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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

High performance superconducting undulator

A high performance superconducting undulator magnet is provided. The superconducting undulator magnet includes inset grooves in which magnetic poles are attached. The superconducting undulator magnet also includes clips for use in winding. The superconducting wire is wound such that the each revolution of the wire has a precise position within each of the grooves, the precise position being repeated in each groove. The superconducting undulator magnet provided will have a mechanical precision to preserve uniformity of the magnetic pole width and coil grooves. The undulator system provides uniformity of the undulator gap.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

High Performance Computing Modeling Advances Accelerator Science for High-Energy Physics

The development and optimization of particle accelerators are essential for advancing our understanding of the properties of matter, energy, space, and time. Particle accelerators are complex devices whose behavior involves many physical effects on multiple scales. Therefore, advanced computational tools utilizing high-performance computing are essential for accurately modeling them. In the past decade, the US Department of Energy's SciDAC program has produced accelerator-modeling tools that have been employed to tackle some of the most difficult accelerator science problems. The authors discuss the Synergia framework and its applications to high-intensity particle accelerator physics. Synergia is an accelerator simulation package capable of handling the entire spectrum of beam dynamics simulations. Our authors present Synergia's design principles and its performance on HPC platforms.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

High performance ultraviolet photodetectors based on ZnO nanoflakes/PVK heterojunction

A high performance ultraviolet (UV) photodetector is receiving increasing attention due to its significant applications in fire warning, environmental monitoring, scientific research, astronomical observation, etc. The enhancement in performance of the UV photodetector has been impeded by lacking of a high-efficiency heterojunction in which UV photons can efficiently convert into charges. In this work, the high performance UV photodetectors have been realized by utilizing organic/inorganic heterojunctions based on a ZnO nanoflakes/poly (N-vinylcarbazole) hybrid. A transparent conducting polymer poly(3,4-ethylene-dioxythiophene):poly(styrenesulfonate)-coated quartz substrate is employed as the anode in replacement of the commonly ITO-coated glass in order to harvest shorter UV light. The devices show a lower dark current density, with a high responsivity (R) of 7.27 × 10{sup 3 }A/W and a specific detectivity (D*) of 6.20 × 10{sup 13} cm Hz{sup 1/2}/W{sup −1} at 2 V bias voltage in ambient environment (1.30 mW/cm{sup 2} at λ = 365 nm), resulting in the enhancements in R and D* by 49% and one order of magnitude, respectively. The study sheds light on developing high-performance, large scale-array, flexible UV detectors using the solution processable method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Building America Case Study: Performance and Costs of Ductless Heat Pumps in Marine Climate High-Performance Homes: Habitat for Humanity -- The Woods, Tacoma, Washington

The Woods is a Habitat for Humanity (HFH) community of ENERGY STAR Homes (c) Northwest (ESHNW)-certified homes located in the marine climate of Tacoma/Pierce County, Washington. This research report builds on an earlier preliminary draft 2014 BA report, and includes significant billing analysis and cost effectiveness research from a collaborative, ongoing Ductless Heat Pump (DHP) research effort for Tacoma Public Utilities (TPU) and Bonneville Power Administration (BPA). This report focuses on the results of field testing, modeling, and monitoring of ductless mini-split heat pump hybrid heating systems in seven homes built and first occupied at various times between September 2013 and October 2014. The report also provides WSU documentation of high-performance home observations, lessons learned, and stakeholder recommendations for builders of affordable high-performance housing such as HFH.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

On Performance Prediction of Big Data Transfer in High-performance Networks

Big data generated by large-scale scientific and industrial applications need to be transferred between different geographical locations for remote storage, processing, and analysis. High-speed dedicated connections provisioned in High-performance Networks (HPNs) are increasingly utilized to carry out such big data transfer. HPN management highly relies on an important capability of performance (mainly throughput) prediction to reserve sufficient bandwidth and meanwhile avoid over-provisioning that may result in unnecessary resource waste. This capability is critical to improving the resource (mainly bandwidth) utilization of dedicated connections and meeting various user requests for data transfer. Conventional methods conduct performance prediction by fitting prior observed transfer history with predefined loss functions, without considering unobservable latent factors such as competing loads on end hosts. Such latent factors also have a significant impact on the application-level data transfer performance, which may result in an inaccurate prediction model. In this paper, we first investigate the impact of latent factors and propose a clustering-based method to eliminate their negative impact on performance prediction. We then develop a robust machine learning-based performance predictor by: i) incorporating the proposed latent factor elimination method into data preprocessing, and ii) adopting a customized domain guided loss function. Extensive experimental results show that our predictor achieves significantly higher prediction accuracy than several other state-of-the-art methods.

Liu, Wuji↗
NASA NTRS1992

High performance computing and communications program

A review of the High Performance Computing and Communications (HPCC) program is provided in vugraph format. The goals and objectives of this federal program are as follows: extend U.S. leadership in high performance computing and computer communications; disseminate the technologies to speed innovation and to serve national goals; and spur gains in industrial competitiveness by making high performance computing integral to design and production.

Holcomb, Lee↗
NASA NTRS1985

High-performance deployable structures for the support of high-concentration ratio solar array modules

A study conducted on high-performance deployable structures for the support of high-concentration ratio solar array modules is discussed. Serious consideration is being given to the use of high-concentration ratio solar array modules or applications such as space stations. These concentrator solar array designs offer the potential of reduced cost, reduced electrical complexity, higher power per unit area, and improved survivability. Arrays of concentrators, such as the miniaturized Cassegrainian concentrator modules, present a serious challenge to the structural design because their mass per unit area (5.7 kg/square meters) is higher than that of flexible solar array blankets, and the requirement for accurate orientation towards the Sun (plus or minus 0.5 degree) requires structures with improved accuracy potentials. In addition, use on a space station requires relatively high structural natural frequencies to avoid deleterious interactions with control systems and other large structural components. The objective here is to identify and evaluate conceptual designs of structures suitable for deploying and accurately supporting high-concentration ratio solar array modules.

Mobrem, M.↗
DOE OSTI2024

Data Center Immersion Cooling: A Case Study and Summary of High-Performance Computing Cooling Technologies

The future of High Performance Computing (HPC) is carved out for all high-performance facilities. As computer processing increases exponentially, especially with the demand for AI training, more speed will equate to more computing density and ultimately more power draw and resource demand. Sandia National Laboratories has not seen or known of anything that would lead us to think this might change in the next 5 to 10 years.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

The High Performance Computing Initiative

The paper discusses NASA High Performance Computing Initiative (HPCI), an essential component of the Federal High Performance Computing Program. The HPCI program is designed to provide a thousandfold increase in computing performance, and apply the technologies to NASA 'Grand Challenges'. The Grand Challenges chosen include integrated multidisciplinary simulations and design optimizations of aerospace vehicles throughout the mission profiles; the multidisciplinary modeling and data analysis of the earth and space science physical phenomena; and the spaceborne control of automated systems, handling, and analysis of sensor data and real-time response to sensor stimuli.

Holcomb, Lee B.↗
DOE OSTI2019

Review Article: Crystal alignment for high performance organic electronics devices

Organic electronics devices based on high-performance small-molecule organic semiconductors have gained substantial attention because of their unique advantages such as excellent charge transport, solution processability, and environmental stability. However, the intrinsic crystallization of small-molecule organic semiconductors is anisotropic, resulting in significant device performance variations of organic electronics devices. In this article, the authors review the various approaches and techniques developed to control and align the crystallization of some benchmark solution-processable, high-performance, small-molecule organic semiconductors, such as 6,13-bis(triisopropylsilylethynyl) pentacene, N,N'-1H,1H-perfluorobutyl dicyanoperylenecarboxydiimide, and 5,11-bis(triethylgermylethynyl)anthradithiophene. These alignment approaches are studied in the context of capillary force-based techniques, patterning-based techniques, solution-shearing-based techniques, and other miscellaneous techniques, including zone-casting, vertical flowing, air flow navigation, temperature gradient alignment, etc. The organic semiconductors and crystal alignment techniques reviewed in this article shed light on important relationship among crystallization, charge transport, and device performance and can be applied to various high-performance organic electronics devices, such as organic thin film transistors and solar cells.

42 ENGINEERING↗
DOE OSTI2016

Performance and Costs of Ductless Heat Pumps in Marine-Climate High-Performance Homes -- Habitat for Humanity The Woods

This final Building America Partnership report focuses on the results of field testing, modeling, and monitoring of ductless mini-split heat pump hybrid heating systems in seven homes built and first occupied at various times between September 2013 and October 2014. The report also provides WSU documentation of high-performance home observations, lessons learned, and stakeholder recommendations for builders of affordable high-performance housing.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Construction of reduced graphene oxide supported molybdenum carbides composite electrode as high-performance anode materials for lithium ion batteries

Highlights: • Reduced graphene oxide supported molybdenum carbides are prepared by two-step strategy. • A unique sheet-on-sheet integrated nanostructure is favorable for fast ion/electron transfer. • The integrated electrode shows excellent Li ion storage performance. - Abstract: Metal carbides are emerging as promising anodes for advanced lithium ion batteries (LIBs). Herein we report reduced graphene oxide (RGO) supported molybdenum carbides (Mo{sub 2}C) integrated electrode by the combination of solution and carbothermal methods. In the designed integrated electrode, Mo{sub 2}C nanoparticles are uniformly dispersed among graphene nanosheets, forming a unique sheet-on-sheet integrated nanostructure. As anode of LIBs, the as-prepared Mo{sub 2}C-RGO integrated electrode exhibits noticeable electrochemical performances with a high reversible capacity of 850 mAh g{sup −1} at 100 mA g{sup −1}, and 456 mAh g{sup −1} at 1000 mA g{sup −1}, respectively. Moreover, the Mo{sub 2}C-RGO integrated electrode shows excellent cycling life with a capacity of ∼98.6 % at 1000 mA g{sup −1} after 400 cycles. Our research may pave the way for construction of high-performance metal carbides anodes of LIBs.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A Visual Analytics Framework for the Detection of Anomalous Call Stack Trees in High Performance Computing Applications

Anomalous runtime behavior detection is one of the most important tasks for performance diagnosis in High Performance Computing (HPC). Most of the existing methods find anomalous executions based on the properties of individual functions, such as execution time. However, it is insufficient to identify abnormal behavior without taking into account the context of the executions, such as the invocations of children functions and the communications with other HPC nodes. We improve upon the existing anomaly detection approaches by utilizing the call stack structures of the executions, which record rich temporal and contextual information. With our call stack tree (CSTree) representation of the executions, we formulate the anomaly detection problem as finding anomalous tree structures in a call stack forest. The CSTrees are converted to vector representations using our proposed stack2vec embedding. Structural and temporal visualizations of CSTrees are provided to support users in the identification and verification of the anomalies during an active anomaly detection process. Furthermore, three case studies of real-world HPC applications demonstrate the capabilities of our approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Evaluation of High-Performance Rooftop HVAC Unit Naval Air Station Key West, Florida

The U.S. Department of Energy (DOE) and the U.S. Navy Facilities Engineering Command (NAVFAC) collaborated on a project to measure the performance of two high performance rooftop HVAC units (RTUs) that were installed at the Navy Exchange at Naval Air Station (NAS) Key West, FL. These RTUs were manufactured by the Daikin Corporation and the Carrier Corporation as part of the Advanced RTU Campaign (http://www.advancedrtu.org) sponsored by DOE’s Commercial Building Energy Alliance. The goal of this campaign was to encourage development of a next-generation RTU that had an integrated energy efficiency rating (IEER) of 18.0 or greater. This threshold had heretofore not been achieved.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Experimental Evaluation of High Performance Integrated Heat Pump

Integrated heat pump (IHP) technology provides significant potential for energy savings and comfort improvement for residential buildings. In this study, we evaluate the performance of a high performance IHP that provides space heating, cooling, and water heating services. Experiments were conducted according to the ASHRAE Standard 206-2013 where 24 test conditions were identified in order to evaluate the IHP performance indices based on the airside performance. Empirical curve fits of the unit s compressor maps are used in conjunction with saturated condensing and evaporating refrigerant conditions to deduce the refrigerant mass flowrate, which, in turn was used to evaluate the refrigerant side performance as a check on the airside performance. Heat pump (compressor, fans, and controls) and water pump power were measured separately per requirements of Standard 206. The system was charged per the system manufacturer s specifications. System test results are presented for each operating mode. The overall IHP performance metrics are determined from the test results per the Standard 206 calculation procedures.

Miller, William A↗
DOE OSTI2023

High-Performance Accelerator Modeling: Toward Improving Controls and Diagnostics for High-Brightness Beams in Experiment

One of the main charges of beam physics is to improve the overall beam quality delivered to experiments and applications, which is generally quantified by the beam brightness. High brightness beams have numerous applications, including x-ray free electron lasers and ultrafast electron diffraction (UED). To these ends, this thesis details efforts to use high-performance models --- high-fidelity models that execute quickly --- for controls and diagnostics. To demonstrate the generality of these techniques, this thesis focuses on three of the most successful photoinjector designs currently used worldwide: the UCLA/SLAC/BNL-type high-gradient S-band gun, the continuous-wave high-repetition rate VHF APEX gun and the L-band DESY-PITZ-type gun. Work will be shown from Pegasus (UCLA), HiRES (LBNL) and FAST (FNAL).Specifically, data-driven models for online virtual diagnostics are presented, in this case, in the context of UED at HiRES, leading to a temporal resolution improvement. Methods for improving the fidelity of physics-based models are discussed, with examples at HiRES, Pegasus and FAST. Markov-chain Monte Carlo analysis is applied to match simulations, in the context of photocathode studies at HiRES and Pegasus. Lastly, the augmentation of online model-based predictions with model-independent optimization is explored in a fluctuating environment at Pegasus and HiRES. A central theme of this dissertation is working with parameter fluctuations when modeling an accelerator beamline. Long-term drifts and shot-to-shot jitter exist in every accelerator to a varying degree and therefore play an important role in every chapter of this dissertation. This thesis attempts to address the issues associated with these fluctuations when trying to develop faithful model representations of the system.

43 PARTICLE ACCELERATORS↗
NASA NTRS2007

A Queue Simulation Tool for a High Performance Scientific Computing Center

The NASA Center for Computational Sciences (NCCS) at the Goddard Space Flight Center provides high performance highly parallel processors, mass storage, and supporting infrastructure to a community of computational Earth and space scientists. Long running (days) and highly parallel (hundreds of CPUs) jobs are common in the workload. NCCS management structures batch queues and allocates resources to optimize system use and prioritize workloads. NCCS technical staff use a locally developed discrete event simulation tool to model the impacts of evolving workloads, potential system upgrades, alternative queue structures and resource allocation policies.

Spear, Carrie↗
DOE OSTI2021

Exploratory analysis and performance prediction of big data transfer in High-performance Networks

Big data transfer in large-scale scientific and business applications is increasingly carried out over connections with guaranteed bandwidth provisioned in High-performance Networks (HPNs) via advance bandwidth reservation. Provisioning agents need to carefully schedule data transfer requests, compute network paths, and allocate appropriate bandwidths. Such reserved bandwidths, if not fully utilized, could be simply wasted due to the exclusive access during the approved time window, and cause extra overhead and complexity for resource management. This calls for accurate performance prediction to reserve bandwidths that match actual needs and avoid over-provisioning. We employ machine learning algorithms to predict big data transfer performance based on extensive performance measurements collected in the past several years from data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated testbeds. We first analyze the performance patterns in response to a comprehensive list of parameters in end-host systems, network connections, and data transfer applications, which motivate the use of machine learning and also help us identify the effects of latent factors. We then propose threshold- and clustering-based methods to eliminate negative effects of latent factors in data preprocessing and build a robust performance predictor based on customized domain-oriented loss functions. The performance of the proposed methods is verified by extensive experiments using SVR and RFR as well as theoretical analysis of the general performance bound.

97 MATHEMATICS AND COMPUTING↗