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DOE OSTI2024

NetDuid

SAND2025-00238O The NetDuid library is a software tool that can manage and manipulate DHCP Unique Identifiers (DUIDs) in .NET applications. It simplifies the process of working with DUIDs by offering functionalities such as parsing, constructing, comparing, checking equality, and formatting DUIDs. The library supports various types of DUIDs, making it easier for developers to handle these identifiers in their applications. The program fills a gap in the .NET/C# ecosystem by providing a specialized tool for managing DHCP Unique Identifiers, offering a straightforward and efficient solution for developers. 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.

Engelhardt, Robert↗

DOE OSTI2025

Calculation Of Neutrino Flux

The CONFLUX software framework, Calculation Of Neutrino FLUX, is built with the goal to simplify and standardize the calculation. CONFLUX packages three methods to calculate neutrinos generated from reactor neutrinos or individual beta decays with common nuclear data and beta theories for direct cross-method comparison. The software prepacked the latest nuclear database, including ENDF.B/VIII, JEFF 3.3, and ENSDF, as well as methods to process the uncertainties. It also allows customized nuclear data and beta theories and user generated time dependent reactor models for convenient adjustment of fission products, theoretical corrections.

Zhang, Xianyi [Lawrence Livermore National Laborat↗

DOE OSTI2020

Hindsight logging for model training

In modern Machine Learning, model training is an iterative, experimental process that can consume enormous computation resources and developer time. To aid in that process, experienced model developers log and visualize program variables during training runs. Exhaustive logging of all variables is infeasible, so developers are left to choose between slowing down training via extensive conservative logging, or letting training run fast via minimalist optimistic logging that may omit key information. As a compromise, optimistic logging can be accompanied by program checkpoints; this allows developers to add log statements post-hoc, and "replay" desired log statements from checkpoint---a process we refer to as hindsight logging. Unfortunately, hindsight logging raises tricky problems in data management and software engineering. Done poorly, hindsight logging can waste resources and generate technical debt embodied in multiple variants of training code. In this paper, we present methodologies for efficient and effective logging practices for model training, with a focus on techniques for hindsight logging. Our goal is for experienced model developers to learn and adopt these practices. To make this easier, we provide an open-source suite of tools for Fast Low-Overhead Recovery (flor) that embodies our design across three tasks: (i) efficient background logging in Python, (ii) adaptive periodic checkpointing, and (iii) an instrumentation library that codifies hindsight logging for efficient and automatic record-replay of model-training. Model developers can use each flor tool separately as they see fit, or they can use flor in hands-free mode, entrusting it to instrument their code end-to-end for efficient record-replay. Our solutions leverage techniques from physiological transaction logs and recovery in database systems. Evaluations on modern ML benchmarks demonstrate that flor can produce fast checkpointing with small user-specifiable overheads (e.g. 7%), and still provide hindsight log replay times orders of magnitude faster than restarting training from scratch.

Computer Science↗

DOE OSTI2024

Seedling nitrogen uptake and rhizodeposition between mycorrhizal types

Tree mycorrhizal associations are associated with patterns in N cycling and soil organic matter (SOM) storage, however, we still lack a mechanistic understanding of what tree and fungal traits drive these patterns and how they will respond to global changes in soil N availability. To address this knowledge gap, we investigated how arbuscular mycorrhizal (AM)- and ectomycorrhizal (EcM)-associated seedlings alter rhizodeposition in response to increased inorganic N acquisition. Specifically, we conducted this greenhouse experiment in a sealed labeling chamber with an enriched 13Carbon atmosphere and 15Nitrogen enriched fertilizer over the course of five months from April 2021 - August 2021. To include the variability across tree species, we grew eight species of seedlings belonging to eight families that were either arbuscular (Acer rubrum, Nyssa sylvatica, Thuja occidentalis, and Prunus seritina) or ectomycorrhizal-associated (Quercus rubra, Tilia americana, Pinus strobus, and Betula lenta). We measured rhizodeposition (mg 13C), plant N uptake from fertilizer (mg N), net soil carbon, and the abundance of mycorrhizal fungi (ITS sequencing and qPCR). We also characterized fungal (ITS2) and bacterial (16S) soil communities.The data from this project are ".csv" files that can up downloaded into a folder, and then run in the associated R markdown scripts after changing the source folder location at the top of the script. These data include raw outputs and processed files (using the R markdown files) for seedling growth and biomass, 15N content, soil 13C content, raw reads and processed file versions for fungal and bacterial ASVS, and a final summary file used for modeling. R software is needed to run these data, and the packages needed are listed at the top of the R markdown file.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

UTrain Manual for Training Administrators

This Institutional Training Administrative Procedure provides the business rules that must be followed when working in UTrain. As commercial off-the-shelf software with customizations, UTrain cannot address all the implementation business requirements, and thus, administrative business rules and processes were defined and documented. Many business rules were incorporated into the UTrain training materials. UTrain is the Laboratory’s official learning management system. UTrain is the system of record for all Laboratory training, qualification, certification, and worker authorization. All training at LANL must be documented in UTrain. The detailed steps of how to operate UTrain are contained in the UTrain courses and training manuals and in the UTrain job aids, not in this document.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2020

Reduction of CO 2 Emissions Through Lightweight Body Panels (Project Final Report)

Lightweight construction is an integral part of Volkswagen’s overall strategy of reducing CO 2 emissions. Due to its low cost, steel is the most commonly used material for automotive exterior body panels today. Unfortunately, steel has a high density, resulting in a relatively low specific strength. Glass fiber based sheet molding compounds (SMC) provide high properties in combination with lower density. The high specific strength of SMC offers an enormous lightweight potential. To unlock the full potential of SMC materials in combination with cutting edge manufacturing processes, Volkswagen Group of America worked together with IACMI (Institute for Advanced Composites Manufacturing Innovation) and the academic partners: University of Tennessee Knoxville, Purdue University and Michigan State University; as well as the industry partners: Ashland, IDI, Owens Corning and Continental Structural Plastics. Leveraging the expertise of all project partners, reaching over the entire supply chain the project demonstrated the potential of these materials. This report will highlight the major steps in the development process on the way to technology readiness for SMC using the example of the Volkswagen Atlas Liftgate. Over the 36-month period of the project, the work focused on three R&D areas: material development, design and simulation, and development of the manufacturing process. Material selection included alternative fibers and resin systems, and accounted for material availability, properties, and cost-efficiency. The work undertaken in the field of design and simulation has pushed the envelope of short fiber reinforced thermoset molding compound process simulation. Design iterations were virtually tested, while the final design was used to validate the simulation software against physical parts. Manufacturing development used cutting-edge technology, while experts along the supply chain were working together to ensure the best possible results. In the final stage of the project, liftgates were molded, trimmed, bonded, painted and assembled before exhaustive testing. The result is an e-coat (electrophoretic dip coating) capable Class-A SMC liftgate, which is ready for high-volume production, and can be used as a technology demonstrator. The prototypes manufactured in the scope of this work have exhibited a mass reduction for the Volkswagen Atlas liftgate of up to 35% compared to the series production steel version, without a degradation of the functionalities.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Waste Compliance and Tracking System (WCATS) Version 3 Requirements Document

This document describes the end-user requirements for the Waste Compliance and Tracking System (WCATS) project in accordance with the WCATS Software Quality Management Plan, EPC-WMP-WCATSPLAN-001. The WCATS application shall support the generation, characterization, processing, and shipment of LANL radioactive, hazardous, and industrial waste. Regulatory drivers include RCRA hazardous waste, DOT shipping, NNSA nuclear material control and accountability, DOE nuclear safety, TSDF permit, and transuranic waste certification requirements. The system will utilize a task-based architecture that supports the spectrum of treatment, storage, disposal, administrative, and characterization based unit operations necessary to manage waste from cradle to grave. The application design shall readily accommodate new facilities, processes, workflow, signature requirements, and so forth, via end-user established metadata. WCATS will provide support for representing waste storage and disposal facilities, buildings, rooms, and grid layouts (x, y, z) to support waste and radioactive material inventory management. Nuclear material at risk (MAR), DOE hazard rating (e.g., Category II facility) compliance per DOE-STD-1027, and permit inventory requirements will be configurable for any storage or disposal facility, or waste operation, and the system will automatically evaluate and enforce those requirements. In addition, the application will support the characterization and management of the entire range of hazardous and radioactive wastes (TRU, MTRU, LLW, MLLW, hazardous waste, etc.) that might be colocated or processed at a permitted facility. Some capabilities not found in traditional systems include user-defined tank systems for liquid waste, user-defined work paths (i.e., sequence of operations), and an equipment subsystem for tracking the calibration, maintenance, and inspection of tools used to process waste, such as torque wrenches, scales, pH probes, etc. The application incorporates a desktop and mobile user interface as shown in Figure 1. The mobile interface supports field operations, such as waste item characterization, intra-facility transfers, internal and external audits, and shipment preparation and receipt.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Evaluation of Apex Alpha with LabWare-LIMS Data Reduction for Alpha Analyses

Savannah River Site's Environmental Bioassay Laboratory is migrating its laboratory information management system (LIMS) from SQL-LIMS to Oracle Labware-LIMS (LW-LIMS) systems to align with the Department of Energy's cyber security policies. Concurrently with the LIMS upgrade, the current VMS based Alpha Measurement System (AMS) software is being replaced with Apex Alpha software to reduce other cyber vulnerabilities, streamline procedural production aspects of data handling, and improve outdated reduction processes to align the program with requirements outlined in ANSI N13.30. The primary technical changes which are being implemented are: - Reagent contributions are added in data reduction, - Moving average background equivalent activity are used for gross signal corrections, - Measured uncertainty of both are included in the decision level and propagated uncertainty, - Tracer levels are increased for precision and accuracy improvements, and - Reports are modified for compliance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Finite Element Analysis System Workflow Tools

A collection of MATLAB functions and class definitions called System Workflow Tools (SWFT) are available to semi-automate steps in the simulation process. Some of these steps are often simple and routine for smaller finite element models, but if done directly by an analyst can quickly become labor intensive, cumbersome, and error prone for larger, system level models. Some of SWFT’s capabilities demonstrated in this report includes writing Sierra input decks and processing Quantities of Interest (QOI) from results files. SWFT also writes scripts in order to utilize other software programs such as Cubit (separating system level CAD into subassemblies and components, creating nodesets and sidesets), DAKOTA (ensemble management), and ParaView (contour plots and animations). Detailed commands and workflows from mesh generation to report generation are provided as examples for analysts to utilize SWFT capabilities.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Advanced Precipitation and Boundary Layer Data Products Derived from ARM Radar Wind Profilers

This research project was successful in delivering on four main objectives. First, software was developed to accurately calculate 915-MHz radar wind profiler (RWP) spectrum moments from the recorded Doppler velocity power spectra. Second, software was developed to calibrate the RWP reflectivity factor using collocated surface disdrometer observations. Third, the Python processing code was documented and given to the ARM Infrastructure to produce ARM ‘b level’ calibrated RWP products. Fourth, calibrated RWP products were uploaded to the ARM Archive as PI Products for 10 years of SGP RWP observations and for GoAmazon and TRACER field campaign RWP observations. In addition to working with RWP observations, this research project also worked with KAZR observations to distinguish insects from boundary layer clouds to help improve the ARSCL cloud mask product. The PI worked with senior and early career ARM funded scientists at BNL exploring how to include calibrated RWP moments into future versions of the ARSCL product.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Validation of Maui PSCAD Model: Motivation, Methodology, and Lessons Learned: Preprint

As power systems become increasingly dependent on inverter-based resources, the dominant physical and control interactions that determine system stability may no longer be accurately captured in positive sequence dynamic simulation tools; electromagnetic transient (EMT) simulations may be needed. This paper describes the process of creating and validating an EMT model of the entire Maui island transmission system in PSCAD software. The model is validated against the utility's PSSE model and against field data for an event that consisted of a single-phase fault followed by a generation trip. The methodology and lessons learned are summarized here.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2020

UQpy: A general purpose Python package and development environment for uncertainty quantification

In this paper, we present the UQpy software toolbox, an open-source Python package for general uncertainty quantification (UQ) in mathematical and physical systems. The software serves as both a user-ready toolbox that includes many of the latest methods for UQ in computational modeling and a convenient development environment for Python programmers advancing the field of UQ. The paper presents an introduction to the software's architecture and existing capabilities, divided in the code in a set of modules centered around different UQ tasks such as sampling methods, generation of random processes and random fields, probabilistic inverse modeling, reliability analysis, surrogate modeling, and active learning. The paper also highlights the importance of the RunModel module, which is used to drive simulations in the uncertainty analyses performed in UQpy. This module conveniently allows the user to define computational models directly in Python, or to run simulations from a third-party software in serial or in parallel. To illustrate the various capabilities, two examples are tracked throughout the paper and analyzed repeatedly for various UQ tasks. The first is a Python model solving a nonlinear structural dynamics problem, used to illustrate UQpy's capabilities in sampling and forward propagation of high dimensional random vectors (stochastic processes), and probabilistic inference. The second model is a third-party Abaqus finite element model solving the thermomechanical response of a beam structure. This example is used to illustrate UQpy's capabilities in variance reduction sampling techniques, reliability analysis, surrogate modeling and active learning techniques.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry

Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

WorkJournalMaker (WJMaker) v0.5

The software generates and maintains daily work journal entries in text format, via a web browser. The journal entries are saved in a structured directory file tree on the system running the software. The software also incorporates a database so that it can track the location of files in the file system and various other metadata. The software allows the users to access their journal entries either through the browser or as discrete text files, facilitating sharing and open science. Additionally, to assist with the yearly PMP process, this tool connects to LLM APIs to provide summarization of the journal entries on a month-by-month or weekly basis. The advantage over similar technologies such as Apple Notes (extremely popular for notetaking) is that the instant software does not force the user to stay inside the Apple ecosystem, since it allows for export of the user's text files. This facilitates open science, so that researchers who use the tool can easily transfer their research notes to any other system. The WebJournalMaker repository is here: https://github.com/lbnl-science-it/WorkJournalMaker The WebJournalMaker repository is forked from the JournalSummarizer: https://github.com/tyfong-lbl/JournalSummarizer and builds on its code. I wrote the code for both of these software repos, using generative AI.

Fong, Timothy [Lawrence Berkeley National Laborato↗

DOE OSTI2022

Mesoflow: An Open-Source Reacting Flow Solver for Catalysis at Mesoscale

We present the capabilities and software performance metrics of our open-source continuum solver for catalysis, Mesoflow, developed specifically for modeling transport and chemistry at the mesoscale. Our solver utilizes Cartesian block-structured adaptive mesh refinement to resolve complex catalyst surface morphologies directly obtained from X-ray tomography data. An immersed boundary based formulation enables rapid representation of complex geometries prevalent in most mesoporous catalyst interfaces. The solver is developed on top of open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Our flexible software framework enables integration of complex chemical mechanisms at heterogenous interfaces and time-split algorithms for circumventing highly disparate reaction and flow time-scales. Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPUs) compared to a single processor for representative problem sizes (2 million cell mesh). We will also present a brief introduction on how to build and use this software for application problems pertaining to catalytic upgrading and gas transport within porous catalyst particles.

adaptive meshing↗

DOE OSTI2022

Future Trends in Nuclear Physics Computing

In nuclear physics (NP) today the study of quarks, gluons and their strong interactions extends across a broad research program at a varied range of collaborative scales, from a few collaborators up to large experiments at scales comparable to those typical of high energy physics (HEP). Overall, the software and computing efforts vary accordingly, from pragmatic do-it-yourself approaches among a few, to substantial organized software and computing activities within large experiments. With new experiments starting up and on the horizon [1], and rapidly increasing data volumes [2, 3] and processing demands even at small experiments, the NP community has in recent years been thinking about the next generation of data processing and analysis workflows that will maximize the science output. One context for this discussion has been a series of workshops, “Future Trends in Nuclear Physics Computing” [4]. The most recent in this series took place in Fall 2020, organized by the authors together with colleagues. The workshop focused on identifying the unique aspects of software and computing in NP, and discussing how the NP community could strengthen common efforts and chart a path forward for the next decade, sure to be an exciting one with rich ongoing scientific programs at Brookhaven National Laboratory (BNL), Jefferson Lab (JLab), and other NP facilities, and culminating in datataking at the Electron-Ion Collider (EIC) [5,6,7] in the early 2030s. Without claiming to present a collective view from the workshop and discussions since—fortunately this is not expected of us in this opinion editorial—we offer here our reflections on the topic, informed by the workshop and the summary we authored with our colleagues [8], as well as discussions and developments in the eventful time since.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

LPBF Processability of NiTiHf Alloys: Systematic Modeling and Single-Track Studies

Research into the processability of NiTiHf high-temperature shape memory alloys (HTSMAs) via laser powder bed fusion (LPBF) is limited; nevertheless, these alloys show promise for applications in extreme environments. This study aims to address this limitation by investigating the printability of four NiTiHf alloys with varying Hf content (1, 2, 15, and 20 at. %) to assess their suitability for LPBF applications. Solidification cracking is one of the main limiting factors in LPBF processes, which occurs during the final stage of solidification. To investigate the effect of alloy composition on printability, this study focuses on this defect via a combination of computational modeling and experimental validation. To this end, solidification cracking susceptibility is calculated as Kou’s index and Scheil–Gulliver model, implemented in Thermo-Calc/2022a software. An innovative powder-free experimental method through laser remelting was conducted on bare NiTiHf ingots to validate the parameter impacts of the LPBF process. The result is the processability window with no cracking likelihood under diverse LPBF conditions, including laser power and scan speed. This comprehensive investigation enhances our understanding of the processability challenges and opportunities for NiTiHf HTSMAs in advanced engineering applications.

36 MATERIALS SCIENCE↗

DOE OSTI2020

TuckerMPI: A Parallel C++/MPI Software Package for Large-scale Data Compression via the Tucker Tensor Decomposition

With this study, our goal is compression of massive-scale grid-structured data, such as the multi-terabyte output of a high-fidelity computational simulation. For such data sets, we have developed a new software package called TuckerMPI, a parallel C++/MPI software package for compressing distributed data. The approach is based on treating the data as a tensor, i.e., a multidimensional array, and computing its truncated Tucker decomposition, a higher-order analogue to the truncated singular value decomposition of a matrix. The result is a low-rank approximation of the original tensor-structured data. Compression efficiency is achieved by detecting latent global structure within the data, which we contrast to most compression methods that are focused on local structure. In this work, we describe TuckerMPI, our implementation of the truncated Tucker decomposition, including details of the data distribution and in-memory layouts, the parallel and serial implementations of the key kernels, and analysis of the storage, communication, and computational costs. We test the software on 4.5 and 6.7 terabyte data sets distributed across 100 s of nodes (1,000 s of MPI processes), achieving compression ratios between 100 and 200,000×, which equates to 99--99.999% compression (depending on the desired accuracy) in substantially less time than it would take to even read the same dataset from a parallel file system. Moreover, we show that our method also allows for reconstruction of partial or down-sampled data on a single node, without a parallel computer so long as the reconstructed portion is small enough to fit on a single machine, e.g., in the instance of reconstructing/visualizing a single down-sampled time step or computing summary statistics. The code is available at https://gitlab.com/tensors/TuckerMPI.

97 MATHEMATICS AND COMPUTING↗