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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 667 records · Page 37

The Atacama Cosmology Telescope: Summary of DR4 and DR5 Data Products and Data Access

Two recent large data releases for the Atacama Cosmology Telescope (ACT), called DR4 and DR5, are available for public access. These data include temperature and polarization maps that cover nearly half the sky at arcminute resolution in three frequency bands; lensing maps and component-separated maps covering ∼2100 deg 2 of sky; derived power spectra and cosmological likelihoods; a catalog of over 4000 galaxy clusters; and supporting ancillary products including beam functions and masks. The data and products are described in a suite of ACT papers; here we provide a summary. In order to facilitate ease of access to these data, we present a set of Jupyter IPython notebooks developed to introduce users to DR4, DR5, and the tools needed to analyze these data. The data products (excluding simulations) and the set of notebooks are publicly available on the NASA Legacy Archive for Microwave Background Data Analysis; simulation products are available on the National Energy Research Scientific Computing Center.

Maya Mallaby-Kay↗

Algebraic Multigrid Benchmark

AMG is a parallel algebraic multigrid solver for linear systems arising from problems on unstructured grids. It has been derived directly from the BoomerAMG solver in the hypre library, a large linear solvers library that is being developed in the Center for Applied Scientific Computing (CASC) at LLNL and is very similar to the AMG2013 benchmark with additional optimizations. The driver provided in the benchmark can build various test problems. The default problem is a Laplace type problem with a 27-point stencil, which can be scaled up and is designed to solve a very large problem. A second problem simulates a time dependent problem, in which successively various smnllcr systems are solved.

Yang, Ulrike↗

Deployable sensor system using mesh networking and satellite communication

A sensor system may be configured for continuous operation in a low resource environment and/or in extreme environmental conditions. The sensor system may have sufficient processing capabilities to provide scientific computing for pre-processing, quality control, statistical analysis, event classification, data compression and corrections (e.g., spikes in the data), autonomous decisions and actions, triggering other nodes, and information assurance functions that provide data confidentiality, data integrity, authentication, and non-repudiation. The hardware may have both mesh networking and satellite and cellular communication capability, and may be available for relatively low cost. Such a network provides the flexibility to have potentially any number of nodes be completely independent from one another. Thus, the network may scale across a diverse terrain.

97 MATHEMATICS AND COMPUTING↗

Flexible and Scalable Data-Acquisition Using the artdaq Toolkit

The Real-Time Systems Engineering Department of the Scientific Computing Division at Fermilab is developing a flexible, scalable, and powerful data-acquisition (DAQ) toolkit which serves the needs of experiments from bench-top hardware tests to large high-energy physics experiments. The toolkit provides data transport and event building capabilities with the option for experimenters to inject art analysis code at key points in the DAQ for filtering or monitoring. The toolkit also provides configuration management, run control, and low-level hardware communication utilities. Firmware blocks for several commercial data acquisition boards are provided, allowing experimenters to approach the DAQ from a high level. A fully-functional DAQ "solution" of the toolkit is provided in otsdaq, sacrificing some flexibility in favor of being ready-to-use. artdaq is being used for several current and upcoming experiments, and will continue to be refined and expanded for use in the next generation of neutrino and muon experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The Fermilab Test Beam Facility Data Acquisition System Based on $otsdaq$

The Real-Time Systems Engineering Department of the Scientific Computing Division at Fermilab has deployed set of customizations to our Off-The-Shelf Data Acquisition solution (otsdaq) at the Fermilab Test Beam Facility (FTBF) to read out the beamline instrumentation in support of FTBF users. In addition to reading out several detectors which use various detection technologies and readout hardware, the FTBF Data Acquisition system (DAQ) can perform basic track reconstruction through the facility in real time and provide data to facility users. An advanced prototype smart coincidence module, known as the NIM+, performs trigger distribution and throttling, allowing the beamline instrumentation to be read out at different rates. Spill data are saved to disk for studies of the facility performance, and hit data are also made available on the FTBF network for experiments' use. A web-based run control and configuration GUI are provided, and the online monitoring snapshots created after each beam spill are viewable from any computer connected to the Fermilab network. The integrated DAQ system for the facility provides users with high-precision tracking data along the beamline and a single location for obtaining data from the facility detectors, which set the baseline for testing their own detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Advances and Enhancements in the Fabric for Frontier Experiments Project at Fermilab

The FabrIc for Frontier Experiments (FIFE) project within the Fermilab Scientific Computing Division is charged with integrating offline computing components into a common computing stack for the non-LHC Fermilab experiments, supporting experiment offline computing, and consulting on new, novel workflows. We will discuss the general FIFE onboarding strategy, the upgrades and enhancements in the FIFE toolset, and plans for the coming year. These enhancements include: expansion of opportunistic computing resources (including GPU and high-performance computing resources) available to experiments; assistance with commissioning computing resources at European sites for individual experiments; StashCache repositories for experiments; enhanced job monitoring tools; and a custom workflow management service. Additionally we have completed the first phase of a Federated Identity Management system to make it easier for FIFE users to access Fermilab computing resources.

Herner, Kenneth↗

Extending the Publish/Subscribe Abstraction for High-Performance I/O and Data Management at Extreme Scale

The Adaptable I/O System (ADIOS) represents the culmination of substantial investment in Scientific Data Management, and it has demonstrated success for several important extreme-scale science cases. However, looking towards the exascale and beyond, we see the development of yet more stringent data management requirements that require new abstractions. Therefore, there is an opportunity to attempt to connect the traditional realms of HPC I/O optimization with the Database / Data Management community. As such, in this paper we offer some specific examples from our ongoing work in managing data structures, services, and performance at the extreme scale for scientific computing. Using the publish/subscribe model afforded by ADIOS, we demonstrate a set of services that connect data format, metadata, queries, data reduction, and high-performance delivery. The resulting publish/subscribe framework facilitates connection to on-line workflow systems to enable the dynamic capabilities that will be required for exascale science.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

LArSoft and Future Framework Directions at Fermilab

The diversity of the scientific goals across HEP experiments necessitates unique bodies of software tailored for achieving particular physics results. The challenge, however, is to identify the software that must be unique, and the code that is unnecessarily duplicated, which results in wasted eort and inhibits code maintainability. Fermilab has a history of supporting and developing software projects that are shared among HEP experiments. Fermilab’s scientific computing division currently expends eort in maintaining and developing the LArSoft toolkit, used by liquid argon TPC experiments, as well as the event-processing framework technologies used by LArSoft, CMS, DUNE, and the majority of Fermilab-hosted experiments. As computing needs for DUNE and the HL-LHC become clearer, the computing models are being rethought. Presented here are Fermilab’s plans for addressing the evolving software landscape as it relates to LArSoft and the data-processing frameworks, specifically as it relates to the DUNE experiment.

Knoepfel, Kyle↗

From Long-distance Entanglement to Building a Nationwide Quantum Internet: Report of the DOE Quantum Internet Blueprint Workshop

A Quantum Path Forward. Today, many scientific experts recognize that building and scaling quantum-protected and enhanced communication networks are among the most important technological frontiers of the 21st century. The international research community perceives the construction of a first prototype global quantum network-the Quantum Internet-to be within reach over the next decade. In February 2020, the U.S. Department of Energy (DOE)'s Office of Advanced Scientific Computing Research hosted the Quantum Internet Blueprint workshop to define a potential roadmap toward building the first nationwide quantum Internet. The workshop participants included representatives from DOE national laboratories, universities, industry, and other U.S. agencies with serious interests in quantum networking. The goal was to provide an outline of the essential research needed, detail any engineering and design barriers, and suggest a path forward to move from today's limited local network experiments to a viable, secure quantum Internet.

Peters, Nicholas↗

Machine Learning Methods for Connection RTT and Loss Rate Estimation Using MPI Measurements Under Random Losses

Scientific computations are expected to be increasingly distributed across wide-area networks, and Message Passing Interface (MPI) has been shown to scale to support their communications over long distances. Application-level measurements of MPI operations reflect the connection Round-Trip Time (RTT) and loss rate, and machine learningmethods have been previously developed to estimate them under deterministic periodic losses. In this paper, we consider more complex, random losses with uniform, Poisson and Gaussian distributions. We study five disparate machine leaning methods, with linear and non-linear, and smooth and non-smooth properties, to estimate RTT and loss rate over 10 Gbps connections with 0–366 ms RTT. The diversity and complexity of these estimators combined with the randomness of losses and TCP’s non-linear response together rule out the selection of a single best among them; instead, we fuse them to retain their design diversity. Overall, the results show that accurate estimates can be generated at low loss ratesbut become inaccurate at loss rates 10% and higher, thereby illustrating both their strengths and limitations.

Rao, Nageswara S.↗

Deployable sensor system using mesh networking and satellite communication

A sensor system may be configured for continuous operation in a low resource environment and/or in extreme environmental conditions. The sensor system may have sufficient processing capabilities to provide scientific computing for pre-processing, quality control, statistical analysis, event classification, data compression and corrections (e.g., spikes in the data), autonomous decisions and actions, triggering other nodes, and information assurance functions that provide data confidentiality, data integrity, authentication, and non-repudiation. The hardware may have both mesh networking and satellite and cellular communication capability, and may be available for relatively low cost. Such a network provides the flexibility to have potentially any number of nodes be completely independent from one another. Thus, the network may scale across a diverse terrain.

Frigo, Janette↗

On the Convergence of Inexact Predictor-Corrector Methods for Linear Programming

Interior point methods (IPMs) are a common approach for solving linear programs (LPs) with strong theoretical guarantees and solid empirical performance. The time complexity of these methods is dominated by the cost of solving a linear system of equations at each iteration. In common applications of linear programming, particularly in machine learning and scientific computing, the size of this linear system can become prohibitively large, requiring the use of iterative solvers, which provide an approximate solution to the linear system. However, approximately solving the linear system at each iteration of an IPM invalidates the theoretical guarantees of common IPM analyses. To remedy this, we theoretically and empirically analyze (slightly modified) predictor-corrector IPMs when using approximate linear solvers: our approach guarantees that, when certain conditions are satisfied, the number of IPM iterations does not increase and that the final solution remains feasible. We also provide practical instantiations of approximate linear solvers that satisfy these conditions for special classes of constraint matrices using randomized linear algebra.

Dexter, Gregory↗

Recovering Topology of Nested Volumes Represented by Single Closed Surfaces

As scientific computing abilities continue to advance, so too have the efforts to model and simulate highly complex geometries in radiation environments. Modeling has advanced from primitive constructive solid geometry (CSG) to voxelized models, and now to high fidelity polygon mesh models. While polygon mesh surface models are very accurate, most Monte Carlo codes do not allow for their direct use. Often they are converted to voxel or tetrahedral mesh models and then used with the physics codes. The Direct Accelerated Geometry Monte Carlo (DAGMC) software package has the ability to efficiently run transport calculations directly on tessellated surface models. Typically the surface meshes used for DAGMC calculations come from CAD-based geometry models generated by solid modeling software. In some cases geometries of interest, like human phantoms, are generated by other means and may not contain all of the necessary information for particle transport. For example, mesh geometries in the OBJ file format contain vertex and connectivity data for each surface, but do not have any information about surface topology. These types of file formats necessitate a tool that can build a hierarchy of surfaces and reconstruct the topological information. The generate hierarchy tool was developed for this purpose. The following summary will explain the algorithm behind the tool, describe a test case, and finally demonstrate a real-world application of the tool with an MCNP5 calculation that directly uses a polygon mesh human phantom.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Scientific Machine Learning using MOOSE

A machine learning interface has been recently developed for the Multiphysics Object-Oriented Simulation Environment (MOOSE). This presentation summarizes the motivation behind using machine learning in scientific computing together with several examples for applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Performance study of atomic tally methods for GPU-accelerated Monte Carlo dose calculation - 25352

Over the past several years, the graphics processing unit (GPU) technology has rapidly gained ground in scientific computing due to its outstanding performance and programmability. GPU implementation of Monte Carlo radiation transport for dose calculations has been reported by many investigators. The majority of these studies adopted single-precision floating point format because of the higher peak floating point operations per second (FLOPS) the GPUs can deliver than double-precision. It has been known that calculation using single-precision is more prone to numerical round-off errors, especially when a single tally data is accumulated 'atomically' and repeatedly by thousands of GPU threads. To mitigate this problem, the least intrusive solution in theory is to replace the single-precision atomic-add tally function with a double-precision version. However, the complexity lies in the fact that some GPUs (Nvidia GPUs prior to the Pascal generation; all current AMD GPUs) do not readily offer such double-precision function at hardware level, and that software emulation is too slow to use if not optimized properly. This paper discusses several atomic-add tally methods with reduced numerical errors used throughout ARCHER development. The original software-based compare-and-swap method (CAS) was shown to be inefficient due to high intra-warp thread contention, whereas the improved software-based warp-aggregated method (WAG) and Kahan summation method (KAS) eliminated the thread contention and performed very well on Kepler and Maxwell GPUs, being more than 13 times faster than CAS in our tests. The hardware-based (HB) double-precision atomic-add feature available on Pascal and Volta GPUs exceeded software emulation and offered the best performance universally, so did WIB, a combination of WAG and HB methods. It was also shown that in a single-precision dose engine, KAS managed to maintain high reliability when the single-precision atomic-add tally underestimated the dose by 25%. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

High-Fidelity Arc-Discharge Model for Hydrogen-Plasma-Smelting-Reduction of Iron Ore

Electrification and use of renewable hydrogen is currently a necessity for decarbonizing the iron-and-steel industry. In this regard, hydrogen plasma smelting reduction (HPSR) is a novel pathway that is being explored for reduction of iron ore. HPSR provides several decarbonization merits compared to conventional blast furnaces. Firstly, the use of renewable hydrogen drastically reduces the CO2 emissions compared to the use of coke. Secondly, renewable electricity in the form of a thermal plasma for making reactive hydrogen species (radicals, ions) are more efficient at reducing iron ore compared to neutral H2. Thirdly, a molten product compatible with downstream processes is obtained from the intense heat transfer from the plasma. However, the scale-up of this technology requires fundamental exploration of hydrogen plasma dynamics and its interaction with complex solid material that include phase changing iron-ore and slag. In this work, we present a first principles continuum scale model for thermal plasmas in Ar/H2 gas mixtures typically used for HPSR. The thermal plasma governing equations for mass, momentum and energy with Lorentz force and Joule heating source terms are solved along with electromagnetic equations for electrostatic and magnetic vector potential. Our solver will be based on Pele, a suite of reacting flow solvers designed for advanced scientific computing architectures (Henry De Frahan et al., Proceedings of SIAM Parallel Processing, 13-25, 2024), and will utilize adaptive mesh generation for enhanced resolutions at locations of intense physicochemical interactions. This study will present the impact of Ar to H2 ratios on excited/dissociated hydrogen species concentrations, plasma temperature and conductivity along with the impact of outgassed species (water, metal vapor, O, OH radicals) from ore surface on gas phase chemistry. Furthermore, the heat and species flux to the surface will be quantified as a function of applied voltages in a transferred arc configuration.

hydrogen plasma↗