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All sources NASA NTRS DOE OSTI

DOE OSTI2021

LIM1TR: Lithium-Ion Modeling with 1-D Thermal Runaway (V.1.0)

LIM1TR (Lithium-Ion Modeling with 1-D Thermal Runaway) is an open-source code that uses the finite volume method to simulate heat transfer and chemical kinetics on a quasi 1-D domain. The target application of this software is to simulate thermal runaway in systems of lithium-ion batteries. The source code for LIM1TR can be found at https://github.com/ajkur/lim1tr. This user guide details the steps required to create and run simulations with LIM1TR starting with setting up the Python environment, generating an input file, and running a simulation. Additional details are provided on the output of LIM1TR as well as extending the code with custom reaction models. This user guide concludes with simple example analyses of common battery thermal runaway scenarios. The corresponding input files and processing scripts can be found in the “Examples” folder in the on-line repository, with select input files included in the appendix of this document.

25 ENERGY STORAGE↗

DOE OSTI2020

Trigger-DAQ and Slow Controls Systems in the Mu2e Experiment

The muon campus program at Fermilab includes the Mu2e experiment that will search for a charged-lepton flavor violating processes where a negative muon converts into an electron in the field of an aluminum nucleus, improving by four orders of magnitude the search sensitivity reached so far. Mu2e's Trigger and Data Acquisition System (TDAQ) uses otsdaq as its solution. Developed at Fermilab, otsdaq uses the artdaq DAQ framework and art analysis framework, under the-hood, for event transfer, filtering, and processing. otsdaq is an online DAQ software suite with a focus on flexibility and scalability, while providing a multi-user, web-based, interface accessible through the Chrome or Firefox web browser. The detector Read Out Controller (ROC), from the tracker and calorimeter, stream out zero-suppressed data continuously to the Data Transfer Controller (DTC). Data is then read over the PCIe bus to a software filter algorithm that selects events which are finally combined with the data flux that comes froma Cosmic Ray Ve to System (CRV). A Detector Control System (DCS) for monitoring, controlling, alarming, and archiving has been developed using the Experimental Physics and Industrial Control System (EPICS) Open Source Platform. The DCS System has also been itegrated into otsdaq. The installation of the TDAQ and the DCS systems in the Mu2e building is planned for 2021-2022, and a prototype has been built at Fermilab's Feynman Computing Center. We report here on the developments and achievements of the integration of Mu2e's DCS system into the online otsdaq software.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Vulnerabilities in Artificial Intelligence and Machine Learning Applications and Data

Artificial intelligence (AI) applications driven by machine learning (ML) are transformational technologies within the international nuclear security regime. Advancements realized by AI—faster and improved data insights, more efficient and automated processes, reductions in human error—enable nuclear security applications such as behavior analysis for insider threat mitigation, source tracking of stolen nuclear material, and facial recognition software for physical protection. In addition to the advantages, however, there are also inherent vulnerabilities and threats associated with its use and risk mitigations must be built into any AI/ML-enabled systems. This work provides a background on AI and ML and different data types used in the field, including open-source intelligence information (OSINT) that is discoverable by AI tools and application data that are used by AI tools for decision-making and automation. Current and potential AI applications and vulnerabilities related to their use within the nuclear security regime are also discussed.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2026

Dataset describing two reference models for full-spectral lighting and daylight simulations together with implementations for two software systems

A dataset of two spectral lighting simulation reference models - one office and one factory hall - is presented. It aims to demonstrate and support full-spectral daylight and electric lighting simulations and facilitate evaluation of non-visual effects of light. The dataset includes Rhino CAD geometry, comprehensive spectral material and light source data and window system BSDF data. Example implementations in the two software tools, Radiance and OWL, enable reproducible workflows and support adoption in other software. The dataset is openly available on Zenodo. The office model reproduces Room 518 at the University of Innsbruck, including a west-facing façade and interior furnishings. The factory hall model follows the proposed geometry in the European standard 15193 for building energy performance. Interior reflectances in the office were measured in-situ using a handheld spectrometer. Exterior spectra and factory hall materials matching specified reflectances were obtained from an online spectral materials database. Glazing transmittance was derived from IGDB data using LBNL Optics/WINDOW. BSDFs for venetian blinds at various tilt angles, and for a diffusing pane adapted from the Complex Glazing Database, were generated in WINDOW. Luminaires in both models are specified with photometric files (Eulumdat/IES) and lamp spectra (Fluorescent 840, 4000 K LED). The provided example implementations (Radiance, OWL) include prepared input data and scripts to run first spectral simulations; example results are also included. The dataset is prepared to support reuse by researchers, designers and software developers for method validation, software engineering and comparison, and development of spectral metrics and controls.

Geisler-Moroder, David↗

DOE OSTI2018

Automated Approach for Construction of Long-Term, Data-Intensive Watershed Models

Watershed models such as the Hydrological Simulation Program in FORTRAN (HSPF) are frequently used to analyze large-scale water quantity and water quality issues. The construction of HSPF models is a difficult and time-consuming process, because it requires compilation of extensive quantities of data into formatted files followed by a simultaneous fitting of many uncertain parameters. Because of these complications, studies are often limited to calibration periods of only a few years even when analyzing long time-scale issues such as climate and land-use changes that are difficult or impossible to reproduce. High-level, open source programming languages provide an environment for automating the extraction and processing of various sources of data in addition to the calibration process required by HSPF. Recently developed software can be used to build HSPF input files, run simulations, and postprocess simulation results using the Python programming language. The combination of tools in Python, public data sets on the Internet, and software extensions enables rapid development of long-term, reproducible, and sophisticated models for new hydrologic insight. Herein, the utility of these tools is illustrated by developing an automated 30-year HSPF model with a Nash-Sutcliffe efficiency of 0.88 for monthly flows and 0.75 for daily flows in a simulation time of approximately 3h. The integration of HSPF with a high-level programming language creates opportunities to more rigorously explore model assumptions, calibration methods, and alternative data sets.

Lampert, Dave J↗

DOE OSTI2021

Continuous Integration, In-Code Documentation, and Automation for Nuclear Quality Assurance Conformance

The Multiphysics Object Oriented Simulation Environment (MOOSE) is an open-source, finite element framework for solving highly coupled sets of nonlinear equations. The development of the framework and applications occurs concurrently using an agile, continuous-integration software package. Included in the framework is an in-code, extensible documentation system. Using these two tools in union with the repository management tools GitHub and GitLab, a software quality plan was created and followed such that MOOSE and a MOOSE-based application (BISON) have been shown to meet the American Society of Mechanical Engineers’ Nuclear Quality Assurance-1 standard. The approach relies heavily on automation for both testing and documentation. The resulting effort demonstrates that a rigorous software quality plan may be implemented that incurs a minimal impact on day-to-day development of the software, satisfying the stringent guidelines necessary to operate the software in a safety function within a nuclear facility.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

NEB-Tool (Multiple Non Energy Benefits Tool) [SWR-24-08]

A user friendly, graphical, open-source implementation of the multiple benefits framework to non-energy-benefits incorporating additional aspects to make the tool effective for use in the United States. The software may be distributed as web, desktop and/or mobile apps. Development is ongoing at the related JUSTIFI repository, found here: https://github.com/ORNL-AMO/JUSTIFI

Perr-Sauer, Jordan↗

DOE OSTI2014

TH-C-12A-12: Veritas: An Open Source Tool to Facilitate User Interaction with TrueBeam Developer Mode

Purpose: To address the challenges of creating delivery trajectories and imaging sequences with TrueBeam Developer Mode, a new open-source graphical XML builder, Veritas, has been developed, tested and made freely available. Veritas eliminates most of the need to understand the underlying schema and write XML scripts, by providing a graphical menu for each control point specifying the state of 30 mechanical/dose axes. All capabilities of Developer Mode are accessible in Veritas. Methods: Veritas was designed using QT Designer, a ‘what-you-is-what-you-get’ (WYSIWIG) tool for building graphical user interfaces (GUI). Different components of the GUI are integrated using QT's signals and slots mechanism. Functionalities are added using PySide, an open source, cross platform Python binding for the QT framework. The XML code generated is immediately visible, making it an interactive learning tool. A user starts from an anonymized DICOM file or XML example and introduces delivery modifications, or begins their experiment from scratch, then uses the GUI to modify control points as desired. The software automatically generates XML plans following the appropriate schema. Results: Veritas was tested by generating and delivering two XML plans at Brigham and Women's Hospital. The first example was created to irradiate the letter ‘B’ with a narrow MV beam using dynamic couch movements. The second was created to acquire 4D CBCT projections for four minutes. The delivery of the letter ‘B’ was observed using a 2D array of ionization chambers. Both deliveries were generated quickly in Veritas by non-expert Developer Mode users. Conclusion: We introduced a new open source tool Veritas for generating XML plans (delivery trajectories and imaging sequences). Veritas makes Developer Mode more accessible by reducing the learning curve for quick translation of research ideas into XML plans. Veritas is an open source initiative, creating the possibility for future developments and collaboration with other researchers. I am an employee of Varian Medical Systems.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2025

Lessons Learned and Scalability Achieved When Porting Uintah to DOE Exascale Systems

A key challenge faced when preparing codes for Department of Energy (DOE) exascale systems was designing scalable applications for systems featuring hardware and software not yet available at leadership-class scale. With such systems now available, it is important to evaluate scalability of the resulting software solutions on these target systems. One such code designed with the exascale DOE Aurora and DOE Frontier systems in mind is the Uintah Computational Framework, an open-source asynchronous many-task (AMT) runtime system. To prepare for exascale, Uintah adopted a portable MPI+X hybrid parallelism approach using the Kokkos performance portability library (i.e., MPI+Kokkos). This paper complements recent work with additional details and an evaluation of the resulting approach on Aurora and Frontier. Results are shown for a challenging benchmark demonstrating interoperability of 3 portable codes essential to Uintah-related combustion research. These results demonstrate single-source portability across Aurora and Frontier with scaling characteristics shown to 3,072 Aurora nodes and 9,216 Frontier nodes. In addition to showing results run to new scales on new systems, this paper also discusses lessons learned through efforts preparing Uintah for exascale systems.

Holmen, John [ORNL] (ORCID:0000000259342641)↗

DOE OSTI2018

CMS Analysis and Data Reduction with Apache Spark

Experimental Particle Physics has been at the forefront of analyzing the world's largest datasets for decades. The HEP community was among the first to develop suitable software and computing tools for this task. In recent times, new toolkits and systems for distributed data processing, collectively called "Big Data" technologies have emerged from industry and open source projects to support the analysis of Petabyte and Exabyte datasets in industry. While the principles of data analysis in HEP have not changed (filtering and transforming experiment-specific data formats), these new technologies use different approaches and tools, promising a fresh look at analysis of very large datasets that could potentially reduce the time-to-physics with increased interactivity. Moreover these new tools are typically actively developed by large communities, often profiting of industry resources, and under open source licensing. These factors result in a boost for adoption and maturity of the tools and for the communities supporting them, at the same time helping in reducing the cost of ownership for the end-users. In this talk, we are presenting studies of using Apache Spark for end user data analysis. We are studying the HEP analysis workflow separated into two thrusts: the reduction of centrally produced experiment datasets and the end-analysis up to the publication plot. Studying the first thrust, CMS is working together with CERN openlab and Intel on the CMS Big Data Reduction Facility. The goal is to reduce 1 PB of official CMS data to 1 TB of ntuple output for analysis. We are presenting the progress of this 2-year project with first results of scaling up Spark-based HEP analysis. Studying the second thrust, we are presenting studies on using Apache Spark for a CMS Dark Matter physics search, comparing Spark's feasibility, usability and performance to the ROOT-based analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Porting the Kitten Lightweight Kernel Operating System to RISC-V

Hardware design in high-performance computing (HPC) is often highly experimental. Exploring new designs is difficult and time-consuming, requiring lengthy vendor cooperation. RISC-V is an open-source processor ISA that improves the accessibility of chip design, including the ability to do hardware/software co-design using open-source hardware and tools. Co-design allows design decisions to easily flow across the hardware/software boundary and influence future design ideas. However, new hardware designs require corresponding software to drive and test them. Conventional operating systems like Linux are massively complex and modification is time-prohibitive. In this paper, we describe our port of the Kitten lightweight kernel operating system to RISC-V in order to provide an alternative to Linux for conducting co-design research. Kitten's small code base and simple resource management policies are well matched for quickly exploring new hardware ideas that may require radical operating system modifications and restructuring. Our evaluation shows that Kitten on RISC-V is functional and provides similar performance to Linux for single-core benchmarks. This provides a solid foundation for using Kitten in future co-design research involving RISC-V.

Gordon, Nick↗

DOE OSTI2025

SpacelyProject/spacely-docs

Quinn, Adam [Fermi National Accelerator Laboratory↗

DOE OSTI2025

An Open-Source Framework for Rapid Validation of Scientific ASICs

Spacely is an open-source framework for the post-silicon validation of analog, digital, and mixed-signal ASICs (Application-Specific Integrated Circuits) which maximizes the reuse of hardware and software, reducing the time taken to achieve meaningful test results. Spacely specifically addresses the needs of small, flexible ASIC design teams commonly found in academia or research institutions which benefit most from sharing the overhead of test stand creation between many unique ASIC designs. Spacely is a set of software, firmware, and design practices. It targets two primary hardware platforms (NI-PXI and Caribou) as well as offering extensible support for bench instruments. Spacely provides a high-level Python interface to all test hardware for accessibility, while also giving more sophisticated teams the opportunity to integrate custom test firmware. The design principles of Spacely are presented in brief. Current documentation is available at https://github.com/SpacelyProject/spacely-docs.

Quinn, Adam [Fermilab]↗

DOE OSTI2024

An Open-Source Framework for Rapid Validation of Scientific ASICs

Spacely is an open-source framework for the post-silicon validation of analog, digital, and mixed-signal ASICs (Application-Specific Integrated Circuits) which maximizes the reuse of hardware and software, reducing the time taken to achieve meaningful test results. Spacely specifically addresses the needs of small, flexible ASIC design teams commonly found in academia or research institutions which benefit most from sharing the overhead of test stand creation between many unique ASIC designs. Spacely is a set of software, firmware, and design practices. It targets two primary hardware platforms (NI-PXI and Caribou) as well as offering extensible support for bench instruments. Spacely provides a high-level Python interface to all test hardware for accessibility, while also giving more sophisticated teams the opportunity to integrate custom test firmware. The design principles of Spacely are presented, along with a demonstrative example of using Spacely to test a pixel detector readout ASIC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Sampling electronic structure quadratic unconstrained binary optimization problems (QUBOs) with Ocean and Mukai solvers

The most advanced D-Wave Advantage quantum annealer has 5000+ qubits, however, every qubit is connected to a small number of neighbors. As such, implementation of a fully-connected graph results in an order of magnitude reduction in qubit count. To compensate for the reduced number of qubits, one has to rely on special heuristic software such as qbsolv, the purpose of which is to decompose a large quadratic unconstrained binary optimization (QUBO) problem into smaller pieces that fit onto a quantum annealer. In this work, we compare the performance of the open-source qbsolv which is a part of the D-Wave Ocean tools and a new Mukai QUBO solver from Quantum Computing Inc. (QCI). The comparison is done for solving the electronic structure problem and is implemented in a classical mode (Tabu search techniques). The Quantum Annealer Eigensolver is used to map the electronic structure eigenvalue-eigenvector equation to a QUBO problem, solvable on a D-Wave annealer. We find that the Mukai QUBO solver outperforms the Ocean qbsolv with one to two orders of magnitude more accurate energies for all calculations done in the present work, both the ground and excited state calculations. This work stimulates the further development of software to assist in the utilization of modern quantum annealers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

An Open Source Extensible Smart Energy Framework

Aggregated distributed energy resources are the subject of much interest in the energy industry and are expected to play an important role in meeting our future energy needs by changing how we use, distribute and generate electricity. This energy future includes an increased amount of energy from renewable resources, load management techniques to improve resiliency and reliability, and distributed energy storage and generation capabilities that can be managed to meet the needs of the grid as well as individual customers. These energy assets are commonly referred to as Distributed Energy Resources (DER). DERs rely on a means to communicate information between an energy provider and multitudes of devices. Today DER control systems are typically vendor-specific, using custom hardware and software solutions. As a result, customers are locked into communication transport protocols, applications, tools, and data formats. Today’s systems are often difficult to extend to meet new application requirements, resulting in stranded assets when business requirements or energy management models evolve. By partnering with industry advisors and researchers, an implementation DER research platform was developed called the Smart Energy Framework (SEF). The hypothesis of this research was that an open source Internet of Things (IoT) framework could play a role in creating a commodity-based eco-system for DER assets that would reduce costs and provide interoperable products. SEF is based on the AllJoynTM IoT open source framework. The demonstration system incorporated DER assets, specifically batteries and smart water heaters. To verify the behavior of the distributed system, models of water heaters and batteries were also developed. An IoT interface for communicating between the assets and a control server was defined. This interface supports a series of “events” and telemetry reporting, similar to those defined by current smart grid communication standards. The results of this effort demonstrated the feasibility and application potential of using IoT frameworks for the creation of commodity-based DER systems. All of the identified commodity-based system requirements were met by the AllJoyn framework. By having commodity solutions, small vendors can enter the market and the cost of implementation for all parties is reduced. Utilities and aggregators can choose from multiple interoperable products reducing the risk of stranded assets. Based on this research it is recommended that interfaces based on existing smart grid communication protocol standards be created for these emerging IoT frameworks. These interfaces should be standardized as part of the IoT framework allowing for interoperability testing and certification. Similarly, IoT frameworks are introducing application level security. This type of security is needed for protecting application and platforms and will be important moving forward. Recommendations are that along with DER-based data model interfaces, platform and application security requirements also be prescribed when IoT devices support DER applications.

25 ENERGY STORAGE↗

DOE OSTI2017

Open Source Release of NJOY2016 and NJOY21

NJOY has been the standard for nuclear data processing for many decades. NJOY is a comprehensive computer code used to produce point-wise and multigroup nuclear data application libraries from cross sections and related quantities obtained from evaluated nuclear data in the Evaluated Nuclear Data Format (ENDF). NJOY was first publicly released in 1977 and distributed by what is now the Radiation Safety Information Computational Center (RSICC) at Oak Ridge National Laboratory and the National Energy Software Center (NESC) at Argonne National Laboratory. From that time until the release of NJOY2012, NJOY has been distributed by RSICC and made available to researchers outside the United States by agreements between RSICC and the NEA Databank. NJOY2012 was distributed by the Feynman Center at Los Alamos National Laboratory which did not have agreements with the NEA Databank, thus making it more difficult for non US citizens to obtain copies of NJOY2012. Furthermore, NJOY has had export control restrictions preventing some researchers from obtaining NJOY at all. Two new versions of NJOY have been released, NJOY2016 and NJOY21, in January of 2017. Both NJOY2016 and NJOY21 have been released with no export control restrictions and are distributed with an open-source license. This is a big departure from previous releases and impacts not only who has access to NJOY, but also how updates are made available to users and how collaboration is facilitated among interested developers. In addition to distributing NJOY2016 and NJOY21 with an open-source license, these two new versions provide new capabilities for NJOY which will maintain NJOY as the standard for nuclear data processing into the foreseeable future. We report in this summary about the changes that come with these two new versions of NJOY and how this impacts the users and long-time contributors to NJOY.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2019

A Scalable Online Monitoring System Based on Elasticsearch for Distributed Data Acquisition in Cms

The part of the CMS Data Acquisition (DAQ) system responsible for data readout and event building is a complex network of interdependent distributed applications. To ensure successful data taking, these programs have to be constantly monitored in order to facilitate the timeliness of necessary corrections in case of any deviation from specified behaviour. A large number of diverse monitoring data samples are periodically collected from multiple sources across the network. Monitoring data are kept in memory for online operations and optionally stored on disk for post-mortem analysis. We present a generic, reusable solution based on an open source NoSQL database, Elasticsearch, which is fully compatible and non-intrusive with respect to the existing system. The motivation is to benefit from an off the-shelf software to facilitate the development, maintenance and support efforts. Elasticsearch provides failover and data redundancy capabilities as well as a programming language independent JSON-over-HTTP interface. The possibility of horizontal scaling matches the requirements of a DAQ monitoring system. The data load from all sources is balanced by redistribution over an Elasticsearch cluster that can be hosted on a computer cloud. In order to achieve the necessary robustness and to validate the scalability of the approach the above monitoring solution currently runs in parallel with an existing in-house developed DAQ monitoring system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗