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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Power/energy use cases for high performance computing

Power and Energy have been identified as a first order challenge for future extreme scale high performance computing (HPC) systems. In practice the breakthroughs will need to be provided by the hardware vendors. But to make the best use of the solutions in an HPC environment, it will likely require periodic tuning by facility operators and software components. This document describes the actions and interactions needed to maximize power resources. It strives to cover the entire operational space in which an HPC system occupies. The descriptions are presented as formal use cases, as documented in the Unified Modeling Language Specification [1]. The document is intended to provide a common understanding to the HPC community of the necessary management and control capabilities. Assuming a common understanding can be achieved, the next step will be to develop a set of Application Programing Interfaces (APIs) to which hardware vendors and software developers could utilize to steer power consumption.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Chemical Looping Combustion Reactions and Systems

Chemical Looping Combustion (CLC) is one promising fuel-combustion technology, which can facilitate economic CO 2 capture in coal-fired power plants. It employs the oxidation/reduction characteristics of a metal, or oxygen carrier, and its oxide, the oxidizing gas (typically air) and the fuel source may be kept separate. This topical report discusses the results of four complementary efforts: (5.1) the development of process and economic models to optimize important design considerations, such as oxygen carrier circulation rate, temperature, residence time; (5.2) the development of high-performance simulation capabilities for fluidized beds and the collection, parameter identification, and preliminary verification/uncertainty quantification; (5.3) the exploration of operating characteristics in the laboratory-scale bubbling bed reactor, with a focus on the oxygen carrier performance, including reactivity, oxygen carrying capacity, attrition resistance, resistance to deactivation, cost and availability; and (5.4) the identification of kinetic data for copper-based oxygen carriers as well as the development and analysis of supported copper oxygen carrier material. Subtask 5.1 focused on the development of kinetic expressions for the Chemical Looping with Oxygen Uncoupling (CLOU) process and validating them with reported literature data. The kinetic expressions were incorporated into a process model for determination of reactor size and oxygen carrier circulation for the CLOU process using ASPEN PLUS. An ASPEN PLUS process model was also developed using literature data for the CLC process employing an iron-based oxygen carrier, and the results of the process model have been utilized to perform a relative economic comparison. In Subtask 5.2, the investigators studied the trade-off between modeling approaches and available simulations tools. They quantified uncertainty in the high-performance computing (HPC) simulation tools for CLC bed applications. Furthermore, they performed a sensitivity analysis for velocity, height and polydispersity and compared results against literature data for experimental studies of CLC beds with no reaction. Finally, they present an optimization space using simple non-reactive configurations. In Subtask 5.3, through a series of experimental studies, behavior of a variety of oxygen carriers with different loadings and manufacturing techniques was evaluated under both oxidizing and reducing conditions. The influences of temperature, degree of carrier conversion and thermodynamic driving force resulting from the difference between equilibrium and system O 2 partial pressures were evaluated through several experimental campaigns, and generalized models accounting for these influences were developed to describe oxidation and oxygen release. Conversion of three solid fuels with widely ranging reactivities was studied in a small fluidized bed system, and all but the least reactive fuel (petcoke) were rapidly converted by oxygen liberated from the CLOU carrier. Attrition propensity of a variety of carriers was also studied, and the carriers produced by freeze granulation or impregnation of preformed substrates displayed the lowest rates of attrition. Subtask 5.4 focused on gathering kinetic data for a copper-based oxygen carrier to assist with modeling of a functioning chemical looping reactor. The kinetics team was also responsible for the development and analysis of supported copper oxygen carrier material.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2014

Computational Design and Experimental Validation of New Thermal Barrier Systems

This project (10/01/2010-9/30/2014), “Computational Design and Experimental Validation of New Thermal Barrier Systems”, originates from Louisiana State University (LSU) Mechanical Engineering Department and Southern University (SU) Department of Computer Science. This project will directly support the technical goals specified in DE-FOA-0000248, Topic Area 3: Turbine Materials, by addressing key technologies needed to enable the development of advanced turbines and turbine-based systems that will operate safely and efficiently using coal-derived synthesis gases. In this project, the focus is to develop and implement novel molecular dynamics method to improve the efficiency of simulation on novel TBC materials; perform high performance computing (HPC) on complex TBC structures to screen the most promising TBC compositions; perform material characterizations and oxidation/corrosion tests; and demonstrate our new thermal barrier coating (TBC) systems experimentally under integrated gasification combined cycle (IGCC) environments.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Computational Design and Experimental Validation of New Thermal Barrier Systems

This project (10/01/2010-9/30/2013), “Computational Design and Experimental Validation of New Thermal Barrier Systems”, originates from Louisiana State University (LSU) Mechanical Engineering Department and Southern University (SU) Department of Computer Science. This project will directly support the technical goals specified in DE-FOA-0000248, Topic Area 3: Turbine Materials, by addressing key technologies needed to enable the development of advanced turbines and turbine-based systems that will operate safely and efficiently using coal-derived synthesis gases. We will develop and implement novel molecular dynamics method to improve the efficiency of simulation on novel TBC materials; perform high performance computing (HPC) on complex TBC structures to screen the most promising TBC compositions; perform material characterizations and oxidation/corrosion tests; and demonstrate our new thermal barrier coating (TBC) systems experimentally under integrated gasification combined cycle (IGCC) environments. The durability of the coating will be examined using the proposed Durability Test Rig.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2014

Improving Memory Error Handling Using Linux

As supercomputers continue to get faster and more powerful in the future, they will also have more nodes. If nothing is done, then the amount of memory in supercomputer clusters will soon grow large enough that memory failures will be unmanageable to deal with by manually replacing memory DIMMs. "Improving Memory Error Handling Using Linux" is a process oriented method to solve this problem by using the Linux kernel to disable (offline) faulty memory pages containing bad addresses, preventing them from being used again by a process. The process of offlining memory pages simplifies error handling and results in reducing both hardware and manpower costs required to run Los Alamos National Laboratory (LANL) clusters. This process will be necessary for the future of supercomputing to allow the development of exascale computers. It will not be feasible without memory error handling to manually replace the number of DIMMs that will fail daily on a machine consisting of 32-128 petabytes of memory. Testing reveals the process of offlining memory pages works and is relatively simple to use. As more and more testing is conducted, the entire process will be automated within the high-performance computing (HPC) monitoring software, Zenoss, at LANL.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Performance Assessment Modeling and Sensitivity Analyses of Generic Disposal System Concepts

The Used Fuel Disposition Campaign (UFDC) of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE) is conducting research and development (R&D) on generic deep geologic disposal systems (i.e., repositories) for high-activity nuclear wastes (i.e., used nuclear fuel (UNF) and high-level radioactive waste (HLW)) that exist today or that could be generated in future fuel cycles. This report describes specific activities in FY2014 toward the development of an enhanced generic disposal system modeling and analysis capability that utilizes high performance computing (HPC) environments to simulate important multi-physics phenomena and couplings associated with the potential behavior of a geologic repository for UNF and HLW.

Sevougian, S. David↗
DOE OSTI2014

Sub-Second Parallel State Estimation

This report describes the performance of Pacific Northwest National Laboratory (PNNL) sub-second parallel state estimation (PSE) tool using the utility data from the Bonneville Power Administrative (BPA) and discusses the benefits of the fast computational speed for power system applications. The test data were provided by BPA. They are two-days’ worth of hourly snapshots that include power system data and measurement sets in a commercial tool format. These data are extracted out from the commercial tool box and fed into the PSE tool. With the help of advanced solvers, the PSE tool is able to solve each BPA hourly state estimation problem within one second, which is more than 10 times faster than today’s commercial tool. This improved computational performance can help increase the reliability value of state estimation in many aspects: (1) the shorter the time required for execution of state estimation, the more time remains for operators to take appropriate actions, and/or to apply automatic or manual corrective control actions. This increases the chances of arresting or mitigating the impact of cascading failures; (2) the SE can be executed multiple times within time allowance. Therefore, the robustness of SE can be enhanced by repeating the execution of the SE with adaptive adjustments, including removing bad data and/or adjusting different initial conditions to compute a better estimate within the same time as a traditional state estimator’s single estimate. There are other benefits with the sub-second SE, such as that the PSE results can potentially be used in local and/or wide-area automatic corrective control actions that are currently dependent on raw measurements to minimize the impact of bad measurements, and provides opportunities to enhance the power grid reliability and efficiency. PSE also can enable other advanced tools that rely on SE outputs and could be used to further improve operators’ actions and automated controls to mitigate effects of severe events on the grid. The power grid continues to grow and the number of measurements is increasing at an accelerated rate due to the variety of smart grid devices being introduced. A parallel state estimation implementation will have better performance than traditional, sequential state estimation by utilizing the power of high performance computing (HPC). This increased performance positions parallel state estimators as valuable tools for operating the increasingly more complex power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

High Performance Computing and Storage Requirements for Nuclear Physics: Target 2017

In April 2014, NERSC, ASCR, and the DOE Office of Nuclear Physics (NP) held a review to characterize high performance computing (HPC) and storage requirements for NP research through 2017. This review is the 12th in a series of reviews held by NERSC and Office of Science program offices that began in 2009. It is the second for NP, and the final in the second round of reviews that covered the six Office of Science program offices. This report is the result of that review

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Where Big Data and Prediction Meet

Our ability to assemble and analyze massive data sets, often referred to under the title of “big data”, is an increasingly important tool for shaping national policy. This in turn has introduced issues from privacy concerns to cyber security. But as IBM’s John Kelly emphasized in the last Innovation, making sense of the vast arrays of data will require radically new computing tools. In the past, technologies and tools for analysis of big data were viewed as quite different from the traditional realm of high performance computing (HPC) with its huge models of phenomena such as global climate or supporting the nuclear test moratorium. Looking ahead, this will change with very positive benefits for both worlds. Societal issues such as global security, economic planning and genetic analysis demand increased understanding that goes beyond existing data analysis and reduction. The modeling world often produces simulations that are complex compositions of mathematical models and experimental data. This has resulted in outstanding successes such as the annual assessment of the state of the US nuclear weapons stockpile without underground nuclear testing. Ironically, while there were historically many test conducted, this body of data provides only modest insight into the underlying physics of the system. A great deal of emphasis was thus placed on the level of confidence we can develop for the predictions. As data analytics and simulation come together, there is a growing need to assess the confidence levels in both data being gathered and the complex models used to make predictions. An example of this is assuring the security or optimizing the performance of critical infrastructure systems such as the power grid. If one wants to understand the vulnerabilities of the system or impacts of predicted threats, full scales tests of the grid against threat scenarios are unlikely. Preventive measures would need to be predicated on well-defined margins of confidence in order to take mitigating actions that could have wide ranging impacts. There is a rich opportunity for interaction and exchange between the HPC simulation and data analytics communities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Multi-meson systems in lattice QCD / Many-body QCD

Nuclear physics entails the study of the properties and interactions of hadrons, such as the proton and neutron, and atomic nuclei and it is central to our understanding of our world at the smallest scales. The underlying basis for nuclear physics is provided by the Standard Model of particle physics which describes how matter interacts through the strong, electromagnetic and weak (electroweak) forces. This theory was developed in the 1970s and provides an extremely successful description of our world at the most fundamental level to which it has been probed. The Standard Model has been, and continues to be, subject to stringent tests at particle accelerators around the world, so far passing without blemish. However, at the relatively low energies that are relevant for nuclear physics, calculations involving the strong interaction, governed by the equations of Quantum Chromodynamics (QCD), are enormously challenging, and to date, the only systematic way to perform them is numerically, using a framework known as lattice QCD (LQCD). In this approach, one discretizes space-time and numerically solves the equations of QCD on a space-time lattice; for realistic calculations, this requires highly optimized algorithms and cutting-edge high performance computing (HPC) resources. Progress over the project period is discussed in detail in the following subsections

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Havery Mudd 2014-2015 Computer Science Conduit Clinic. Final Report

Conduit, a new open-source library developed at Lawrence Livermore National Laboratories, provides a C++ application programming interface (API) to describe and access scientific data. Conduit’s primary use is for inmemory data exchange in high performance computing (HPC) applications. Our team tested and improved Conduit to make it more appealing to potential adopters in the HPC community. We extended Conduit’s capabilities by prototyping four libraries: one for parallel communication using MPI, one for I/O functionality, one for aggregating performance data, and one for data visualization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Evaluating Application Resilience with XRay

The rising count and shrinking feature size of transistors within modern computers is making them increasingly vulnerable to various types of soft faults. This problem is especially acute in high-performance computing (HPC) systems used for scientific computing, because these systems include many thousands of compute cores and nodes, all of which may be utilized in a single large-scale run. The increasing vulnerability of HPC applications to errors induced by soft faults is motivating extensive work on techniques to make these applications more resilient to such faults, ranging from generic techniques such as replication or checkpoint/restart to algorithm-specific error detection and tolerance techniques. Effective use of such techniques requires a detailed understanding of how a given application is affected by soft faults to ensure that (i) efforts to improve application resilience are spent in the code regions most vulnerable to faults and (ii) the appropriate resilience technique is applied to each code region. This paper presents XRay, a tool to view the application vulnerability to soft errors, and illustrates how XRay can be used in the context of a representative application. In addition to providing actionable insights into application behavior XRay automatically selects the number of fault injection experiments required to provide an informative view of application behavior, ensuring that the information is statistically well-grounded without performing unnecessary experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Fast Dynamic Simulation-Based Small Signal Stability Assessment and Control

Power grid planning and operation decisions are made based on simulation of the dynamic behavior of the system. Enabling substantial energy savings while increasing the reliability of the aging North American power grid through improved utilization of existing transmission assets hinges on the adoption of wide-area measurement systems (WAMS) for power system stabilization. However, adoption of WAMS alone will not suffice if the power system is to reach its full entitlement in stability and reliability. It is necessary to enhance predictability with "faster than real-time" dynamic simulations that will enable the dynamic stability margins, proactive real-time control, and improve grid resiliency to fast time-scale phenomena such as cascading network failures. Present-day dynamic simulations are performed only during offline planning studies, considering only worst case conditions such as summer peak, winter peak days, etc. With widespread deployment of renewable generation, controllable loads, energy storage devices and plug-in hybrid electric vehicles expected in the near future and greater integration of cyber infrastructure (communications, computation and control), monitoring and controlling the dynamic performance of the grid in real-time would become increasingly important. The state-of-the-art dynamic simulation tools have limited computational speed and are not suitable for real-time applications, given the large set of contingency conditions to be evaluated. These tools are optimized for best performance of single-processor computers, but the simulation is still several times slower than real-time due to its computational complexity. With recent significant advances in numerical methods and computational hardware, the expectations have been rising towards more efficient and faster techniques to be implemented in power system simulators. This is a natural expectation, given that the core solution algorithms of most commercial simulators were developed decades ago, when High Performance Computing (HPC) resources were not commonly available.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

A Report on Simulation-Driven Reliability and Failure Analysis of Large-Scale Storage Systems

High-performance computing (HPC) storage systems provide data availability and reliability using various hardware and software fault tolerance techniques. Usually, reliability and availability are calculated at the subsystem or component level using limited metrics such as, mean time to failure (MTTF) or mean time to data loss (MTTDL). This often means settling on simple and disconnected failure models (such as exponential failure rate) to achieve tractable and close-formed solutions. However, such models have been shown to be insufficient in assessing end-to-end storage system reliability and availability. We propose a generic simulation framework aimed at analyzing the reliability and availability of storage systems at scale, and investigating what-if scenarios. The framework is designed for an end-to-end storage system, accommodating the various components and subsystems, their interconnections, failure patterns and propagation, and performs dependency analysis to capture a wide-range of failure cases. We evaluate the framework against a large-scale storage system that is in production and analyze its failure projections toward and beyond the end of lifecycle. We also examine the potential operational impact by studying how different types of components affect the overall system reliability and availability, and present the preliminary results

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Rapid development of an ice sheet climate application using the components-based approach

In the third year of a five-year jointly funded project, Sandia’s Albany/FELIX simulation code for ice sheet dynamics is being developed to be run in two modes: (1) as a stand-alone model for scientific investigations, and (2) as part of the land-ice component of coupled climate simulations in the Department of Energy’s (DOE’s) earth system model. The land-ice component simulates changes to the Greenland and Antarctic ice sheets, including their contributions to global sea-level rise. Using high performance computing (HPC), Sandia has recently completed a controlled mesh convergence study to compute the rate at which the Greenland ice sheet is flowing. The study demonstrated that the HPC code is capable of working accurately, efficiently, and reliably on larger scales (over 1 billion unknowns). The study also identified, for the first time, the minimum number of vertical levels needed in the mesh to maintain accuracy

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Performance Assessment Institute-NV

The National Supercomputing Center for Energy and the Environment’s intention is to purchase a multi-purpose computer cluster in support of the Performance Assessment Institute (PA Institute). The PA Institute will serve as a research consortium located in Las Vegas Nevada with membership that includes: national laboratories, universities, industry partners, and domestic and international governments. This center will provide a one-of-a-kind centralized facility for the accumulation of information for use by Institutions of Higher Learning, the U.S. Government, and Regulatory Agencies and approved users. This initiative will enhance and extend High Performance Computing (HPC) resources in Nevada to support critical national and international needs in "scientific confirmation". The PA Institute will be promoted as the leading Modeling, Learning and Research Center worldwide. The program proposes to utilize the existing supercomputing capabilities and alliances of the University of Nevada Las Vegas as a base, and to extend these resource and capabilities through a collaborative relationship with its membership. The PA Institute will provide an academic setting for interactive sharing, learning, mentoring and monitoring of multi-disciplinary performance assessment and performance confirmation information. The role of the PA Institute is to facilitate research, knowledge-increase, and knowledge-sharing among users.

Lombardo, Joesph↗
DOE OSTI2015

Advanced Simulation and Computing Co-Design Strategy

This ASC Co-design Strategy lays out the full continuum and components of the co-design process, based on what we have experienced thus far and what we wish to do more in the future to meet the program’s mission of providing high performance computing (HPC) and simulation capabilities for NNSA to carry out its stockpile stewardship responsibility.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Application of Generic Disposal System Models

This report describes specific GDSA activities in fiscal year 2015 (FY2015) toward the development of the enhanced disposal system modeling and analysis capability for geologic disposal of nuclear waste. The GDSA framework employs the PFLOTRAN thermal-hydrologic-chemical multi-physics code (Hammond et al., 2011) and the Dakota uncertainty sampling and propagation code (Adams et al., 2013). Each code is designed for massively-parallel processing in a high-performance computing (HPC) environment. Multi-physics representations in PFLOTRAN are used to simulate various coupled processes including heat flow, fluid flow, waste dissolution, radionuclide release, radionuclide decay and ingrowth, precipitation and dissolution of secondary phases, and radionuclide transport through the engineered barriers and natural geologic barriers to a well location in an overlying or underlying aquifer. Dakota is used to generate sets of representative realizations and to analyze parameter sensitivity.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗