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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Accelerating Scientific Applications With SambaNova Reconfigurable Dataflow Architecture

Here, our exploratory work finds that the SambaNova Reconfigurable Dataflow Architecture (RDA) along with the SambaFlow software stack provides for an attractive system and solution to accelerate AI for science workloads. We have observed the efficacy of using the system with a diverse set of science applications and reasoned their suitability for performance gains over traditional hardware. As the Data-Scale system provides for a very large memory capacity, the system can be used to train models that typically do not fit in a GPU. The architecture also provides for deeper integration with upcoming supercomputers at the Argonne Leadership Computing Facility (ALCF), a US Department of Energy Office of Science user facility, to help advance science insights.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Outcomes of HPC User Support using a Science Gateway AI Assistant

High Performance Computing (HPC) is a vital resource for nuclear energy research, facilitating advanced simulations and complex modeling of the quantification and qualification of advanced reactor technology. However, a common gap in knowledge exists around utilizing HPC systems, particularly for nuclear energy researchers unfamiliar with specific HPC systems. A researcher may be well-versed in using one HPC system and understanding its associated processes. Yet, they might struggle when faced with a different HPC system and its unique processes. HPC support staff play a crucial role in addressing these challenges by providing educational resources and assisting users. However, they also face the challenge of maintaining these systems and ensuring they run efficiently for all users, a responsibility that can be challenging to scale effectively with the increasing demand and expansion of HPC systems. This paper addresses this knowledge gap with an artificial intelligence (AI) assistant that offers on-demand, site-specific HPC support for researchers. Idaho National Laboratory (INL) has deployed an AI assistant that is intended to supplement expert HPC support staff and assist nuclear energy researchers. This paper reports on a four-and-a-half-month study evaluating the integration of an AI assistant within a science gateway, with the goal of enhancing existing HPC support.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Emerging systems biology approaches in nanotoxicology: Towards a mechanism-based understanding of nanomaterial hazard and risk

Engineered nanomaterials are being developed for a variety of technological applications. However, the increasing use of nanomaterials in society has led to concerns about their potential adverse effects on human health and the environment. During the first decade of nanotoxicological research, the realization has emerged that effective risk assessment of the multitudes of new nanomaterials would benefit from a comprehensive understanding of their toxicological mechanisms, which is difficult to achieve with traditional, low-throughput, single end-point oriented approaches. Therefore, systems biology approaches are being progressively applied within the nano(eco)toxicological sciences. This novel paradigm implies that the study of biological systems should be integrative resulting in quantitative and predictive models of nanomaterial behaviour in a biological system. To this end, global ‘omics’ approaches with which to assess changes in genes, proteins, metabolites, etc. are deployed allowing for computational modelling of the biological effects of nanomaterials. Here, we highlight omics and systems biology studies in nanotoxicology, aiming towards the implementation of a systems nanotoxicology and mechanism-based risk assessment of nanomaterials. - Highlights: • Systems nanotoxicology is a multi-disciplinary approach to quantitative modelling. • Transcriptomics, proteomics and metabolomics remain the most common methods. • Global “omics” techniques should be coupled to computational modelling approaches. • The discovery of nano-specific toxicity pathways and biomarkers is a prioritized goal. • Overall, experimental nanosafety research must endeavour reproducibility and relevance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

iMicrobe: Tools and data-driven discovery platform for the microbiome sciences

Background: Scientists have amassed a wealth of microbiome datasets, making it possible to study microbes in biotic and abiotic systems on a population or planetary scale; however, this potential has not been fully realized given that the tools, datasets, and computation are available in diverse repositories and locations. To address this challenge, we developed iMicrobe.us, a community-driven microbiome data marketplace and tool exchange for users to integrate their own data and tools with those from the broader community. Findings: The iMicrobe platform brings together analysis tools and microbiome datasets by leveraging National Science Foundation–supported cyberinfrastructure and computing resources from CyVerse, Agave, and XSEDE. The primary purpose of iMicrobe is to provide users with a freely available, web-based platform to (1) maintain and share project data, metadata, and analysis products, (2) search for related public datasets, and (3) use and publish bioinformatics tools that run on highly scalable computing resources. Analysis tools are implemented in containers that encapsulate complex software dependencies and run on freely available XSEDE resources via the Agave API, which can retrieve datasets from the CyVerse Data Store or any web-accessible location (e.g., FTP, HTTP). Conclusions: iMicrobe promotes data integration, sharing, and community-driven tool development by making open source data and tools accessible to the research community in a web-based platform.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

SU-E-T-570: New Quality Assurance Method Using Motion Tracking for 6D Robotic Couches

Purpose: To accommodate geometrically accurate patient positioning, a robotic couch that is capable of 6-degrees of freedom has been introduced. However, conventional couch QA methods are not sufficient to enable the necessary accuracy of tests. Therefore, we have developed a camera based motion detection and geometry calibration system for couch QA. Methods: Employing a Visual-Tracking System (VTS, BonitaB10, Vicon, UK) which tracks infrared reflective(IR) markers, camera calibration was conducted using a 5.7 × 5.7 × 5.7 cm{sup 3} cube attached with IR markers at each corner. After positioning a robotic-couch at the origin with the cube on the table top, 3D coordinates of the cube’s eight corners were acquired by VTS in the VTS coordinate system. Next, positions in reference coordinates (roomcoordinates) were assigned using the known relation between each point. Finally, camera calibration was completed by finding a transformation matrix between VTS and reference coordinate systems and by applying a pseudo inverse matrix method. After the calibration, the accuracy of linear and rotational motions as well as couch sagging could be measured by analyzing the continuously acquired data of the cube while the couch moves to a designated position. Accuracy of the developed software was verified through comparison with measurement data when using a Laser tracker (FARO, Lake Mary, USA) for a robotic-couch installed for proton therapy. Results: VTS system could track couch motion accurately and measured position in room-coordinates. The VTS measurements and Laser tracker data agreed within 1% of difference for linear and rotational motions. Also because the program analyzes motion in 3-Dimension, it can compute couch sagging. Conclusion: Developed QA system provides submillimeter/ degree accuracy which fulfills the high-end couch QA. This work was supported by the National Research Foundation of Korea funded by Ministry of Science, ICT & Future Planning. (2013M2A2A7043507 and 2012M3A9B6055201)

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Non-Empirical and Self-Interaction Corrections for DFTB: Towards Accurate Quantum Simulations for Large Mesoscale Systems (Final Report)

This project was comprised of two complementary (but parallel) thrusts: (1) implementing massively-parallelized computing hardware (with new computational hardware that may replace GPUs) in the density functional tight binding (DFTB) approach and (2) developing new capabilities in DFTB to calculate the electronic structure and dynamics of large chemical systems. While classical molecular dynamics can handle hundreds of thousands of atoms, it cannot provide a first-principles based description of chemical systems at the quantum level. At the other extreme, conventional Kohn-Sham DFT methods can probe the true quantum mechanical nature of chemical systems; however, these methods cannot tackle the large sizes and length scales relevant to dynamics simulations of realistic systems. The DFTB formalism utilized in this project provides a viable approach for probing these large systems at a quantum mechanical level of detail. However, to utilize the DFTB approach for accurate calculations of electronic properties, it is crucial to incorporate quantum-based corrections in DFTB since exchange-correlation effects can still remain very strong in these large systems. At the same time, enhancing the computational efficiency of DFTB is also essential since optimal computational performance is required for addressing the large size scales associated with realistic chemical systems. As such, the new non-empirical corrections and computing hardware enhancements implemented in this project will enable accurate and computationally efficient approaches to directly probe electronic properties in these large, complex systems.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Trinity Era Storage

This report discusses the Trinity Storage system, its infrastructure, requirements, and erasure code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Two-phase flow measurements and observations in a cooling panel of the reactor cavity cooling system

The analysis of the flow behavior within a cooling panel of a scaled water-cooled reactor cavity cooling system has been performed supported by high-resolution measurements of the void fraction at the risers’ outlet. The results have shown a stable, symmetric distribution of the flow through the risers during subcooled boiling conditions, characterized by small, slow bubbles with average void fraction lower than 0.3 for all risers. As the temperature increased to saturation, flow distribution appeared strongly asymmetrical and unstable, with peaks of void fraction as high as 0.9. Large, faster bubbles were observed during these peaks, immediately followed by flow of subcooled liquid water. Flow stagnation and inversion has also been observed. The high resolution void fraction results, complemented by the measurements of the coolant flow rate and temperatures, not only have further described the behavior of the system under hypothetical accident conditions, but represent a unique set of data to support the validation of system-level codes, and more advanced computational tools.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Complexity and error potential of digital I and C - 135

Utilization of digital I and C for application in nuclear power plants led to a growing discussion on how to create methods for a probabilistic evaluation on such systems. Issues arise on the one hand due to a lack of commonly accepted models for quantitative evaluation of availability and reliability and on the other hand due to the integration of such models into the evaluation of reliability of an overall system. Nevertheless programmable and even more complex systems are implemented to satisfy growing functionality requirements. Therefore the question for a method to evaluate the reliability of systems based on software or on programmable logic became even more urgent. The approach described is based on the commonly accepted assumption that more complex designs are less reliable. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Warming Permafrost Model Intercomparision Project (WrPMIP): Pan-Arctic Perturbation Warming Simulations

Title: Warming Permafrost Model Intercomparision Project (WrPMIP): Pan-Arctic Perturbation Warming Simulations Description: WrPMIP Pan-Arctic simulations including historial baseline and two warming simulations. Models were perturbed similarly to known experimental warming trials that have been implemented across the Pan-Arctic over the last several decades. More information about the dataset can be found at the following links: https://warmingpermafrost.nau.edu/ The dataset is available at: https://esgf-node.ornl.gov/search/project=WrPMIP&mip_era=CMIP6&activity_id=WrPMIP

54 ENVIRONMENTAL SCIENCES↗
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↗
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 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↗