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All sources NASA NTRS DOE OSTI

DOE OSTI2026

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗

DOE OSTI2016

A New Light Weight Structural Material for Nuclear Structures

Radiation shielding materials are commonly used in nuclear facilities to attenuate the background ionization radiations to a minimum level for creating a safer workplace, meeting regulatory requirements and maintaining high quality performance. The conventional radiation shielding materials have a number of drawbacks: heavy concrete contains a high amount of elements that are not desirable for an effective shielding such as oxygen, silicon, and calcium; a well known limitation of lead is its low machinability and toxicity, which is causing a major environmental concern. Therefore, an effective and environmentally friendly shielding material with increased attenuation and low mass density is desirable. Close-cell composite metal foams (CMFs) and open-cell Al foam with fillers are light-weight candidate materials that we have studied in this project. Close-cell CMFs possess several suitable properties that are unattainable by conventional radiation shielding materials such as low density and high strength for structural applications, high surface area to volume ratio for excellent thermal isolation with an extraordinary energy absorption capability. Open-cell foam is made up of a network of interconnected solid struts, which allows gas or fluid media to pass through it. This unique structure provided a further motive to investigate its application as radiation shields by infiltrating original empty pores with high hydrogen or boron compounds, which are well known for their excellent neutron shielding capability. The resulting open-cell foam with fillers will not only exhibit light weight and high specific surface area, but also possess excellent radiation shielding capability and good processability. In this study, all the foams were investigated for their radiation shielding efficiency in terms of X-ray, gamma ray and neutron. X-ray transmission measurements were carried out on a high-resolution microcomputed tomography (microCT) system. Gamma-emitting sources: 3.0mCi 60 Co, 1.8mCi 137 Cs, 13.5mCi 241 Am, and 5.0mCi 133 Ba were used for gamma-ray attenuation analysis. The evaluations of neutron transmission measurements were conducted at the Neutron Powder Diffractometer beam facility at North Carolina State University. The experimental results were verified theoretically through XCOM and Monte Carlo Z-particle Transport Code (MCNP). A mechanical investigation was performed by means of quasi-static compressive testing. Thermal characterizations were carried out through effective thermal conductivity and thermal expansion analyses in terms of high temperature guarded-comparative-longitudinal heat flow technique and thermomechanical analyzer (TMA), respectively. The experimental results were compared with analytical results obtained from, respectively, Brailsford and Major’s model and modified Turner’s model for verification. Flame test was performed in accordance with United States Nuclear Regulatory Commission (USNRC) standard. CMF sample and a 304L stainless steel control sample were subjected to a fully engulfing fire with an average flame temperature of 800°C for a period of 30 minutes. Finite Element Analysis was conducted to secure the credibility of the experimental results. This research indicates the potential of utilizing the light-weight close-cell CMFs and open-cell Al foam with fillers as shielding material replacing current heavy structures with additional advantage of high-energy absorption and excellent thermal characteristics.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Multiverse: Bayesian model selection for neural networks

Multiverse is a code repository for a set of tools for Bayesian model selection for neural networks. The goal of the tools is to provide capabilities for selecting among prior and model specifications for Bayesian neural networks. Multiverse will include tools for creating Bayesian neural networks, evaluating the Bayesian model evidence, and performing inference in Bayesian neural networks. These components are written in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning and signal processing.

Klein, Natalie↗

DOE OSTI2024

GPAW: An open Python package for electronic structure calculations

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for the implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE), providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe–Salpeter Equation, variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn–Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support for graphics processing unit (GPU) acceleration has been achieved with minor modifications to the GPAW code thanks to the CuPy library. We end the review with an outlook, describing some future plans for GPAW.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

STOMP-W

STOMP is a numerical simulator, developed by PNNL, for solving problems involving multifluid coupled flow and reactive transport in geologic media. The code has been under development at PNNL for more than twentyfive years. This release of STOMP will allow users to directly access the software, and will be limited to selected operational modes. The initial release will include STOMPW. Additional operational modes will be released depending on market trends and user needs.The STOMP simulator has been available to parties outside of PNNL via license agreements. A new trend in projects supported by the U.S. government is that software be available as open source. This release of the STOMP software will meet that need. The initial target operational mode, STOMPW, is one that solves isothermal problems involving variably saturated geologic systems with nonreactive solutes and reactive species. The capabilities of this simulator are often applied to environmental stewardship and restoration problems, such as those at the Hanford Site.

Source record↗

DOE OSTI2017

Assessing Occupant and Outdoor Air Impacts on Indoor Air Quality in New California Homes

In 2008 the State of California adopted new building codes that required the use of mechanical ventilation systems in homes that meet the requirements of ASHRAE Standard 62.2. The standard requires both a dwelling unit mechanical ventilation system and exhaust fans in kitchens and bathrooms. A field study was undertaken to evaluate the IAQ and ventilation performance of homes built to these requirements. For ventilation system performance, the airflows of all mechanical ventilation systems were measured and their use was monitored for a one-week period. To evaluate IAQ, key pollutants were measured indoors and outdoors during the week, and occupants completed satisfaction surveys. The key pollutants included: formaldehyde, humidity, PM2.5 and NO2. Passive samplers were used to determine average concentrations for the week. Active samplers were used to develop time-series results that can be used to correlate pollutant concentrations with occupant activities. Other ventilation/IAQ related parameters were also recorded, such as stove top temperatures to indicate cooking, exterior door contact switches to know when large openings were being used for ventilation and sensors to determine when clothes dryers were being used. The building envelope and duct leakage were measured to enable estimates of infiltration and duct leakage effects. This paper presents an overview of the test procedures and preliminary results from several homes. The results show that although average concentrations may be reasonable compared to available standards (with the exception of formaldehyde), occupants have a strong impact on pollutant variability and source strength and that outdoor concentrations cannot be ignored. Overall, these mechanically ventilated homes have reasonable IAQ. The homes and duct systems are moderately tight, though not excessively so, by US standards. Significant concerns have been expressed regarding compliance with the ventilation requirements in the California building code. However, almost all the ventilation systems in this study complied with the ventilation air flow requirements and on average were significantly higher than the minimum required air flow rates.

Walker, IS↗

DOE OSTI2025

The Blending ToolKit: A simulation framework for evaluation of galaxy detection and deblending

We present an open source Python library for simulating overlapping (i.e., blended) images of galaxies and performing self-consistent comparisons of detection and deblending algorithms based on a suite of metrics. The package, named Blending Toolkit (BTK), serves as a modular, flexible, easy-to-install, and simple-to-use interface for exploring and analyzing systematic effects related to blended galaxies in cosmological surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time (LSST). BTK has three main components: (1) a set of modules that perform fast image simulations of blended galaxies, using the open source image simulation package GalSim; (2) a module that standardizes the inputs and outputs of existing deblending algorithms; (3) a library of deblending metrics commonly defined in the galaxy deblending literature. In combination, these modules allow researchers to explore the impacts of galaxy blending in cosmological surveys. Additionally, BTK provides researchers who are developing a new deblending algorithm a framework to evaluate algorithm performance and make principled comparisons with existing deblenders. BTK includes a suite of tutorials and comprehensive documentation. The source code is publicly available on GitHub at https://github.com/LSSTDESC/BlendingToolKit.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Accessorizing Building Science – A Web Platform to Support Multiple Market Transformation Programs

As demand for improved energy efficiency in homes increases, builders need information on the latest findings in building science, rapidly ramping-up energy codes, and technical requirements for labeling programs. The Building America Solution Center is a Department of Energy (DOE) website containing hundreds of expert guides designed to help residential builders install efficiency measures in new and existing homes. Builders can package measures with other media for customized content. Website content provides technical support to market transformation programs such as ENERGY STAR and has been cloned and adapted to provide content for the Better Buildings Residential Program. The Solution Center uses the Drupal open source content management platform to combine a variety of media in an interactive manner to make information easily accessible. Developers designed a unique taxonomy to organize and manage content. That taxonomy was translated into web-based modules that allow users to rapidly traverse structured content with related topics, and media. We will present information on the current design of the Solution Center and the underlying technology used to manage the content. The paper will explore development of features, such as “Field Kits” that allow users to bundle and save content for quick access, along with the ability to export PDF versions of content. Finally, we will discuss development of an Android based mobile application, and a visualization tool for interacting with Building Science Publications that allows the user to dynamically search the entire Building America Library.

Madison, Michael C.↗

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 OSTI2016

AiiDA: automated interactive infrastructure and database for computational science

Computational science has seen in the last decades a spectacular rise in the scope, breadth, and depth of its efforts. Notwithstanding this prevalence and impact, it is often still performed using the renaissance model of individual artisans gathered in a workshop, under the guidance of an established practitioner. Great benefits could follow instead from adopting concepts and tools coming from computer science to manage, preserve, and share these computational efforts. We illustrate here our paradigm sustaining such vision, based around the four pillars of Automation, Data, Environment, and Sharing. We then discuss its implementation in the open-source AiiDA platform (http://www.aiida.net), that has been tuned first to the demands of computational materials science. AiiDA’s design is based on directed acyclic graphs to track the provenance of data and calculations, and ensure preservation and searchability. Remote computational resources are managed transparently, and automation is coupled with data storage to ensure reproducibility. Last, complex sequences of calculations can be encoded into scientific workflows. We believe that AiiDA’s design and its sharing capabilities will encourage the creation of social ecosystems to disseminate codes, data, and scientific workflows.

Materials Science↗

DOE OSTI2018

QMCPACK : an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

QMCPACK is an open source quantum Monte Carlo package for ab-initio electronic structure calculations. It supports calculations of metallic and insulating solids, molecules, atoms, and some model Hamiltonians. Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo. QMCPACK uses Slater-Jastrow type trial wave functions in conjunction with a sophisticated optimizer capable of optimizing tens of thousands of parameters. The orbital space auxiliary field quantum Monte Carlo method is also implemented, enabling cross validation between different highly accurate methods. The code is specifically optimized for calculations with large numbers of electrons on the latest high performance computing architectures, including multicore central processing unit (CPU) and graphical processing unit (GPU) systems. We detail the program’s capabilities, outline its structure, and give examples of its use in current research calculations. The package is available at http://www.qmcpack.org.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

An Open-Source Python Package for CFD Solution Verification

Informed decision-making using computational fluid dynamics (CFD) results requires quantifying the errors and uncertainties of a simulation. Verification, validation, and uncertainty quantification (VVUQ) methods were developed to address this need and have matured. However, these VVUQ analyses are often non-trivial and require CFD analysts and practitioners to have specific skill sets. This has led to the uneven adoption of VVUQ analyses, in part, based on the availability of software tools to aid CFD analysts and practitioners. Solution verification, a procedure to evaluate the accuracy of a simulation by estimating potential errors arising from the computational model and computing the uncertainties without comparing to results from a physical system, is one of the lagging VVUQ analyses as the absence of software has forced CFD analysts and practitioners to develop their own codes or piece together incomplete software from across the internet. This work presents an opensource Python package, CFDverify, to lower the barrier of entry and fill in the technological gap in solution verification. CFDverify also provides a streamlined framework to remove some potential errors in post-processing CFD results. The hope is that CFDverify can improve the quality and quantity of CFD solution verification in scientific and research studies and attract interest in developing a communal tool. This paper describes the design, features, and an example use of CFDverify.

Weinmeister, Justin [ORNL] (ORCID:0000000160090237↗

DOE OSTI2016

Assessment of the Analysis Capability for Core-wide PWR Pellet-Clad Interaction (PCI) Screening

The Level 1 Milestone, L1:CASL.P13.03, “Assess the analysis capability for core-wide PWR Pellet-Clad Interaction (PCI) screening and demonstrate detailed 3-D analysis on selected sub-region.”, has been completed by the Fuels, Materials and Chemistry and Physics Integration focus areas of CASL. This report illustrates the application of VERA simulation to PWR core-wide PCI screening, with emphasis on the multi-dimensional analysis capabilities of BISON fuel performance code. The VERA codes utilized in this effort are: the fuel performance code BISON and the VERA-CS sub-element, which combines the neutron transport code MPACT and the thermal-hydraulics code COBRA-TF (CTF). The target reactor for this work is Watts Bar Unit 1, Cycles 6 and 7, selected on the basis that PCI failures had occurred during power start-up in both cycles, despite the moderate power levels, which offered an interesting test of the code’s veracity and a particularly challenging condition for this Milestone’s assessment. The analysis began by performing BISON-IN-VERA, i.e. VERA-CS + BISON, quarter-core depletion calculations, from which limiting assemblies and limiting fuel rods were selected using a four-parameter selection criterion: high power, high temperature, small gap thickness and high cladding hoop stress. The cladding material being Westinghouse Zirlo, the analysis utilized a new material model developed for this cladding by CASL’s FMC team using open literature sources. The VERA-CS + BISON analysis resulted in identifying 51 limiting rods as candidates for more detailed PCI analysis using stand-alone BISON, employing local 2D and 3D geometric models. This local-effects BISON analysis provided detailed PCI failure assessment, considering the impact of power histories on the two potential sources of PCI failure: the classical SCC-PCI and the missing pellet surface geometry MPS-PCI. The 51-rod analyses of Watts Bar Unit 1 cycle 6 and 7 revealed that the classical SCC-PCI stress levels were well below the failure threshold determined in a previous CASL study, which implicated the other mode of failure, namely MPS-PCI. Considering MPS defects to be the root cause for the failure, the local-effects calculations was repeated using MPS defect sizes equal to and larger than Westinghouse quality assurance standards. Initial results of this new analysis showed a significant increase in the cladding stress, indicating that an MPS may have been present in cycle 6 and 7 for the failure to occur. In order to determine the size of MPS needed for cycle 6 and 7 rods to fail, a sensitivity study using 2-D and 3-D models was performed. The results showed cladding hoop stresses, while remaining below the failure level for an MPS of equal size to the acceptance standard, continued to increase as the size of the MPS increased. This report has demonstrated the use of BISON, in consort with VERA’s simulation methodology, for core-wide PCI failure screening capability. Utilizing this demonstration, and emulating the PCI margin analysis methodology developed in the EPRI PCI guidelines, BISON-IN-VERA simulation can be used very effectively to develop core power histories to minimize PCI failure potential.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

GX: a GPU-native gyrokinetic turbulence code for tokamak and stellarator design

GX is a code designed to solve the nonlinear gyrokinetic system for low-frequency turbulence in magnetized plasmas, particularly tokamaks and stellarators. In GX, our primary motivation and target is a fast gyrokinetic solver that can be used for fusion reactor design and optimization along with wide-ranging physics exploration. Here, this has led to several code and algorithm design decisions, specifically chosen to prioritize time to solution. First, we have used a discretization algorithm that is pseudospectral in the entire phase space, including a Laguerre–Hermite pseudospectral formulation of velocity space, which allows for smooth interpolation between coarse gyrofluid-like resolutions and finer conventional gyrokinetic resolutions and efficient evaluation of a model collision operator. Additionally, we have built GX to natively target graphics processors (GPUs), which are among the fastest computational platforms available today. Finally, we have taken advantage of the reactor-relevant limit of small $\rho _*$ by using the radially local flux-tube approach. In this paper we present details about the gyrokinetic system and the numerical algorithms used in GX to solve the system. We then present several numerical benchmarks against established gyrokinetic codes in both tokamak and stellarator magnetic geometries to verify that GX correctly simulates gyrokinetic turbulence in the small $\rho _*$. Moreover, we show that the convergence properties of the Laguerre–Hermite spectral velocity formulation are quite favourable for nonlinear problems of interest. Coupled with GPU acceleration, which we also investigate with scaling studies, this enables GX to be able to produce useful turbulence simulations in minutes on one (or a few) GPUs and higher fidelity results in a few hours using several GPUs. GX is open-source software that is ready for fusion reactor design studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

Plant phenotyping is typically a time-consuming and expensive endeavor, requiring large groups of researchers to meticulously measure biologically relevant plant traits, and is the main bottleneck in understanding plant adaptation and the genetic architecture underlying complex traits at population scale. In this work, we address these challenges by leveraging few-shot learning with convolutional neural networks to segment the leaf body and visible venation of 2,906 Populus trichocarpa leaf images obtained in the field. In contrast to previous methods, our approach (a) does not require experimental or image preprocessing, (b) uses the raw RGB images at full resolution, and (c) requires very few samples for training (e.g., just 8 images for vein segmentation). Traits relating to leaf morphology and vein topology are extracted from the resulting segmentations using traditional open-source image-processing tools, validated using real-world physical measurements, and used to conduct a genome-wide association study to identify genes controlling the traits. In this way, the current work is designed to provide the plant phenotyping community with (a) methods for fast and accurate image-based feature extraction that require minimal training data and (b) a new population-scale dataset, including 68 different leaf phenotypes, for domain scientists and machine learning researchers. All of the few-shot learning code, data, and results are made publicly available.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Kosh

Kosh allows codes to store, query, share data via an easy-to-use Python API. Kosh lies on top of Sina and as a result can use any database backend supported by Sina. In adition Kosh aims to make data access and sharing as simple as possible. Via "loaders" kosh can open files associated with datasets in a seemless fashion independently of the actual file format. Kosh's loader can also load data in different format, although numpy is the most usual output type. Once loaded data from sources, data can be further processed via "transformers"

Doutriaux, Charles↗

DOE OSTI2014

SU-E-T-253: Open-Source Automatic Software for Quantifying Biological Assays of Radiation Effects

Purpose: Clonogenic cell survival is a common assay for quantifying the effect of drugs and radiation. Manual counting of surviving colonies can take 30–90seconds per plate, a major limitation for large studies. Currently available automatic counting tools are not easily modified for radiation oncology research. Our goal is to provide an open-source toolkit for precise, accurate and fast analysis of biological assays in radiation oncology. Methods: As an example analysis, we used HeLa cells incubated with gadolinium nanoparticles prior to irradiation. After treatment, the cells are grown for 14days to allow for colony formation. To analyze the colony growth, we capture images of each dish for archiving and automatic computer-based analysis. A FujifilmX20 camera is placed at the top of a box setup, 20cm above the sample, which is backlit by a LED lamp placed at the bottom of the box. We use a Gaussian filter (width=1.3mm) and color threshold (19–255). The minimum size for a colony to be counted is 1mm. For this example, 20 dishes with a large range of colonies were analyzed. Each dish was counted 3 times manually by 3 different users and then compared to our counter. Results: Automatic counting of cell colonies takes an average of 7seconds, enabling the analysis process to be accelerated 4–12 times. The average precision of the automatic counter was 1.7%. The Student t-test demonstrated the non-significant differences between the two counting methods (p=0.64). The ICC demonstrated the reliability of each method with ICC>0.999 (automatic) and ICC=0.95 (manual). Conclusion: We developed an open-source automatic toolkit for the analysis of biological assays in radiation oncology and demonstrated the accuracy, precision and effort savings for clonogenic cell survival quantification. This toolkit is currently being used in two laboratories for routine experimental analysis and will be made freely available on our departmental website.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

ParFlow

ParFlow is an open-source, modular, parallel watershed flow model. It includes fully-integrated overland flow, the ability to simulate complex topography, geology and heterogeneity and coupled land-surface processes including the land-energy budget, biogeochemistry and snow (via CLM). It is multi-platform and runs with a common I/O structure from laptop to supercomputer. ParFlow is the result of a long, multi-institutional development history and is now a collaborative effort between CSM, LLNL, UniBonn and UCB. ParFlow has been coupled to the mesoscale, meteorological code ARPS and the NCAR code WRF.

Smith, Steven↗