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DOE OSTI2024

EMRALD Technology Advancements for Commercial Grade Dedication Readiness

Event Modeling Risk Assessment using Linked Diagrams (EMRALD) is a software tool developed at Idaho National Laboratory for researching the capabilities of dynamic probabilistic risk assessment. It provides a simple interface to represent complex interactions often seen when developing dynamic models. EMRALD can also interface with other applications by modifying inputs as well as running and using their results within EMRALD for dynamic and integrated assessment. To enable wider industry use cases, collaborative work between Idaho National Laboratory and FPoliSolutions was performed through the technology commercialization fund TCF-20-21448. This report covers the additional features and capabilities developed under this work.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Bioinformatic teaching resources - for educators, by educators - using KBase, a free, user-friendly, open source platform

Over the past year, biology educators and staff at the Department of Energy Systems Biology Knowledgebase (KBase) initiated a collaborative effort to develop a curriculum for bioinformatics education. KBase is a free and easily accessible data science platform that integrates many bioinformatics resources into a graphical user interface built upon reproducible analysis notebooks. KBase held conversations with college and high school instructors to understand how KBase could potentially support their educational goals. These conversations morphed into a working group of biological and data science instructors that adapted the KBase platform to their curriculum needs, specifically around concepts in Genomics, Metagenomics, Pangenomics, and Phylogenetics. The KBase Educators Working Group developed modular, adaptable, and customizable instructional units. Each instructional module contains teaching resources, publicly available data, analysis tools, and markdown capability to tailor instructions and learning goals for each class. The online user interface enables students to conduct hands-on data science research and analyses without requiring programming skills or their own computational resources (these are provided by KBase). Alongside these resources, KBase continues to work with instructors, supporting the development of additional curriculum modules. For anyone new to the platform, KBase, and the growing KBase Educators Organization, provides a community network, accompanied by community-sourced guidelines, instructional templates, and peer support to use KBase within a classroom whether virtual or in-person.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Bioenergy Knowledge Discovery Framework Fact Sheet

The Bioenergy Knowledge Discovery Framework (KDF) supports the development of a sustainable bioenergy industry by providing access to a variety of data sets, publications, and collaboration and mapping tools that support bioenergy research, analysis, and decision making. In the KDF, users can search for information, contribute data, and use the tools and map interface to synthesize, analyze, and visualize information in a spatially integrated manner.

bioenergy, bioenergy kdf, Bioenergy knowledge disc↗

DOE OSTI2022

Generating and Analyzing Program Call Graphs using Ontology

Call graph or caller-callee relationships have been used for various kinds of static program analysis, performance analysis and profiling, and for program safety or security analysis such as detecting anomalies of program execution or code injection attacks. However, different tools generate call graphs in different formats, which prevents efficient reuse of call graph results. In this paper, we present an approach of using ontology and resource description framework (RDF) to create knowledge graphs for specifying call graphs to facilitate the construction of full-fledged and complex call graphs of computer programs, realizing more interoperable and scalable program analyses than conventional approaches. We create a formal ontology-based specification of call graph information to capture concepts and properties of both static and dynamic call graphs so different tools can collaboratively contribute to more comprehensive analysis results. Our experiments show that ontology enables merging of call graphs generated from different tools and flexible queries using a standard query interface. Index Terms—Callgraph, ontology, knowl

Dorta, E.↗

DOE OSTI2019

Electron Ion Collider Machine Detector Interface

Here we review the major physics requirements, accelerator challenges and some magnet design issues for the Machine Detector Interface (MDI) of an Electron Ion Collider (EIC) Interaction Region (IR). In order to fully exploit the rich physics potential of an EIC, an IR MDI team must balance a complex interplay that arises when combining hadron and electron collider accelerators in an optimized IR. The work described in this paper results from ongoing close collaboration between many people at BNL, JLab and other institutes to realize an EIC as the next, highest priority, future nuclear physics project.

43 PARTICLE ACCELERATORS↗

DOE OSTI2015

Electronic Structure of Buried Interfaces - Oral Presentation [Slides]

In the electronics behind computer memory storage, the speed and size are dictated by the performance of permanent magnets inside devices called read heads. Complicated magnets made of stacked layers of thin films can be engineered to have properties that yield more energy storage and faster switching times compared to conventional iron or cobalt magnets. The reason is that magnetism is a result of subtle interactions amongst electrons; just how neurons come together on large scales to make cat brains and dog brains, ensembles of electrons interact and become ferromagnets and paramagnets. These interactions make magnets too difficult to study in their entirety, so I focus on the interfaces between layers, which are responsible for the coupling materials physicists hope to exploit to produce next-generation magnets. This project, I study a transition metal oxide material called LSCO, Lanthanum Cobaltite, which can be a paramagnet or a ferromagnet depending on how you tweak the electronic structure. It exhibits an exciting behavior: its sum is greater than the sum of its parts. When another similar material called a LSMO, Lanthanum Manganite, is grown on top of it, their interface has a different type of magnetism from the LSCO or the LSMO! I hope to explain this by demonstrating differently charged ions in the interface. The typical method for quantifying this is x-ray absorption, but all conventional techniques look at every layer simultaneously, averaging the interfaces and the LSCO layers that we want to characterize separately. Instead, I must use a new reflectivity technique, which tracks the intensity of reflected x-rays at different angles, at energies near the absorption peaks of certain elements, to track changes in the electronic structure of the material. The samples were grown by collaborators at the Takamura group at U.C. Davis and probed with this “resonant reflectivity” technique on Beamline 2-1 at the Stanford Synchrotron Radiation Lightsource. This project was funded by the Department of Energy and supported by the SLAC National Accelerator Laboratory. Preliminary results suggest that different ionic charges are indeed responsible for the different magnetic properties at the interface, which is promising because charge is easy to control. Once scientists understand how to tune the magnetic properties of materials like LSCO and LSMO, industries get closer to designing the magnets that will soon revolutionize consumer electronics.

36 MATERIALS SCIENCE↗

DOE OSTI2020

The Kokkos Ecosystem [Brief]

In 2016/2017, the field of High-Performance Computing (HPC) entered a new era driven by fundamental physics challenges to produce ever more energy and cost-efficient processors. Since the convergence on the Message-Passing Interface (MPI) standard in the mid-1990s, application developers enjoyed a seemingly static view of the underlying machine — that of a distributed collection of homogeneous nodes executing in collaboration. However, after almost two decades of dominance, the sole use of MPI to derive parallelism acted as a limiter to improved future performance. While MPI is widely expected to continue to function as the basic mechanism for communication between compute nodes for the immediate future, additional parallelism is required on the computing node itself if high performance and efficiency goals are to be realized. When reviewing the architectures of the top HPC systems today, the change in paradigm is clear: the compute nodes of the leading machines in the world are either powered by many-core chips with a few dozen cores each, or use heterogeneous designs, where traditional CPUs marshal work to massively parallel compute accelerators which has as many as 200,000 processing threads in flight simultaneously. Complicating matters further for application developers, each processor vendor has its own preferred way of writing code for their architecture.The Kokkos EcoSystem was released by Sandia in 2017 to address this new era in HPC system design by providing a vendor independent performance portable programming system for scientific, engineering, and mathematical software applications written in the C++ programming language. Using Kokkos, application developers can be more productive because they will not have to create and maintain separate versions of their software for each architecture, nor will they have to be experts in each architecture's peculiar requirements. Instead, they will have a single method of programming for the diverse set of modern HPC architectures. While Kokkos started in 2011 as a programming model only, it soon became clear that complex applications needed more. It is also critical to have a portable mathematical functions and developers need tools to debug their applications, gain insight into the performance characteristics of their codes and tune algorithm performance parameters through automated processes. The Kokkos EcoSystem addresses those needs through its three main components: the Kokkos Core programming model, the Kokkos Kernels math library, and the Kokkos Tools project.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

KBase: The DOE Systems Biology Knowledgebase: An Overview

The Department of Energy Systems Biology Knowledgebase (KBase) is a knowledge creation and discovery environment designed for both biologists and bioinformaticians. KBase integrates a large variety of public data and analysis tools into an easy-to-use graphical user interface and leverages DOE computational infrastructure to perform sophisticated systems biology analyses. KBase is a freely available system that enables scientists to upload their own data, analyze it alongside collaborator and public data, build validated systems biology models, and share workflows and conclusions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

A data acquisition system for HV-CMOS sensor research and development in the upgrade of ATLAS experiment

In the High Luminosity LHC (HL-LHC) upgrade of ATLAS experiment in 2026, the new inner tracker detector will be installed. As a promising candidate for the outer layer of the inner tracker detector, the High Voltage CMOS (HV-CMOS) pixel sensors are being investigated by the ATLAS collaboration. A Front-End LInk eXchange (FELIX) based Data Acquisition (DAQ) system is developed for the R&D of the HV-CMOS sensors. A FELIX card with PCIe interface in the back-end is used to control, monitor, calibrate and read out the front-end electronics. In the front-end, a Xilinx evaluation board ZC706 works as the interface between the back- end and custom boards with HV-CMOS sensors and the readout ASIC. In conclusion, the DAQ system was successfully deployed for the testbeam experiment at CERN. Design of the DAQ system, the tuning of sensors and testbeam results will be described in details.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

Optimization and Control of Burning Plasmas Through High Performance Computing

This project has revived the FACETS code, that has been developed under SciDAC fund- ing in 2008-2012. The code has been dormant for a number of years after the SciDAC funding stopped. FACETS depends on external packages. The external packages and libraries such as PETSc, FFTW, HDF5 and NETCDF that are included in FACETS have evolved during these years. Some packages in FACETS are also parts of other codes such as PlasmaState, NUBEAM, GACODES, and UEDGE. These packages have been also evolved together with their host codes which include TRANSP, TGYRO and XPTOR. Finally, there is also a set of packages in FACETS that are being developed and maintained by Tech-X. These packages include BILDER, SciMake, and FcioWrappers. Many of these packages evolved significantly during the last several years and FACETS had to be updated to synchronize with the re- cent progress in the external packages. The PI has introduced new changes to the BILDER package to support the updated interfaces to the external modules. During the last year of the project, the FACETS version of the UEDGE code has been extracted from FACETS as a standalone package. The PI collaborates with the scientists from LLNL on the updated UEDGE model in FACETS. Drs. T. Rognlien, M. Umansky and A. Dimits from LLNL are contributing to this task.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Bioinformatic Teaching Resources – For Educators, by Educators – Using KBase, a Free, User-Friendly, Open Source Platform

Over the past year, biology educators and staff at the U.S. Department of Energy Systems Biology Knowledgebase (KBase) initiated a collaborative effort to develop a curriculum for bioinformatics education. KBase is a free web-based platform where anyone can conduct sophisticated and reproducible bioinformatic analyses via a graphical user interface. Here, we demonstrate the utility of KBase as a platform for bioinformatics education, and present a set of modular, adaptable, and customizable instructional units for teaching concepts in Genomics, Metagenomics, Pangenomics, and Phylogenetics. Each module contains teaching resources, publicly available data, analysis tools, and Markdown capability, enabling instructors to modify the lesson as appropriate for their specific course. We present initial student survey data on the effectiveness of using KBase for teaching bioinformatic concepts, provide an example case study, and detail the utility of the platform from an instructor’s perspective. Even as in-person teaching returns, KBase will continue to work with instructors, supporting the development of new active learning curriculum modules. For anyone utilizing the platform, the growing KBase Educators Organization provides an educators network, accompanied by community-sourced guidelines, instructional templates, and peer support, for instructors wishing to use KBase within a classroom at any educational level–whether virtual or in-person.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

White Box Access to Quantum Testbeds for Co-Design

At Lawrence Livermore National Laboratory (LLNL), we operate and maintain the Quantum Device and Integration Testbed (QuDIT) facility, a small quantum testbed that supports about 10 active research teams (including our own) and over 50 internal and external collaborators. This testbed is designed to give remote white box access to users for research, training, and outreach. A guiding principle behind the development of our testbed infrastructure, software and user interfaces is to empower users to perform experiments at the cutting edge of quantum information science at any level of abstraction, from materials studies, device physics and control and characterization techniques to algorithm development and quantum operating system design. Our testbed targets a multilevel quantum system (qudit) to expand the accessible Hilbert space of a simple-to-manufacture quantum device and focuses on quantum simulation, typically implemented through custom gates designed with quantum optimal control methods, rather than on a universal computing framework with a fixed gate set. We leverage the Lab’s high-performance computing (HPC) program and related expertise to simulate quantum systems, develop hybrid algorithms, and generate gates optimized for given simulations. Additionally, we have adopted a co-design philosophy from the HPC community in designing new hardware, so that the systems we develop are optimized for the specific physics simulations we plan to use them for.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

ExaSGD: 2022 Kernel Thrust Activities

The Kernel Thrust milestone ADSE22-407 covers the development of device-capable optimization algorithms and solvers technologies required by the ExaSGD project’s software stack in order to solve security-constrained alternating current optimal power flow (SC-ACOPF) problems on emerging exascale architectures. To this extent, in FY22 the main objective of the Kernel Thrust was (i) provide sparse optimization solver that runs efficiently on hardware accelerator devices (i.e., NVIDIA and AMD GPUs) to perform intra-node computations, (ii) strengthen the reliability and increase the performance of the mixed-dense sparse (MDS) solver of HiOp for deployment on the FY22 target architectures, Summit and Crusher, and (iii) increase performance by improving the mathematical algorithm and refining the parallel MPI-based implementation of the coarse-grain parallel solver HiOp-PriDec for capabilities deployment on the FY22 target architectures, Summit and Crusher. This document presents the developments and contributions done by the Kernels Thrust Team in FY22 toward completion of the above-mentioned objectives. These contributions progressed along four main development (sub)thrusts: (1) Design and implementation of a sparse optimization solver for use on hardware accelerators; (2) Improvement of the mathematical algorithm and of the parallel implementation of HiOp-PriDec to ensure readiness and efficient coarse-grain parallelism for FY23 target exascale machine; and (3) Support Software and Application Development Thrusts of the exaSGD project in their deployment of the project’s software stack on AMD- and NVIDIA-based architectures. The development of the sparse optimization solver (thrust 1 above) was new in FY22 and resulted in a new sparse solver in HiOp (available as of version 0.6). The second development thrust was a continuation of the efforts from FY21 and improved the mathematical algorithm and the communication strategy of the HiOp-PriDec solver. The last developement thrust is a large collaborative effort. Namely, the project’s teams from multiple labs (LLNL, PNNL, ORNL, and NREL) performed large-scale demonstration of the ExaSGD software stack, namely the optimization solvers of HiOp interfaced with the modeling front-end ExaGO and the stochastic sampler PowerScenarios. These demonstration efforts solved large-scale instances of the SC-ACOPF challenge problem of medium network sizes (10, 000-bus system) and large number of contingencies on Summit (NVIDIA accelerators) and Crusher (AMD accelerators) systems at ORNL.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Advancements in Multiphysics Microdepletion Analysis of an eVinci TM -like Microreactor Leveraging OpenMC-CRAB Workflow

Nuclear microreactors (MRs) are a class of nuclear reactor technology, characterized by reduced dimensions, modular design, and reduced power output in contrast to conventional Light Water Reactors (LWRs). MRs are proposed for supplying electricity and eventual process heat to remote locations, such as military installations and disaster-affected areas. Current research work sponsored by the US Department of Energy Microreactor Program (MRP) is devoted to the development of novel modeling and simulation tools to better support MR vendors and regulatory bodies. Notably, the NRC is projected to utilize the CRAB multiphysics software driver for executing both design and beyond-design-basis accident analyses. Furthermore, the NRC has been utilizing the MELCOR code to calculate mechanistic source terms during accidents. Since MELCOR relies on isotopic inventory and reactor temperature/power profiles under accident conditions, which theoretically can be derived from CRAB, the goal is to establish a comprehensive CRAB-MELCOR computational framework. Past work was focused on testing and demonstrating CRAB's capability to generate results that can be used to inform mechanistic source term calculations in MELCOR. In particular, a computational workflow leveraging OpenMC-generated microscopic cross sections and CRAB was first applied to perform multiphysics microscopic depletion calculation followed by an accident scenario for a stylized microreactor problem. In fiscal year 2024, the research work has been focused on applying the OpenMC-CRAB workflow, which was first tested in fiscal year 2023, to a realistic 3D heat-pipe cooled MR problem representative of the eVinci TM design. The latter computational problem was developed with inputs from WEC to conserve selected neutronic and thermal characteristics of the eVinci TM design without releasing proprietary data. The results of this simulation, encompassing isotopic inventory, power density distribution, and kinetic parameters, will inform both MELCOR and the WEC-developed FATE code for mechanistic source terms calculations. The results from the two codes will then be compared for code verification purposes. This report contains the design characteristics of the realist heat pipe cooled microreactor developed as a use-case for the verification exercise, and the current results for the multiphysics microscopic depletion performed with the OpenMC-CRAB workflow. The results include eigenvalue as a function of time, power distribution at EOL, in addition to nuclides inventory's time evolution and spatial distribution. Finally, we report improvements to the workflow efficiency achieved through a collaboration with the NEAMS programs. Through this collaborative effort, we were able to strongly decrease the computational time for the multiphysics microdepletion calculation (i.e., from 17.4 hours to 5.7 hours on 280 processors) in addition to simplifying the interface to generate isotopics spatial distribution utilizable by FATE and MELCOR. Future work, including the improvement of the current microscopic cross-sections' library and the simulation of an accident scenario at EOL, is also discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

Direct Feed Low Activity Waste Integrated Permitting - 16642

An overall Hanford permitting strategy for the U. S. Department of Energy (DOE) Office of River Protection (ORP) is being developed to support the Direct Feed Low- Activity Waste (DFLAW) Program. The strategy identifies new permits and modifications of existing permits, as well as major regulatory approvals to support the startup and operation of nuclear systems necessary to feed low activity tank waste, pretreat the waste, operate the Waste Treatment and Immobilization Plant (WTP) Low Activity Waste (LAW) facility to treat tank waste, and dispose of waste streams. Types of permits include hazardous waste, toxic air, and radiological air licenses. Four different Contractors manage operations at Tank Farms, WTP, Utilities/Infrastructure, and Waste Disposal. Due to this complexity and the number of interfaces required, the need to have a strategic overview of all permits was evident. Approximately 25 permits and 4 major regulatory approvals are identified to implement DFLAW. The strategy will help guide integrated planning, scheduling and sequencing of permits and regulatory approvals to support DOE ORP's overall schedule for construction, commissioning and operation of DFLAW. Development of the strategy included extensive collaboration and coordination of an Integrated Permitting Team with staff and management representation from DOE, CH2M Hill Plateau Remediation Contractor (CHPRC), Washington River Protection Solutions LLC (WRPS), and Bechtel National Inc. (BNI). Information sessions and briefings have been conducted with the Washington State Department of Ecology (Ecology) and Washington State Department of Health (DOH) in the development of this overall strategy. Additionally, interface meetings are held with Ecology and DOH on specific projects early in the design phase to validate the permitting approach, identify key issues and information, and discuss requirements and assumptions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

DOE BSSD Performance Management Metrics Report Q1

Microbes play key roles in our biosphere, from driving global nutrient cycling to impacting plant, animal and human health and disease. Complex data from microbial genomes, proteins, and metabolites provide a window into these tiny engines that drive life on our planet. Yet these data are dispersed among researchers’ laboratories and various repositories, making it difficult to access. This calls for new ways of managing data, improving data interoperability, advancing community standards, and creating an infrastructure where data are shared efficiently. We have built the National Microbiome Data Collaborative (NMDC) to advance how scientists create, use, and reuse data to redefine the way we understand and harness the power of microbes. The vision of the National Microbiome Data Collaborative (NMDC) is to drive a microbiome data sharing network connecting data, people, and ideas to advance microbiome innovation and discovery. The NMDC was launched in 2019 and brought together DOE National Laboratories to collaborate across resources, capabilities, and expertise. The NMDC team was strategically assembled to include software developers, microbial researchers, metadata experts, and multi-omics specialists. The diversity of the NMDC team reflects the inherently interdisciplinary nature of microbiome science, and we leverage the strengths of the DOE National Laboratory system. Towards BER’s goal of advancing an iterative systems biology approach to the understanding of microbial genomes, the NMDC serves as a foundation for infrastructure, data standards, and community building. Together with the flagship DOE User Facilities, the Joint Genome Institute (JGI) and the Environmental Molecular Sciences Laboratory (EMSL), we are developing core capabilities in metadata standards for environmental descriptors and sample handling and processing; standardized bioinformatic workflows; an interface for data search and access; and robust community engagement activities. The NMDC production platform supports long-term data infrastructure and community building for BER’s bioenergy and environmental research goals. Our approach leverages lessons learned and an ambitious framework for collaborative, interdisciplinary data infrastructure to support microbiome research. The NMDC supports data, information, and knowledge access through three defined software tools – the Submission Portal, NMDC EDGE, and the Data Portal – driven by community needs. Herein, we describe the value proposition for the microbiome research community, our overarching strategy, and challenges and opportunities for developing the NMDC as both an infrastructure and community engagement program.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

A Software Defined Storage Approach to Exascale Storage Services (Final Technical Report)

The Mochi project began in 2015 in recognition of a set of changes that were set to alter the landscape of storage and I/O for DOE science. On the one hand, an influx of new classes of applications including an initial set of data intensive and machine learning applications were operating with new types of data and in new ways, as compared to traditional computational science simulation codes. Simultaneously, new memory, storage, and networking technologies were driving a need to adapt software designs to a rapidly changing design space. The goal of the three-year Mochi project was to develop and demonstrate an approach for composing storage services which provides new levels of functionality, performance, and reliability for science applications at extreme scale. The team, including a mix of Laboratory, university, and industry collaborators, focused on systems and applications of interest to DOE Office of Science, tracking developments at NERSC and the LCFs as well as application trends within ECP and SciDAC. Technical work focused on three themes: composition (understand the building blocks needed to provide storage services that meet DOE mission needs and how these components are flexibly composed), application interfacing (what service compositions are most effective for common DOE application use cases), and consistency and synchronization (taking advantage of knowledge about, and from, the system and scientific applications to provide better service than would otherwise be possible). The project was highly successful, producing 13 publications and tens of thousands of lines of open source software that is now being used by multiple ECP teams, HPC software vendors, and international collaborators. The uptake of Mochi technologies speaks to both the value of the service composition model and the quality of architecture and software developed by the team. Through continued funding under ASCR and ECP, the Mochi team and its technologies are on track to further contribute to DOE science successes into the exascale timeframe.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

A Closed-Loop Distribution System Restoration Tool for Natural Disaster Recovery. Final CRADA report

We propose to continue the development of the restoration algorithms and the tool’s user interface, both of which have been developed under the GMLC-0131 project. This project aims to develop a distribution restoration decision support tool that will assist utilities in performing distribution restoration after extreme weather events in an optimal and efficient manner. The tool will integrate the weather information/forecasts and system fragility assessment together with the field measurement data to improve the situational awareness and estimate the system damage status. Advanced optimization models will be leveraged to dispatch repair crews and associated resources. New resources (e.g., automatic switches and distributed generators (DGs)) enabled by distribution automation and smart grid development will be utilized to reconfigure distribution grids and pick up loads promptly to reduce the outage sizes and durations. The closed-loop feature of the tool will make the tool adaptive to the evolving weather events and varying restoration capabilities. In this CRADA, we will collaborate with S&C Electric Company (S&C) to refine ANL-1060 (07/17/2019) the restoration algorithms that can be potentially applicable for any utility systems and vendor products, including: 1) Customizable information from both utility users and vendor users; 2) User interface design.

54 ENVIRONMENTAL SCIENCES↗