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DOE OSTI2020

Quantitative Determination of Total Cesium in Savannah River Site (SRS) Tank Waste by Inductively Coupled Plasma Emission Spectroscropy

Utilization of the significant and unique wavelength dynamic range (165 to 1100 nm) available on the Leeman Prodigy Inductively Coupled Plasma Emission Spectroscopy (ICP-ES) allows for quantification of cesium using the emission line 894.347 nm without the potential of Barium interference in nuclear waste samples. Samples are added to a Sodium Peroxide Fusion and Lithium Carbonate buffer in 2% nitric acid solution to increase sensitivity of the easily ionizable (<6 eV) cesium for quantitation to 5 pbb. Through direct comparison of analytical data results, the method is proven to be complementary to the Inductively Coupled Plasma Mass Spectrometry (ICP-MS) analysis (LOQ 100 ppt) in support of the Department of Energy’s (DOE) Nuclear Waste Mission.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Automated qualification data tool for high temperature metallic materials

This report describes a framework for storing, processing, and displaying qualification data for high temperature mechanical properties. The framework automates the process of generating design data from mechanical test results, for example for a data qualification report for the ASME Boiler \& Pressure Vessel Code. The framework has three parts: a data storage model with common formats for several types of typical mechanical property tests, a backend based on the \pycreep Python library for correlating and extrapolating the data to generate design material properties and allowable stresses, and a demonstration user interface for displaying, sorting, and filtering the data and exploring different options for modeling the design mechanical properties. The report discusses the options available for data processing, with illustrations from real test data on Alloy 617, Alloy 709, Alloy 740H, and Laser-Powder Bed Fusion 316H. The framework is complete for ASME type data analysis and will be used to store test data generated by the Department of Energy, Office of Nuclear Energy, Advanced Materials and Manufacturing Technologies sponsored qualification programs. Future work could extend the tool to other types of material properties and/or expand the demo user interface to make it accessible across the AMMT program.

36 MATERIALS SCIENCE↗

DOE OSTI2026

A Field Guide to Corralling the Chaos: A Conceptual Framework for Using Models to Guide Opportunistic Field Studies of Natural Disturbances

Watersheds regulate biogeochemical processes and provide ecosystem services to human societies, but disturbances can fundamentally alter these processes across space and time. Determining when and where to sample to capture disturbance impacts in watersheds remains a central challenge. Manipulation studies and long-term monitoring are often constrained by scope, and opportunistic studies often lack pre-disturbance data needed to statistically determine disturbance impacts. We identify a persistent knowledge gap: the absence of a clear, transferable framework to guide opportunistic disturbance research where pre-disturbance data collection is not a feasible option. To address this gap, we present a conceptual framework that intentionally integrates modeling and empirical observation in an iterative, stepwise model–experiment workflow. We demonstrate its application through two contrasting case studies: wildfire impacts on headwater streams using a pre-disturbance preparedness approach, and saltwater flooding impacts on coastal forests using an ‘ex-post-facto’ approach. From these applications, we assess strengths, limitations, and the critical role of team science for transferability across disturbance types and study designs. Broadly, this framework offers a scalable path towards more rigorous, timely, and actionable disturbance science that can inform watershed management, hazard risk reduction, and ecosystem resilience.

Coastal Biogeochemistry↗

DOE OSTI2023

National Diagnostic Working Group (NDWG) for inertial confinement fusion (ICF)/high-energy density (HED) science: The whole exceeds the sum of its parts

The National Diagnostic Working Group (NDWG) has led the effort to fully exploit the major inertial confinement fusion/high-energy density facilities in the US with the best available diagnostics. These diagnostics provide key data used to falsify early theories for ignition and suggest new theories, recently leading to an experiment that exceeds the Lawson condition required for ignition. The factors contributing to the success of the NDWG, collaboration and scope evolution, and the methods of accomplishment of the NDWG are discussed in this Review. Examples of collaborations in neutron and gamma spectroscopy, x-ray and neutron imaging, x-ray spectroscopy, and deep-ultraviolet Thomson scattering are given. Here, an abbreviated history of the multi-decade collaborations and the present semiformal management framework is given together with the latest National Diagnostic Plan.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Multidecadal Biological Monitoring and Abatement Program assessing human impacts on aquatic ecosystems within the Oak Ridge Reservation in eastern Tennessee, USA

Human activities can be powerful drivers of ecosystem change within catchments. While most long-term catchment studies have been conducted at pristine sites, such studies are less common from sites more impacted by human activity. The Oak Ridge National Laboratory's Biological Monitoring and Abatement Program (BMAP) was developed in the mid-1980s to (1) assess compliance with environmental regulations, (2) identify causes of adverse ecological impacts, (3) provide data for human and ecological risk assessments, and (4) evaluate the effectiveness of remedial actions taken to mitigate the impacts of contaminants in soils, groundwater, and surface water by documenting ecological recovery on the Oak Ridge Reservation (ORR), a federally owned 33,476-acre site in eastern Tennessee, USA, managed by the U.S. Department of Energy. The ORR is composed of multiple watersheds containing many small to mid-size streams. BMAP uses an integrated approach for determining stream health; its databases include long-term seasonal records of contaminant concentrations in water and biota, data from aquatic toxicity testing, and surveys of macroinvertebrate and fish assemblages from impacted and reference streams. These long-term data provide valuable records of degradation and recovery in catchment ecosystems. Our objective in this work is to describe our study system and data series in order to increase awareness of the availability of these long-term data to the catchment science community.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Enabling Sustainable Landscape Design for Continual Improvement of Operating Bioenergy Supply Systems

This unique and highly effective project catalyzed collaboration among government, university, and private sector partners through a multi-state research and technology transfer project designed to support continuous improvement of bioenergy feedstock supply systems. Conceived and built upon the foundation created by prior DOE investments in the Billion Ton Study, Sun Grant Regional Project, and many other feedstock production, harvest, storage and transportation studies, this project addressed seven tasks with more than 29 subtasks. All goals were met with key accomplishments being: (1) on-farm establishment of potential perennial plant mixtures that could not only become sustainable feedstock sources but also enhance soil health, (2) a reduction in potential wind and water erosion by improving corn stover harvest techniques and incorporating cover crops into current row-crop production systems, (3) reduced potential for surface and groundwater contamination while also increasing potential biodiversity and sustainability of Midwestern USA landscapes, and (4) development of site-specific land management, data visualization, and sustainability assessment tools. Twenty-two Case Studies highlighting accomplishments and lessons learned through this public-private partnership investment are incorporated into this final report. On-farm and replicated field plot studies were used to provide the real-world data needed to verify baseline assumptions for extensive feedstock logistic modeling and greenhouse gas (GHG) assessments needed to develop sustainable bioenergy and bio-product industries at national and international scales.

09 BIOMASS FUELS↗

DOE OSTI2020

Proposed Analytical Methods for Determining Filter Media Properties

High Efficiency Particulate Air (HEPA) filters, commonly used in nuclear filtration applications, are an integral part of the waste management processes in nuclear plants. HEPA filters are 99.97% efficient filtration devices characterized by their high resistance to air flow, or pressure drop. From theoretical models, the initial pressure drop across a clean filter is proven to be a function of the filter media fiber diameters and porosity of the media. These filter properties are relatively difficult to obtain with traditional manual methods; therefore, there is a need to develop analytical methods to find the fiber diameter and porosity to determine the pressure drop. Typically, these values can be found by substituting a calculated representative value based upon measured values, such as equivalent fiber diameter based upon a clean pressure drop. However, these values may also be directly recorded and measured by incorporating Scanning Electron Microscope (SEM) image analysis and other measurement methods to analyze the filter media and determine its physical properties without the need for media testing. DiameterJ, an open source Java plug-in, used with ImageJ, can process images of filter media taken by an SEM to find statistical data such as mean fiber diameter and porosity. To produce the raw data, SEM images of two filter media type samples are taken and segmented in DiameterJ using the traditional and statistical region merging segmentation algorithms. Manual segmentation is necessary after the initial segmentation by the algorithms as the images tend to be too complex for the algorithms to output with the necessary accuracy. However, complications exist in the manual segmentation process as these methods can be time intensive and prone to the individual bias of the user. This in turn can skew the final mean fiber diameter result, and lead to either an over or under prediction of the pressure drop. It was also discovered that the porosity data produced by DiameterJ is inaccurate, as the SEM analyzes the three-dimensional filter media by projecting its geometry onto a plane and analyzing it as a two-dimensional binary image. Thus, the porosity is artificially inflated through the segmentation process, rendering this result incorrect. Alternatively, density determination, gravimetric analysis, and thickness testing of the filter media is collectively used to determine the filter fiber porosity. Together, the SEM image analysis and analytical lab methods produce results through direct measurements which allow for the prediction of the initial pressure drop from clean filter media without the need for prior media testing to collect pressure data. By improving upon this proposed analytical method in the future, there is potential to streamline the process of finding these filter properties into a more direct methodology for determining the pressure drop across HEPA filters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

ExpoKids: An R-based tool for characterizing aggregate chemical exposure during childhood

Background: Aggregate exposure, the combined exposures to a single chemical from all pathways, is a critical children’s health issue. Objective: The primary objective is to develop a tool to illustrate potential differences in aggregate exposure at various childhood lifestages and the adult lifestage. Methods: We developed ExpoKids (an R-based tool) using oral exposure estimates across lifestages generated by US EPA’s Exposure Factors Interactive Resource for Scenarios Tool (ExpoFIRST). Results: ExpoKids is applied to illustrate aggregate oral exposure, for ten media, as average daily doses (ADD) and lifetime average daily doses (LADD) in five graphs organized across seven postnatal childhood lifestages and the adult lifestage. This data visualization tool conveys ExpoFIRST findings, from available exposure data, to highlight the relative contributions of media and lifestages to chemical exposure. To evaluate the effectiveness of ExpoKids, three chemical case examples (di[2-ethylhexyl] phthalate [DEHP], manganese, and endosulfan) were explored. Data available from the published literature and databases for each case example were used to explore research questions regarding media and lifestage contributions to aggregate exposure. Significance: These illustrative case examples demonstrate ExpoKids’ versatile application to explore a diverse set of children’s health risk assessment and management questions by visually depicting specific media and lifestage contributions to aggregate exposure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Enabling AI in synthetic biology through Construction File specification

The Construction File (CF) specification establishes a standardized interface for molecular biology operations, laying a foundation for automation and enhanced efficiency in experiment design. It is implemented across three distinct software projects: PyDNA_CF_Simulator, a Python project featuring a ChatGPT plugin for interactive parsing and simulating experiments; ConstructionFileSimulator, a field-tested Java project that showcases 'Experiment' objects expressed as flat files; and C6-Tools, a JavaScript project integrated with Google Sheets via Apps Script, providing a user-friendly interface for authoring and simulation of CF. The CF specification not only standardizes and modularizes molecular biology operations but also promotes collaboration, automation, and reuse, significantly reducing potential errors. The potential integration of CF with artificial intelligence, particularly GPT-4, suggests innovative automation strategies for synthetic biology. While challenges such as token limits, data storage, and biosecurity remain, proposed solutions promise a way forward in harnessing AI for experiment design. This shift from human-driven design to AI-assisted workflows, steered by high-level objectives, charts a potential future path in synthetic biology, envisioning an environment where complexities are managed more effectively.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

MARSAME Release Report for Replacement Water Lines From TA-48 to TA-55, Revision 2

Environmental Protection and Compliance, Environmental Stewardship (EPC-ES) has determined that only a portion of the soil associated with Replacement Water Lines from Technical Area (TA)-48 to TA 55 (Figure 1) meets the criteria for unrestricted release to the public under Department of Energy (DOE) Order 458.1, Radiation Protection for the Public and the Environment (DOE, 2020). The remaining soil did not meet the criteria for unrestricted release and must be managed appropriately. These conclusions are based on the known history of the area combined with soil sample data collected in 2022; the findings are consistent with DOE Order 458.1 and Los Alamos National Laboratory (LANL) Functional Series Document EPC-ES-FSD-004, Environmental Radiation Protection (LANL, 2021). Sampling and data analysis, as described in this report, were sufficient to meet measurement quality objectives (MQOs) under the Multi-Agency Radiation Survey and Assessment of Materials and Equipment (MARSAME) manual (NUREG, 2009) and LANL procedures (LANL, 2020). Final approvals for waste disposition will come from LANL’s Waste Management Program.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Large Vessel Activity and Low-Frequency Underwater Sound Benchmarks in United States Waters

Chronic low-frequency noise from commercial shipping is a worldwide threat to marine animals that rely on sound for essential life functions. Although the U.S. National Oceanic and Atmospheric Administration recognizes the potential negative impacts of shipping noise in marine environments, there are currently no standard metrics to monitor and quantify shipping noise in U.S. marine waters. However, one-third octave band acoustic measurements centered at 63 and 125 Hz are used as international (European Union Marine Strategy Framework Directive) indicators for underwater ambient noise levels driven by shipping activity. We apply these metrics to passive acoustic monitoring data collected over 20 months in 2016–2017 at five dispersed sites throughout the U.S. Exclusive Economic Zone: Alaskan Arctic, Hawaii, Gulf of Mexico, Northeast Canyons and Seamounts Marine National Monument (Northwest Atlantic), and Cordell Bank National Marine Sanctuary (Northeast Pacific). To verify the relationship between shipping activity and underwater sound levels, vessel movement data from the Automatic Identification System (AIS) were paired to each passive acoustic monitoring site. Daily average sound levels were consistently near to or higher than 100 dB re 1 μPa in both the 63 and 125 Hz one-third octave bands at sites with high levels of shipping traffic (Gulf of Mexico, Northeast Canyons and Seamounts, and Cordell Bank). Where cargo vessels were less common (the Arctic and Hawaii), daily average sound levels were comparatively lower. Specifically, sound levels were ~20 dB lower year-round in Hawaii and ~10-20 dB lower in the Alaskan Arctic, depending on the season. Although these band-level measurements can only generally facilitate differentiation of sound sources, these results demonstrate that international acoustic indicators of commercial shipping can be applied to data collected in U.S. waters as a unified metric to approximate the influence of shipping as a driver of ambient noise levels, provide critical information to managers and policy makers about the status of marine environments, and to identify places and times for more detailed investigation regarding environmental impacts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Automated and Distributed Monte Carlo Generation for GlueX

MCwrapper is a set of systems that manages the entire Monte Carlo production workflow for GlueX and provides standards for how that Monte Carlo is produced. MCwrapper was designed to be able to utilize a variety of batch systems in a way that is relatively transparent to the user, thus enabling users to quickly and easily produce valid simulated data at home institutions worldwide. Additionally, MCwrapper supports an autonomous system that takes user’s project submissions via a custom web application. The system then atomizes the project into individual jobs, matches these jobs to resources, and monitors the jobs status. The entire system is managed by a database which tracks almost all facets of the systems from user submissions to the individual jobs themselves. Users can interact with their submitted projects online via a dashboard or, in the case of testing failure, can modify their project requests from a link contained in an automated email. Beginning in 2018 the GlueX Collaboration began to utilize the Open Science Grid (OSG) to handle a bulk of simulation tasks; these tasks are currently being performed on the OSG automatically via MCwrapper. This talk will outline the entire system of MCwrapper, its use cases, and the unique challenges facing the system.

Britton, Thomas↗

DOE OSTI2020

Neural-based time series forecasting of loss of coolant accidents in nuclear power plants

During the last few years, deep learning in neural networks has demonstrated impressive successes in the areas of computer vision, speech and image recognition, text generation, and many others. However, sensitive engineering areas such as nuclear engineering benefited less from these efficient techniques. In this work, deep learning expert systems are utilized to model and predict time series progression of a design-basis nuclear accident, featuring a loss of coolant accident. Two major findings are accomplished in this work. First, the ability to train expert systems with high accuracy, which could help nuclear power plant operators to figure out plant responses during the accident. Second, building fast, efficient, and accurate deep models to simulate nuclear phenomena, which could be valuable to nuclear computational science. In this work, large amount of time series data is obtained from simulation tools by simulating different conditions of the base-case/nominal accident scenario. Four critical outputs/responses are monitored during the accident (e.g. temperature, pressure, break flow rate, water level). Two approaches are adopted in this work. The first approach is to use feedforward deep neural networks (DNN) to fit all time steps and outputs in a single model. The second approach is to use long short-term memory (LSTM) to fit all time steps together for each reactor response separately. Both DNN and LSTM demonstrate very good performance in predicting the test and base-case scenarios, with accuracy as low as 92% and as high as 99%, where these test scenarios are unknown to the expert systems and are not included in the model training. In addition, both approaches demonstrate a significant reduction in computational costs, as the deep expert system is able to accurately predict the accident 100,000 times faster than the original simulation tool. Given sufficient data, the methodology adopted in this study demonstrates that DNN/LSTM expert systems can be used as a decision support system to model advanced time series phenomena within nuclear power plants with high accuracy and negligible computational costs.

42 ENGINEERING↗

DOE OSTI2026

Central Hanford Vernal Pool Monitoring Report for Calendar Year 2025

This report summarizes vernal pool monitoring data collected in calendar year (CY) 2025 and provides management recommendations. Monitoring efforts occurred on the portion of the Hanford Site managed by the U.S. Department of Energy, Hanford Field Office (HFO), referred to herein as Central Hanford. The goal of monitoring is to collect data to evaluate the conservation status of this imperiled habitat. Monitoring in CY 2025 built on previous efforts, as reported in HNF-62115, Ecological Monitoring Report Vernal Pools on the Hanford Site.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Aligning Standards Communities for Omics Biodiversity Data: Sustainable Darwin Core-MIxS Interoperability

The standardization of data, encompassing both primary and contextual information (metadata), plays a pivotal role in facilitating data (re-)use, integration, and knowledge generation. However, the biodiversity and omics communities, converging on omics biodiversity data, have historically developed and adopted their own distinct standards, hindering effective (meta)data integration and collaboration. In response to this challenge, the Task Group (TG) for Sustainable DwC-MIxS Interoperability was established. Convening experts from the Biodiversity Information Standards (TDWG) and the Genomic Standards Consortium (GSC) alongside external stakeholders, the TG aimed to promote sustainable interoperability between the Minimum Information about any (x) Sequence (MIxS) and Darwin Core (DwC) specifications. To achieve this goal, the TG utilized the Simple Standard for Sharing Ontology Mappings (SSSOM) to create a comprehensive mapping of DwC keys to MIxS keys. This mapping, combined with the development of the MIxS-DwC extension, enables the incorporation of MIxS core terms into DwC-compliant metadata records, facilitating seamless data exchange between MIxS and DwC user communities. Through the implementation of this translation layer, data produced in either MIxS- or DwC-compliant formats can now be efficiently brokered, breaking down silos and fostering closer collaboration between the biodiversity and omics communities. To ensure its sustainability and lasting impact, TDWG and GSC have both signed a Memorandum of Understanding (MoU) on creating a continuous model to synchronize their standards. These achievements mark a significant step forward in enhancing data sharing and utilization across domains, thereby unlocking new opportunities for scientific discovery and advancement.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Status of DUNE Offline Computing

We summarize the status of Deep Underground Neutrino Experiment (DUNE) Offline Software and Computing program. We describe plans for the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes in pursuit of the experiment's physics goals of precision measurements of neutrino oscillation parameters, detection of astrophysical neutrinos, measurement of neutrino interaction properties and searches for physics beyond the Standard Model. In contrast to traditional HEP computational problems, DUNE's Liquid Argon Time Projection Chamber data consist of simple but very large (many GB) data objects which share many characteristics with astrophysical images. We have successfully reconstructed and simulated data from 4% prototype detector runs at CERN. The data volume from the full DUNE detector, when it starts commissioning late in this decade will present memory management challenges in conventional processing but significant opportunities to use advances in machine learning and pattern recognition as a frontier user of High Performance Computing facilities capable of massively parallel processing. Our goal is to develop infrastructure resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Multisectoral analysis of drought impacts and management responses to the 2008–2015 record drought in the Colorado Basin, Texas

Abstract. Drought has long posed an existential threat to society. Engineering and technological advancements have enabled the development of complex, interconnected water supply systems that buffer societies from the impacts of drought, enabling growth and prosperity. However, increasing water demand from population growth and economic development, combined with more extreme and prolonged droughts due to climate change, poses significant challenges for governments in the 21st century. Improved understanding of the cascading multisectoral impacts and adaptive responses resulting from extreme drought can aid in adaptive planning and highlight key processes in modeling drought impacts. The record drought spanning 2008 to 2015 in the Colorado Basin in the state of Texas, United States, serves as an outstanding illustration to assess multisectoral impacts and responses to severe, multi-year drought. The basin faces similar water security challenges to those across the western US, such as groundwater depletion and sustainability, resource competition between agriculture and growing urban populations, limited options for additional reservoir expansion, and the heightened risk of more severe and frequent droughts due to climate change. By analyzing rich, high-quality data sourced from nine different local, state, and federal sources, we demonstrate that characterizing regional multisector dynamics is crucial to predicting and understanding future vulnerability and possible approaches to reduce impacts to human and natural systems in the face of extreme drought conditions. This review reveals that, despite the severe hydrometeorological conditions of the drought, the region's advanced economy and existing water infrastructure effectively mitigated economic and societal impacts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Two new SciDAC institutes promote mathematical tools and software technology for high-performance computing

Bigger is often said to be better, and the newest extreme-scale computers certainly are bigger, with millions of processing units. Moreover, the breadth of science performed on the U.S. Department of Energy (DOE) computing facilities is expanding, with new technology such as artificial intelligence emerging. These advances are exciting, creating new opportunities for scientific discovery; however, they also raise new questions for scientists who want to exploit these advances for tackling more complex problems. Will my simulation code be able to utilize the accelerators in extreme-scale computing systems? Can I take advantage of the deepening memory hierarchy in heterogeneous processors? Is there a way around bottlenecks caused by the widening ratio of peak floating-point operations per second to I/0 bandwidth? How can I manage my huge amounts of data effectively? Can I analyze data in situ, or must I transfer it to offline storage for later analysis? To address such questions, DOE announced that it is providing $57.5 million over the next five years for two multidisciplinary teams — FASTMath and RAPIDS2 — to develop new tools and techniques to harness supercomputers for scientific discovery. The teams, called SciDAC Institutes, are part of the Scientific Discovery through Advanced Computing program.

97 MATHEMATICS AND COMPUTING↗