Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “argonne”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Software Quality Assurance Plan: Cardinal

The Cardinal Software Quality Assurance (SQA) Program aims to provide the controls and processes necessary to enable continuous, high-quality software development while meeting user and program sponsor requirements. This SQA Plan (SQAP) delineates the SQA Program framework for Cardinal by describing the Program activities, organization, and documentation, and by clearly defining the interconnection of all Program items. It should be noted that this SQAP is aligned with the current version of the Argonne Quality Assurance Program Plan, which was designed to align with DOE O 414.1D. This SQAP is also aligned with the revision 10 of the SQAP for MOOSE and MOOSE-based applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

DASSH-F: Subchannel Based Thermal Analysis

The DASSH thermal analysis code is designed to rapidly allow a reactor design engineer to obtain flow rates requirements that satisfy peak temperature constraints in the domain. The advantage of using DASSH over a hand calculation is that it has a more rigorous treatment of the pin power distribution and coolant heat transfer within an assembly and between assemblies. The advantage of using DASSH over a conventional 3D subchannel code or a computational fluid dynamics code (CFD) is that it can obtain the desired solution in a matter of minutes in serial with minor computer memory needs. The DASSH methodology for pin lattice models is virtually identical to SUPERENERGY-2 with additional functionalities taken from follow on work to SUPERENERGY-2 done at ANL in the 1980s. DASSH today is an integral component of the Argonne Fast Reactor analysis suite for reactor design work. DASSH obtains the power distribution from a coupled neutron-gamma heating calculation in GAMSOR (including DIF3D) at each time point of a companion fuel cycle analysis calculation with REBUS. The domain in DASSH assumes a hexagonal grid typical for fast reactors with much of the geometry information taken from the DIF3D model. DASSH assumes the assemblies that are loaded into each grid position are ducted to control the coolant flow. The user can alternatively provide their own geometry and power profile instead of inheriting it from DIF3D. Considerable detail is given on the subchannel formulation of DASSH in this document. Much of the formulation and design of the code builds upon research done by previous authors with little new investigation. Thus the decisions made in developing the subchannel model used in DASSH have their origins over 50 years ago. Much of the heat transfer methodology in DASSH is built upon correlations for both the coolant mixing and heat transfer coefficients for pins and ducts. DASSH is thus not a rigorous treatment of a given problem, but a rapid assessment of the temperature field that has known limitations with respect to an experimental measurement or CFD calculation. The DASSH input and output are detailed along with usage of the software. The DASSH output provides tables of evaluated material properties and key coolant and pin temperature results. DASSH can create Python scripts that generate domain summary pictures. DASSH can also generate assembly temperature maps and VTK output files which allow the DASSH solution to be visualized. As the primary purpose of the DASSH software is to compute the coolant and fuel pin temperature distribution for a given model of a reactor, much of the output focus is giving the user quick summary tables needed to assess the performance of a given orifice flow specification. The present version of DASSH has a crude orifice search capability and a sufficient orifice flow search capability. The flow search tries to meet user specified constraints for 1) peak 2-sigma clad temperature, 2) peak coolant temperature, and 3) desired bulk outlet temperature. This document serves as the manual for the Fortran based DASSH software that was developed to replace the Python version of DASSH developed as part of the VTR program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Engineered Barrier System Research Activities at SNL: FY25 Report

This report describes research and development (R&D) activities conducted at Sandia National Laboratories (SNL) during Fiscal Year 2025 (FY25) specifically related to the Engineered Barrier System (EBS) Properties & Processes Work Package in the Spent Fuel and High-Level Waste Disposition (SFHLWD) Campaign supported by the United States (U.S.) Department of Energy (DOE). SNL activities focus on understanding EBS component evolution and interactions within the EBS, as well as interactions between the host media and the EBS. The team represented in this report consists of individuals from SNL, Argonne National Laboratory (Advanced Photon Source), and Vanderbilt University. The activities represented in this report include development of anion sorbent materials for buffer formulations, properties of pure bentonite and bentonite mixtures, and characterization of cement interfaces relevant to the EBS. The SNL EBS activities also leverage interactions with EBS teams from other national laboratories, and international collaborations to ensure that the DOE program is active and abreast of the latest advances in nuclear waste disposal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Requirements Description of DASSH-F

This report reviews the modeling and simulation capabilities of Argonne National Laboratory’s DASSH code that is used in present reactor analysis activities. These capabilities will be used to establish the set of verification tasks necessary to verify DASSH for use on commercial projects. A similar approach was taken for the PERSENT, REBUS and DIF3D software packages. The DASSH program is a thermal analysis code designed to rapidly allow a reactor design engineer to obtain flow rates requirements that satisfy peak temperature constraints in the domain. DASSH is a follow-on development to the SE2-ANL software and SUPERENERGY-2 software that it is based upon. DASSH was designed to account for both neutron and gamma heating and is inherently connected to the GAMSOR part of the ARC suite of fast reactor analysis software. SE2-ANL is a developed piece of software from the 1980s while DASSH is a modern implementation with notable improvements in geometry handling. The most important upgrade of DASSH relative to SE2-ANL is that it can analyze multiple time points in a single run where SE2-ANL can only treat a single time point. This allows the user to understand the impact of and search the flow distribution for the entire operational period of a reactor design considering pressure drop, peak coolant and fuel temperatures, and thermal striping. DASSH has three input paths that have to be verified. The first input path builds the geometry and power distribution based upon the DIF3D model but ignores the gamma heating aspects of the problem. The second input path also builds the geometry from the DIF3D model but it takes the neutron and gamma heating distributions from GAMSOR. The third input path is to take the geometry and power distribution directly from user input (i.e. not coupled to DIF3D or GAMSOR). DASSH also has many built in correlations for material properties along with a user defined specification of the fuel, structure, and coolant properties. There are correlations for flow split, mixing, pressure drop, and heat transfer coefficients (subchannel rather than a direct methodology). In total, verification of DASSH will require an extensive testing to cover all possible user features of the software.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

2025 LDRD Annual Report

This summary report provides an overview of all LDRD projects at Argonne National Laboratory that concluded in Fiscal Year 2025. Many projects are funded for multiple years, the fiscal year for each project is indicated by the first four digits of the LDRD project number.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

First Axionlike Particle Results from a Broadband Search for Wavelike Dark Matter in the 44 to 52 μ eV Range with a Coaxial Dish Antenna

We present the results from the first axionlike particle search conducted using a dish antenna. The experiment was conducted at room temperature and sensitive to axionlike particles in the 44 – 52 μ eV range (10.7–12.5 GHz). The novel dish antenna geometry was proposed by the BREAD Collaboration and previously used to conduct a dark photon search in the same mass range. To allow for axionlike particle sensitivity, the BREAD dish antenna was placed in a 3.9 T solenoid magnet at Argonne National Laboratory. In the presence of a magnetic field, axionlike dark matter converts to photons at the conductive surface of the reflector. The signal is focused onto a custom coaxial horn antenna and read out with a low-noise radio-frequency receiver. No evidence of axionlike dark matter was observed in this mass range and we place the most stringent laboratory constraints on the axion-photon coupling strength, g a γ γ , in this mass range at 90% confidence.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

CHICOX, a heavy-ion detection system for GRETA

The CHICOX detection system is an array of position sensitive parallel plate avalanche counters used for heavy ion detection in in-beam particle-gamma coincidence experiments. CHICOX, an upgrade of the CHICO2 array, is geometrically compatible with the GRETINA and GRETA gamma-ray arrays and provides an angular resolution sufficient to utilize the excellent position resolution of GRETINA/GRETA. CHICOX was successfully commissioned and fielded as an auxiliary detector to GRETINA in a campaign of stable-beam Coulomb excitation experiments at the ATLAS facility of Argonne National Laboratory. We report here on the design and in-beam performance of the CHICOX array.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Raw Lidar and Camera Data Synchronized with Precipitation and Present Weather Data

As part of the sensor characterization task of the SMART 2.0 project, this dataset includes raw data from three spinning lidars ([Ouster OS2-128](https://ouster.com/products/scanning-lidar/os2-sensor/), [Velodyne Puck (VLP-16)](https://velodynelidar.com/products/puck/), and [Velodyne Ultra Puck (VLP-32)](https://velodynelidar.com/products/ultra-puck/)), one camera ([Mako G-319](https://www.alliedvision.com/en/camera-selector/detail/mako/g-319/)), and one present weather sensor ([Vaisala FD-70](https://www.vaisala.com/en/products/weather-environmental-sensors/forward-scatter-fd70)). All data were synchronized, with the log start time indicated in the file name (HHMMSS). The data can be filtered by date, log time (HHMMSS), sensor, frame ID, and weather classification. These data were gathered statically at the Argonne Testbed for Multiscale Observational Science (ATMOS). Two target stop signs were placed in view of the sensors to contribute a target for comparing sensor data under different conditions. The weather data for each day are stored in netCDF “.nc” files. The lidar data contain the X, Y, Z, intensity, reflectivity, and ring from Ouster OS2-128 rev6, Velodyne VLP-16, and Velodyne VLP-32 lidars. ![raw lidar image](LiDAR_pointcloud_ATMOS.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Autonomie Simulation Datasets in Support of U.S. DOT-NHTSA Advanced Vehicle Technology Research

Understanding how new vehicle technologies affect fuel economy and energy use is critical to the regulatory work performed by the U.S. Department of Transportation’s National Highway Traffic Safety Administration (NHTSA), which sets Corporate Average Fuel Economy (CAFE) standards under the Energy Policy and Conservation Act of 1975. In order to support this work, Argonne National Laboratory uses Autonomie, a full-vehicle simulation tool, to evaluate advanced powertrain architectures and their effects on vehicle energy consumption and performance. A wide range of vehicle classes has been assessed (i.e., internal combustion engine vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, battery-electric vehicles, and fuel cell electric vehicles), as well as the effects of various technology improvements such as lightweighting, aerodynamic refinements, and low-rolling-resistance tires. Simulations have been run across multiple drive cycles to capture fuel and electricity use under realistic operating conditions. The resulting datasets include detailed vehicle-level results, model assumptions, and validation reports, all of which have been made publicly available through NHTSA in support of the 2023 notice of proposed rulemaking covering light-duty vehicles for model years 2027 to 2035. These data are critical to stakeholders working in fuel economy regulation, vehicle technology assessment, and energy policy analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

WM2024 Symposia Student Poster - ARG-US System Remote Area Monitoring at INL Experimental Proxy Design and Early Results

The patent-pending ARG-US system uses customizable high-tech sensors and monitoring systems in conjunction with a remote network connection to provide easy and quick access to the status of nuclear and radiological facilities and storage containers. In a partnership with the Argonne National Laboratory and the Idaho National Laboratory, the research team are finding new ways to customize and test the limitations the ARG-US system. This presentation is for the student poster session.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Exploiting the Spinel Structure for Li-ion Battery Applications: A Tribute to John B. Goodenough

This review provides a personal account of career-long efforts, interwoven with the contributions of others, to exploit the [B 2 ]O 4 framework of an A[B 2 ]O 4 spinel structure for lithium-ion battery applications, where A = Li, and B is one or more metal cations. The narrative begins at the Council for Scientific and Industrial Research (CSIR) in South Africa in the mid-1970s when, in response to the Middle East oil crisis, worldwide efforts were turned to develop high-temperature sodium and lithium batteries to power electric vehicles. In 1981, results in CSIR's program on a high-temperature lithium battery led to a collaborative project on room-temperature lithium cells with Prof. John B. Goodenough at Oxford University, where studies of Fe 3 O 4 , Mn 3 O 4 , and LiMn 2 O 4 cathodes led to the recognition of the broad utility of the [B2]O4 spinel framework as an anode, cathode, or solid electrolyte for rechargeable lithium cells. This finding has had a profound and lasting impact, influencing further ideas and discoveries at the CSIR, Argonne National Laboratory, and elsewhere. The narrative emphasizes the compositional versatility of the spinel structure and the opportunities to tailor the electrochemical potential and stability of a Li-ion cell.

25 ENERGY STORAGE↗
DOE OSTI2021

Utilizing ensemble learning for performance and power modeling and improvement of parallel cancer deep learning CANDLE benchmarks

Abstract Machine learning (ML) continues to grow in importance across nearly all domains in modeling to learn from data. Often a tradeoff exists between a model's ability to minimize bias and variance. In this article, we utilize ensemble learning to combine linear, nonlinear, and tree‐/rule‐based ML methods to cope with the bias‐variance tradeoff and result in more accurate models. We use the datasets collected for two parallel cancer deep learning CANDLE benchmarks, NT3 and P1B2, to build performance and power models based on hardware performance counters using single‐object and multiple‐objects ensemble learning to identify the most important counters for improvement on the Cray XC40 Theta at Argonne National Laboratory. Based on the insights from these models, we improve the performance and energy of P1B2 and NT3 by optimizing the deep learning environments TensorFlow, Keras, Horovod, and Python under the huge page size of 8 MB. Experimental results show that ensemble learning not only produces more accurate models but also provides more robust performance counter ranking. We achieve up to 61.15% performance improvement and up to 62.58% energy saving for P1B2 and up to 55.81% performance improvement and up to 52.60% energy saving for NT3 on up to 24,576 cores.

Wu, Xingfu↗
DOE OSTI2022

Performance and power modeling and prediction using MuMMI and 10 machine learning methods

Energy-efficient scientific applications require insight into how high performance computing system features impact the applications' power and performance. This insight can result from the development of performance and power models. Here, in this article, we use the modeling and prediction tool MuMMI (Multiple Metrics Modeling Infrastructure) and 10 machine learning methods to model and predict performance and power consumption and compare their prediction error rates. We use an algorithm-based fault-tolerant linear algebra code and a multilevel checkpointing fault-tolerant heat distribution code to conduct our modeling and prediction study on the Cray XC40 Theta and IBM BG/Q Mira at Argonne National Laboratory and the Intel Haswell cluster Shepard at Sandia National Laboratories. Our experimental results show that the prediction error rates in performance and power using MuMMI are less than 10% for most cases. By utilizing the models for runtime, node power, CPU power, and memory power, we identify the most significant performance counters for potential application optimizations, and we predict theoretical outcomes of the optimizations. Based on two collected datasets, we analyze and compare the prediction accuracy in performance and power consumption using MuMMI and 10 machine learning methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales

As we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical and challenging. We propose a low-overhead autotuning framework to autotune performance and energy for various hybrid MPI/OpenMP scientific applications at large scales and to explore the tradeoffs between application runtime and power/energy for energy efficient application execution, then use this framework to autotune four ECP proxy applications—XSBench, AMG, SWFFT, and SW4lite. Our approach uses Bayesian optimization with a Random Forest surrogate model to effectively search parameter spaces with up to 6 million different configurations on two large-scale HPC production systems, Theta at Argonne National Laboratory and Summit at Oak Ridge National Laboratory. The experimental results show that our autotuning framework at large scales has low overhead and achieves good scalability. Using the proposed autotuning framework to identify the best configurations, we achieve up to 91.59% performance improvement, up to 21.2% energy savings, and up to 37.84% EDP (energy delay product) improvement on up to 4096 nodes.

Autotuning↗
DOE OSTI2022

Phase Contrast X‐Ray Imaging of the Collapse of an Engineered Void in Single‐Crystal HMX

Abstract Imaging the collapse of a single void that creates a hot spot initiation site in an otherwise defect‐free explosive is challenging given the spatial and temporal scales involved in explosive systems. This work presents our attempt to examine a single hot spot mode (void collapse) in single‐crystal octahydro‐l,3,5,7‐tetranitro‐l,3,5,7‐tetrazocine (HMX) embedded in Sylgard. The hot spot heating mechanisms involved with pore collapse include adiabatic heating, jetting, and viscoplastic dissipation. Quantifying the dynamics of a pore collapse is a crucial step to understanding which mechanisms dominate during ignition events. Our experiments were conducted with a single‐stage, light‐gas gun at Argonne National Laboratory's Advanced Photon Source, applying the phase contrast imaging technique while collecting high‐speed video. The details of HMX single crystal production, defect (pore) engineering, and sample construction, along with experimental results are presented here. These results demonstrate that detailed collapse dynamics can be obtained from homogeneous, single‐crystal explosives with this approach. Qualitative comparisons are made with simulation data which show good agreement in the transition between a quasi‐symmetric pore collapse and an asymmetric collapse with jetting across the pore as measured with normalized pore area and pore circularity.

42 ENGINEERING↗
DOE OSTI2024

History of the Beer Game

This article describes the history of the Beer Game. By triangulating information from literature, archival analysis, and interviews with experts in the field, the main changes in the game over its almost 70-year history are identified. The article discusses three aspects of the game: 1) its structure (phases of its history, stocks and flows, parameters, etc.); 2) the process for playing the game; and 3) the game debrief. The structure of the Beer Game, and the process for running it, have stabilized over the years into what is now a de facto standard approach. Additional work is needed in the game debrief, specifically in the clarification of key insights and messages (depending on the context of the use of the game), in how to communicate such messages to different audiences, and in the development of support materials for its delivery. © 2024 UChicago Argonne, LLC. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

GeoSoilEnviroCARS (Sector 13) at the Advanced Photon Source: a comprehensive synchrotron radiation facility for Earth science research at ambient and extreme conditions

GeoSoilEnviroCARS (GSECARS) is a comprehensive analytical laboratory for Earth and environmental science research using X-ray beams from the Advanced Photon Source, Argonne National Laboratory. State-of-the-art instruments are available for (1) high-pressure/high- or low-temperature diffraction, total scattering, and spectroscopy (Brillouin, Raman, and VIS-IR) using the laser heated diamond anvil cell (DAC); (2) high-pressure/high-temperature diffraction, scattering, and imaging as well as acoustic emission (AE) and ultrasonics using the large-volume press (LVP); (3) powder, single crystal, and surface/interface diffraction; (4) X-ray absorption fine structure spectroscopy; (5) X-ray fluorescence microprobe analysis; and (6) microtomography. As shown here, experiments are facilitated by senior level staff who collaborate on all aspects of the analytical work including experiment design, sample preparation, data collection, data interpretation, and publication preparation. Both technical and scientific synergies occur as a result of the intimate association of the various techniques and scientists experienced in the applications of synchrotron radiation to Earth, environmental, and planetary science problems. The facility includes state-of-the-art instrumentation designed and built in-house, including custom X-ray optics, online and offline laser-based systems, specialized sample environments and positioning systems, as well as pixel-array and multi-crystal energy dispersive X-ray detectors, which are available to be shared among the experimental stations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Signatures of Thermal and Electrical Crosstalk in a Microwave Multiplexed Hard X-ray Transition Edge Sensor Array

We investigate the crosstalk between Transition-Edge Sensor (TES) pixels in a 24-pixel hard X-ray spectrometer array fabricated at the Advanced Photon Source, Argonne National Laboratory. Analysis shows thermal cross talk, possibly associated with insufficient thermalization, and rare but larger in magnitude electrical crosstalk between specific perpetrator-victim pixel combinations, potentially due to defects in the bias wiring or microwave multiplexing circuit. We use a method based on group-triggering and averaging to isolate the crosstalk response despite only having access to X-ray photon illumination uniform across the entire array. This allows us to identify thermal and electrical crosstalk between pixel pairs in repeated measurements to the level of 1 part in 1000 or better. In the array under study, the magnitude of observed crosstalk is small but comparable to the resolving power of this pixel design (E/Delta E similar to\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$E/\Delta {}E \sim$$\end{document} 1000 at 20 keV) and so potentially responsible for a degradation in energy resolution of the array at high incident photon rates. Having proven the methods to identify and quantify crosstalk in our setup, we can now consider mitigations.

Triamkitsawat, Panthita↗