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DOE OSTI2024

IRIS: A Performance-Portable Framework for Cross-Platform Heterogeneous Computing

From edge to exascale, computer architectures are becoming more heterogeneous and complex. The systems typically have fat nodes, with multicore CPUs and multiple hardware accelerators such as GPUs, FPGAs, and DSPs. This complexity is causing a crisis in programming systems and performance portability. Several programming systems are working to address these challenges, but the increasing architectural diversity is forcing software stacks and applications to be specialized for each architecture. As we show, all of these approaches critically depend on their software framework for discovery, execution, scheduling, and data orchestration. To address this challenge, we believe that a more agile and proactive software framework is essential to increase performance portability and improve user productivity. To this end, we have designed and implemented IRIS: a performance-portable framework for cross-platform heterogeneous computing. IRIS can discover available resources, manage multiple diverse programming platforms (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, OpenMP) simultaneously in the same execution, respect data dependencies, orchestrate data movement proactively, and provide for user-configurable scheduling. To simplify data movement, IRIS introduces a shared virtual device memory with relaxed consistency among different heterogeneous devices. IRIS also adds an automatic kernel workload partitioning technique using the polyhedral model so that it can resize kernels for a wide range of devices. Our evaluation on three architectures, ranging from Qualcomm Snapdragon to a Summit supercomputer node, shows that IRIS improves portability across a wide range of diverse heterogeneous architectures with negligible overhead.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

HIDES: Hybrid Intrusion Detector for Energy Systems

The establishment of a resilient electric grid accompanied by a secure communications network is an ongoing battle as advanced persistent threats continue to exploit existing vulnerabilities in legacy supervisory control and data acquisition system (SCADA) infrastructure. Traditional intrusion detection systems (IDSs) lack consistent performance because of the continuously evolving attack surface of SCADA systems. These shortcomings can be overcome by integrating logical system behavior, protocol-specific knowledge, and data-based learning to develop a comprehensive IDS solution. In this paper, we present a Hybrid Intrusion Detector for Energy Systems by integrating a network-based IDS, state-of-the-art machine learning-based IDS, and model-based IDS to detect unknown and stealthy cyberattacks targeting the SCADA networks. The proposed IDS uses synchrophasor measurements and cyber logs to learn patterns of different scenarios based on spatiotemporal behaviors of power systems. As a proof of concept, we implement and validate the proposed IDS by leveraging resources available at the National Renewable Energy Laboratory's Energy Systems Integration Facility test bed. Experimental results show promising performance in detecting cyberattacks while providing realtime visualization of power system measurements and cyber logs.

machine-learning intrusion detection system↗

DOE OSTI2026

Integrated Neutronics Modeling for Inertial Fusion Energy Systems: Development and Application to LD-FIRST

Lawrence Livermore National Laboratory (LLNL) is proposing a new Laser Driven Fusion Integration Research and Science Test Facility (LD-FIRST) with the goal of providing an experimental testbed for future Inertial Fusion Energy (IFE) systems. However, IFE systems require detailed and accurate multiphysics modeling to quantify material damage, thermal loading, and tritium breeding within complex chamber environments. This article presents the first step in an integrated multiphysics framework that couples meshed CAD-based geometry within Monte Carlo neutronic simulations to enable high-fidelity analysis of IFE chamber concepts, with future coupling to external codes. The neutronics workflow utilizes OpenMC and its third-party capability to use CAD-based geometries through DAGMC and tally on unstructured meshes with Libmesh to evaluate neutron transport behavior, geometric fidelity, and material performance under reactor-relevant conditions. The use of tailored tallies on unstructured meshes in this framework allows direct transfer without interpolating to CFD simulation tools. Two IFE chambers were evaluated, both conceived by LLNL: HYLIFE-II and Laser IFE (LIFE). This work produced high-fidelity conformal surface and volumetric meshes of the HYLIFE-II and LIFE chambers with mapped spatial insight into material damage, thermal loading, and tritium breeding. The HYLIFE-II model was built utilizing available resources and used as a test case to verify that the neutronics framework can handle complex geometries. The LIFE chamber CAD was provided by LLNL and was the main focus of this work. This work analyzes multiple ternary alloy breeding materials for the LIFE chamber, across different 6 Li enrichments to produce data relevant to the LD-FIRST project. This work also investigates the level of model fidelity for the LIFE chamber, and results show that inclusion of detailed first wall and coolant structures increased the predicted tritium breeding ratio (TBR) by ~30%, highlighting the sensitivity of tritium breeding and the need for a high-fidelity simulation framework for IFE chambers. These developments provide a scalable toolset for the design and optimization of next-generation IFE chambers, forming a solid foundation for future coupled multiphysics analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2013

Benefits of Colocating Concentrating Solar Power and Wind

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29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Location generalizability of image-based air quality models

This paper is to be submitted at the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Computer Vision for Earth Observation workshop. The full paper abstract is below: The ability to rapidly quantify atmospheric pollutants is important both for global emissions monitoring and for mitigating the adverse effects that follow a hazardous chemical release. In the aftermath of a chemical release, imagery is often the only available resource to assess local conditions. Recent work has demonstrated initial success in predicting particulate matter pollution from imagery; however, these results are tied to a specific site and do not generalize to new geographic locations. In this work, we seek to understand how easily deep learning models generalize to new locations in the context of image-based air quality assessments, targeting two distinct tasks: (1) broad measures of particulate matter pollution, and (2) the mass of a given chemical released in hazardous plumes. For the latter, we focus on sulfur dioxide, a toxic aerosol and a major component of particulate matter pollution caused by industrial fossil fuel consumption. To develop a model that operates in the widest possible range of environments, we test different training strategies, including the use of new geolocation foundation models. The best performing models achieve >80% accuracy when evaluating unseen imagery at previously seen sites, but we find significant drops in performance when evaluating imagery from unseen sites, at best 65%. Additionally, we present the public release of the National Parks Air Quality Index Dataset, a new medium-sized dataset that pairs imagery with sensor-based air quality measurements at 15 different national parks.

Byler, Eleanor B. [BATTELLE (PACIFIC NW LAB)]↗

DOE OSTI2020

Relative reproductive phenology and synchrony affect neonate survival in a nonprecocial ungulate

Abstract Degree of reproductive synchronization in prey is hypothesized as a predator defense strategy reducing prey risk via predator satiation or predator avoidance. Species with precocial young, especially those exposed to specialist predators, should be highly synchronous to satiate predators (predator satiation hypothesis), while prey with nonprecocial (i.e. altricial) young, especially those exposed to generalist predators, should become relatively asynchronous to avoid predator detection (predator avoidance hypothesis). The white‐tailed deer Odocoileus virginianus in North America is an example of a nonprecocial ungulate that uses the hider strategy early in life; its primary predator (coyote; Canis latrans ) is a generalist, making white‐tailed deer a good model species to test the predator avoidance hypothesis. We used birth dates and known fates of white‐tailed deer neonates ( n = 1,032) across nine study sites varying in relative synchrony and predator assemblages to test the predator avoidance hypothesis. We predicted that relative birthing asynchrony of the population would increase relative survival at the population level; therefore, at the individual scale, neonate birth date nearer to mean birthing date in a respective population would not influence individual survival. Coyotes were responsible for the majority of predation events, and survival of those neonates increased the closer the individual was born to peak birthing season in each respective population. Also, at the population level, reproductive asynchronization negatively affected survival. Contrary to the predator avoidance hypothesis, our data indicate patterns in neonate survival for white‐tailed deer better support the predator satiation hypothesis at the individual and population level. Additionally, coyotes may present a selective force great enough to shift reproductive synchrony such that predator satiation may become a feasible defense strategy for neonates at local spatial scales. Our results indicate that synchronizing reproduction may still be the most effective strategy to reduce individual predation risk from generalist predators, particularly when the window of heightened resource availability to the prey is narrow. A free Plain Language Summary can be found within the Supporting Information of this article.

Michel, Eric S.↗

DOE OSTI2023

Land use alters bacterial growth dynamics in soil

Microbial growth and mortality are major determinants of soil carbon cycling. We measured in situ growth dynamics of individual bacterial taxa in cropped and successional soils in response to a resource pulse. We hypothesized that land use imposes selection pressures on growth characteristics. We estimated growth and death for 453 and 73 taxa, respectively. The average generation time was 5.04 ± 6.28 (SD; range 0.7–63.5) days. Lag times were shorter in cultivated than successional soils and resource amendment decreased lag times. Taxa exhibiting the greatest growth response also exhibited the greatest mortality, indicative of boom-and-bust dynamics. We observed a bimodal growth rate distribution, representing fast- and slow-growing clusters. Both clusters grew more rapidly in successional soils, which had more organic matter, than cultivated soils. Resource amendment increased the growth rate of the slower growing but not the faster-growing cluster via a mixture of increased growth rates and species turnover, indicating that competitive dynamics constrain growth rates in situ. Furthermore, these two clusters show that copiotrophic bacteria in soils may be subdivided into different life history groups and that these subgroups respond independently to land use and resource availability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms, a State-of-the-art (STAR) Report

The considerable interest in the high performance computing (HPC) community regarding analyzing and visualization data without first writing to disk, i.e., in situ processing, is due to several factors. First is an I/O cost savings, where data is analyzed /visualized while being generated, without first storing to a filesystem. Second is the potential for increased accuracy, where fine temporal sampling of transient analysis might expose some complex behavior missed in coarse temporal sampling. Third is the ability to use all available resources, CPU’s and accelerators, in the computation of analysis products. This STAR paper brings together researchers, developers and practitioners using in situ methods in extreme-scale HPC with the goal to present existing methods, infrastructures, and a range of computational science and engineering applications using in situ analysis and visualization.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Rhizosphere processes are quantitatively important components of terrestrial carbon and nutrient cycles

Abstract While there is an emerging view that roots and their associated microbes actively alter resource availability and soil organic matter ( SOM ) decomposition, the ecosystem consequences of such rhizosphere effects have rarely been quantified. Using a meta‐analysis, we show that multiple indices of microbially mediated C and nitrogen (N) cycling, including SOM decomposition, are significantly enhanced in the rhizospheres of diverse vegetation types. Then, using a numerical model that combines rhizosphere effect sizes with fine root morphology and depth distributions, we show that root‐accelerated mineralization and priming can account for up to one‐third of the total C and N mineralized in temperate forest soils. Finally, using a stoichiometrically constrained microbial decomposition model, we show that these effects can be induced by relatively modest fluxes of root‐derived C, on the order of 4% and 6% of gross and net primary production, respectively. Collectively, our results indicate that rhizosphere processes are a widespread, quantitatively important driver of SOM decomposition and nutrient release at the ecosystem scale, with potential consequences for global C stocks and vegetation feedbacks to climate.

Finzi, Adrien C.↗

DOE OSTI2018

Testing the light:nutrient hypothesis: Insights into biofilm structure and function using metatranscriptomics

Aquatic biofilms are hotspots of biogeochemical activity due to concentrated microbial biomass (Battin, Kaplan, Newbold, & Hansen, 2003). However, biofilms are often considered a single entity when their role in biogeochemical transformations is assessed, even though these biofilms harbour functionally diverse microbial communities (Battin, Besemer, Bengtsson, Romani, & Packmann, 2016; Veach, Stegen, Brown, Dodds, & Jumpponen, 2016). Often overlooked are the biotic interactions among biofilm components that can affect ecosystem-scale processes such as primary production and nutrient cycling. These interactions are likely to be especially important under resource limitation. Light is a primary resource mediating algal photosynthesis and both phototrophic and heterotrophic production due to bacterial reliance on C-rich algal exudates (Cole, 1982). However, current understanding of function–structure linkages in streams has yet to unravel the relative degree of these microbial feedbacks under resource availability gradients. In this issue of Molecular Ecology, Bengtsson, Wagner, Schwab, Urich, and Battin (2018) studied stream biofilm responses to light availability to understand its impact across three domains of life. By integrating biogeochemical rate estimation and metatranscriptomics within a microcosm experiment, they were able to link primary production and nutrient uptake rates to algal and bacterial metabolic processes and specify what taxa contributed to gene expression. Under low light, diatoms and cyanobacteria upregulated photosynthetic machinery and diatom-specific chloroplast rRNA suggesting heightened transcriptional activity under light limitation to maintain phototrophic energy demands. Under high light, heterotrophic bacteria upregulated mRNAs related to phosphorous (P) metabolism while biofilm P uptake increased indicating high bacterial-specific P demand when algal biomass was high. Together, these results indicate that biogeochemical function is mediated by complex microbial interactions across trophic levels.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Environmental resource deficit may drive the evolution of intraspecific trait variation in invasive plant populations

Intraspecific trait variation within natural populations (i.e. intra-population trait variation, IPTV) is the basic source for selection and can have significant ecological consequences. Higher IPTV may increase a population's niche breath and benefit interspecies competition under a resource-limited environment, thus affecting the ability of a species to move into novel habitats. However, the reciprocal influences of variation in environmental conditions and phenotypic trait expression in spreading plant populations are not clearly defined. Here, we propose that during invasion, IPTV and its relative change in response to key resource enrichment may increase with the resource deficit of invaded sites, and that this relationship may facilitate plant invasions into resource-limited environments. We analyzed the invasion trend, IPTV and its response to water enrichment, and moisture variability among populations of an annual grass Brachypodium hybridum in California, United States. We incorporated a genotyping-by-sequencing approach, a common garden experiment that had two water level treatments, and public plant and climate databases. Our hypothesis was supported by the observation that for populations that invaded sites with higher spring moisture deficit, both their seed biomass IPTV (for the water-enriched treatment only) and relative change of the IPTV across water treatments were larger when examined in the common garden experiment. A generally north to south spreading direction was found in these B. hybridum populations, towards a drier and warmer climate exhibiting higher moisture deficit for plant growth. Our results suggest a role for interactions between IPTV (rather than trait means) and environmental resource availability in promoting plant invasions, providing new insights into the significance of IPTV in shaping plant geographic distributions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Functionally discrete fine roots differ in microbial assembly, microbial functional potential, and produced metabolites

Traditionally, fine roots were grouped using arbitrary size categories, rarely capturing the heterogeneity in physiology, morphology and functionality among different fine root orders. Fine roots with different functional roles are rarely separated in microbiome-focused studies and may result in confounding microbial signals and host-filtering across different root microbiome compartments. Using a 26-year-old common garden, we sampled fine roots from four temperate tree species that varied in root morphology and sorted them into absorptive and transportive fine roots. The rhizoplane and rhizosphere were characterized using 16S rRNA gene and internal transcribed spacer region amplicon sequencing and shotgun metagenomics for the rhizoplane to identify potential microbial functions. Fine roots were subject to metabolomics to spatially characterize resource availability. Both fungi and bacteria differed according to root functional type. We observed additional differences between the bacterial rhizoplane and rhizosphere compartments for absorptive but not transportive fine roots. Rhizoplane bacteria, as well as the root metabolome and potential microbial functions, differed between absorptive and transportive fine roots, but not the rhizosphere bacteria. Functional differences were driven by sugar transport, peptidases and urea transport. Our data highlights the importance of root function when examining root-microbial relationships, emphasizing different host selective pressures imparted on different root microbiome compartments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

REopt: A Platform for Energy System Integration and Optimization: Preprint

REopt is NREL's energy planning platform offering concurrent, multi-technology integration and optimization capabilities to help clients meet their cost savings and energy performance goals. The REopt platform provides techno-economic decision-support analysis throughout the energy planning process, from agency-level screening and macro planning to project development to energy asset operation. REopt employs an integrated approach to optimizing a site?s energy costs by considering electricity and thermal consumption, resource availability, complex tariff structures including time-of-use, demand and sell-back rates, incentives, net-metering, and interconnection limits. Formulated as a mixed integer linear program, REopt recommends an optimally-sized mix of conventional and renewable energy, and energy storage technologies; estimates the net present value associated with implementing those technologies; and provides the cost-optimal dispatch strategy for operating them at maximum economic efficiency. The REopt platform can be customized to address a variety of energy optimization scenarios including policy, microgrid, and operational energy applications. This paper presents the REopt techno-economic model along with two examples of recently completed analysis projects.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2014

TH-C-9A-01: Lean Tools and Methods

Lean thinking has revolutionized the manufacturing industry. Toyota has pioneered and leveraged this aspect of Lean thinking. Application of Lean thinking and Lean Six Sigma techniques into Healthcare and in particular in Radiation Oncology has its merits and challenges. To improve quality, safety and patient satisfaction with available resources or reducing cost in terms of time, staff and resources is demands of today's healthcare. Radiation oncology treatment involves many processes and steps, identifying and removing the non-value added steps in a process can significantly improve the efficiency. Real projects undertaken in radiation oncology department in cutting down the procedure time for MRI guided brachytherapy to 40% less using lean thinking will be narrated. Simple Lean tools and techniques such as Gemba walk, visual control, daily huddles, standard work, value stream mapping, error-proofing, etc. can be applied with existing resources and how that improved the operation in a Radiation Oncology department's two year experience will be discussed. Lean thinking focuses on identifying and solving the root-cause of a problem by asking “Why” and not “Who” and this requires a culture change of no blame. Role of leadership in building lean culture, employee empowerment and trains and develops lean thinkers will be presented. Why Lean initiatives fail and how to implement lean successfully in your clinic will be discussed. Learning Objectives: Concepts of lean management or lean thinking. Lean tools and techniques applied in Radiation Oncology. Implement no blame culture and focus on system and processes. Leadership role in implementing lean culture. Challenges for Lean thinking in healthcare.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

SU-E-E-07: An Adaptable Approach for Education On Medical Physics at Undergraduate and Postgraduate Levels

Purpose: To contribute to the professional profile of future medical physicists, technologists and physicians, and implement an adaptable educational strategy at both undergraduate and postgraduate levels. Methods: The Medical Physics Block of Electives (MPBE) designed was adapted to the Program of B.S. in Physics. The conferences and practical activities were developed with participatory methods, with interdisciplinary collaboration from research institutions and hospitals engaged on projects of Research, Development and Innovation (RDI). The scientific education was implemented by means of critical analysis of scientific papers and seminars where students debated on solutions for real research problems faced by medical physicists. This approach included courses for graduates not associated to educational programs of Medical Physics (MP). Results: The implementation of the MPBE began in September 2014, with the electives of Radiation MP and Introduction to Nuclear Magnetic Resonance. The students of second year received an Introduction to MP. This initiative was validated by the departmental Methodological Workshop, which promoted the full implementation of the MPBE. Both postgraduated and undergraduate trainees participated in practices with our DICOM viewer system, a local prototype for photoplethysmography and a home-made interface for ROC analysis, built with MATLAB. All these tools were designed and constructed in previous RDI projects. The collaborative supervision of University’s researchers with clinical medical physicists will allow to overcome the limitations of residency in hospitals, to reduce the workload for clinical supervisors and develop appropriate educational activities. Conclusion: We demonstrated the feasibility of adaptable educational strategies, considering available resources. This provides an innovative way for prospective medical physicists, technologists and radiation oncologists. This strategy can be implemented in several regions without formal programs of MP, like most of developing countries. Starting with undergraduate students would allow to reach appropriate certification faster than most of traditional or alternative approaches for education on MP. The authors acknowledge Radiation Consulting Group, LLC, an Arizona Corporation which promotes the use of ionizing radiation in the healing arts, for the “Oscar Luis Caballero” travel grant. The authors thanks to professors Meisbel Daudinot, David Adame and Alexander Pascau for the practices through imagis, imageROC and ANGIODIN PD3000 respectively.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-P-19: Fetal Dose Estimate for a High-Dose Fluoroscopy Guided Intervention Using Modern Data Tools

Purpose: An accurate dose estimate is necessary for effective patient management after a fetal exposure. In the case of a high-dose exposure, it is critical to use all resources available in order to make the most accurate assessment of the fetal dose. This work will demonstrate a methodology for accurate fetal dose estimation using tools that have recently become available in many clinics, and show examples of best practices for collecting data and performing the fetal dose calculation. Methods: A fetal dose estimate calculation was performed using modern data collection tools to determine parameters for the calculation. The reference point air kerma as displayed by the fluoroscopic system was checked for accuracy. A cumulative dose incidence map and DICOM header mining were used to determine the displayed reference point air kerma. Corrections for attenuation caused by the patient table and pad were measured and applied in order to determine the peak skin dose. The position and depth of the fetus was determined by ultrasound imaging and consultation with a radiologist. The data collected was used to determine a normalized uterus dose from Monte Carlo simulation data. Fetal dose values from this process were compared to other accepted calculation methods. Results: An accurate high-dose fetal dose estimate was made. Comparison to accepted legacy methods were were within 35% of estimated values. Conclusion: Modern data collection and reporting methods ease the process for estimation of fetal dose from interventional fluoroscopy exposures. Many aspects of the calculation can now be quantified rather than estimated, which should allow for a more accurate estimation of fetal dose.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-AB-204-00: CDRH/FDA Regulatory Processes and Device Science Activities

The responsibilities of the Food and Drug Administration (FDA) have increased since the inception of the Food and Drugs Act in 1906. Medical devices first came under comprehensive regulation with the passage of the 1938 Food, Drug, and Cosmetic Act. In 1971 FDA also took on the responsibility for consumer protection against unnecessary exposure to radiation-emitting devices for home and occupational use. However it was not until 1976, under the Medical Device Regulation Act, that the FDA was responsible for the safety and effectiveness of medical devices. This session will be presented by the Division of Radiological Health (DRH) and the Division of Imaging, Diagnostics, and Software Reliability (DIDSR) from the Center for Devices and Radiological Health (CDRH) at the FDA. The symposium will discuss on how we protect and promote public health with a focus on medical physics applications organized into four areas: pre-market device review, post-market surveillance, device compliance, current regulatory research efforts and partnerships with other organizations. The pre-market session will summarize the pathways FDA uses to regulate the investigational use and commercialization of diagnostic imaging and radiation therapy medical devices in the US, highlighting resources available to assist investigators and manufacturers. The post-market session will explain the post-market surveillance and compliance activities FDA performs to monitor the safety and effectiveness of devices on the market. The third session will describe research efforts that support the regulatory mission of the Agency. An overview of our regulatory research portfolio to advance our understanding of medical physics and imaging technologies and approaches to their evaluation will be discussed. Lastly, mechanisms that FDA uses to seek public input and promote collaborations with professional, government, and international organizations, such as AAPM, International Electrotechnical Commission (IEC), Image Gently, and the Quantitative Imaging Biomarkers Alliance (QIBA) among others, to fulfill FDA’s mission will be discussed. Learning Objectives: Understand FDA’s pre-market and post-market review processes for medical devices Understand FDA’s current regulatory research activities in the areas of medical physics and imaging products Understand how being involved with AAPM and other organizations can also help to promote innovative, safe and effective medical devices J. Delfino, nothing to disclose.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-AB-204-01: Device Approval Process

60 APPLIED LIFE SCIENCES↗