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At least 1,711 records · Page 95

PyBLM (Python-based Battery Life Model) [SWR-21-50]

PyBLM is a battery life model to predict the capacity fade of two home battery energy storage systems, manufactured by LG and Tesla. The battery life model is built from experimental test data, and accounts for calendar and cycling aging mechanisms as functions of cell environmental conditions and use. PyBLM is developed in Python and formatted to work in conjunction with another NREL software named TEMPEST (Thermo-Electric Model for Powering Energy Storage Technologies).

Mishra, Partha↗

Weak-Form Latent Space Dynamics Identification

This software showcases the enhanced capabilities of the Latent Space Dynamics Identification (LaSDI) algorithm through the application of the weak form, resulting in WLaSDI. WLaSDI first compresses the data, then projects it onto test functions, and subsequently learns the local latent space models. Notably, WLaSDI demonstrates significantly improved robustness to noise. Using weak-form equation learning techniques, WLaSDI achieves local latent space modeling. Compared to the standard sparse identification of nonlinear dynamics (SINDy) used in LaSDI, the variance reduction of the weak form ensures robust and precise latent space recovery, enabling fast, robust, and accurate simulations. We demonstrate the efficacy of WLaSDI against LaSDI using several common benchmark examples, including viscid and inviscid Burgers', radial advection, and heat conduction. For instance, in 1D inviscid Burgers' simulations with up to 100% Gaussian white noise, WLaSDI maintains relative errors consistently below 6%, whereas LaSDI errors can exceed 10,000%. Similarly, in radial advection simulations, WLaSDI keeps relative errors below 16%, compared to potential errors of up to 10,000% with LaSDI. Additionally, WLaSDI achieves significant speedups, such as a 140X speedup in 1D Burgers' simulations compared to the corresponding full order model.

Choi, Youngsoo↗

Mnemosyne

SAND2024-08570O Mnemosyne is an interactive tool for finding, retrieving, and exploring information about U.S. nuclear tests documented in the National Nuclear Security Administration’s NV-209 report. It also acts as an information architecture and codebase for integrating additional information and computational tools related to these tests at the unclassified and classified levels. Users can search by any number of nuclear test attributes—name, yield range, altitude ranges, purpose of a test—and find all matching tests. Users can also retrieve specific test information published in NV-209. The tool displays geospatial and topological data about test location, and it provides an information architecture for storing additional contextual material, such as photographs. Mnemosyne provides a capability of interfacing with HYCHEM, Sandia's nuclear detonation optical waveform tool. The software is designed for use by government, academia, military, and research institutions. The software will likely be advanced to integrate seismic data and the nuclear detonation optical signal simulation code radCTH. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fisher, Dustin↗

RENEWABLE ENERGY AND ENVIRONMENTAL SUSTAINABILITY USING BIOMASS FROM DAIRY AND BEEF ANIMAL PRODUCTION

The Texas Panhandle is regarded as the "Cattle Feeding Capital of the World", producing 42% of the fed beef cattle in the United States within a 200-mile radius of Amarillo generating more than 5 million tons of feedlot manure /year. Apart from feedlots, the Bosque River Region in Erath County, just north of Waco, Texas with about 110,000 dairy cattle in over 250 dairies, produces 1.8 million tons of manure biomass (excreted plus bedding) per year. While the feedlot manure has been used extensively for irrigated and dry land crop production, most dairies, as well as other concentrated animal feeding operations (CAFO's), the dairy farms utilize large lagoon areas to store wet animal biomass. Water runoff from these lagoons has been held responsible for the increased concentration of phosphorus and other contaminates in the Bosque River which drains into Lake Waco—the primary source of potable water for Waco's 108,500 people. The concentrated animal feeding operations may lead to land, water, and air pollution if waste handling systems and storage and treatment structures are not properly managed. Manure-based biomass (MBB) has the potential to be a source of green energy at large coal-fired power plants and on smaller-scale combustion systems at or near confined animal feeding operations. Although MBB particularly cattle biomass (CB) is a low quality fuel with an inferior heat value compared to coal and other fossil fuels, the concentration of it at large animal feeding operations can make it a viable source of fuel. The overall objective of this interdisciplinary proposal is to develop environmentally benign technologies to convert low-value inventories of dairy and beef cattle biomass into renewable energy. Current research expands the suite of technologies by which cattle biomass (CB: manure, and premature mortalities) could serve as a renewable alternative to fossil fuel. The work falls into two broad categories of research and development. Category 1 – Renewable Energy Conversion. This category addressed mostly in volume I involves developing. Thermo-chemical conversion technologies including cofiring with coal, reburn to reduce nitrogen oxide (NO, N2O, NOx, etc.) and Hg emissions and gasification to produce low-BTU gas for on-site power production in order to extract energy from waste streams or renewable resources. Category 2 – Biomass Resource Technology. This category, addressed mostly in Volume II, deals with the efficient and cost-effective use of CB as a renewable energy source (e.g. through and via aqueous-phase, anaerobic digestion or biological gasification). The investigators formed an industrial advisory panel consisting fuel producers (feedlots and dairy farms) and fuel users (utilities), periodically met with them, and presented the research results; apart from serving as dissemination forum, the PIs used their critique to red-direct the research within the scope of the tasks. The final report for the 5 to 7 year project performed by an interdisciplinary team of 9 professors is arranged in three volumes: Vol. I (edited by Kalyan Annamalai) addressing thermo-chemical conversion and direct combustion under Category 1 and Vol. II and Vol. III ( edited by J M Sweeten) addressing biomass resource Technology under Category 2. Various tasks and sub-tasks addressed in Volume I were performed by the Department of Mechanical Engineering (a part of TEES; see Volume I), while other tasks and sub-tasks addressed in Volume II and IIII were conducted by Texas AgriLife Research at Amarillo; the TAMU Biological & Agricultural Engineering Department (BAEN) College Station; and West Texas A&M University (WTAMU) (Volumes II and III). The three volume report covers the following results: fuel properties of low ash and high ash CB (particularly DB) and MB (mortality biomass and coals, non-intrusive visible infrared (NVIR) spectroscopy techniques for ash determination, dairy energy use surveys at 14 dairies in Texas and California, cofiring of low quality CB with high quality coal, emission results and ash fouling behavior, using CB as reburn fuel for NOx and Hg reduction, gasification of fuels to produce low quality gases, modeling of reburn, pilot scale test results, synthesis of engineering characterization, geographical mapping, a transportation cost study to determine potential handling and transportation systems for co-firing with coal at regional coal-fired power plants, software analyses for the design of off-site manure, pre-processing and storage systems for a typical dairy farm or beef cattle feedlot, recursive production functions/systems models for both cattle feedlots, systems modeling, stocks and flows of energy involved in the CAFO system, feedback from an Industry Advisory Committee (IAC) to the investigators on project direction and task emphasis and economics of using CB as cofiring and reburn fuel.

09 BIOMASS FUELS↗

RENEWABLE ENERGY AND ENVIRONMENTAL SUSTAINABILITY USING BIOMASS FROM DAIRY AND BEEF ANIMAL PRODUCTION

The Texas Panhandle is regarded as the "Cattle Feeding Capital of the World", producing 42% of the fed beef cattle in the United States within a 200-mile radius of Amarillo generating more than 5 million tons of feedlot manure/year. Apart from feedlots, the Bosque River Region in Erath County, just north of Waco, Texas with about 110,000 dairy cattle in over 250 dairies, produces 1.8 million tons of manure biomass (excreted plus bedding) per year. While the feedlot manure has been used extensively for irrigated and dry land crop production, most dairies, as well as other concentrated animal feeding operations (CAFO's), the dairy farms utilize large lagoon areas to store wet animal biomass. Water runoff from these lagoons has been held responsible for the increased concentration of phosphorus and other contaminates in the Bosque River which drains into Lake Waco -- the primary source of potable water for Waco's 108,500 people. The concentrated animal feeding operations may lead to land, water, and air pollution if waste handling systems and storage and treatment structures are not properly managed. Manure-based biomass (MBB) has the potential to be a source of green energy at large coal-fired power plants and on smaller-scale combustion systems at or near confined animal feeding operations. Although MBB particularly cattle biomass (CB) is a low quality fuel with an inferior heat value compared to coal and other fossil fuels, the concentration of it at large animal feeding operations can make it a viable source of fuel. The overall objective of this interdisciplinary proposal is to develop environmentally benign technologies to convert low-value inventories of dairy and beef cattle biomass into renewable energy. Current research expands the suite of technologies by which cattle biomass (CB: manure, and premature mortalities) could serve as a renewable alternative to fossil fuel. The work falls into two broad categories of research and development. Category 1 -- Renewable Energy Conversion. This category addressed mostly in volume I involves developing. Thermo-chemical conversion technologies including cofiring with coal, reburn to reduce nitrogen oxide (NO, N2O, NOx, etc.) and Hg emissions and gasification to produce low-BTU gas for on-site power production in order to extract energy from waste streams or renewable resources. Category 2 -- Biomass Resource Technology. This category, addressed mostly in Volume II, deals with the efficient and cost-effective use of CB as a renewable energy source (e.g. through and via aqueous-phase, anaerobic digestion or biological gasification). The investigators formed an industrial advisory panel consisting fuel producers (feedlots and dairy farms) and fuel users (utilities), periodically met with them, and presented the research results; apart from serving as dissemination forum, the PIs used their critique to re-direct the research within the scope of the tasks. The final report for the 5 to 7 year project performed by an interdisciplinary team of 9 professors is arranged in three volumes: Vol. I (edited by Kalyan Annamalai) addressing thermo-chemical conversion and direct combustion under Category 1 and Vol. II and Vol. III ( edited by J M Sweeten) addressing biomass resource Technology under Category 2. Various tasks and sub-tasks addressed in Volume I were performed by the Department of Mechanical Engineering (a part of TEES; see Volume I), while other tasks and sub-tasks addressed in Volume II and IIII were conducted by Texas AgriLife Research at Amarillo; the TAMU Biological & Agricultural Engineering Department (BAEN) College Station; and West Texas A&M University (WTAMU) (Volumes II and III). The three volume report covers the following results: fuel properties of low ash and high ash CB (particularly DB) and MB (mortality biomass and coals, non-intrusive visible infrared (NVIR) spectroscopy techniques for ash determination, dairy energy use surveys at 14 dairies in Texas and California, cofiring of low quality CB with high quality coal, emission results and ash fouling behavior, using CB as reburn fuel for NOx and Hg reduction, gasification of fuels to produce low quality gases, modeling of reburn, pilot scale test results, synthesis of engineering characterization, geographical mapping, a transportation cost study to determine potential handling and transportation systems for co-firing with coal at regional coal-fired power plants, software analyses for the design of off-site manure, pre-processing and storage systems for a typical dairy farm or beef cattle feedlot, recursive production functions/systems models for both cattle feedlots, systems modeling, stocks and flows of energy involved in the CAFO system, feedback from an Industry Advisory Committee (IAC) to the investigators on project direction and task emphasis and economics of using CB as cofiring and reburn fuel.

01 COAL, LIGNITE, AND PEAT↗

MCNP6™ Release 1.0: Creating and Testing the Code Distribution

This report documents the preparations for and testing of the production release of MCNP6™ through RSICC at ORNL. It addresses tests on supported operating systems (Linux, MacOSX, Windows) with the supported compilers (Intel, Portland Group International, PathsScale and gfortran). Verification and Validation test results are documented elsewhere. This report does not address in detail the overall packaging of the distribution. Specifically, it does not address the nuclear and atomic data collection, the other included software packages (MCNP5 and MCNPX) and the collection of reference documents.

07 ISOTOPE AND RADIATION SOURCES↗

MCNP(TM) Release 6.1.1 beta: Creating and Testing the Code Distribution

This report documents the preparations for and testing of the production release of MCNP6™1.1 beta through RSICC at ORNL. It addresses tests on supported operating systems (Linux, MacOSX, Windows) with the supported compilers (Intel, Portland Group and gfortran). Verification and Validation test results are documented elsewhere. This report does not address in detail the overall packaging of the distribution. Specifically, it does not address the nuclear and atomic data collection, the other included software packages (MCNP5, MCNPX and MCNP6) and the collection of reference documents.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

High Performance Data Analytics on a Commodity Private Cloud

Sandia is researching novel methods of analysis for large datasets. The term “Big Data” has been used frequently in recent years to describe a discipline of computer science that attempts to distil an increasing quantity of data into a result or meaningful subset that can be easily visualized and acted upon by human consumers. These data are frequently characterized by one or more of the following: high volume, velocity, variety, and veracity. Sandia scientists and researchers are no strangers to large datasets, which often typify the result of high-performance computing workloads. The challenge for Sandia data scientists, however, comes at the arrival of exascale computing, which has become mandated by executive order for national computing centers. Because of power and networking limitations, exascale computing precludes the movement of datasets at exascale from data production to data analysis. Such analysis must be done in-situ, to mitigate the time and power costs of network transport. Currently, many of Sandia’s data analytics environments exist as independent entities, often specialized for individual use cases, interconnected to other data analytics, high-performance computing, and storage systems. Sandia is procuring, installing, and researching future platforms for such data analytics. A memory footprint of 256 GB per node, fourteen data rate (FDR) InfiniBand networking, PCIe connected non-volatile memory (NVMe) data storage, and an object data store will characterize the coming institutional data analytics platforms. The combined systems will contain 300 compute nodes. A cloud-inspired software stack resulting from collaboration between the Sandia centers will allow the systems to support a flexible mix of user and system-facing workloads and use cases including code development and testing in R and Python, Apache Hadoop and Spark, distributed in-memory databases, graph analytics, emulytics, system log and predictive analytics, and data visualization for institutional and mission customers. These systems will arrive at the end of FY 2015 and production is planned by the spring of FY 2016.

97 MATHEMATICS AND COMPUTING↗

Faster-than-real-time Simulation with Demonstration for Resilient DER Integration

The US electric grid is facing operational, stability, and security challenges. Transmission system operators need some measure of visibility into distribution system renewable generation. Distribution system generation needs to support transmission system voltage. The grid is experiencing an expansion in measurement systems. How to take full advantage of this expansion and defend against attacks, both cyber and physical, poses additional challenges. The Faster-than-real-time Simulation with demonstration for Resilient DER Integration project set out to do the following: a. Flatten the voltage profile through the feeders and system for cost saving and voltage stabilization needs. b. Increase the amount of intermittent distributed energy resources (IDERs) that could be deployed on a utility feeder and provide 100% or more energy needed for the demands on that feeder, and c. based on an accurate model (Digital Twin) of the utilities system, be able to detect any abnormalities on the utilities distribution system. To manage the voltage and increase IDER penetration (a,b), Graph Trace Analysis is employed in a time-series, optimal power flow to coordinate the time-varying feedback control setpoints of a distribution feeder’s utility control devices. Under the coordinated control are a Load Tap Changing Transformer, a voltage regulator, and five switched capacitor banks. The feeder serves over 2000 customers, the feeder secondaries are modeled, and the feeder has 2.3 MW of PV generation, corresponding to a 17.4% penetration of PV generation. The feeder model has over 12,000 components, where every customer load bus and PV generator are modeled. The accuracy of the power flow solution is compared against historical meter voltage measurements, the improvement in conservation voltage reduction energy savings as a function of the coordinated control desired voltage profile is investigated, and the increase in PV penetration of the coordinated control over the existing control is presented. To achieve improved control performance while observing system operation constraints, bellwether Advanced Metering Infrastructure (AMI) voltage measurements are used to adjust the desired voltage profile used by the optimal power flow analysis. To detect and alleviate or negate attacks or failures on the distribution and transmission utility grids (c) the grid needs to be resilient and self-healing. In this project software was designed to do just that. At the center of the software is an Integrated System Model (ISM) that spans from transmission to secondary distribution. The ISM is employed in real-time abnormality detection, voltage stability forecasting, and multi-mode control. Testing results are presented for: 1—attacks on utility infrastructure; 2—energy savings from optimal control; 3—distribution system control response during a low voltage transmission system event; 4—cyber-attacks on PV inverters, where physical inverters are used in hard-ware-in-the-simulation-loop studies. Contributions of this work include real-time analysis that spans from three-phase transmission through secondary distribution; an approach for detecting abnormalities that employs measurements from three independent measurement systems; and a multi-mode distribution system control that responds to cyber-attacks, physical attacks, equipment failures, and transmission system needs.

Integrated System Model, Graph Trace Analysis, Adv↗

Multi-Purpose, Application-Centric, Scalable I/O Proxy Application

MACSio is a Multi-purpose, Application-Centric, Scalable I/O proxy application. It is designed to support a number of goals with respect to parallel I/O performance testing and benchmarking including the ability to test and compare various I/O libraries and I/O paradigms, to predict scalable performance of real applications and to help identify where improvements in I/O performance can be made within the HPC I/O software stack.

Miller, M. C.↗

GPU Usage in ATLAS Reconstruction and Analysis

With Graphical Processing Units (GPUs) and other kinds of accelerators becoming ever more accessible, High Performance Computing Centres all around the world using them ever more, ATLAS has to find the best way of making use of such accelerators in much of its computing. Tests with GPUs - mainly with CUDA - have been performed in the past in the experiment. At that time the conclusion was that it was not advantageous for the ATLAS offline and trigger software to invest time and money into GPUs. However as the usage of accelerators has become cheaper and simpler in recent years, their re-evaluation in ATLAS's offline software is warranted. We show new results of using GPU accelerated calculations in ATLAS's offline software environment using the ATLAS offline/analysis (xAOD) Event Data Model. We compare the performance and flexibility of a couple of the available GPU programming methods, and show how different memory management setups affect our ability to offload different types of calculations to a GPU efficiently.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Impact of delayed neutron precursor mobility in fissile solution systems

A research version of the Monte Carlo software package MCNP6 is modified to incorporate advection and diffusion of delayed neutron precursors, resulting in the emission of delayed neutrons at locations different from the original fission sites. Results of two test problems, a pipe carrying flowing fissile solution and a sphere of fissile solution with precursor diffusion, show that the fission product mobility tends to perturb the fundamental mode, has a negative reactivity effect, and, perhaps most importantly, causes a decrease in the effective delayed neutron fraction. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Dual Alpha/Gamma Imaging Tool to Manage Decommissioning Operations

The knowledge of the radiological state of a nuclear plant under decommissioning is a key factor at any stage of the project: from the initial characterization (to define the best scenario and the main dismantling steps), during the monitoring of the decontamination operations, for the waste management and, last but not least, for the final controls. During a facility's operation, a clear view of the process radiological level is equally necessary, in order to plan maintenance scheduling and optimize interventions by personnel. Radiation protection teams generally ensure worker radiological safety, and also supply dose mappings for each of the areas associated with typical spectra. In most cases, this mapping does not give enough information to be used as input data when preparing maintenance or clean-up work. With advances in activity modeling calculation codes (using 3D), the way measurements are made to recover the best input radiological data on site is a key factor. Nuclear instrumentation is still in progress and the evolution of the technologies and software allow us to get imaging information in real time. The gamma camera is going to evolve and to become more compact and more sensitive. New portable gamma cameras have to be tested under high level dose rate. The alpha camera is also evolving: from the first prototype tested on site to solar blind alpha camera (to reduce the influence of light) to the new dual alpha/gamma prototype. (authors)

42 ENGINEERING↗

Leveraging FPGA Advantages for Quicker Data Processing for LBNF

The Long Baseline Neutrino Facility (LBNF) will deliver a 2.4 MW muon neutrino beam from Fermilab to the Deep Underground Neutrino Experiment (DUNE), requiring unprecedented precision in beamline alignment to achieve DUNE's neutrino oscillation measurement goals. Vertical misalignments of beamline components as small as 0.5 mm can contribute 6-7\% uncertainty in predicted neutrino flux, necessitating sub-0.1 mm alignment monitoring capabilities. The Horn Location Sensor (HLS) system employs frequency sweep interferometry (FSI) in a distributed hydrostatic leveling network to achieve the required precision under harsh radiation conditions up to 5000 kRad/year. Traditional FSI implementations suffer from laser sweep nonlinearities that degrade resolution and require computationally intensive post-processing corrections using gas reference cells. This work presents a real-time FPGA-based implementation of the HLS data acquisition and processing system using a sweep tracker interferometer for dynamic sweep linearization. The system utilizes a PYNQ-Z2 FPGA with programmable logic implementing parallel 16k-point FFT processing across four channels, synchronized by the sweep tracker signal to eliminate post-processing requirements. Spectral performance testing demonstrates significant improvements in peak sharpness compared to traditional fixed-frequency digitization. The FPGA implementation enables real-time displacement monitoring with processing speeds orders of magnitude faster than software-based approaches, essential for the operational requirements of LBNF's eventual distributed sensor network. This advancement in real-time FSI processing directly supports DUNE's precision neutrino physics program by providing the rapid feedback necessary for maintaining stringent beamline alignment tolerances during high-power beam operations.

Rossel, Jacob↗

Real-Time FPGA Implementation For Frequency Sweep Interferometry In The LBNF Complex

The Long Baseline Neutrino Facility (LBNF) will deliver a 2.4 MW muon neutrino beam from Fermilab to the Deep Underground Neutrino Experiment (DUNE), requiring unprecedented precision in beamline alignment to achieve DUNE's neutrino oscillation measurement goals. Vertical misalignments of beamline components as small as 0.5 mm can contribute 6-7\% uncertainty in predicted neutrino flux, necessitating sub-0.1 mm alignment monitoring capabilities. The Horn Location Sensor (HLS) system employs frequency sweep interferometry (FSI) in a distributed hydrostatic leveling network to achieve the required precision under harsh radiation conditions up to 5000 kRad/year. Traditional FSI implementations suffer from laser sweep nonlinearities that degrade resolution and require computationally intensive post-processing corrections using gas reference cells. This work presents a real-time FPGA-based implementation of the HLS data acquisition and processing system using a sweep tracker interferometer for dynamic sweep linearization. The system utilizes a PYNQ-Z2 FPGA with programmable logic implementing parallel 16k-point FFT processing across four channels, synchronized by the sweep tracker signal to eliminate post-processing requirements. Spectral performance testing demonstrates significant improvements in peak sharpness compared to traditional fixed-frequency digitization. The FPGA implementation enables real-time displacement monitoring with processing speeds orders of magnitude faster than software-based approaches, essential for the operational requirements of LBNF's eventual distributed sensor network. This advancement in real-time FSI processing directly supports DUNE's precision neutrino physics program by providing the rapid feedback necessary for maintaining stringent beamline alignment tolerances during high-power beam operations.

Rossel, A. Jacob [Fermilab; Unlisted]↗

Simulations and analysis tools for charge-exchange (d, 2 He) reactions in inverse kinematics with the AT-TPC

Charge-exchange (d, 2 He) reactions in inverse kinematics at intermediate energies are a very promising method to investigate the Gamow–Teller transition strength in unstable nuclei. A simulation and analysis software based on the attpcroot package was developed to study this type of reactions with the active-target time projection chamber (AT-TPC). The simulation routines provide a realistic detector response that can be used to understand and benchmark experimental data. Analysis tools and correction routines can be developed and tested from simulations in ATTPCROOT , because they are processed in the same way as the real data. In particular, we study the feasibility of using coincidences with beam-like particles to unambiguously identify the (d, 2 He) reaction channel, and to develop a kinematic fitting routine for future applications. More technically, the impact of space-charge effects in the track reconstruction, and a possible correction method are investigated in detail. Finally, this analysis and simulation package constitutes an essential part of the software development for the fast-beams program with the AT-TPC.

(d,2He)↗

On the Strong Scaling of the Spectral Element Solver Nek5000 on Petascale Systems. In: EASC '16 Proceedings of the Exascale Applications and Software Conference 2016, Article No. 5

The present work is targeted at performing a strong scaling study of the high-order spectral element fluid dynamics solver Nek5000. Prior studies such as [5] indicated a recommendable metric for strong scalability from a theoretical viewpoint, which we test here extensively on three parallel machines with different performance characteristics and interconnect networks, namely Mira (IBM Blue Gene/Q), Beskow (Cray XC40) and Titan (Cray XK7). The test cases considered for the simulations correspond to a turbulent flow in a straight pipe at four different friction Reynolds numbers Reτ = 180, 360, 550 and 1000. Considering the linear model for parallel communication we quantify the machine characteristics in order to better assess the scaling behaviors of the code. Subsequently sampling and profiling tools are used to measure the computation and communication times over a large range of compute cores. We also study the effect of the two coarse grid solvers XXT and AMG on the computational time. Super-linear scaling due to a reduction in cache misses is observed on each computer. The strong scaling limit is attained for roughly 5000-10,000 degrees of freedom per core on Mira, 30,000 - 50,0000 on Beskow, with only a small impact of the problem size for both machines, and ranges between 10,000 and 220,000 depending on the problem size on Titan. This work aims at being a reference for Nek5000 users and also serves as a basis for potential issues to address as the community heads towards exascale supercomputers.

Offermans, Nicolas↗

FY2021 Status Report on the Computing Systems for the Yucca Mountain Project TSPA-LA Models and Testing of Selected Process Models

Sandia National Laboratories continued evaluation of the total system performance assessment (TSPA) for License Application (LA) computing systems for the previously considered Yucca Mountain Project (YMP). This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. The FY21 task included continued operation of the cluster; maintenance of the TSPA-LA models (with GoldSim 9.60.300); continued assessment of the status of the Infiltration Model; (a process model that feeds the TSP -LA) and preliminary assessments of the Unsaturated Zone Flow Model and the Saturated Zone Flow and Transport Model Abstraction (process models that feed the TSPA-LA). The 2014 cluster and supporting software systems are currently fully operational to support TSPA-LA type analyses.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗