this system against plant trait and flux tower net ecosystem exchange (NEE) using a novel emulated hierarchical Bayesian approach. Next, we extended the Tobit–Wishart ensemble filter (TWEnF) state data assimilation (SDA) framework, a generalization of the common ensemble Kalman filter which accounts for censored data and provides a fully Bayesian estimate of model process error, to a regional-scale system with a calibrated localization. Combined with additional workflows for propagating parameter, initial condition, and driver uncertainty, this represents the most complete and robust uncertainty accounting available for terrestrial carbon models. Our initial reanalysis was run on an irregular grid of ∼ 500 points selected using a stratified sampling method to efficiently capture environmental heterogeneity. Remotely sensed observations of aboveground biomass (Landsat LandTrendr) and leaf area index (LAI) (MODIS MOD15) were sequentially assimilated into the SIPNET model. Reanalysis soil carbon, which was indirectly constrained based on modeled covariances, showed general agreement with SoilGrids, an independent soil carbon data product. Reanalysis NEE, which was constrained based on posterior ensemble weights, also showed good agreement with eddy flux tower NEE and reduced root mean square error (RMSE) compared to the calibrated forecast. Ultimately, PEcAn's new open-source regional data assimilation framework provides a scalable workflow for harmonizing multiple data constraints and providing a uniform synthetic platform for carbon monitoring, reporting, and verification (MRV) as well as accelerating terrestrial carbon cycle research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A parcel-level evaluation of distributed wind opportunity in the contiguous United States

This study examines the potential for distributed wind (DW) energy across the contiguous United States, leveraging advancements in the National Renewable Energy Laboratory's distributed wind model, dWind. The novel modeling approach described here utilizes a high-resolution dataset and analyzes over 150 million parcels, a significant improvement from prior methods that extrapolated results from a smaller random sample. This achievement is enabled through key model performance improvements, such as transitioning to multiprocessing, which reduces runtime by 97 %. This optimized, high-resolution approach allows the inspection of technology deployment potential and impact on a variety of scales tailored to individual properties and regions. The results here align with prior work showing substantial opportunity for energy generation using DW technologies. Key findings reveal a substantial increase from prior results in estimated technical and economic potential for DW. Metrics tuned to highlight economic potential also show increased incentives supporting rural adoption. Results are spatially aggregated for usability and published via the U.S. Department of Energy Wind Data Portal and a custom scenario visualization platform, aiding policymakers, industry, and property owners in assessing DW viability across various scenarios and spatial scales.

17 WIND ENERGY↗
DOE OSTI2011

Dynamic Analysis of Electrical Power Grid Delivery: Using Prime Mover Engines to Balance Dynamic Wind Turbine Output

This paper presents an investigation into integrated wind + combustion engine high penetration electrical generation systems. Renewable generation systems are now a reality of electrical transmission. Unfortunately, many of these renewable energy supplies are stochastic and highly dynamic. Conversely, the existing national grid has been designed for steady state operation. The research team has developed an algorithm to investigate the feasibility and relative capability of a reciprocating internal combustion engine to directly integrate with wind generation in a tightly coupled Hybrid Energy System. Utilizing the Idaho National Laboratory developed Phoenix Model Integration Platform, the research team has coupled demand data with wind turbine generation data and the Aspen Custom Modeler reciprocating engine electrical generator model to investigate the capability of reciprocating engine electrical generation to balance stochastic renewable energy.

17 WIND ENERGY↗
DOE OSTI2011

Electrical Power Grid Delivery Dynamic Analysis: Using Prime Mover Engines to Balance Dynamic Wind Turbine Output

This paper presents an investigation into integrated wind + combustion engine high penetration electrical generation systems. Renewable generation systems are now a reality of electrical transmission. Unfortunately, many of these renewable energy supplies are stochastic and highly dynamic. Conversely, the existing national grid has been designed for steady state operation. The research team has developed an algorithm to investigate the feasibility and relative capability of a reciprocating internal combustion engine to directly integrate with wind generation in a tightly coupled Hybrid Energy System. Utilizing the Idaho National Laboratory developed Phoenix Model Integration Platform, the research team has coupled demand data with wind turbine generation data and the Aspen Custom Modeler reciprocating engine electrical generator model to investigate the capability of reciprocating engine electrical generation to balance stochastic renewable energy.

17 WIND ENERGY↗
DOE OSTI2017

Bellerophon

The Bellerophon software system supports CHIMERA, a production-level HPC application that simulates the evolution of core-collapse supernovae. Bellerophon enables CHIMERA's geographically dispersed team of collaborators to perform job monitoring and real-time data analysis from multiple supercomputing resources, including platforms at OLCF, NERSC, and NICS. Its multi-tier architecture provides an encapsulated, end-to-end software solution that enables the CHIMERA team to quickly and easily access highly customizable animated and static views of results from anywhere in the world via a cross-platform desktop application.

Lingerfelt, Eric J↗
DOE OSTI2019

Empirical Validation of Building Energy Modeling using Flexible Research Platform

Recently, efforts have been made to provide reliable empirical data for ANSI/ASHRAE Standard 140, Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs, to enable improved accuracy of building energy model (BEM) engines and improved characterization of their accuracy. The motivation for this effort is that the use of reliable empirical validation data sets in the evaluation of building energy modeling tools will lead to more consistent and validated simulation engines across all software vendors. This would expedite the use of building energy modeling in designing new buildings and retrofitting existing buildings, which delivers more energy efficient buildings.As part of a three-year multi-lab empirical validation project sponsored by U.S. DOE, this research project generated cooling season test plans by reviewing ASHRAE Standard 140, and the tests were performed based on the test plan. Finally, the experimental data sets were compared with the EnergyPlus model to demonstrate the validation procedure.

Im, Piljae↗
DOE OSTI2015

Residual waste detection in HLW tanks - 15701

This research uses commercial sonar technology to monitor residual waste in the U.S. Department of Energy's (DOE) Hanford Site high-level-waste staging tanks, with primary focus on the detection and imaging of the settled solids at specified areas of interest along the tank surface within a limited amount of time. High-level waste (HLW) is generated at the US-DOE Hanford Site as a by-product from the processing of nuclear materials. Waste is currently stored in 177 underground carbon-steel waste tanks. Pulse jet mixers (PJM) are often used to break loose and suspend the solids that have settled at the bottom of the tanks. A typical tank can have 6-8 pulse tubes. The Solid Liquid Interface Monitor (SLIM) must be capable of measuring dynamic movements in Region 1 zone between each PJM cycle. SLIM was originally developed to map the sludge/supernate interface within the U.S. DOE Hanford Site's HLW tanks. SLIM is a dual-axis mechanically rotating sonar and consists of an acoustic transducer, rotation motor with gearbox, tilt motor, position reference sensor, and pressure balancing mechanisms and its associated deployment platform. The sonar gathers a swath of data in the horizontal plane and rotates the transducer through a programmed angle around the vertical axis. Oil-filled device. No user serviceable parts. No semiconductors. Hard anodized aluminum and polyurethane delrin. May be deployed in areas of significant radioactivity. Kaolin will be used during mixing operations in order to simulate the physical properties of the expected slurry. In order to reduce the amount of time needed to image and object, all settings were decreased to their minimal state. The low resolution settings provide insufficient data for the manufacturer's 3D profiler to compile a visible point cloud and much less to allow the meshing algorithm to work properly. Several filtering algorithms have been applied to each scan in order to remove erroneous spikes and ghosting effects. Data has been collected for the mixing process of kaolin. This data consists of scans executed while the pump was active and inactive. The imaging algorithm has also been used with data derived from scans of 3% or less of kaolin. Future work: Mixing of kaolin within an experimental tank will be conducted in order to simulate the settling time of the HLW within the tank. The same filtering algorithms will be applied to each of these scans to evaluate the SLIM's efficiency to image solids at the bottom of a tank through increasing volume of kaolin.

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

Development of the ARM Lagrangian Large-Scale Forcing Data (ARMLAGTRAJ) Value-Added Product Based on the lagtraj Framework

The Atmospheric Radiation Measurement (ARM) large-scale forcing data developed based on the constrained variational analysis (VARANAL) value-added product (VAP) (Zhang and Lin 1997, Zhang et al. 2001, Xie et al. 2004, Tang et al. 2019) has been widely used for single-column models (SCMs), cloud-resolving models (CRMs), and large-eddy simulation models (LESs) to understand and improve physical processes in models. Recently, the U.S. Department of Energy (DOE) ARM user facility conducted several major field campaigns using ship-based moving observational platforms. For example, the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign focused on the role of subtropical marine-boundary layer (MBL) clouds, and the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign aimed to improve understanding of the coupled climate systems in the Arctic. Observations from moving platforms are critical to provide a comprehensive characterization of coupled-system processes associated with all stages of the cloud and/or sea-ice life cycle. Traditional ARM large-scale forcing data have been developed at fixed locations. They need to be extended to include these moving platforms to address data needs for ship-based field campaigns or to support LES modeling in a Lagrangian framework. With these considerations in mind, we develop ARM-type Lagrangian large-scale forcing data sets based on the lagtraj framework (Boeing et al. 2020) with notable enhancements in generating forcings that are more suitable for ARM field campaigns. The lagtraj is a novel tool that generates forcings for LES and SCM simulation in both Lagrangian and Eulerian perspective. This technical report focuses on the major changes we performed on the lagtraj algorithm and provides an overview of the ARM Lagrangian Large-Scale Forcing Data (ARMLAGTRAJ) value-added products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Towards a Public Event Display for DUNE

The Deep Underground Neutrino Experiment (DUNE) is a next generation long baseline neutrino experiment based at Fermilab, with a near detector near the beam target and a Far Detector (FD) in South Dakota. As the experiment prepares for its first data runs, creating pathways for public engagement and data transparency is essential. We present the first-ever DUNE event display designed for public outreach and education. Developed using data from the ProtoDUNE detectors at the CERN Neutrino Platform, this tool provides an intuitive and interactive interface that allows non-experts to visualise and explore particle interactions in a Liquid Argon Time Projection Chamber (LArTPC). By translating raw experimental data into a browser-accessible format, we establish the essential infrastructure for DUNE’s pathway to open data. This talk will detail the technical development of the display, its current implementation with ProtoDUNE data, and the strategic roadmap for integrating it into DUNE’s long-term open-access framework.

Sabater, Eva [U. Sussex (main)] (ORCID:00090001748↗
DOE OSTI2024

Rapid Detection and Quick Characterization of African Swine Fever Virus Using the VolTRAX Automated Library Preparation Platform

African swine fever virus (ASFV) is the causative agent of a severe and highly contagious viral disease affecting domestic and wild swine. The current ASFV pandemic strain has a high mortality rate, severely impacting pig production and, for countries suffering outbreaks, preventing the export of their pig products for international trade. Early detection and diagnosis of ASFV is necessary to control new outbreaks before the disease spreads rapidly. One of the rate-limiting steps to identify ASFV by next-generation sequencing platforms is library preparation. Here, we investigated the capability of the Oxford Nanopore Technologies’ VolTRAX platform for automated DNA library preparation with downstream sequencing on Nanopore sequencing platforms as a proof-of-concept study to rapidly identify the strain of ASFV. Within minutes, DNA libraries prepared using VolTRAX generated near-full genome sequences of ASFV. Thus, our data highlight the use of the VolTRAX as a platform for automated library preparation, coupled with sequencing on the MinION Mk1C for field sequencing or GridION within a laboratory setting. These results suggest a proof-of-concept study that VolTRAX is an effective tool for library preparation that can be used for the rapid and real-time detection of ASFV.

60 APPLIED LIFE SCIENCES↗