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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Distributed-memory lattice H-matrix factorization

We parallelize the LU factorization of a hierarchical low-rank matrix (H-matrix) on a distributed-memory computer. This is much more difficult than the H-matrix-vector multiplication due to the dataflow of the factorization, and it is much harder than the parallelization of a dense matrix factorization due to the irregular hierarchical block structure of the matrix. Block low-rank (BLR) format gets rid of the hierarchy and simplifies the parallelization, often increasing concurrency. However, this comes at a price of losing the near-linear complexity of the H-matrix factorization. In this work, we propose to factorize the matrix using a “lattice H-matrix” format that generalizes the BLR format by storing each of the blocks (both diagonals and off-diagonals) in the H-matrix format. These blocks stored in the H-matrix format are referred to as lattices. Thus, this lattice format aims to combine the parallel scalability of BLR factorization with the near-linear complexity of H-matrix factorization. We first compare factorization performances using the H-matrix, BLR, and lattice H-matrix formats under various conditions on a shared-memory computer. Our performance results show that the lattice format has storage and computational complexities similar to those of the H-matrix format, and hence a much lower cost of factorization than BLR. In conclusion, we then compare the BLR and lattice H-matrix factorization on distributed-memory computers. Our performance results demonstrate that compared with BLR, the lattice format with the lower cost of factorization may lead to faster factorization on the distributed-memory computer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Measurement and modeling of electric field and space-charge distributions in obstructed helium discharge

Axial and radial variations of electric field have been measured in dielectric shielded 0.025 m diameter parallel plate electrode with 0.0065 m gap for 1.6 mA, 2260 V helium dc discharge at 1.75 Torr. The axial and radial electric field profiles have been measured from the Stark splitting of 2{sup 1}S→11 {sup 1}P transition through collision induced fluorescence from 4{sup 3}D→2{sup 3}P. The electric field values showed a strong radial variation peaking to 500 kV/m near the cathode radial boundary, and decreasing to about 100 kV/m near the anode edge, suggesting the formation of an obstructed discharge for this low nd condition, where n is the gas density and d is the gap distance. The off-axis Stark spectra showed that the electric field vector deviates from normal to the cathode surface which permits longer path electron trajectories in the inter-electrode gap. Also, the on-axis electric field gradient was very small and off-axis electric field gradient was large indicating a radially non-uniform current density. In order to obtain information about the space charge distribution in this obstructed discharge, it was modeled using the 2-d axisymmetric Poisson solver with the COMSOL finite element modeling program. The best fit to the measured electric field distribution was obtained with a space charge variation of ρ(r) = ρ{sub 0}(r/r{sub 0}){sup 3}, where ρ(r) is the local space charge density, ρ{sub 0} = 6 × 10{sup −3} Coulomb/m{sup 3}, r is the local radial value, and r{sub 0} is the radius of the electrode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

MO-F-CAMPUS-I-04: Characterization of Fan Beam Coded Aperture Coherent Scatter Spectral Imaging Methods for Differentiation of Normal and Neoplastic Breast Structures

Purpose: This study intends to characterize the spectral and spatial resolution limits of various fan beam geometries for differentiation of normal and neoplastic breast structures via coded aperture coherent scatter spectral imaging techniques. In previous studies, pencil beam raster scanning methods using coherent scatter computed tomography and selected volume tomography have yielded excellent results for tumor discrimination. However, these methods don’t readily conform to clinical constraints; primarily prolonged scan times and excessive dose to the patient. Here, we refine a fan beam coded aperture coherent scatter imaging system to characterize the tradeoffs between dose, scan time and image quality for breast tumor discrimination. Methods: An X-ray tube (125kVp, 400mAs) illuminated the sample with collimated fan beams of varying widths (3mm to 25mm). Scatter data was collected via two linear-array energy-sensitive detectors oriented parallel and perpendicular to the beam plane. An iterative reconstruction algorithm yields images of the sample’s spatial distribution and respective spectral data for each location. To model in-vivo tumor analysis, surgically resected breast tumor samples were used in conjunction with lard, which has a form factor comparable to adipose (fat). Results: Quantitative analysis with current setup geometry indicated optimal performance for beams up to 10mm wide, with wider beams producing poorer spatial resolution. Scan time for a fixed volume was reduced by a factor of 6 when scanned with a 10mm fan beam compared to a 1.5mm pencil beam. Conclusion: The study demonstrates the utility of fan beam coherent scatter spectral imaging for differentiation of normal and neoplastic breast tissues has successfully reduced dose and scan times whilst sufficiently preserving spectral and spatial resolution. Future work to alter the coded aperture and detector geometries could potentially allow the use of even wider fans, thereby making coded aperture coherent scatter imaging a clinically viable method for breast cancer detection. United States Department of Homeland Security; Duke University Medical Center - Department of Radiology; Carl E Ravin Advanced Imaging Laboratories; Duke University Medical Physics Graduate Program.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Integration Of PanDA Workload Management System With Supercomputers for ATLAS and Data Intensive Science

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System for managing the workflow for all data processing on over 150 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. While PanDA currently uses more than 250,000 cores with a peak performance of 0.3 petaFLOPS, LHC data taking runs require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF), MIRA supercomputer at Argonne Leadership Computing Facilities (ALCF), Supercomputer at the National Research Center Kurchatov Institute , IT4 in Ostrava and others). Current approach utilizes modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single threaded workloads in parallel on LCFs multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms for ALICE and ATLAS experiments and it is in full production for the ATLAS experiment since September 2015. We will present our current accomplishments with running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.

Data-intensive science↗
DOE OSTI2017

Evaluating the Performance Envelope of Axial Flow HEPA Filter Designs - 17466

Nuclear grade high efficiency particulate air (HEPA) filters are routinely employed as the final control element in confinement ventilation systems. Approximately 6000 nuclear grade HEPA filters are purchased each year for use in the Department of Energy National Nuclear Security Administration (DOE/NNSA) complex. The traditional HEPA filter utilizes a pleated filter medium of fibrous glass that has been produced in a manner analogous to manufacturing paper. Containment ventilation systems are designed to condition the air-stream (temperature, relative humidity, moisture, particle size distribution of aerosols, and aerosol concentration) to levels and conditions that fibrous glass HEPA filters can handle. Axial Flow filters can be purchased with physical separators or embossed medium to maintain proper pleat geometry. Separator-less designs use media embossed with a corrugation pattern to retain pleat geometry. At least some versions of the separator-less filter packs have demonstrated unexpected and rapid failure under slightly elevated temperature and humidity conditions. The effects of age on HEPA filter performance have been a concern for at least two decades. A combination of physical evaluation of aged filter media and a review of filter failure records resulted in Appendix C of the Nuclear Air Cleaning Handbook (NACH), Determination of HEPA Filter Life. Mississippi State University is conducting studies to more clearly identify the operating envelope of separator and separator-less designs of ASME AG-1 Section FC axial flow HEPA filters under a set of generic design basis conditions. A parallel study is also being conducted to evaluate the effects of age on fibrous glass HEPA filters. Activities described in this paper have been conducted under Institute for Clean Energy Technology (ICET's) NQA-1 nuclear quality assurance program approved by DOE-EM. Testing meets the requirements of EM Quality Assurance Program (QAP) EM-QA-001, Rev. 1, June 11, 2012 that includes the applicable requirements of NQA-1-2008/2009a and DOE Order 414.1D. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

Evaluating quantitative 3-D image analysis as a design tool for low enriched uranium fuel compacts for the transient reactor test facility: A preliminary study

In this study, 3-D image analysis when combined with a non-destructive examination technique such as X-ray computed tomography (CT) provides a highly quantitative tool for the investigation of a material’s structure. In this investigation 3-D image analysis and X-ray CT were combined to analyze the microstructure of a preliminary subsized fuel compact for the Transient Reactor Test Facility’s low enriched uranium conversion program to assess the feasibility of the combined techniques for use in the optimization of the fuel compact fabrication process. The quantitative image analysis focused on determining the size and spatial distribution of the surrogate fuel particles and the size, shape, and orientation of voids within the compact. Additionally, the maximum effect of microstructural features on heat transfer through the carbonaceous matrix of the preliminary compact was estimated. The surrogate fuel particles occupied 0.8% of the compact by volume with a log-normal distribution of particle sizes with a mean diameter of 39 μm and a standard deviation of 16 μm. Roughly 39% of the particles had a diameter greater than the specified maximum particle size of 44 μm suggesting that the particles agglomerate during fabrication. The local volume fraction of particles also varies significantly within the compact although uniformities appear to be evenly dispersed throughout the analysed volume. The voids produced during fabrication were on average plate-like in nature with their major axis oriented perpendicular to the compaction direction of the compact. Finally, the microstructure, mainly the large preferentially oriented voids, may cause a small degree of anisotropy in the thermal diffusivity within the compact. α∥/α⊥, the ratio of thermal diffusivities parallel to and perpendicular to the compaction direction are expected to be no less than 0.95 with an upper bound of 1.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Data Analytics for Electrical Distribution Systems with Micro PMUs (GMLC 1.4.9 Technical Report)

This report describes how electrical utilities with residential, industrial, commercial and government customers make decisions using Data Analytics (DA) applications and discusses how OpenFMB was leveraged to share that data among disparate types of devices for DA. OpenFMB is a data standard developed by utilities for distributed communication and control of power system assets. Here we explored how OpenFMB can be used for sharing analytics and what those analytics could be for a set of representative grid devices. A review of DA applications performed by electrical utilities and customers is presented. An overview of how the testbed we used was built and configured is summarized. Several experiments which were carried out to explore the capabilities of OpenFMB alongside other data sharing mechanisms for gathering sensor measurements and sharing analytics is also discussed. And finally a comparison of OpenFMB and LBNL’s SPARK framework is summarized. Today’s electrical utilities focus on monitoring the real-time customer consumptions, offering new real-time tariff models based on customer usage habits (rewards and punishments), providing energy peak during peak load times (plan energy generation and distribution), improving the load management for transformers and power lines, and controlling the energy and grid resources efficiently. On the other hand, the DA applications for residential customers are based on modifying the customer electricity usage habit to save money, making accurate and timely decisions for electrical billing. However, the DA applications for industrial, commercial and government customers focus on creating efficient programs to improve the environmental condition (reducing CO₂ emission), developing better load forecasting for industrial and/or commercial activities. In this project, a testbed was built to explore how the OpenFMB framework can be used to distribute data among various types of representative grid edge devices. Micro PMUs (Phasor Measurement Unit) were used to collect and transmit data to an OpenPDC server alongside relays with a framework configured with a system using OpenFMB to collect and transmit data. The testbed was composed of a physical asset based on a 60 Hz AC radial power system constructed using SI-GRID components. The power system consisted of a 3-phase 14 volts line-to-ground (24 volts line-to-line) power source, three 3-phase line emulators, a programmable resistive load bank, two smart relays, two micro PMUs, and a (SCADA) and Phasor Data Concentrator (PDC) computer. This testbed configuration allowed us to perform breaker operation tests collecting data from the micro PMUs and from the relays’ sensors. During the micro PMU breaker operation tests we collected the measured and estimated fundamental voltages, currents, frequency as well as the total true, reactive and apparent power. The displacement power factor from two micro PMUs located in parallel power lines was also used. The software steps for the implementation of the Synchrophasor system are explained in detail in this report. The setting (1-2-3) and data collection (4-5) phases were performed with a free download open source software. In the setting phase, the micro PMUs were set (1), the data stream for each micro PMU was validated, and the connection and configuration files were created (2). The PDC computer was set using the connection and configuration files of the micro PMUs (3). In the data collection phase, the binary data from the micro PMUs was collected (4), and the binary data files of the micro PMUs was converted to analyze the test results (5). OpenFMB was configured to use protocol translators to read Modbus and transform the reading into the OpenFMB data model to be read for DA applications.Our experiments showed that by leveraging the OpenFMB data model and the micro PMUs together we could obtain better situational awareness of network faults, which in some cases could lead to failures in the system and would be less perceivable otherwise. For example, in one experiment the fundamental RMS current angle, and the fundamental displacement power factor (estimated by the ratio between the measured real and apparent total power) had a disturbance at the micro PMU connected to the beginning of the parallel power line because the breaker was opened without the operators or SCADA system’s knowledge, and no current was available. Based on the breaker state scenarios and micro PMU locations, the DA applications using the current angle and displacement power factor from the micro PMUs should be studied in detail to avoid a non-desired measurement that could affect the decision from the DA. Also, the sample rates for PMU, Relay and micro PMU devices were compared. The DA application improved the control and operation between the electrical utilities and their customers (residential, industrial, transportation, commercial and government). The higher the sample rate, the better the quality of the measurement for DA estimations.

42 ENGINEERING↗
DOE OSTI2024

Multiphysics Demonstration of Temperature-Driven Assembly Bowing in SFRs using MOOSE-Based Codes

Core bowing is an important passive safety mechanism in liquid metal cooled fast reactors. When the core restraint system is properly designed, temperature and flux gradients influence assemblies in the core to bow into less reactive configurations during accident scenarios, resulting in negative reactivity feedback. Prediction of core bowing involves complex interplay of radiation transport, impacts of fluid flow and heat transfer on duct temperature, and mechanical responses to the induced temperature and flux gradients. Under the U.S. Department of Energy Office of Nuclear Energy’s Advanced Modeling and Simulation (NEAMS) Program [1], an integrated multiphysics approach is being developed to model the core bowing phenomena in liquid metal-cooled fast reactors with the Multiphysics Object Oriented Simulation Environment (MOOSE) [2]. In this methodology, the MOOSE-based reactor physics code Griffin [3] will solve the neutron transport equation and determine the power distribution. With the detailed power distribution from Griffin, the subchannel analysis codes MOOSE-Subchannel [4] and Pronghorn [5] are utilized to calculate the assembly temperature distribution. MOOSE’s Solid Mechanics [6] and Contact [7] Modules are leveraged to calculate the thermal expansion and duct bowing displacement with the duct wall temperature from thermal hydraulics calculation. In this work, an initial one-way coupling demonstration of the integrated multiphysics approach has been performed on a seven-assembly problem based on the sodium-cooled fast reactor ABR-1000 design [8]. The neutronics calculation with Griffin is not yet involved in the current simulation. MOOSE-Subchannel and Pronghorn evaluate fluid and solid temperature based on a fixed power distribution. In addition, one-way coupling is utilized in this coupled calculation, via Pronghorn passing the duct temperature data to the MOOSE Solid Mechanics calculation. An assessment of the Solid Mechanics module was performed in parallel to verify duct bowing behavior with duct-to-duct contact phenomenon [9]. The displacement from MOOSE Solid Mechanics is not yet transferred back and utilized in the Pronghorn and MOOSE-Subchannel calculation. This model will be available on the National Reactor Innovation Center (NRIC) Virtual Test Bed (VTB) repository [10]. Future stages of this work will involve solving problems of increasing complexity as well as adding more physics (e.g. reactor physics) to the integrated workflow to reach the end goal of modeling the core bowing phenomenon with an integrated multiphysics workflow.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

FINAL REPORT - Development of High Pressure Hydrogen Storage Tank for Storage and Gaseous Truck Delivery

The “Development of High Pressure Hydrogen Storage Tanks for Storage and Gaseous Truck Delivery” project [DE-FG36-08GO18062] was initiated on 01 July 2008. Hexagon Lincoln (then Lincoln Composites) received grant funding from the U.S. Department of Energy to support the design and development of an improved bulk hauling and storage solution for hydrogen in terms of cost, safety, weight and volumetric efficiency. The development of this capability required parallel development and qualification of large all-composites pressure vessels, a custom ISO container to transport and store said tanks, and performance of trade studies to identify optimal operating pressure for the system. Qualification of the 250 bar TITAN® module was completed in 2009 with supervision from the American Bureau of Shipping [ABS], and the equipment has been used internationally for bulk transportation of fuel gases since 2010. Phase 1 of the project was successfully completed in 2012 with the issuance of USDOT SP 14951, the special permit authorizing the manufacture, marking, sale and use of TITAN® Mobile Pipeline® equipment in the United States. The introduction of tube trailers with light weight composite tankage has meant that 2 to 3 times as much gaseous fuel can be transported with each trip. This increased hauling efficiency offers dramatically reduced operating costs and has enabled a profitable business model for over-the-road compressed natural gas delivery. The economic drivers of this business opportunity vary from country to country and region to region, but in many places gas distribution companies have realized profitable operations. Additional testing was performed in 2015 to characterize hydrogen-specific operating protocols for use of TITAN® systems in CHG service at 250 bar. This program demonstrated that existing compression and decompression methodologies can efficiently and safely fill and unload lightweight bulk hauling systems. Hexagon Lincoln and U.S. DOE agreed to continue into Phase 2 of the project without pursuing the development of higher pressure capabilities as originally planned. At 250 bar, development of equipment for hydrogen transport is supported by strong activity in the adjacent natural gas transportation sector. Trade studies performed since 2011 indicate optimization of hauling efficiency and system cost for hydrogen transport at about 350 bar (5076 psi). However, due to reduced efficiency of compression of natural gas above 250 bar, 350 bar operation is not an attractive option for natural gas transportation. The CHG market is not developed at this time, and it is difficult to forecast the arrival of significant revenues. On the investment side, the cost to fully qualify a large tank module at 350 bar is estimated at $3MM to $5MM. There is insufficient CHG market definition to support a stand-alone business case for this investment without near term revenue in the adjacent CNG transportation market. Therefore development of a 350 bar TITAN® system was deferred and not pursued under this project. Hexagon Lincoln continues to support the development of tankage and equipment for operation at 350 bar and above; with 700 bar vehicle tanks and 950 bar tanks for ground storage applications. Phase 2 activities were focused on reducing system cost, increasing system capacity, increasing system safety and characterization of polymer material performance specific to hydrogen pressure vessel usage. With the successful launch of TITAN® modules and trailers in natural gas transportation, over 600 units have been produced through the end of 2016, resulting in improved purchasing power for raw materials and manufactured components. This has allowed Hexagon Lincoln to approach the current project goals for system cost. At $590/kg of compressed hydrogen delivered, the system cost of the baseline TITAN® module is below the project’s 2015 target of $730/kg H2 delivered, and very close to the project’s 2020 target of $575/kg H2 delivered. [Based on product pricing in 1Q2017.] Emphasis was placed on configuration of larger capacity systems within the vehicle weights and dimensions allowed on federal and state highways in the United States and other countries. These activities resulted in the design and development of integrated tube trailer systems that have increased delivery capacities by 45%. The hydrogen delivery capacity of our largest system is 845 kg, exceeding the project’s 2015 target of 700 kg H2 delivered. Emerging technologies offering improvement of the safety systems used on the equipment were investigated, with particular focus on improving the reliability and cost of the emergency venting system for fire protection. Finally, investment in our materials laboratory improved detection and characterization of hydrogen-induced damage in polymer materials, supporting the development of operational protocols to avoid damage to pressure vessel liners and valve components.

08 HYDROGEN↗
DOE OSTI2019

Proactive Data Containers for Scientific Storage (Final Report)

Emerging HPC systems are expected to be deployed with an unprecedented level of complexity, due to a deep system memory/storage hierarchy and heterogeneity of the storage hardware. This hierarchy is expected to range from CPU cache through several levels of volatile memory to nonvolatile memory, traditional hard disks, and tape. Simple and efficient methods of data management and movement through this hierarchy is critical for scientific applications using exascale systems. Existing storage system and I/O (SSIO) technologies face severe challenges in dealing with these requirements. POSIX and MPI I/O standards that are the basis for existing I/O libraries and parallel file systems present fundamental challenges in the areas of scalable metadata operations, semantics-based data movement performance tuning, asynchronous operation, and support for scalable consistency of distributed operations. Moving toward new paradigms for SSIO in the extreme-scale era, we have proposed to investigate novel object-based data abstractions and storage mechanisms that take advantage of the deep storage hierarchy and enable proactive automated performance tuning. In order to achieve these overarching goals, we initiated an effort to develop a fundamental new data abstraction, called Proactive Data Containers (PDC). A PDC is a container within a locus of storage (memory, NVRAM, disk, etc.) that stores science data in an object-centric manner. Managing data as objects enables powerful optimization opportunities for data movement and transformations. The R&D focus of this project are: 1) formulation of object-oriented PDCs and their mapping in different levels of the exascale storage hierarchy; 2) efficient strategies for moving data in deep storage hierarchies using PDCs; 3) techniques for transforming and reorganizing data based on application requirements; and 4) novel analysis paradigms for enabling data transformations and user-defined analysis on data in PDCs. Toward achieving these overarching goals, we designed an object-centric application programing interface (API) for HPC, scalable metadata management for object-centric storage systems, and data movement optimizations such as Data Elevator for moving data between two levels of storage devices and TAPIOCA for efficient aggregation of data on compute nodes. We then implemented several components of the PDC system. They include metadata management, data placement services, remote procedure calls, data aggregation, etc. We have put them together into the overall PDC framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Proactive Operations and Investment Planning via Stochastic Optimization to Enhance Power Systems’ Extreme Weather Resilience

We present scalable stochastic optimization approaches for improving power systems’ resilience to extreme weather events. We consider both proactive redispatch and transmission line hardening as alternatives for mitigating expected load shed due to extreme weather, resulting in large-scale stochastic linear programs (LPs) and mixed-integer linear programs (MILPs). We solve these stochastic optimization problems with progressive hedging (PH), a parallel, scenario-based decomposition algorithm. Our computational experiments indicate that our proposed method for enhancing power system resilience can provide high-quality solutions efficiently. With up to 128 scenarios on a 2,000-bus network, the operations (redispatch) and investment (hardening) resilience problems can be solved in approximately 6 min and 2 h of wall-clock time, respectively. Additionally, we solve the investment problems with up to 512 scenarios, demonstrating that the approach scales very well with the number of scenarios. Moreover, the method produces high quality solutions that result in statistically significant reductions in expected load shed. Our proposed approach can be augmented to incorporate a variety of other operational and investment resilience strategies, or a combination of such strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

HTGR Multiphysics Application Drivers FY26 Updates

This report summarizes FY26 progress under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program's high-temperature gas-cooled reactor (HTGR) application driver work, covering a wide range of activities such as code validation and multi-physics code assessment. 1) A detailed SAM model of the High-Temperature Engineering Test Reactor (HTTR) was developed using a unique-block grouping approach, with an extended parallel thermal network method to capture block-to-block conduction and radiation heat transfer, and applied to steady-state simulations of the HTTR 30~MW and 9~MW cases. 2) In another activity, SAM's newly implemented multi-component gas flow model was validated against the Natural convection Shutdown heat removal Test Facility (NSTF) argon ingress experiment, correctly capturing the density-driven suppression and thermal recovery of natural circulation observed when argon is introduced into the air-cooled Reactor Cavity Cooling System (RCCS) loop. 3) For the OECD/NEA High Temperature Test Facility (HTTF) benchmark, we co-led the international benchmark activities as well as the OECD/NEA final benchmark report to be released at the end of this year. 4) Finally, the coupled Griffin-SAM modeling capability for pebble-bed HTGRs was advanced by verifying the Griffin neutronics solution against Serpent Monte Carlo for a realistic non-uniform temperature distribution, resolving several deficiencies in the SAM-to-Griffin temperature transfer scheme, and enabling distinct fuel kernel, moderator, and coolant temperatures for cross section feedback. These new features were demonstrated in a PBR load-following transient.

Lee, Alvin↗
DOE OSTI2015

SU-E-T-778: Use of the 2D MatriXX Detector for Measuring Scanned Ion Beam Parameters

Purpose: The quality assurance (QA) procedure has to check the most relevant beam parameters to ensure the delivery of the correct dose to patients. Film dosimetry, which is commonly used for scanned ion beam QA, does not provide immediate results. The purpose of this work is to answer whether, for scanned ion beam therapy, film dosimetry can be replaced with the 2D MatriXX detector as a real-time tool. Methods: MatriXX, equipped with 32×32 parallel plate ion-chambers, is a commercial device intended for pre-treatment verification of conventional radiation therapy.The MatriXX, placed at the isocenter, and GAFCHROMIC films, positioned on the MatriXX entrance, were exposed to 131.44 MeV proton and 221.45 MeV/u Carbon-ion beams.The OmniPro-I’mRT software, applied for the data taking of MatriXX, gives the possibility of acquiring consecutive snapshots. Using the NI LabVIEW, the data from snapshots were logged as text files for further analysis. Radiochromic films were scanned with EPSON scanner and analyzed using software programs developed in-house for comparative purposes. Results: The field dose uniformity, flatness, beam position and beam width were investigated. The field flatness for the region covering 6×6 cm{sup 2} square field was found to be better than 2%. The relative standard deviations, expected to be constant over 2×2, 4×4 and 6×6 pixels from MatriXX measurement gives a uniformity of 1.5% in good agreement with the film results.The beam center position is determined with a resolution better than 200 µm for Carbon and less than 100 µm for proton beam.The FWHM determination for a beam wider than 10 mm is satisfactory, whilst for smaller beams the determination is uncertain. Conclusion: Precise beam position and fast 2D dose distribution can be determined in real-time using MatriXX detector. The results show that MatriXX is quick and accurate enough to be used in charged-particle therapy QA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

PLATO (Parallel Load Assignment Tool): A Parallel Workload Partitioner for Particle-based Methods

A key first step in many large-scale high-performance scientific computing applications is the distribution of the computational domain across all participating processors of a parallel computing platform such as a shared memory machine, cluster or a tightly-coupled supercomputer. The primary goal of such a partitioning step is to ensure that the computational work performed by each process remains load-balanced throughout the execution of the parallel application. In this project, a general-purpose parallel partitioning tool, code-named PLATO, was designed and implemented. PLATO assumes that the workload is a set of points in an n-dimensional metric space. These points are abstractions of computational units that may represent point-like computational units such as celestial objects in astrophysics, atoms in materials sciences and molecules in biology/chemistry, or may represent more abstract computational units such as grid points in finite difference methods, grid elements in finite element methods or n-dimensional points in the feature space of a host of other applications. PLATO supports several key and useful capabilities, namely: (a) multiple load partitioning strategies, (b) support for arbitrary user-defined processor topology, (c) pre-fetching data from neighboring processors based on user-defined parameters, and (d) support for arbitrary number and types of attributes associated with each point in the computational domain. PLATO is implemented in the C programming language using Message Passing Interface (MPI) for inter-processor communications and its parallel performance tested on up to 48 processors of a shared memory machine. This report includes a detailed performance study of PLATO using parallel speedup and iso-efficiency as the two main metrics of parallel performance. In addition, a user manual and DOXYGEN generated code documentation have been included for completeness.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

MPI-FAUN: An MPI-Based Framework for Alternating-Updating Nonnegative Matrix Factorization

Non-negative matrix factorization (NMF) is the problem of determining two non-negative low rank factors W and H, for the given input matrix A, such that A≈WH. NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient parallel algorithms to solve the problem for big data sets. The main contribution of this work is a new, high-performance parallel computational framework for a broad class of NMF algorithms that iteratively solves alternating non-negative least squares (NLS) subproblems for W and H. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). The framework is flexible and able to leverage a variety of NMF and NLS algorithms, including Multiplicative Update, Hierarchical Alternating Least Squares, and Block Principal Pivoting. Our implementation allows us to benchmark and compare different algorithms on massive dense and sparse data matrices of size that spans from few hundreds of millions to billions. We demonstrate the scalability of our algorithm and compare it with baseline implementations, showing significant performance improvements. The code and the datasets used for conducting the experiments are available online.

2D↗
DOE OSTI2024

Using Parameter Sweep in WaterTAP to Analyze New Water Treatment Technologies

We describe a powerful and generalized parameter sweep tool in this report that was originally developed to analyze the performance of existing and novel water treatment models being developed in WaterTAP. Since WaterTAP is built upon IDAES and Pyomo, the parameter sweep tool can be used to systematically explore and debug the behavior of most Pyomo and IDAES numerical models. In order to enable meaningful analyses, the parameter sweep tool has been designed with the following features: 1) Model flexibility: The parameter sweep tool does not enforce any restrictions on the types of models that can be used with it. As long as a Pyomo model can be solved and the parameter is active and mutable, the tool only needs functions that describe how to run the model, the sweep parameters, and the output quantities of interest. 2) Flexible sampling: The parameter sweep tool has inbuilt functions to generate samples from a random distribution or a multidimensional Euclidean space. Furthermore, the users have to ability to supply samples generated from a tool of their choice. 3) Multiple sweep types: A user can choose from one of 3 types of parameter sweeps depending on their needs. 4) Detailed outputs: Outputs generated by the parameter sweep tool can be stored in detailed H5 file or user-friendly CSV files for post processing. 5) Parallel computing: The parameter sweep supports shared and distributed memory parallel computing to enable the use of high performance computers (HPC) for large-scale analyses. 6) Modular: The parameter sweep tool is self-contained and can easily be integrated within an outer-loop analysis or as desired by the user. 7) Ease of use: The tool is well documented and a simple sweep can be easily executed by following the online documentation in a few lines of code. We demonstrate the use of the parameter sweep tool on a simple water treatment system from the WaterTAP repository and show its parallel scaling performance on an Apple laptop and NREL's Eagle HPC. The parameter sweep tool is actively being used with models currently being developed within WaterTAP and we expect its use to grow beyond it to other IDAES and Pyomo models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Cataloging the visible universe through Bayesian inference in Julia at petascale

A key task in astronomy is to locate astronomical objects in images and to characterize them according to physical parameters such as brightness, color, and morphology. This task, known as cataloging, is challenging for several reasons: many astronomical objects are much dimmer than the sky background, labeled data is generally unavailable, overlapping astronomical objects must be resolved collectively, and the datasets are enormous – terabytes now, petabytes soon. In this work, we infer an astronomical catalog from 55 TB of imaging data using Celeste, a Bayesian variational inference code written entirely in the high-productivity programming language Julia. Using over 1.3 million threads on 650,000 Intel Xeon Phi cores of the Cori Phase II supercomputer, Celeste achieves a peak rate of 1.54 DP PFLOP/s. Celeste is able to jointly optimize parameters for 188 M stars and galaxies, loading and processing 178 TB across 8192 nodes in 14.6 min. To achieve this, Celeste exploits parallelism at multiple levels (cluster, node, and thread) and accelerates I/O through Cori’s burst buffer. Julia’s native performance enables Celeste to employ high-level constructs without resorting to hand-written or generated low-level code (C/C++/Fortran) while still achieving petascale performance.

Regier, Jeffrey↗
DOE OSTI2027

Nodal capacity expansion planning with flexible large-scale load siting

We propose explicitly incorporating large-scale load siting into a stochastic nodal power system capacity expansion planning model that concurrently co-optimizes generation, transmission, and storage expansion. The potential operational flexibility of some of these large loads is also taken into account by considering them as consisting of a set of tranches with different reliability requirements, which are modeled as a constraint on expected served energy across operational scenarios. We implement our model as a two-stage stochastic mixed-integer optimization problem with cross-scenario expectation constraints. To overcome the challenge of scalability, we build upon existing work to implement this model on a high performance computing platform and exploit scenario parallelization using an augmented Progressive Hedging Algorithm. The algorithm is implemented using the bounding features of mpisppy, which have shown to provide satisfactory provable optimality gaps despite the absence of theoretical guarantees of convergence. We test our approach and assess the value of this proactive planning framework on total system cost and reliability metrics using realistic testcases geographically assigned to San Diego and South Carolina, with datacenter and direct air capture facilities as large loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗