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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

New Generator Technology

New generator technology project is driven by the need to be able to remotely deploy generator technology where it is needed, when it is needed. Both the military and aid programs that provide assistance after disasters could use the ability to deploy energy generation that fits the needs of the situation. Currently, pre-specified generators are deployed, sometime more than half way around the world to provide electricity. Through our Phase-I to Phase III DARPA grant, we will provide a mechanism where a 3d print station and raw materials could be shipped to a deployment site and remotely deployed personnel. These remote personnel can collaborate with engineers at a home location where 3d print plans can be optimized for the remote purpose. The plans can then be sent electronically to the remote location for printing, much like NASA sent the plans for a socket wrench to the International Space Station for printing in . If multiple generators need to be deployed at different remote locations, within miles of each other the printer rig can be moved to print the generators where they are needed. 3d printing is growing in the field of manufacturing. 3d printing has matured to the point where many types of materials are now available for many types of manufacturing. Both magnetic and electrically conductive material materials have recently been developed which can now lead to 3d printing of engines and generators. Our project will provide a successful printer rig that can be remotely deployed, to print a generator design in the field as well as provide a process for deploying the printed generator as well. This Systems Engineering Management Plan(SEMP) will provide the planning required for a Phase I DARPA grant that may also include goals for Phase II and Phase II grants. The SEMP provides a proposed project schedule, references, system engineering processes, specialty engineering system deployment and product support sections. Each section will state how our company will provide the necessary services to make this project succeed.

3D printing, manufacturing, generator technology, ↗
DOE OSTI2026

Level-2 Milestone 9009: Flux and Rabbit Capabilities on El Capitan

This document is the milestone delivery report for the ASC 2025 L2 milestone (See Table 1) for advanced I/O capabilities for El Capitan via Flux Workload Manager support and the new I/O hardware designed for El Capitan, the Rabbit Storage System. In this document we describe the design of the Rabbit Storage System and how it is managed by Flux. We evaluate the performance and usability of Rabbit using ARES, IOR, and an AI inference workload. Overall, we find that Rabbit shows good scalability, especially in node-local storage configurations, and is more scalable than the global Lustre parallel file system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Resource Aware Intelligent Network Services (RAINS) Final Technical Report

The Resource Aware Intelligent Network Services (RAINS) project conducted research and developed technologies in the area of cyber infrastructure resource modeling and computation. The goal of this work was to provide a foundation to enable intelligent, software defined services which spanned the network AND the resources which connect to the network. A Multi-Resource Service Plane (MRSP) was defined, which allows resource owners/managers to locate and place themselves from a topology and service availability perspective within the dynamic networked cyberinfrastructure ecosystem. The MRSP enables the presentation of integrated topology views and computation results which can include resources across the spectrum of compute, storage, and networks. The RAINS project developed MSRP includes the following key components: i) Multi-Resource Service (MRS) Ontology/Multi-Resource Markup Language (MRML), ii) Resource Computation Engine (RCE), iii) Modular Driver Framework (to allow integration of a variety of external resources). The MRS/MRML is a general and extensible modeling framework that allows for resource owners to model, or describe, a wide variety of resource types. All resources are described using three categories of elements: Resources, Services, and Relationships between the elements. This modeling framework defines a common method for the transformation of cyber infrastructure resources into data in the form of MRML models. In order to realize this infrastructure datification, the RAINS project developed a model based computation system, i.e. “RAINS Computation Engine (RCE)”. The RCE has the ability to ingest, process, integrate, and compute based on automatically generated MRML models. The RCE interacts with the resources thru system drivers which are specific to the type of external network or resource controller. The RAINS project developed a modular and pluggable driver system which facilities a variety of resource controllers to automatically generate, maintain, and distribute MRML based resource descriptions. Once all of the resource topologies are absorbed by the RCE, a connected graph of the full distributed system topology is constructed, which forms the basis for computation and workflow processing. The RCE includes a Modular Computation Element (MCE) framework which allows for tailoring of the computation process to the specific set of resources under control, and the services desired. The input and output of an MCE are both model data based on MRS/MRML ontology and schema. Some of the RAINS project accomplishments include: Development of general and extensible multi-resource modeling framework; Design of a Resource Computation Engine (RCE) system which includes the following key capabilities; Absorb a variety of multi-resource model types and build integrated models; Novel architecture which uses model based communications across the full stack for all Flexible provision of abstract or intent based user facing interfaces; Workflow processing based on model descriptions; Release of the RCE as an open source software; Deployment of RCE in the University of Maryland/Mid-Atlantic Crossroad ScienceDMZ in prototype mode with a plan under way to transition to production; Deployment at the Argonne National Laboratory DTN Facility in prototype mode; Selection of RCE by the DOE SENSE (SDN for End-to-end Networked Science at the Exascale) project as the basis for their orchestration service.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SU-F-T-218: Validation of An In-Vivo Proton Range Verification Method for Reducing the Risk of Permanent Alopecia in the Treatment of Pediatric Medulloblastoma

Purpose: The clinical commissioning of a workflow for pre-treatment range verification/adjustment for the head treatment of pediatric medulloblastoma patients, including dose monitoring during treatment. Methods: An array of Si-diodes (DIODES Incorporated) is placed on the patient skin on the opposite side to the beam entrance. A “scout” SOBP beam, with a longer beam range to cover the diodes in its plateau, is delivered; the measured signal is analyzed and the extracted water equivalent path lengths (WEPL) are compared to the expected values, revealing if a range correction is needed. Diodes stay in place during treatment to measure dose. The workflow was tested in solid water and head phantoms and validated against independent WEPL measurements. Both measured WEPL and skin doses were compared to computed values from the TPS (XiO); a Markus chamber was used for reference dose measurements. Results: The WEPL accuracy of the method was verified by comparing it with the dose extinction method. It resulted, for both solid water and head phantom, in the sub-millimeter range, with a deviation less than 1% to the value extracted from the TPS. The accuracy of dose measurements in the fall-off part of the dose profile was validated against the Markus chamber. The entire range verification workflow was successfully tested for the mock-treatment of head phantom with the standard delivery of 90 cGy per field per fraction. The WEPL measurement revealed no need for range correction. The dose measurements agreed to better than 4% with the prescription dose. The robustness of the method and workflow, including detector array, hardware set and software functions, was successfully stress-tested with multiple repetitions. Conclusion: The performance of the in-vivo range verification system and related workflow meet the clinical requirements in terms of the needed WEPL accuracy for pretreatment range verification with acceptable dose to the patient.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Biosurveillance Data Stream Framework: A Novel Approach to Characterization and Evaluation

Multiple data sources are used in a variety of biosurveillance systems. With the advent of new technologies, globalization, high performance computing, and "big data" opportunities, there are seemingly unlimited potential data streams that could be useful in biosurveillance. Data streams have not been universally defined in either the literature or by specific biosurveillance systems. Furthermore, the definitions and framework that we have developed enable a characterization methodology that facilitates understanding of data streams and can be universally applicable for use in evaluating and understanding a wide range of biosurveillance activities- filling a gap recognized in both the public health and biosurveillance communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Evading strength and ductility trade-off in an inverse nacre structured magnesium matrix nanocomposite

Mimicking nacre structure is an often-used strategy for developing materials which combine high strength and high toughness. Here, a novel strategy, named inverse nacre structure, is proposed where elongated and curled soft constituents are embedded in a matrix of hard constituent to form an ordered brick-and-mortar arrangement. This strategy is demonstrated in a particle reinforced metal matrix composite, using pure Mg as the soft phase and SiC nanoparticle reinforced Mg as the hard phase. In this work, the resulting nanocomposite yields high strength, and especially high tensile elongation which is five times that of the homogeneous counterpart. The superior comprehensive strengthening-toughening effect originates from the tailored inverse nacre structure which enables a stable microcrack-multiplication process by sufficiently promoting strain hardening so as to avoid any significant decrease in post-ultimate tensile strength. This strategy, while demonstrated here for the specific case of particle reinforced Mg, is not restricted to any particular material system but constitutes a generic pathway for the development of high-performance materials for engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Graph-EAM: An Interpretable and Efficient Graph Neural Network Potential Framework

The development of deep learning interatomic potentials has enabled efficient and accurate computations in quantum chemistry and materials science, circumventing computationally expensive ab initio calculations. However, the huge number of learnable parameters in deep learning models and their complex architectures hinder physical interpretability and affect the robustness of the derived potential. In this work, we propose graph-EAM, a lightweight graph neural network (GNN) inspired by the empirical embedded atom method to model the interatomic potential of single-element structures. Four material systems: platinum, niobium, silicon, and amorphous-carbon, for which quantum simulation data sets are publicly available, are examined to demonstrate that graph-EAM can achieve high energy and force prediction accuracy-comparable or better than existing state-of-the-art machine learning models-with much fewer parameters. It is also shown that the explicit inclusion of the angular information via three-body atomic density increases the prediction accuracy. In conclusion, the accuracy and efficiency of potentials obtained from graph-EAM can help accelerate the molecular dynamics simulation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Multiplex base editing to convert $\mathrm{TAG}$ into $\mathrm{TAA}$ codons in the human genome

Whole-genome recoding has been shown to enable nonstandard amino acids, biocontainment and viral resistance in bacteria. Here we take the first steps to extend this to human cells demonstrating exceptional base editing to convert TAG to TAA for 33 essential genes via a single transfection, and examine base-editing genome-wide (observing ~40 C-to-T off-target events in essential gene exons). We also introduce GRIT, a computational tool for recoding. This demonstrates the feasibility of recoding, and highly multiplex editing in mammalian cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Analytical evaluation of thermal conductance and heat capacities of one-dimensional material systems

We theoretically predict some thermal properties versus temperature dependence of one dimensional (1D) material nanowire systems. A known method is used to provide an efficient and reliable analytical procedure for wide temperature range. Predicted formulas are expressed in terms of Bloch-Grüneisen functions and Debye functions. Computing results has proved that the expressions are in excellent agreement with the results reported in the literature even if it is in very low dimension limits of nanowire systems. Therefore the calculation method is a fully predictive approach to calculate thermal conductivity and heat capacities of nanowire material systems.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A Big Data Analytics Framework for HPC Log Data: Three Case Studies Using the Titan Supercomputer Log

Reliability, availability and serviceability (RAS) logs of high performance computing (HPC) resources, when closely investigated in spatial and temporal dimensions, can provide invaluable information regarding system status, performance, and resource utilization. These data are often generated from multiple logging systems and sensors that cover many components of the system. The analysis of these data for finding persistent temporal and spatial insights faces two main difficulties: the volume of RAS logs makes manual inspection difficult and the unstructured nature and unique properties of log data produced by each subsystem adds another dimension of difficulty in identifying implicit correlation among recorded events. To address these issues, we recently developed a multi-user Big Data analytics framework for HPC log data at Oak Ridge National Laboratory (ORNL). This paper introduces three in-progress data analytics projects that leverage this framework to assess system status, mine event patterns, and study correlations between user applications and system events. We describe the motivation of each project and detail their workflows using three years of log data collected from ORNL's Titan supercomputer.

Park, Byung↗
DOE OSTI2017

Optimal Transmission Line Switching under Geomagnetic Disturbances

Recently, there have been increasing concerns about how geomagnetic disturbances (GMDs) impact electrical power systems. Geomagnetically-induced currents (GICs) can saturate transformers, induce hot spot heating and increase reactive power losses. These effects can potentially cause catastrophic damage to transformers and severely impact the ability of a power system to deliver power. To address this problem, we develop a model of GIC impacts to power systems that includes 1) GIC thermal capacity of transformers as a function of normal Alternating Current (AC) and 2) reactive power losses as a function of GIC. We also use this model to derive an optimization problem that protects power systems from GIC impacts through line switching, generator dispatch, and load shedding. We then employ state-of-the-art convex relaxations of AC power flow equations to lower bound the objective. We demonstrate the approach on a modified RTS96 system and UIUC 150-bus system and show that line switching is an effective means to mitigate GIC impacts. We also provide a sensitivity analysis of decisions with respect to GMD direction.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

SU-E-T-435: Development and Commissioning of a Complete System for In-Vivo Dosimetry and Range Verification in Proton Therapy

Purpose: In-vivo dose and beam range verification in proton therapy could play significant roles in proton treatment validation and improvements. Invivo beam range verification, in particular, could enable new treatment techniques one of which, for example, could be the use of anterior fields for prostate treatment instead of opposed lateral fields as in current practice. We have developed and commissioned an integrated system with hardware, software and workflow protocols, to provide a complete solution, simultaneously for both in-vivo dosimetry and range verification for proton therapy. Methods: The system uses a matrix of diodes, up to 12 in total, but separable into three groups for flexibility in application. A special amplifier was developed to capture extremely small signals from very low proton beam current. The software was developed within iMagX, a general platform for image processing in radiation therapy applications. The range determination exploits the inherent relationship between the internal range modulation clock of the proton therapy system and the radiological depth at the point of measurement. The commissioning of the system, for in-vivo dosimetry and for range verification was separately conducted using anthropomorphic phantom. EBT films and TLDs were used for dose comparisons and range scan of the beam distal fall-off was used as ground truth for range verification. Results: For in-vivo dose measurement, the results were in agreement with TLD and EBT films and were within 3% from treatment planning calculations. For range verification, a precision of 0.5mm is achieved in homogeneous phantoms, and a precision of 2mm for anthropomorphic pelvic phantom, except at points with significant range mixing. Conclusion: We completed the commissioning of our system for in-vivo dosimetry and range verification in proton therapy. The results suggest that the system is ready for clinical trials on patient.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

TH-AB-202-02: Real-Time Verification and Error Detection for MLC Tracking Deliveries Using An Electronic Portal Imaging Device

Purpose: The added complexity of the real-time adaptive multi-leaf collimator (MLC) tracking increases the likelihood of undetected MLC delivery errors. In this work we develop and test a system for real-time delivery verification and error detection for MLC tracking radiotherapy using an electronic portal imaging device (EPID). Methods: The delivery verification system relies on acquisition and real-time analysis of transit EPID image frames acquired at 8.41 fps. In-house software was developed to extract the MLC positions from each image frame. Three comparison metrics were used to verify the MLC positions in real-time: (1) field size, (2) field location and, (3) field shape. The delivery verification system was tested for 8 VMAT MLC tracking deliveries (4 prostate and 4 lung) where real patient target motion was reproduced using a Hexamotion motion stage and a Calypso system. Sensitivity and detection delay was quantified for various types of MLC and system errors. Results: For both the prostate and lung test deliveries the MLC-defined field size was measured with an accuracy of 1.25 cm{sup 2} (1 SD). The field location was measured with an accuracy of 0.6 mm and 0.8 mm (1 SD) for lung and prostate respectively. Field location errors (i.e. tracking in wrong direction) with a magnitude of 3 mm were detected within 0.4 s of occurrence in the X direction and 0.8 s in the Y direction. Systematic MLC gap errors were detected as small as 3 mm. The method was not found to be sensitive to random MLC errors and individual MLC calibration errors up to 5 mm. Conclusion: EPID imaging may be used for independent real-time verification of MLC trajectories during MLC tracking deliveries. Thresholds have been determined for error detection and the system has been shown to be sensitive to a range of delivery errors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Physics-Informed Learning for Predictive Multi-Scale Modeling of Water Cycle and Extreme Events

Climate and earth system models have limited skill in predicting water cycle and associated extremes such as intense rain- and wind-producing storms and resulting hazards across all timescales. Water cycle predictions are inherently limited by the predictability of the chaotic system, but large potential for improving predictions remains untapped due to limited use of data-model integration to improve predictive modeling. This white paper proposes a hybrid data-physics paradigm based on physics-informed neural networks (PINNs) to improve the Energy Exascale Earth System Model (E3SM). In particular, we aim to predict and quantify uncertainties of water cycle processes and low probability high impact events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effect of loading path on grain misorientation and geometrically necessary dislocation density in polycrystalline aluminum under reciprocating shear

Solid phase processing (SPP) is a promising alloy fabrication technique to produce fine and homogeneous grain structures for high-performance alloys. However, there is very limited modeling capability to understand and predict the grain refinement during SPP. In this work, the crystal plasticity theory was used to study elastic-plastic deformation in polycrystalline aluminums under large shear deformation. Two approaches, kernel averaged misorientation (KAM) and grain reference orientation deviation (GROD), were used to assess the grain misorientations. The geometrically necessary dislocation (GND) density was computed with the plastic strain rate. The deformation simulations were carried out under two loading conditions to investigate the effect of loading paths on the evolutions of grain misorientation and GND density. The results show that the regions with high misorientation and GND density first appear near grain boundaries. These regions then extend toward interior grains. The loading path affects dislocation system activation and dislocation recovery, hence dislocation evolution and misorientation. In conclusion, both two- and three-dimensional simulations showed that the spatial and temporal evolutions of GROD, KAM, and GND density in are closely correlated, which indicates they all can be used as criteria of grain refinement or recrystallization.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Direct Visualization of Charge Migration in Bilayer Tantalum Oxide Films by Multimodal Imaging

Inspired by biological neuromorphic computing, artificial neural networks based on crossbar arrays of bilayer tantalum oxide memristors have shown to be promising alternatives to conventional complementary metal-oxide-semiconductor (CMOS) architectures. In order to understand the driving mechanism in these oxide systems, tantalum oxide films are resistively switched by conductive atomic force microscopy (C-AFM), and subsequently imaged by kelvin probe force microscopy (KPFM) and spatially resolved time-of-flight secondary ion mass spectrometry (ToF-SIMS). These workflows enable induction and analysis of the resistive switching mechanism as well as control over the resistively switched region of the film. In this work it is shown that the resistive switching mechanism is driven by both current and electric field effects. Reversible oxygen motion is enabled by applying low (<1 V) electric fields, while high electric fields generate irreversible breakdown of the material (>1 V). Fully understanding oxygen motion and electrical effects in bilayer oxide memristor systems is a fundamental step toward the adoption of memristors as a neuromorphic computing technology.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Fractal nature structure reconstruction method in designing microstructure properties

Highlights: • Structure and material’s properties, within the material’s consolidation triad: Synthesis – Structure – Properties. • The grain prediction methods is based on the measurements of the solid Euclidean geometric fractal characteristics. • The intergranular contacts inside the BaTiO3 -ceramic are responsible for intergranular capacities. • The inner complex geometry of intergrain contacts imposes fractal correction factor for permeability. - Abstract: In the process of predicting materials properties, it is necessary to predict microstructures. This is important for ceramic materials, for the purpose of miniaturization and for a higher level of integration. Although the method of material structure reconstruction is for the first time used on BaTiO{sub 3}-ceramics by these authors, it can also be used for silicate, refractory and other ceramics, and, for any powder-based material. The reconstruction is based on the grain perimeter fractal analysis and the Richardson method. The main contribution of this paper is establishing the relationship between the electronic properties of BaTiO{sub 3}-ceramics and its microstructural fractal nature. Similar relations can be used for any ceramics or even any materials. The samples consolidation includes both powder pressing (cold sintering phase) and sintering in a furnace (hot sintering phase). The fractal nature characterization has a very important role from the powder phase up to the final microstructure, through which structures it directly impacts electro-physical and other ceramics properties. Thereby, the new possibilities in the microstructure characterization applications are directly introduced to an engineering system, providing the new solutions related to computer aided support. This creates new industrial production and application possibilities, especially in the process of ceramics material consolidation, now based on microstructural properties, which is providing a basis for “fractal electronics’’ development.

36 MATERIALS SCIENCE↗