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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Multiscale Patterning from Competing Interactions and Length Scales

We live in an era of complexity marked by impressive new tools powering the scientific method to accelerate discovery, prediction, and control of increasingly complex systems. In common with many disciplines and societal challenges and opportunities, materials and condensed matter sciences are beneficiaries. The volume and fidelity of experimental, computational, and visualization data available, and tools to rapidly interpret them, are remarkable. Conceptual frameworks, including multiscale, multiphysics modeling of this complexity, are fueled by the data and, in turn, guide directions for future experimental and computational strategies. In this spirit, we discuss the importance of competing interactions, length scales, and constraints as pervasive sources of spatio-temporal complexity. We use representative examples drawn from materials and condensed matter, including the important role of elasticity in some technologically important quantum materials.

36 MATERIALS SCIENCE↗
NASA NTRS1982

Computer Science Research at Langley

A workshop was held at Langley Research Center, November 2-5, 1981, to highlight ongoing computer science research at Langley and to identify additional areas of research based upon the computer user requirements. A panel discussion was held in each of nine application areas, and these are summarized in the proceedings. Slides presented by the invited speakers are also included. A survey of scientific, business, data reduction, and microprocessor computer users helped identify areas of focus for the workshop. Several areas of computer science which are of most concern to the Langley computer users were identified during the workshop discussions. These include graphics, distributed processing, programmer support systems and tools, database management, and numerical methods.

Voigt, S. J.↗
NASA NTRS1991

Technology 2000, volume 1

The purpose of the conference was to increase awareness of existing NASA developed technologies that are available for immediate use in the development of new products and processes, and to lay the groundwork for the effective utilization of emerging technologies. There were sessions on the following: Computer technology and software engineering; Human factors engineering and life sciences; Information and data management; Material sciences; Manufacturing and fabrication technology; Power, energy, and control systems; Robotics; Sensors and measurement technology; Artificial intelligence; Environmental technology; Optics and communications; and Superconductivity.

Source record↗
NASA NTRS1991

A survey of spacecraft thermal design solutions

A review of activities at the NASA/Marshall Space Flight Center in the heat transfer and thermodynamics disciplines as well as attendant fluid mechanics, transport phenomena, and computer science applications is presented. Attention is focused on recent activities including the Hubble Space Telescope, and large space instruments, particularly telescope thermal control systems such as those flown aboard Spacelab 2 and the Astro missions. Emphasis is placed on defining the thermal control features, unique design schemes, and performance of selected programs. Results obtained both by ground testing and analytical means, as well as flight and postflight data are presented.

Humphries, R.↗
NASA NTRS1993

European aerospace science and technology, 1992: A bibliography with indexes

This bibliography contains 1916 annotated references to reports and journal articles of European intellectual origin entered into the NASA Scientific and Technical Information System during 1992. Representative subject areas include: spacecraft and aircraft design, propulsion technology, chemistry and materials, engineering and mechanics, earth and life sciences, communications, computers and mathematics, and the natural space sciences.

Source record↗
DOE OSTI2016

Improving Contrast and Resolution in Plant Root Imaging

Plants play a vital role in our agro-economy, serving as a food source for both humans and animals, as exploitable sources of 'green' energy, and carbon/nitrogen fixing organisms important for atmospheric health. Roots, often hidden from view, represent one of the major connections shared between plants and their environment. Enhancing our understanding of the process of root growth in the face of complex soil compositions, and abundances or shortages of both nutrients and available water, will enable researchers to develop or improve strategies to select on genetic traits that increase the likelihood of plant survival under stress. A major setback associated with the study of plant root structures in-situ has been the inability to view the root using standard optical methods. X-ray imaging has been used since the 1980's to produce images from 'simple' 2D attenuation contrast scans to 3D computed tomography generated volumes. A large majority of previous experimental analysis has been conducted with commercial x-ray systems designed for life-sciences and/or materials analysis applications. These commercial packages were never intended for use with targets composed mostly of inorganic materials resulting in information loss. We have investigated methods to optimize imaging contrast and resolution to help reveal the very small features of root systems embedded within varying soil substrates. (authors)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Amplify scientific discovery with artificial intelligence

Computing innovations have fundamentally changed many aspects of scientific inquiry. For example, advances in robotics, high-end computing, networking, and databases now underlie much of what we do in science such as gene sequencing, general number crunching, sharing information between scientists, and analyzing large amounts of data. As computing has evolved at a rapid pace, so too has its impact in science, with the most recent computing innovations repeatedly being brought to bear to facilitate new forms of inquiry. Recently, advances in Artificial Intelligence (AI) have deeply penetrated many consumer sectors, including for example Apple’s Siri™ speech recognition system, real-time automated language translation services, and a new generation of self-driving cars and self-navigating drones. However, AI has yet to achieve comparable levels of penetration in scientific inquiry, despite its tremendous potential in aiding computers to help scientists tackle tasks that require scientific reasoning. We contend that advances in AI will transform the practice of science as we are increasingly able to effectively and jointly harness human and machine intelligence in the pursuit of major scientific challenges.

artificial intelligence↗
DOE OSTI2020

dCache – Efficient Message Encoding For Inter-Service Communication in dCache: Evaluation of Existing Serialization Protocols as a Replacement for Java Object Serialization

As a well established, large-scale distributed storage system, dCache is used to manage and serve huge amounts of data collected by high energy physics, astrophysics and photon science experiments. Based on a microservices-like architecture, dCache is built as a modular distributed system, where each component provides a different core functionality. These services communicate by passing serialized messages to each other, a core behavior whose performance properties can consequently affect the entire system.This paper compares and evaluates different data serialization protocols in computer science with the objective of replacing and improving upon Java Object Serialization (JOS), which has increasingly presented itself as no longer being sufficiently performant for encoding messages. The criteria for choosing a new framework are collected, analyzed and formalized. The primary motivation for replacing Java serialization for encoding dCache messages is increasing the general speed of message-passing and thereby reducing the round-trip time for user requests. Emphasis is also placed on schema evolution capabilities and framework usability. Approaches for generalizing (de)serialization speed and size measurements based on data structure complexity are introduced, criteria for measuring documentation, learning curve, maintainability and introduction effort are defined. Finally, several selected serialization protocols are evaluated and compared accordingly, concluding with a recommendation for a suitable JOS replacement.

Morschel, Lea↗
DOE OSTI2021

Comparative evaluation of deep learning workloads for leadership-class systems

Deep learning (DL) workloads and their performance at scale are becoming important factors to consider as we design, develop and deploy next-generation high-performance computing systems. Since DL applications rely heavily on DL frameworks and underlying compute (CPU/GPU) stacks, it is essential to gain a holistic understanding from compute kernels, models, and frameworks of popular DL stacks, and to assess their impact on science-driven, mission-critical applications. At Oak Ridge Leadership Computing Facility (OLCF), we employ a set of micro and macro DL benchmarks established through the Collaboration of Oak Ridge, Argonne, and Livermore (CORAL) to evaluate the AI readiness of our next-generation supercomputers. In this paper, we present our early observations and performance benchmark comparisons between the Nvidia V100 based Summit system with its CUDA stack and an AMD MI100 based testbed system with its ROCm stack. We take a layered perspective on DL benchmarking and point to opportunities for future optimizations in the technologies that we consider.

Yin, Junqi↗
DOE OSTI2016

SU-F-J-196: A Prototype System for Portal Imaging for Intensity Modulated Neutron Therapy

Purpose: Fast neutron therapy is offered at the University of Washington Medical Center for treatment of selected cancers. The hardware and control systems of the UW Clinical Neutron Therapy System are undergoing upgrades to enable delivery of IMNT. To clinically implement IMNT, dose verification tools need to be developed. We propose a portal imaging system that relies on the creation of positron emitting isotopes ({sup 11}C and {sup 15}O) through (n, 2n) reactions with a PMMA plate placed below the patient. After field delivery, the plate is retrieved from the vault and imaged using a reader that detects the annihilation photons. The pattern of activity produced in the plate provides information to reconstruct the neutron fluence map that can be compared to fluence maps from Monte Carlo (MCNP) simulations to verify treatment delivery. We have previously performed Monte Carlo simulations of the portal imaging system (GATE simulations) and the beam line (MCNP simulations). In this work, initial measurements using a prototype system are presented. Methods: Custom electronics were developed for BGO detectors read out with photomultiplier tubes (previous generation PET detectors from a CTI ECAT 953 scanner). Two detectors were placed in coincidence, with a detector separation of 2 cm. Custom software was developed to create the crystal look up tables and perform a limited angle planar reconstruction with a stochastic normalization. To test the initial capabilities of the system, PMMA squares were irradiated with neutrons at a depth of 1.5 cm and read out using the prototype system. Doses ranging from 10–200 cGy were delivered. Results: Using the prototype system, dose differences in the therapeutic range could be determined. Conclusion: The prototype portal imaging system is capable of detecting neutron doses as low as 10–50 cGy and shows great promise as a patient QA tool for IMNT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Towards Optimization of ACRT Schedules Applied to the Gradient Freeze Growth of Cadmium Zinc Telluride

Historically, the melt growth of II-VI crystals has benefitted by the application of the accelerated crucible rotation technique (ACRT). Here, we employ a comprehensive numerical model to assess the impact of two ACRT schedules designed for a cadmium zinc telluride growth system per the classical recommendations of Capper and co-workers. The “flow maximizing” ACRT schedule, with higher rotation, effectively mixes the solutal field in the melt but does not reduce supercooling adjacent to the growth interface. The ACRT schedule derived for stable Ekman flow, with lower rotation, proves more effective in reducing supercooling and promoting stable growth. Furthermore, these counterintuitive results highlight the need for more comprehensive studies on the optimization of ACRT schedules for specific growth systems and for desired growth outcomes.

36 MATERIALS SCIENCE↗
DOE OSTI2014

SU-C-18C-03: Dual-Energy X-Ray Fluoroscopy Imaging System

Purpose: This work studies the clinical utility of dual energy (DE) subtraction fluoroscopy for fiducial-free tumor tracking in lung radiation therapy (RT). Improvement in tumor visualization and quantification of tumor shift within a breathing cycle were analyzed. Methods: Twenty subjects who were undergoing RT for lung cancer were recruited following institutional review board approval. The subjects had a range of tumor sizes, locations in the lungs, and body sizes. An x-ray imaging system was setup with the following components: (a) x-ray tube (Varian G-242, Varian Medical Systems (VMS), CA) (b) flat panel detector (4030CB, VMS, CA) and (c) x-ray generator (EPS 50RF, EMD, Canada). Firmware and software modifications were made to the generator to allow 10 x-ray pulse pairs with alternating low/high kV, 100 ms apart for ∼4s (one breathing cycle). Images were obtained at 4 angles: 0°, 45°, 90° and 135°. Weighted subtraction of a kV-pair image set was used to create a “bone-free” image of the lungs. The 2D tumor-shift in each subtracted image and the 3D shift during a breathing cycle was calculated using all views. Results: The subjects enrolled had the following statistics: average age 62.3±7.1 years, 5 female/15 male, 11 had tumors on the right and 9 on the left and the average tumor size was ∼31.4±10.8 mm. X-ray imaging conditions for the pulse pairs were: 70/120 kVp, 280/221 mA and 65/8 ms. For views where these parameters were insufficient 80/130 kVp, 280/221 mA and 60/12 ms was used. Tumor visibility improved for 0°, 45°, 90° and 135° in 100%, 55%, 75% and 80% of the cases respectively. Tumor shift during a breathing cycle was: 2.4±1.0 mm AP, 2.7±1.4 mm LR and 7.6±4.8 mm IS. Conclusion: DE subtraction fluoroscopy allowed improved visualization and quantification of movement of tumors in the lungs during a breathing cycle. This study was entirely funded by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Earth System Model Improvement Pipeline via Uncertainty Attribution and Active Learning

Primary focal area: 2 (Predictive Modeling via AI): We develop methods to formally quantify uncertainties in Earth System models for the land-atmosphere coupled system. Science Challenge: Earth system models still have significant biases in historical predictions of the intensity and frequency of water cycling extremes (e.g., droughts and flood events), leading to low confidence in future projections. Uncertainties arise from incomplete understanding of land and atmospheric processes, and insufficient observational constraints on model parameters. Many observations, including those from key DOE investments such as ARM and AmeriFlux, are used to evaluate model performance but have not been used to formally quantify model uncertainty because of the expense of running ESM simulations. An efficient pipeline engaging cutting-edge machine learning (ML) and uncertainty quantification (UQ) methods is needed to improve the predictive understanding of water cycle extremes in the Earth system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Online monitoring using cloud-based applications.

Online monitoring using cloud-based applications presentation. Enabling online monitoring using cloud services will require additional sensors, systems and choices.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Building an AI-enhanced modeling framework to address multiscale predictability challenges

Focal Area(s): Build an AI-enhanced modeling framework that integrates the three focus areas in the solicitation. Science Challenge: The 4M-2N complexities (Multiscale, Multiphysics, Multibody, Multidimension, Non-linearity, and Non-Gaussianality) of atmospheric aerosol-cloud-precipitation-turbulence-radiation system poses physical and computational challenges to further advance predictive models; We plan to address the challenges by developing an AI-enhanced modeling framework that facilitates automated calibration and improvement of subgrid parameterizations, enhance data assimilation of measurements to improve initial and boundary conditions used to drive the physical model, and optimally blends data-driven and physics-based forecasting models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Virtual Framework for Development and Testing of Federation Software Stack

Softwarization of networked infrastructures combined with containerization of codes promises unprecedented computing capabilities distributed across the federations of computing systems and physical instruments. The development and testing of a software stack that implements these capabilities over an expensive physical production infrastructure is not cost-effective, and in the early stages, may potentially cause service disruptions. To address these aspects, we develop the Virtual Federated Science Instrument Environment (VFSIE), a digital twin of the physical infrastructure that emulates a multi-site federation. Each federated site is emulated using containers and virtual hosts that are connected over local-area networks, and the sites, in turn, are connected over an emulated wide-area network. We describe the framework design and implementation details. We also illustrate its application by emulating a federation of four laboratories that use Jupyter Notebook for computations and the EPICS software system for instrument control.

Al Najjar, Anees↗
DOE OSTI2024

Coaxial color channel focus evaluation to estimate standoff height in directed energy deposition additive manufacturing

Directed energy deposition (DED) is an additive manufacturing process that is being rapidly adopted by industry and is well suited for the fabrication of complex components in a variety of metal alloys. In laser cladding systems such as DED, powder is blown in a stream to a metal substrate coincident with a laser necessary to deposit molten metal with 3D spatial control. The focus of both the laser and the powder stream are crucial, and best deposition occurs at a predetermined standoff height between the build surface and the print head. Generally, no monitoring of this distance is implemented in commercial DED systems. Due to potential over or under building, the standoff height often changes over time but tends to self-correct. However, inexpensive and minimally intrusive methods to identify optimal standoff are required to provide real-time control to maintain the optimal distance. The present work explores the quantification of the focus of the three-color channels of a coaxial camera to determine the standoff height. An experiment was performed in which a 254 mm wall is built and the standoff height, initially 5.0 mm below the optimal position, was then intentionally increased every 25.4 mm of wall length by an amount of 1.0 mm to a final position 7.0 mm above optimal. Computer vision is demonstrated to monitor the amount of focus in each color band and estimate standoff distance. Finally, a response can be calculated in under 40 ms using simple hardware and can work in most laser-based DED systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Benchmarking the PCMCI Causal Discovery Algorithm for Spatiotemporal Systems

Causal discovery algorithms construct hypothesized causal graphs that depict causal dependencies among variables in observational data. While powerful, the accuracy of these algorithms is highly sensitive to the underlying dynamics of the system in ways that have not been fully characterized in the literature. In this report, we benchmark the PCMCI causal discovery algorithm in its application to gridded spatiotemporal systems. Effectively computing grid-level causal graphs on large grids will enable analysis of the causal impacts of transient and mobile spatial phenomena in large systems, such as the Earth’s climate. We evaluate the performance of PCMCI with a set of structural causal models, using simulated spatial vector autoregressive processes in one- and two-dimensions. We develop computational and analytical tools for characterizing these processes and their associated causal graphs. Our findings suggest that direct application of PCMCI is not suitable for the analysis of dynamical spatiotemporal gridded systems, such as climatological data, without significant preprocessing and downscaling of the data. PCMCI requires unrealistic sample sizes to achieve acceptable performance on even modestly sized problems and suffers from a notable curse of dimensionality. This work suggests that, even under generous structural assumptions, significant additional algorithmic improvements are needed before causal discovery algorithms can be reliably applied to grid-level outputs of earth system models.

54 ENVIRONMENTAL SCIENCES↗