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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Physics-Dynamics Coupling in Weather, Climate, and Earth System Models: Challenges and Recent Progress

Geophysical models of the atmosphere and ocean invariably involve parameterizations. These represent two distinct areas: a) Subgrid processes which the model cannot (yet) resolve, due to its discrete resolution, and b) sources in the equation, due to radiation for example. Hence coupling between these physics parameterizations and the resolved fluid dynamics and also between the dynamics of the different fluids in the system (air and water) is necessary. This coupling is an important aspect of geophysical models. However, often model development is strictly segregated into either physics or dynamics. Hence, this area has many more unanswered questions than in-depth understanding. Furthermore, recent developments in the design of dynamical cores (significant increase of resolution, move to non-hydrostatic equation sets etc), extended process physics (prognostic micro physics, 3D turbulence, non-vertical radiation etc) and predicted future changes of the computational infrastructure (Exascale with its need for task parallelism, data locality and asynchronous time stepping for example) is adding even more complexity and new questions.

Gross, Markus↗
DOE OSTI2015

Design, Testing and Modeling of the Direct Reactor Auxiliary Cooling System for AHTRs

The principal objective of this research is to test and model the heat transfer performance and reliability of the Direct Reactor Auxiliary Cooling System (DRACS) for AHTRs. In addition, component testing of fluidic diodes is to be performed to examine the performance and viability of several existing fluidic diode designs. An extensive database related to the thermal performance of the heat exchangers involved will be obtained, which will be used to benchmark a computer code for the DRACS design and to evaluate and improve, if needed, existing heat transfer models of interest. The database will also be valuable for assessing the viability of the DRACS concept and benchmarking any related computer codes in the future. The experience of making a liquid fluoride salt test facility available, with lessons learned, will greatly benefit the development of the Fluoride Salt-cooled High-temperature Reactor (FHR) and eventually the AHTR programs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

UPR/Mayaguez High Energy Physics

This year the University of Puerto Rico at Mayaguez (UPRM) High Energy Physics (HEP) group continued with the ongoing research program outlined in the grant proposal. The program is centered on the Compact Muon Solenoid (CMS) experiment at the proton-proton (pp) collisions at the Large Hadron Collider (LHC) at CERN in Geneva, Switzerland. The main research focus is on data analysis and on the preparation for the High Luminosity (HL) LHC or experiment detector upgrade. The physics data analysis included Higgs Doublet Search and measurement of the (1) Λ 0 b branching fraction, (2) B meson mass, and (3) hyperon θ - b lifetime. The detector upgrade included work on the preparations for the Forward Pixel (FPIX) detector Silicon Sensor Testing in a production run at Fermilab. In addition, the group has taken responsibilities on the Software Release through our former research associate Dr. Eric Brownson who acted until last December as a Level Two Offline Manager for the CMS Upgrade. In support of the CMS data analysis activities carried out locally, the UPRM group has built and maintains an excellent Tier3 analysis center in Mayaguez. This allowed us to analyze large data samples and to continue the development of algorithms for the upgrade tracking robustness we started several years ago, and we plan to resume in the near future. This project involves computer simulation of the radiation damage to be suffered at the higher luminosities of the upgraded LHC. This year we continued to serve as a source of outstanding students for the field of high energy physics. Three of our graduate students finished their MS work in May, 2014, Their theses research were on data analysis of heavy quark b-physics. All of them are currently enrolled at Ph.D. physics program across the nation. One of them (Hector Moreno) at New Mexico University (Hector Moreno), one at University of New Hampshire (Sandra Santiesteban) and one at University of Puerto Rico-Rio Piedras (Carlos Malca). The students H. Moreno and C. Malca has been directly supervised by Dr. Mendez and S. Santiesteban supervised by Dr. Ramirez. During the last 13 years, our group have graduated 23 MS students on experimental High Energy Physics data analysis and applied hardware techniques. Most of the students have been supported by DOE grants, included this grant. Since 2001, Dr. Mendez have directly supervised eleven students, Dr. Ramirez three students and the former PI (Dr. Lopez) nine students. These theses work are fully documented in the group web page (http://charma.uprm.edu). The High Energy Physics group at Mayaguez is small and presently consists of three Physics faculty members, the Senior Investigators Dr. Hector Mendez (Professor) and Dr. Juan Eduardo Ramirez (Professor), and Dr. Sudhir Malik who was just hired in July 2014. Dr. Ramirez is in charge of the UPRM Tier-3 computing and will be building the network bandwidth infrastructure for the campus, while Dr. Mendez will continues his effort in finishing the heavy quark physics data analysis and moving to work on SUSY analysis for the 2015 data. Our last grant application in 2012 was awarded only for 2013-2014. As a result our postdoc position was lost last month of March. Since then, we have hired Dr. Malik as a new faculty in order to reinforce the group and to continue our efforts with the CMS experiment. Our plan is to hire another junior faculty in the next two years to strengthen the HEP group even further. Dr. Mendez continues with QuarkNet activities involving an ever larger group of high school physics teachers from all around Puerto Rico.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Fault Tolerance Assistant (FTA): An Exception Handling Programming Model for MPI Applications

Future high-performance computing systems may face frequent failures with their rapid increase in scale and complexity. Resilience to faults has become a major challenge for large-scale applications running on supercomputers, which demands fault tolerance support for prevalent MPI applications. Among failure scenarios, process failures are one of the most severe issues as they usually lead to termination of applications. However, the widely used MPI implementations do not provide mechanisms for fault tolerance. We propose FTA-MPI (Fault Tolerance Assistant MPI), a programming model that provides support for failure detection, failure notification and recovery. Specifically, FTA-MPI exploits a try/catch model that enables failure localization and transparent recovery of process failures in MPI applications. We demonstrate FTA-MPI with synthetic applications and a molecular dynamics code CoMD, and show that FTA-MPI provides high programmability for users and enables convenient and flexible recovery of process failures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

PIPER: Performance Insights for Programmers and Exascale Runtimes

During the lifetime of the project, the PIPER at the University of Utah worked in collaboration with the team from the partner institutions to establish a set of software tools for analyzing and improving the performance parallel computing tools. These activities complement and complete the work performed by the other X-Stack 2 projects with the definition of a common data models and computing infrastructures, which have been a central element in the targeted performance analysis pipeline and new programming models. The University of Utah team have focused mainly on developing data analysis and visualization systems to facilitate exploration, comparison and evaluation of the behavior and performance of complex algorithms in modern HPC infrastructures. This is involved several demonstrations of the performance achieved and presentation of the results in a way that facilitates the users understand bottlenecks and ways to overcome them. One major focus of the University of Utah activities has been the analysis of the performance characteristics of Fat-Tree and Dragonfly topology networks. The work involved the development of practical visualization systems especially in collaboration with the team at LLNL, and published several papers and gave invited talks at prestigious venues such as the Salishan Conference on High-Speed Computing or the International Conference on High Performance Computing, Data, and Analytics. In addition, the university of Utah team has advanced the core activities on analyzing the performance characteristics of I/O and other data movement systems and their practical use for scaling Uintah and other simulation codes poised for use in the exascale computing environments of the future.

42 ENGINEERING↗
DOE OSTI2021

Supporting Co-Design of Extreme-Scale Systems with In Situ Visual Analysis of Event-Driven Simulations (Final Report)

Extreme-scale systems for compute- and data-centric science are pushing the boundaries of system architectures in order to achieve ambitious goals in terms of computing capability, resilience, and power efficiency. Future systems necessitate emerging designs that incorporate new technologies, system organizations, and computer science techniques, and these changes are not yet well understood. Discrete-event-driven simulation of computing system architectures and subsystems has emerged as a productive and cost-effective means to evaluating potential designs, along with capabilities for executing these simulations of extreme-scale systems. However, techniques for analyzing the behavior of these simulations have not kept pace with our ability to perform the simulations, preventing us from extracting the most value from this promising approach. The objective of this project is to support the codesign of extreme-scale system architectures for compute and data-centric science through research and development of novel methods for analysis and visualization of large-scale event-driven simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A hierarchical evaluation framework for assessing climate simulations relevant to the energy-water-land nexus (Final Report)

The overarching goal was to construct a hierarchy of new and well-tested metrics and analysis tools that support both fundamental and use-inspired research. Motivating this goal was a convergence of needs from climate scientists and stakeholders alike for a systematic, robust framework of model evaluation and diagnosis to provide scientific insights, inform model development, support best practices for the use of climate model outputs, and facilitate communication of climate information in the evolving landscapes of multi-model, multi-resolution, and large ensemble simulations that generate terabytes of data for any single climate run. Steps toward attaining these goals benefited from expertise and established capability of the project team, which included leadership of the North American Regional Climate Change Assessment Program (NARCCAP) and the Coordinated Regional Downscaling Experiment (CORDEX), development of hierarchical model evaluation approaches, and successful research in the analysis and diagnosis of climate model skill, as well as the understanding and modeling of regional climate processes in North America. As part of the overarching goal, the project worked to disseminate a suite of methodologies, algorithms, and software components that the wider community can employ to advance climate science and applications. With rigorous demonstration, the evaluation framework and the mix of standard and high risk / high reward approaches helped form the basis for future development of a computationally enabled user-friendly system for community use.

17 WIND ENERGY↗
DOE OSTI2026

Transition Metal Taggants in UO 2 from First Principles

The incorporation of transition metals into nuclear fuel has gained attention both to improve fuel properties and as a possible nuclear forensics tool. Recent experimental studies by Ulrich et al. and Adorno Lopes et al. have investigated Ni and Fe as candidate transition metal dopants for potential nuclear forensics purposes and found that there is minimal alteration to key UO 2 fuel properties. In the present work, we performed density functional theory (DFT) investigations into possible defect structures for Ni and Fe incorporation. The dynamic stability of these defect structures was validated by calculating the phonon density of states. We found that transition metal incorporation likely occurs via substitution at U sites in the fluorite crystal structure with a nearby O vacancy for charge-balancing, which agrees with experimentally proposed structures. Additionally, this defect structure does not cause long-range alterations to the crystal parameters—an important consideration for use as a nuclear fuel taggant. Future needed work involves computational investigation of additional defect concentrations using larger supercells, additional transition metal charge states, and thermal effects. Such investigations can be carried forward into sintering models for a more complete understanding of the suitability of Ni and Fe as fuel taggants.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Operator Insights and Usability Evaluation of Machine Learning Assistance for Power Grid Contingency Analysis

Introducing machine learning (ML) assistance into any established process comes with adoption barriers, including entrenched procedures, technological and human readiness levels, human-machine trust, and work culture resistance to change. These barriers are even greater in critical operations such as operating a national or regional power grid, in which both regulatory frameworks and the importance of maintaining reliability levels causes additional resistance to the adoption of new computational support. Developers of future systems and job aides must consider not only technical aspects, but also whether new systems are usable by power system operators. This work presents the methodology and results of a study to evaluate the usability and readiness of a prototype recommender system for power grid contingency analysis. We explore operator cognitive load and evaluate operator performance when solving a collection of scenarios both with and without recommender assistance. We also examine operator trust in the system. We report insights gained on the readiness of the system using a collection of evaluation techniques.

Human-Machine Teaming, Power Systems, usability ev↗
DOE OSTI2014

Improving the Performance of the Extreme-scale Simulator

Investigating the performance of parallel applications at scale on future high-performance computing (HPC) architectures and the performance impact of different architecture choices is an important component of HPC hardware/software co-design. The Extreme-scale Simulator (xSim) is a simulation-based toolkit for investigating the performance of parallel applications at scale. xSim scales to millions of simulated Message Passing Interface (MPI) processes. The overhead introduced by a simulation tool is an important performance and productivity aspect. This paper documents two improvements to xSim: (1) a new deadlock resolution protocol to reduce the parallel discrete event simulation management overhead and (2) a new simulated MPI message matching algorithm to reduce the oversubscription management overhead. The results clearly show a significant performance improvement, such as by reducing the simulation overhead for running the NAS Parallel Benchmark suite inside the simulator from 1,020\% to 238% for the conjugate gradient (CG) benchmark and from 102% to 0% for the embarrassingly parallel (EP) and benchmark, as well as, from 37,511% to 13,808% for CG and from 3,332% to 204% for EP with accurate process failure simulation.

Engelmann, Christian↗
DOE OSTI2016

Taking a fresh look at boiling heat transfer on the road to improved nuclear economics and efficiency

Here, in the effort to reinvigorate innovation in the way we design, build, and operate the nuclear power generating stations of today and tomorrow, nothing can be taken for granted. Not even the seemingly familiar physics of boiling water. The Consortium for the Advanced Simulation of Light Water Reactors, or CASL, is focused on the deployment of advanced modeling and simulation capabilities to enable the nuclear industry to reduce uncertainties in the prediction of multi-physics phenomena and continue to improve the performance of today’s Light Water Reactors and their fuel. An important part of the CASL mission is the development of a next generation thermal hydraulics simulation capability, integrating the history of engineering models based on experimental experience with the computing technology of the future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Virtual Facility at Fermilab: Infrastructure and Services Expand to Public Clouds

In preparation for its new Virtual Facility Project, Fermilab has launched a program of work to determine the requirements for running a computation facility on-site, in public clouds, or a combination of both. This program builds on the work we have done to successfully run experimental workflows of 1000-VM scale both on an on-site private cloud and on Amazon AWS. To do this at scale we deployed dynamically launched and discovered caching services on the cloud. We are now testing the deployment of more complicated services on Amazon AWS using native load balancing and auto scaling features they provide. The Virtual Facility Project will design and develop a facility including infrastructure and services that can live on the site of Fermilab, off-site, or a combination of both. We expect to need this capacity to meet the peak computing requirements in the future. The Virtual Facility is intended to provision resources on the public cloud on behalf of the facility as a whole instead of having each experiment or Virtual Organization do it on their own. We will describe the policy aspects of a distributed Virtual Facility, the requirements, and plans to make a detailed comparison of the relative cost of the public and private clouds. Furthermore, this talk will present the details of the technical mechanisms we have developed to date, and the plans currently taking shape for a Virtual Facility at Fermilab.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2019

Understanding the Impact of Dynamic Power Capping on Application Progress

Electrical power has become an important design constraint in high-performance computing (HPC) systems. On future HPC machines, power is likely to be a budgeted resource and thus managed dynamically. Power management software needs to reliably measure application performance at runtime in order to respond effectively to changes in application behavior. Execution time tells us little about how the science in the application is progressing toward an application-defined end goal. To the best of our knowledge, no study has defined or categorized online application progress in the context of power management. Based on semi-structured interviews with HPC application-specialists, we define an online notion of progress—an application-specific metric that can be monitored at runtime to provide a sense of the rate at which application science is being performed. Using instrumentation, we characterize and categorize the progress of various production scientific applications and benchmarks. We propose a model of the impact of dynamic power capping on application progress. By experimental evaluation, we show that our model accurately captures the general behavior of the progress of different classes of applications under a power cap. We believe that such a model is an important first step toward the design of more dynamic power management policies for HPC systems.

application progress↗
DOE OSTI2012

High-Performance Computing for Advanced Smart Grid Applications

The power grid is becoming far more complex as a result of the grid evolution meeting an information revolution. Due to the penetration of smart grid technologies, the grid is evolving as an unprecedented speed and the information infrastructure is fundamentally improved with a large number of smart meters and sensors that produce several orders of magnitude larger amounts of data. How to pull data in, perform analysis, and put information out in a real-time manner is a fundamental challenge in smart grid operation and planning. The future power grid requires high performance computing to be one of the foundational technologies in developing the algorithms and tools for the significantly increased complexity. New techniques and computational capabilities are required to meet the demands for higher reliability and better asset utilization, including advanced algorithms and computing hardware for large-scale modeling, simulation, and analysis. This chapter summarizes the computational challenges in smart grid and the need for high performance computing, and present examples of how high performance computing might be used for future smart grid operation and planning.

computational challenges↗
DOE OSTI2022

Quantum computing and preconditioners for hydrological linear systems

Modeling hydrological fracture networks is a hallmark challenge in computational earth sciences. Accurately predicting critical features of fracture systems, e.g. percolation, can require solving large linear systems far beyond current or future high performance capabilities. Quantum computers can theoretically bypass the memory and speed constraints faced by classical approaches, however several technical issues must first be addressed. Chief amongst these difficulties is that such systems are often ill-conditioned, i.e. small changes in the system can produce large changes in the solution, which can slow down the performance of linear solving algorithms. We test several existing quantum techniques to improve the condition number, but find they are insufficient. We then introduce the inverse Laplacian preconditioner, which improves the scaling of the condition number of the system from O(N) to O($\sqrt{N}$) and admits a quantum implementation. These results are a critical first step in developing a quantum solver for fracture systems, both advancing the state of hydrological modeling and providing a novel real-world application for quantum linear systems algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery

Future scientific discoveries will rely on flexible ecosystems that incorporate modern scientific instruments, high performance computing resources, parallel distributed data storage, and performant networks across multiple, independent facilities. In addition to connecting physical resources, such an ecosystem presents many challenges in logistics and accessibility, especially in orchestrating computations and experiments that span across leadership computing systems and experimental instruments. Past efforts have typically been application-specific or limited to interfaces for computing resources. This paper proposes a general framework for integrating computation resources and instrument operations, addressing challenges in code development/execution, data staging and collection, software stack, control mechanisms, resource authorization and governance, and hardware integration. We also describe a demonstration use case wherein a Bayesian optimization algorithm running on an edge computing resource guides a scanning probe microscope to autonomously and intelligently characterize a material sample. This science edge ecosystem framework will provide a blueprint for federating multi-institutional, disparate resources and orchestrating scientific workflows across them to enable next-generation discoveries.

Somnath, Suhas↗
DOE OSTI2015

Lateral organization, bilayer asymmetry, and inter-leaflet coupling of biological membranes

Understanding of cell membrane organization has evolved significantly from the classic fluid mosaic model. It is now recognized that biological membranes are highly organized structures, with differences in lipid compositions between inner and outer leaflets and in lateral structures within the bilayer plane, known as lipid rafts. These organizing principles are important for protein localization and function as well as cellular signaling. However, the mechanisms and biophysical basis of lipid raft formation, structure, dynamics and function are not clearly understood. One key question, which we focus on in this review, is how lateral organization and leaflet compositional asymmetry are coupled. Detailed information elucidating this question has been sparse because of the small size and transient nature of rafts and the experimental challenges in constructing asymmetric bilayers. Resolving this mystery will require advances in both experimentation and modeling. We discuss here the preparation of model systems along with experimental and computational approaches that have been applied in efforts to address this key question in membrane biology. Furthermore, we seek to place recent and future advances in experimental and computational techniques in context, providing insight into in-plane and transverse organization of biological membranes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Reverse Computation for Rollback-based Fault Tolerance in Large Parallel Systems

Reverse computation is presented here as an important future direction in addressing the challenge of fault tolerant execution on very large cluster platforms for parallel computing. As the scale of parallel jobs increases, traditional checkpointing approaches suffer scalability problems ranging from computational slowdowns to high congestion at the persistent stores for checkpoints. Reverse computation can overcome such problems and is also better suited for parallel computing on newer architectures with smaller, cheaper or energy-efficient memories and file systems. Initial evidence for the feasibility of reverse computation in large systems is presented with detailed performance data from a particle simulation scaling to 65,536 processor cores and 950 accelerators (GPUs). Reverse computation is observed to deliver very large gains relative to checkpointing schemes when nodes rely on their host processors/memory to tolerate faults at their accelerators. A comparison between reverse computation and checkpointing with measurements such as cache miss ratios, TLB misses and memory usage indicates that reverse computation is hard to ignore as a future alternative to be pursued in emerging architectures.

Perumalla, Kalyan S↗