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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

LLNL Response to the DOE ASCR RFI, "Stewardship of Software for Scientific and High-Performance Computing"

For decades, Lawrence Livermore National Laboratory (LLNL) has been engaged in significant research, development, and support for software to enable scientific computing and, particularly, the use of high performance computing (HPC) in the NNSA mission space. In particular, the move in the mid-1990’s to simulation as a leading component of stockpile stewardship through the ASCI and the successor ASC programs, as well as the need for reliable data acquisition and control software for the National Ignition Facility, have been important drivers in building expertise in production-quality software development at LLNL. LLNL has also been a leader in the DOE SciDAC FASTMath Institute and the DOE Exascale Computing Project (ECP), both of which have striven to make scientific computing software – in particular, the enabling technologies underpinning simulation capabilities – more widely adopted and sustainable. As such, we believe that our experience can inform the broader goal of software stewardship for scientific and high-performance computing. LLNL strongly supports the formation of a new DOE ASCR program element in software stewardship and sustainment. Historically, DOE ASCR has funded applied mathematics and computer science research that has led to the development of important new capabilities and algorithms that are expressed as artifacts in research software. Such frameworks, libraries, and tools have seldom been directly funded to address the important issues of code maintenance, documentation, robustness, and community building. Software engineering and support have typically been done on the side in support of the ASCR-driven research products. DOE funding priorities have been slow to recognize that good software engineering, the kind that ensures research investments have more adoption and longevity, requires significant resources. Based upon our experiences, we have prepared this response to highlight the concerns and issues we believe to be important as DOE ASCR considers its role in scientific software stewardship. We believe that role is important and will require a significant investment of new funding to legitimately support the technologies past and future DOE ASCR investments have and will produce to facilitate their uptake and adoption in the broader scientific computing community. Following a summary of our involvement in scientific software development, the remainder our response is organized around the nine topics specifically identified in the RFI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

LipidMiner: A Software for Automated Identification and Quantification of Lipids from Multiple Liquid Chromatography-Mass Spectrometry Data Files

We have developed a tool for automated, high-throughput analysis of LC-MS/MS data files, which greatly simplifies LC-MS based lipidomics analysis. Our results showed that LipidMiner is accurate and comprehensive in identification and quantification of lipid molecular species. In addition, the workflow implemented in LipidMiner is not limited to identification and quantification of lipids. If a suitable metabolite library is implemented in the library matching module, LipidMiner could be reconfigured as a tool for general metabolomics data analysis. It is of note that LipidMiner currently is limited to singly charged ions, although it is adequate for the purpose of lipidomics since lipids are rarely multiply charged,[14] even for the polyphosphoinositides. LipidMiner also only processes file formats generated from mass spectrometers from Thermo, i.e. the .RAW format. In the future, we are planning to accommodate file formats generated by mass spectrometers from other predominant instrument vendors to make this tool more universal.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2017

Applications of NMR and computational methodologies to study protein dynamics

The overwhelming evidence now illustrates the defining role of atomic-scale protein flexibility in biological events such as allostery, cell signaling, and enzyme catalysis. Over the years, spin relaxation nuclear magnetic resonance (NMR) has provided significant insights on the structural motions occurring on multiple time frames over the course of a protein life span. The present review article aims to illustrate to the broader community how this technique continues to shape many areas of protein science and engineering, in addition to being an indispensable tool for studying atomic-scale motions and functional characterization. Continuing developments in underlying NMR technology alongside software and hardware developments for complementary computational approaches now enable methodologies to routinely provide spatial directionality and structural representations traditionally harder to achieve solely using NMR spectroscopy. In addition to its well-established role in structural elucidation, we present recent examples that illustrate the combined power of selective isotope labeling, relaxation dispersion experiments, chemical shift analyses, and computational approaches for the characterization of conformational sub-states in proteins and enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Methodology to Assess No Touch Audit Software Using Simulated Building Utility Data

This report describes a methodology developed for assessing the performance of no touch building audit tools and presents results for an available tool. Building audits are conducted in many commercial buildings to reduce building energy costs and improve building operation. Because the audits typically require significant input obtained by building engineers, they are usually only affordable for larger commercial building owners. In an effort to help small building and business owners gain the benefits of an audit at a lower cost, no touch building audit tools have been developed to remotely analyze a building's energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Open and Extensible Control & Analytics Platform for Synchrophasor Data (Final Report)

The objective of the Open and Extensible Control and Analytics (openECA) Platform for Phasor Data project was to develop an open source software platform that significantly accelerates the production, use, and ongoing development of real-time decision support tools, automated control systems, and off-line planning systems that (1) incorporate synchrophasor data and (2) enhance system reliability while enabling the North American Electric Reliability Corporation (NERC) operating functions of reliability coordinator, transmission operator, and/or balancing authority to be executed more effectively.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

SIMBER: the Simula Berkeley Education and Research Collaboration (CRADA Final Report)

The SIMBER project is centered around advancing the state-of-the-art in the science of modelling of the human heart and leveraging the collaborations between leading research groups at the University of California Berkeley (UC Berkeley), the Lawrence Berkeley National Laboratory (Berkeley Lab), and Simula Research Laboratory (Simula). In particular, the following areas of expertise are shared and expanded through this project: “heart-on-chip” experimental systems from UC Berkeley, mathematical modelling of the heart from Simula, and supercomputing software from Simula and Berkeley Lab. This intersection of expertise is already enabling the development of novel tools and knowledge that produce more accurate models of the human heart in both health and disease, which in turn are leading to drug screening technologies that make cardiac drug development faster, cheaper and more humane.

Li, Xiaoye Sherry [Lawrence Berkeley National Labo↗
DOE OSTI2018

openECA Platform and Analytics Alpha Test Results

The objective of the Open and Extensible Control and Analytics (openECA) Platform for Phasor Data project is to develop an open source software platform that significantly accelerates the production, use, and ongoing development of real-time decision support tools, automated control systems, and off-line planning systems that (1) incorporate high-fidelity synchrophasor data and (2) enhance system reliability while enabling the North American Electric Reliability Corporation (NERC) operating functions of reliability coordinator, transmission operator, and/or balancing authority to be executed more effectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

openECA Platform and Analytics Beta Demonstration Results

The objective of the Open and Extensible Control and Analytics (openECA) Platform for Phasor Data project is to develop an open source software platform that significantly accelerates the production, use, and ongoing development of real-time decision support tools, automated control systems, and off-line planning systems that (1) incorporate high-fidelity synchrophasor data and (2) enhance system reliability while enabling the North American Electric Reliability Corporation (NERC) operating functions of reliability coordinator, transmission operator, and/or balancing authority to be executed more effectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Behind the Meter Storage for Electric Vehicle Charging, Electrochemical and Thermal Energy Storage, and Solar Photovoltaic

In response to the potentially large and irregular demand from EVs, along with changing load profiles from buildings with on-site generation, utilities are evaluating multiple options for managing dynamic loads, including time-of-use pricing, demand charges, battery storage, and curtailment of variable generation. Buildings, as well as commercial, public, and workplace EV charging operations, can use a combination of electrochemical battery storage and thermal energy storage coupled with on-site generation to manage energy costs as well as provide resiliency and reliability for EV charging and building energy loads. We are completing a behind the meter storage analysis that focuses on determining the optimal system designs and energy flows for thermal and electrochemical behind the meter storage with on-site solar photovoltaic (PV) generation enabling electric vehicle charging in various climates, building types, and utility rate structures. In completing this analysis, we have developed a tool that combines existing battery models via the System Advisor Model (SAM) and building modeling software via EnergyPlus into a single interface. This tool allows us to simulate a building with a detailed battery model to properly size the battery, thermal energy storage, and solar PV systems to maximize profit for the system owner. This also allows us to assess how the battery degrades under various supervisory control dispatch algorithms to control charging/discharging; we can also see how thermal energy storage is created and used to complement the battery to reduce thermal loads in the building. With this project, we can analyze new batteries that are designed specifically for energy storage, rather than designed to be extremely energy dense for electric vehicle applications, using battery lifetime models from other national labs and the existing SAM battery model, which has detailed lifetime and degradation parameters. We can also assess novel thermal storage technologies by integrating them into the whole building energy simulation program EnergyPlus. Because the model calls both SAM and EnergyPlus, required inputs need to be compatible for both models. These inputs include, on a high-level, the following: weather files, building and electric vehicle load profiles, electricity rate tariff information, and system cost information for the stationary battery, solar PV, and thermal storage system. The various buildings we are studying for this analysis are retail big-box grocery store, commercial office building, fleet vehicle depot and operations facility, multi-family residential, and electric vehicle charging station. For these different applications, the battery and thermal storage will be dispatched differently, and the various technologies are sized differently to optimize cost.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2019

XScan: An Integrated Tool for Understanding Open Source Community-Based Scientific Code

Many scientific communities have adopted community-based models that integrate multiple components to simulate whole system dynamics. The community software projects’ complexity, stems from the integration of multiple individual software components that were developed under different application requirements and various machine architectures, has become a challenge for effective software system understanding and continuous software development. The paper presents an integrated software toolkit called X-ray Software Scanner (in abbreviation, XScan) for a better understanding of large-scale community-based scientific codes. Our software tool provides support to quickly summarize the overall information of scientific codes, including the number of lines of code, programming languages, external library dependencies, as well as architecture-dependent parallel software features. The XScan toolkit also realizes a static software analysis component to collect detailed structural information and provides an interactive visualization and analysis of the functions. We use a large-scale community-based Earth System Model to demonstrate the workflow, functions and visualization of the toolkit. We also discuss the application of advanced graph analytics techniques to assist software modular design and component refactoring.

Zheng, Weijian↗
DOE OSTI2015

openPMD-viewer

Many simulation software produce data in the form of a set of field values or of a set of particle positions. (one such example is that of particle-in-cell codes, which produce data on the electromagnetic fields that they simulate.) However, each particular software uses its own particular format and layout, for the output data. This makes it difficult to compare the results of different simulation software, or to have a common visualization tool for these results. However, a standardized layout for fields and particles has recently been developed: the openPMD format ( HYPERLINK "http://www.openpmd.org/"www.openpmd.org) This format is open- source, and specifies a standard way in which field data and particle data should be written. The openPMD format is already implemented in the particle-in-cell code Warp (developed at LBL) and in PIConGPU (developed at HZDR, Germany). In this context, the proposed software (openPMD-viewer) is a Python package, which allows to access and visualize any data which has been formatted according to the openPMD standard. This package contains two main components: - a Python API, which allows to read and extract the data from a openPMD file, so as to be able to work with it within the Python environment. (e.g. plot the data and reprocess it with particular Python functions) - a graphical interface, which works with the ipython notebook, and allows to quickly visualize the data and browse through a set of openPMD files. The proposed software will be typically used when analyzing the results of numerical simulations. It will be useful to quickly extract scientific meaning from a set of numerical data.

Lehe, Remi↗
DOE OSTI2015

openPMD-viewer

Many simulation software produce data in the form of a set of field values or of a set of particle positions. (one such example is that of particle-in-cell codes, which produce data on the electromagnetic fields that they simulate.) However, each particular software uses its own particular format and layout, for the output data. This makes it difficult to compare the results of different simulation software, or to have a common visualization tool for these results. However, a standardized layout for fields and particles has recently been developed: the openPMD format ( HYPERLINK "http://www.openpmd.org/"www.openpmd.org) This format is open- source, and specifies a standard way in which field data and particle data should be written. The openPMD format is already implemented in the particle-in-cell code Warp (developed at LBL) and in PIConGPU (developed at HZDR, Germany). In this context, the proposed software (openPMD-viewer) is a Python package, which allows to access and visualize any data which has been formatted according to the openPMD standard. This package contains two main components: - a Python API, which allows to read and extract the data from a openPMD file, so as to be able to work with it within the Python environment. (e.g. plot the data and reprocess it with particular Python functions) - a graphical interface, which works with the ipython notebook, and allows to quickly visualize the data and browse through a set of openPMD files. The proposed software will be typically used when analyzing the results of numerical simulations. It will be useful to quickly extract scientific meaning from a set of numerical data.

Lehe, Remi↗
DOE OSTI2017

What can we learn from in-soil imaging of a live plant: X-ray Computed Tomography and 3D numerical simulation of root-soil system

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to farming, forest management and climate change. X-ray computed tomography (XCT) has been proven to be an effective tool for non-invasive root imaging and analysis. A combination of XCT, open-source software, and our own code was used to noninvasively image a prairie dropseed (Sporobolus heterolepis) specimen, segment the root data to obtain a 3D image of the root structure at 31µm resolution, and extract quantitative information (root volume and surface area) from the 3D data, respectively. Based on the mesh generated from the root structure, computational fluid dynamics (CFD) simulations were applied to numerically investigate the root-soil-groundwater system. The plant root conductivity, soil hydraulic conductivity and transpiration rate were shown to control the groundwater distribution. The flow variability and soil water distributions under different scenarios were investigated. Parameterizations were evaluated to show their impacts on the average conductivity. The pore-scale modeling approach provides realistic simulations of rhizosphere flow processes and provides useful information that can be linked to upscaled models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

What's in a Name? Developing a Standardized Taxonomy for HVAC System Faults

Faults occurring in heating, ventilation and air-conditioning (HVAC) systems have significantly negative impacts on building energy consumption, occupant comfort, and indoor air quality. In the past thirty years, extensive research has been conducted on fault detection and diagnostics (FDD) methods, and there are now dozens of commercially available FDD software tools. Growing adoption of FDD tools has the potential to generate a massive and useful data set on fault characteristics. However, the lack of a unifying taxonomy is a significant barrier to efficient analysis and evaluation of FDD outputs. Therefore, there is a strong need to develop a robust taxonomy which can better represent and interpret FDD output data. This paper documents the development of a unifying taxonomy for HVAC system faults in commercial buildings, with initial focus on air handling units, variable air volume terminal units, and roof top unit systems. The developed fault taxonomy employs both a physical hierarchy of HVAC equipment and a cause-effect relationship model as tools to better understand and support root cause analysis for HVAC faults. A variable air volume terminal unit is used as an example to demonstrate the application of the developed fault taxonomy. The taxonomy has short-term application in a major U.S. study on fault prevalence, and promises longer term benefits to FDD software developers and building operators by creating a foundation for improved approaches to identifying and resolving HVAC faults.

Chen, Yimin↗
DOE OSTI2019

Software Requirement Document: Benchmarking Algorithms for RadioNuclide Identification (BARNI)

The Department of Energy (DOE) Office of Nuclear Smuggling Detection and Deterrence (NSDD) seeks to improve the performance of RadioIsotope Identification Devices (RIIDs). RIIDs enable users to identifying threat nuclides in applications such as secondary search, facility inspection, and emergency response. As part of this effort NSDD has developed Replicative Assessment of Spectroscopic Equipment (RASE), an open-source tool which generates synthetic spectra and analyzes them with vendor’s radionuclide identification software in order to evaluate performance.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data

Plant roots play a critical role in plant-soil-microbe interactions that occur in the rhizosphere, as well as processes with important implications to climate change and forest management. Quantitative size information on roots in their native environment is invaluable for studying root growth and environmental processes involving the plant. X ray computed tomography (XCT) has been demonstrated to be an effective tool for in situ root scanning and analysis. Our group at the Environmental Molecular Sciences Laboratory (EMSL) has developed an XCT-based tool to image and quantitatively analyze plant root structures in their native soil environment. XCT data collected on a Prairie dropseed (Sporobolus heterolepis) specimen was used to visualize its root structure. A combination of open-source software RooTrak and DDV were employed to segment the root from the soil, and calculate its isosurface, respectively. Our own computer script named 3DRoot-SV was developed and used to calculate root volume and surface area from a triangular mesh. The process utilizing a unique combination of tools, from imaging to quantitative root analysis, including the 3DRoot-SV computer script, is described.

58 GEOSCIENCES↗
DOE OSTI2019

Development of an Automated J-R Curve Analysis Software Based on the ASTM E1820-18 Normalization Method

The J-integral versus crack-growth resistance curve (J-R curve) is a useful tool for evaluating material fracture toughness in the ductile region. A widely accepted practice for conducting J-R curve testing is ASTM standard E1820, which introduces the normalization method. This method does not require compliance measurements during testing, significantly simplifying J-R curve testing compared with the conventional elastic unloading compliance (EUC) method. Despite the advantage in testing, analysis procedures for the normalization method are very complicated. Also, there is no open source software currently available to perform such analysis.The authors developed an open source automated J-R curve-analysis software based on the normalization method in ASTM E1820-18. Source codes were written in MATLAB and the compiled software, in the form of a stand-alone executable, has a user-friendly graphic interface and is readily compatible with modern Windows operating systems. Both source codes and the compiled executable file are available for download at https://code.ornl.gov/xc8/ANJR.git. Comparisons between resulting J-R curves from the software and manual analysis procedures show essentially identical results, indicating the suitability of applying the automated software for J-R curve analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multispectral and thermal surface imagery and surface elevation mosaics (camspec-air)

This dataset contains high resolution image products (orthomosaics) acquired from midsized uncrewed aerial systems, which have been processed for value added quality. The instrument itself, a multispectral imager, the Altum by Micasense, captures 6 spectral bands (red, green blue, NIR, red edge, and LWIR/thermal1) as radiance, which is converted to reflectance. The code used to develop these images first uses tools from the Micasense python library2 to apply dark level corrections, row gradient corrections, and radiometric corrections. Next it uses the processing API from Agisoft Metashape software to align and mosaic the processed imagery, following the processes developed by the USGS' structure from motion workflow documentation3. Captures at different altitudes (recorded in MSL) produce an orthomosaic, a tif image containing information related to the 6 spectral bands, and a digital elevation model (DEM), a tif image containing information related to the elevation of the surveyed terraine. Metadata included in every image can be used to extract lat, lon, and reflectance values. 1https://www.arm.gov/publications/tech_reports/handbooks/doe-sc-arm-tr-281.pdf 2https://micasense.github.io/imageprocessing/MicaSense%20Image%20Processing%20Setup.html 3https://pubs.usgs.gov/of/2021/1039/ofr20211039.pdf

54 ENVIRONMENTAL SCIENCES↗