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NASA NTRS2009

Human System Risk Management - Tools of our Trade

The risk of infectious disease to select individuals has historically been difficult to predict in either spaceflight or on Earth with health care efforts relying on broad-based prevention and post-infection treatment. Over the past 10 years, quantitative microbial risk assessment evaluations have evolved to formalize the assessment process and quantify the risk. This process of hazard identification, exposure assessment, dose-response assessment, and risk characterization has been applied by the water and food safety industries to address the public health impacts associated with the occurrence of and human exposure to pathogens in water and food for the development of preventive strategies for microbial disease. NASA is currently investigating the feasibility of using these techniques to better understand the risks to astronauts and refine their microbiological requirements. To assess these techniques, NASA began an evaluation of the potable water system on the International Space Station to determine how the microbial risk from water consumption during flight differed from terrestrial sources, such as municipal water systems. The ultimate goal of this work is to optimize microbial requirements which would minimize unnecessary cargo and use of crew time, while still protecting the health of the crew. Successful demonstration of this risk assessment framework with the water system holds the potential to maximize the use of available resources during spaceflight missions and facilitate investigations into the evaluation of other routes of infection, such as through the spaceflight foods system.

Ott, C. Mark↗

DOE OSTI2025

Manganese in drinking-water reservoirs: a multi-disciplinary review of current issues, biogeochemical controls, and oxygenation-based management

Decreased water quality and increased treatment costs due to excess manganese (Mn) in drinking-water supplies are critical issues globally. To combat on-going and emerging taste and odour issues with Mn and other contaminants (e.g., algal toxins), many utilities are using engineered oxygenation or aeration (EOA) systems to improve water quality in lakes and reservoirs. Resultant shifts in key biogeochemical and physical processes are still poorly understood, often leading to inefficiently managed systems. Paired with knowledge gaps regarding environmental drivers of Mn and the complexity of Mn redox kinetics, Mn problems persist. This review presents the state of current research in areas critical to optimisation of EOA mitigation of Mn, with focus on i) Mn biogeochemical cycling within drinking-water reservoirs; ii) influences of local catchment geology, hydrology, and land use on Mn dynamics; and iii) Mn management using different EOA approaches. The importance of considering the combined implications of these factors for successful Mn management in reservoirs is highlighted by an evaluation of relevant field-based studies; a wide range in EOA performance is observed, from a 97 % decrease in soluble Mn up to a ∼400 % increase in total Mn. Despite the breadth of studies that consider Mn in water-supply systems, there are still several areas of research which warrant further investigation, including: the influence of natural sources and anthropogenic activities on Mn within a given catchment, Mn speciation and transport in stratified and destratified lakes and reservoirs, and optimal site-specific EOA strategies for Mn mitigation.

Aeration↗

DOE OSTI2023

Effects of Livestock Exclusion on Stream Habitat and Aquatic Biota: A Review and Recommendations for Implementation and Monitoring

Abstract To inform riparian restoration, research, and monitoring and to provide management recommendations, we reviewed published studies evaluating the physical and biological effectiveness of livestock exclusion and grazing reduction on various metrics in riparian and aquatic areas. We identified 95 North American studies that reported the effects of livestock grazing reduction on physical habitat (channel morphology, mesohabitats, substrate, and bank stability), biological assemblages (riparian vegetation, macroinvertebrates, fish, and birds), and water quality metrics (temperature, nitrates, phosphorus, and turbidity). Most studies reported that methods to reduce or exclude livestock decreased channel width, width-to-depth ratio, bank erosion, soil bulk density, bare ground, water temperature, nitrogen, and phosphorus and increased riparian vegetation (cover, height, productivity, biomass, and abundance), riparian bird abundance, and young-of-the-year fishes. Results for channel depth, instream substrate, mesohabitats, water depth, juvenile and adult fishes, and macroinvertebrates showed no consistent response to exclusion. Project success was influenced by the time since exclusion; whether there was complete exclusion or continued grazing; and local climate, geology, and soils. Apart from bank erosion and stability, most of the physical and biological metrics took more than a decade to respond to livestock exclusion. However, coupling exclusion with planting and other restoration measures decreased the recovery time. Complete exclusion of livestock produced more consistent improvements in riparian condition and other metrics than rest–rotation or other grazing management strategies. Understanding how physical and biological metrics respond to livestock exclusion will require (1) focused, long-term studies using before–after or before–after, control–impact designs; and (2) monitoring of metrics that most consistently respond to exclusion. Ultimately, the design of exclusions should be driven by local climate, geology, biophysical conditions, and management history. Our results highlight the need for watershed-scale approaches to excluding livestock from broad areas and the need for implementation monitoring to ensure that fencing and other exclusion measures continue to exclude livestock and produce the desired responses.

Krall, Michelle↗

DOE OSTI2025

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Reverse Osmosis (RO) are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in (ultra-filtration) UF systems. Recent advancements in machine learning (ML) have enabled the development of accurate data-driven models for Model Predictive Control (MPC), often requiring minimal prior knowledge of underlying physical processes. In this study, we present predictive regression models based on Random Forest (RF) and Auto-Regressive (AR) approaches to forecast the initial Trans-Membrane Pressure (TMP) for each filtration cycle in data generated by Direct Potable Reuse (DPR) systems. The proposed RF-based model demonstrates superior performance compared to baseline methods, including historical mean, Last Observation Carried Forward (LOCF), and naïve AR models, across various forecasting horizons in terms of root mean square error (RMSE) metric. To evaluate how different classes of process variables contribute to TMP dynamics over time, we examine the feature importance of independent covariates across multiple forecast horizons. This analysis provides insight into the temporal relevance of operational and sensor-derived features, guiding control and monitoring strategies. Additionally, the impact of hyperparameter tuning on TMP prediction performance is studied for both direct and recursive RF modelling approaches across increasing forecast horizons. Accurate prediction of initial TMP is critical for optimizing RO operations, as it enables the development of robust modelling frameworks by accurately estimating membrane fouling trends, thereby enhancing process efficiency and long-term reliability. The demonstrated efficacy of the RF-based approach highlights its potential as a tool for real-time decision-making in water treatment systems, paving the way for advanced process optimization and sustainable water resource management.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗

DOE OSTI2026

Best Practices for Resilience Hub Development and Management

The Carbon League and its community partners in East St. Louis, Illinois, have identified five facilities to serve as resilience hubs. These hubs are intended to support the local community through a range of services and resources during blue-sky (everyday), gray-sky (pre-event), and black-sky (emergency) conditions. Transforming these facilities into fully functional resilience hubs requires a broad operational improvement and programmatic planning roadmap. This memo outlines best practices to guide the development of these resilience hubs in East St. Louis, including recommendations for infrastructure services; safety and physical protection; community services; operational protocols; and a phased implementation strategy aligned with realistic funding and capacity constraints. Infrastructure recommendations include strengthening electric power, communications, water, sanitation, and transportation/logistics capabilities, all of which are essential for hubs that may serve as cooling and warming centers, distribution points, and information hubs during emergencies. Safety recommendations focus on accessibility, emergency action planning, indoor air quality, and secure storage of critical equipment. A phased roadmap provides guidance from immediate, low-cost readiness actions to long-term optimization and community integration. Performance metrics and maintenance protocols ensure continuous improvement and operational readiness. This guidance draws on best practices that can be used to support the development of resilient, community-centered hubs capable of enhancing public safety, health, and well-being during everyday operations and emergencies alike.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Bayesian characterization of uncertainties surrounding fluvial flood hazard estimates

Fluvial floods drive severe risk to riverine communities. There is strong evidence of increasing flood hazards in many regions around the world. The choice of methods and assumptions used in flood hazard estimates can impact the design of risk management strategies. In this study, we characterize the expected flood hazards conditioned on the uncertain model structures, model parameters, and prior distributions of the parameters. We construct a Bayesian framework for river stage return level estimation using a nonstationary statistical model that relies exclusively on the Indian Ocean Dipole Index. We show that ignoring uncertainties can lead to biased estimation of expected flood hazards. We find that the considered model parametric uncertainty is more influential than model structures and model priors. Our results highlight the importance of incorporating uncertainty in extreme flood stage estimates, and are of practical use for informing water infrastructure designs in a changing climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Federal Energy Management Program’s Technical Resilience Navigator: Communications Plan

The Federal Energy Management Program is working to develop a standard, agency-neutral energy and water technical resilience navigator (TRN) to assist federal agencies with their resilience planning efforts, building on agency-expressed needs. The TRN Communications Plan defines how the project team and FEMP will generate awareness of the TRN, recruit validators, encourage its use across federal agencies, increase awareness among various audiences, and solicit user feedback on its usefulness including suggestions for improvement. In support of this purpose, the communications plan characterizes the key audiences, messages, communications channels, and activities needed to help ensure success. The role of communications is to define strategy and ensure leadership and consistency in messaging, writing, outreach, media relations, editing, and design related to the TRN.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

TRAILS Output Files

Overview This data repository contains ZIP files that store compressed versions of the output of running the WaterPaths utility planning and management tool in the DU Re-Evaluation mode (to download the tool, please see this GitHub repository). The tool was used to simulate the six-utility North Carolina Research Triangle problem. Details on the contents of each ZIP file can be seen below. Data details Temporal range: Weekly data for 2,344 weeks from 2015 to 2060 (45 years). Spatial range: Six water utilities in the North Carolina Research Triangle region (0: Chapel Hil/OWASA, 1: Durham, 2: Cary, 3: Raleigh, 4: Pittsboro, and 5: Chatham) File types: CSV and OUT Different solutions available The solution numbers correspond to the different pathway strategies (henceforth referred to as "solutions") discussed in paper's main and supporting text (abstract and link to the paper here). They are as follows: Sol92: The Durham-focused pathway strategy Sol132: The Raleigh-focused pathway strategy Sol140: The regionally-robust pathway strategy Objectives files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Objectives_RDMXX_solsXX_to_XX.csv files. Each CSV file will consist of a row representing all the objective values for that specific solution, while every six columns represents the reliability, restriction frequency, infrastructure net present value ($ mil), peak financial cost, worst-case cost, and unit cost ($ per MG; in that order) for each of the six utilities. There will be 1,000 such files, denoting the performance of the six utilities across the 1,000 deeply uncertain states of the world (DU SOWs). Pathway files These files can be accessed by unzipping solXX_objectives_pathways.zip that contains 1,000 Pathways_sXX_RDMXX.out file. Each OUT corresponds to the set of infrastructure being triggered in a specific DU SOW, and each file will have the name file will consist of four tab-delimited columns that are described as follows: Realization: The realization in which an infrastructure options being triggered utility: The utility currently triggering infrastructure week: The week in which a specific infrastructure option is being triggered infra.: The infrastructure option being triggered If the OUT file contains only the header line, no infrastructure was triggered for that specific DU SOW. Policies files These files can be obtained by unzipping Policies.zip. Each of the 1,000 CSV files within the unzipped folder will contain weekly water use restriction policies for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: 0rest_m: restriction multiplier for utility 0 (values between 0 and 1) 1rest_m: restriction multiplier for utility 1 (values between 0 and 1) 2rest_m: restriction multiplier for utility 2 (values between 0 and 1) 3rest_m: restriction multiplier for utility 3 (values between 0 and 1) 4rest_m: restriction multiplier for utility 4 (values between 0 and 1) 5rest_m: restriction multiplier for utility 5 (values between 0 and 1) 0transf: transfer volume for utility 0 (in MGD) 1transf: transfer volume for utility 1 (in MGD) 2transf: transfer volume for utility 2 (in MGD) 3transf: transfer volume for utility 3 (in MGD) 4transf: transfer volume for utility 4 (in MGD) 5transf: transfer volume for utility 5 (in MGD) Water Sources files These files can be obtained by unzipping WaterSources_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each water source for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xvolume: available water volume from source X (in MGD) Xs_area: surface area of source X (in ACF) Xdemand: demand drawn from a water source from source X (in MGD) Xup_spill: upstream spillage from source X (in MGD) Xww_inflow: wastewater inflow from source X (in MGD) Xcatch_inflow: upstream catchment inflow to source X (in MGD) Xevap: evaporation multiplier for source X (values between 0 and 1) Xds_spill: downstream spillage from source X (in MGD) X_Y_alloc_cap: the allocated capacity from source X to utility Y (values between 0 and 1) X_Y_alloc_dem: the allocated demand from source X to utility Y (values between 0 and 1) Xtrmt_alloc_Y: the allocated treatment capacity from source X to utility Y (values between 0 and 1) Utilities files These files can be obtained by unzipping Utilities_subset.zip. Each of the 100 CSV files within the unzipped folder will contain weekly state variables at each utility for all 1,000 hydroclimatic realizations within a specific DU SOW. The column structure is as follows: Xst_vol: total available storage volume of utility X (in MG) Xcapacity: total storage capacity of utility X (in MG) Xnet_inf: : net inflow for all storage infrastructure for utility X (in MGD) Xst_rof: short term ROF for utility X (values between 0 and 1) Xst_stor_rof: short-term storage ROF for utility X (values between 0 and 1) Xst_trmt_rof: short-term treatment ROF for utility X (values between 0 and 1) Xlt_rof: long-term ROF for utility X (values between 0 and 1) Xlt_stor_rof: long-term storage ROF for utility X (values between 0 and 1) Xlt_trmt_rof: long-term treatment ROF for utility X (values between 0 and 1) Xrest_demand: restricted demand for utility X (in MGD) Xunrest_demand: unrestricted demand for utility X (in MGD) Xunfulf_demand: unfulfilled demand for utility X (in MGD) Xwastewater: wastewater return for utility X (in MGD) Xtreat_capacity: total treatment capacity for utility X (in MG) Xcont_fund: reserve (contingency) fund balance for utility X Xins_pout: insurance payout for utility X (% annual volumetric revenue) Xins_price: insurance price for utility X (% annual volumetric revenue) Xinfra_npv: infrastructure net present value for utility ($mil) Xst_vol: total available storage volume of utility X (in MG) Xdebt_serv: debt service for utility X (usually once per year if the infrastructure is triggered; % annual volumetric revenue) Xstor_vol: total stored volume (in MGD) Xobs_ann_dem: observed annual demand for utility X (in MGD) Xproj_dem: projected annual demand for utility X (in MGD) Xpv_debt_serv: present value of debt service payments for utility X (% annual volumetric revenue) Xgross_rev: gross revenue for utility X ($mil) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

Artificial Intelligence↗

DOE OSTI2023

Unusual Temperature Dependence of Water Sorption in Semicrystalline Hydrogels

Abstract Water vapor sorption is a ubiquitous phenomenon in nature and plays an important role in various applications, including humidity regulation, energy storage, thermal management, and water harvesting. In particular, capturing moisture at elevated temperatures is highly desirable to prevent dehydration and to enlarge the tunability of water uptake. However, owing to the thermodynamic limit of conventional materials, sorbents inevitably tend to capture less water vapor at higher temperatures, impeding their broad applications. Here, an inverse temperature dependence of water sorption in poly(ethylene glycol) (PEG) hydrogels, where their water uptake can be doubled with increasing temperature from 25 to 50 °C, is reported. With mechanistic modeling of water–polymer interactions, this unusual water sorption is attributed to the first‐order phase transformation of PEG structures, and the key parameters for a more generalized strategy in materials development are identified. This work elucidates a new regime of water sorption with an unusual temperature dependence, enabling a promising engineering space for harnessing moisture and heat.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Radiolytic evaluation of a new technetium redox control reagent for advanced used nuclear fuel separations

Technetium is a problematic radioisotope for used nuclear fuel (UNF) and subsequent waste management owing to its high environmental mobility and coextraction in reprocessing technologies as the pertechnetate anion (TcO 4 - ). Consequently, several strategies are under development to control the transport of this radioisotope. A proposed approach is to use diaminoguanidine (DAG) for TcO 4 - and transuranic ion redox control. Although the initial DAG molecule is ultimately consumed in the redox process, its susceptibility to radiolysis is currently unknown under envisioned UNF reprocessing conditions, which is a critical knowledge gap for evaluating its overall suitability for this role. To this end, we report the impacts of steady-state gamma irradiation on the rate of DAG radiolysis in water, aqueous 2.0 M nitric acid (HNO 3 ), and in a biphasic solvent system composed of aqueous 2.0 M HNO 3 in contact with 1.5 M N,N-di-(2-ethylhexyl)isobutyramide (DEHiBA) dissolved in n-dodecane. In addition, we report chemical kinetics for the reaction of DAG with key transients arising from electron pulse radiolysis, specifically the hydrated electron (e aq - ), hydrogen atom (H ˙ ), and hydroxyl ( ˙ OH) and nitrate (NO 3 ˙ ) radicals. The DAG molecule exhibited significant reactivity with the ˙ OH and NO 3 ˙ radicals, indicating that oxidation would be the predominant degradation pathway in radiation environments. This is consistent with its role as a reducing agent. Steady-state gamma irradiations demonstrated that DAG is readily degraded within a few hundred kilogray, the rate of which was found to increase upon going from water to HNO 3 containing solutions and solvents systems. This was attributed to a thermal reaction between DAG and the predominant HNO 3 radiolysis product, nitrous acid (HNO 2 ), k(DAG + HNO 2 ) = 5480 ± 85 M -1 s -1 . Although no evidence was found for the radiolysis of DAG altering the radiation chemistry of the contacted DEHiBA/n-dodecane phase in the investigated biphasic system, the utility of DAG as a redox control reagent will likely be limited by significant competition with its degradation by HNO 2 .

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2023

Assessment of Cloud-Based Applications Enabling a Scalable Risk-Informed Predictive Maintenance Strategy Across the Nuclear Fleet

The current light water reactor fleet uses time-based or failure-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging technologies in terms of artificial intelligence (AI) and cloud computing to enable a cost-effective, predictive maintenance strategy. This report examines the feasibility of cloud computing for the nuclear industry’s needs in terms of the cloud’s computing capabilities, feasibility, and regulatory concerns. The technical viability of cloud computing was analyzed using one year worth of data from a boiling water reactor’s safety relief valve. Models were hosted on a local desktop, Idaho National Laboratory’s high-performance computer, and Microsoft Azure. Data was loaded, processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was used to determined that cloud computing has adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, there is a benefit as the plant no longer needs manage their own servers, software, cybersecurity, and IT support staff. Many of these features can be offloaded on to the cloud provider. A comprehensive analysis was completed that showed the current annual cost of operating is more expensive than using cloud computing resources. Lastly, the regulatory framework does not explicitly address AI or autonomous control. Currently, the NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than new regulations to address the use of AI and ML. But since many of the AI applications are focused on non-safety related applications, such as balance-of-plant components, they will likely have little or no regulatory restrictions or necessary approvals. Demonstrating how AI can improve maintenance and operation of these non-safety related systems seems like the likely path forward for implementing AI and cloud computing resources inside nuclear power plants (NPPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2013

Memory-Efficient Onboard Rock Segmentation

Rockster-MER is an autonomous perception capability that was uploaded to the Mars Exploration Rover Opportunity in December 2009. This software provides the vision front end for a larger software system known as AEGIS (Autonomous Exploration for Gathering Increased Science), which was recently named 2011 NASA Software of the Year. As the first step in AEGIS, Rockster-MER analyzes an image captured by the rover, and detects and automatically identifies the boundary contours of rocks and regions of outcrop present in the scene. This initial segmentation step reduces the data volume from millions of pixels into hundreds (or fewer) of rock contours. Subsequent stages of AEGIS then prioritize the best rocks according to scientist- defined preferences and take high-resolution, follow-up observations. Rockster-MER has performed robustly from the outset on the Mars surface under challenging conditions. Rockster-MER is a specially adapted, embedded version of the original Rockster algorithm ("Rock Segmentation Through Edge Regrouping," (NPO- 44417) Software Tech Briefs, September 2008, p. 25). Although the new version performs the same basic task as the original code, the software has been (1) significantly upgraded to overcome the severe onboard re source limitations (CPU, memory, power, time) and (2) "bulletproofed" through code reviews and extensive testing and profiling to avoid the occurrence of faults. Because of the limited computational power of the RAD6000 flight processor on Opportunity (roughly two orders of magnitude slower than a modern workstation), the algorithm was heavily tuned to improve its speed. Several functional elements of the original algorithm were removed as a result of an extensive cost/benefit analysis conducted on a large set of archived rover images. The algorithm was also required to operate below a stringent 4MB high-water memory ceiling; hence, numerous tricks and strategies were introduced to reduce the memory footprint. Local filtering operations were re-coded to operate on horizontal data stripes across the image. Data types were reduced to smaller sizes where possible. Binary- valued intermediate results were squeezed into a more compact, one-bit-per-pixel representation through bit packing and bit manipulation macros. An estimated 16-fold reduction in memory footprint relative to the original Rockster algorithm was achieved. The resulting memory footprint is less than four times the base image size. Also, memory allocation calls were modified to draw from a static pool and consolidated to reduce memory management overhead and fragmentation. Rockster-MER has now been run onboard Opportunity numerous times as part of AEGIS with exceptional performance. Sample results are available on the AEGIS website at http://aegis.jpl.nasa.gov.

Burl, Michael C.↗

DOE OSTI2020

Understanding Life History Diversity of a Wild Steelhead Population and Managing for Resiliency

Abstract Diversity in steelhead Oncorhynchus mykiss (anadromous Rainbow Trout) is often characterized by varying time spent in freshwater and saltwater environments. However, ontogenetic shifts are not often highlighted as an important diversity characteristic in salmonids. Larger water bodies can play a key role in population stability by buffering limited resources in smaller tributary systems. Based on freshwater and saltwater ages of adult steelhead in Fish Creek, Idaho, there were 12 different life history trajectories observed. Juvenile abundance varied from 12,083 (SE = 1,225.7) to 62,463 (SE = 1,753.8), with ages ranging from young of the year (age 0) to 4 years. Adult abundance fluctuated from 17 (SE < 0.1) to 499 (SE = 67.1), and total age of adults varied from 3 to 7 years. Diversity was most evident in juvenile movement and rearing strategies. We observed four types of movement and rearing pathways in which juveniles either directly migrated to the ocean from Fish Creek or resided for up to three winters in main-stem river habitat in the Clearwater River basin prior to ocean migration. Most juveniles emigrated in the fall at age 2, and most ocean-emigrating smolts were age 3. Subsequently, most juveniles resided for at least one additional winter period before ocean migration. Juvenile diversity was also reflected in adult ages; the mean proportion that spent 3 years in freshwater was 0.55 (SE = 0.03), and the mean proportion that spent 2 years in freshwater was 0.41 (SE = 0.03). Adult sex ratio was female biased (mean ± SE = 0.66 ± 0.02), with a higher proportion of females (0.89 ± 0.03) than males (0.65 ± 0.05) residing in the ocean for at least 2 years. Density-dependent mechanisms were evident in juvenile rearing habitat in Fish Creek for cohorts of high female abundance. Population productivity potentials can be met when tributary and main-stem rearing habitat can be utilized, and this will be essential in attaining recovery goals.

Dobos, Marika E.↗

DOE OSTI2020

Remediation of Temporary Storage Sites in Support of the Port Hope Area Initiative - 20295

The Port Hope Area Initiative is a community-based solution for the long-term management of historic low level radioactive waste (LLRW) resulting from 60 years of uranium and radium processing operations in the Town of Port Hope which is located in Ontario, Canada. The Eldorado refinery, on the north shore of Lake Ontario, began refining radium-226 from pitchblende ore, later transitioning to the refining of uranium. Through the history of the operation, LLRW was deposited throughout the town of Port Hope as a result of fugitive emissions from the plant and/or through the re-use of process residues as building material and backfill. Historical clean-up activities conducted in the late 1970's involved the remediation of approximately 400 properties and the relocation of 100,000 cubic metres of contaminated soil to a disposal facility in Chalk River operated by Atomic Energy of Canada Limited (AECL). Owing to space limitations at that disposal facility, any LLRW identified through construction monitoring since that time has been stored in the community at three temporary storage sites located throughout the town. These include: the Centre Pier mound that contained approximately of 19,800 m{sup 3} of LLRW-impacted soil that originated from the construction of a new water treatment plant; two mounds located at a licensed storage facility containing LLRW obtained from residential clean-up activities (11,000 m{sup 3}); and a small pad adjacent to the municipal sewage treatment plant containing 2200 m{sup 3} of LLRW-containing sludge. With the construction of a new long-term waste management facility (LTWMF) that has been designed to house all of the LLRW identified within Port Hope, the three sites were early candidates for remediation. The clean-up of the three temporary storage sites was a significant milestone for the Port Hope Area Initiative. After a decade of planning and consultation, this work represents the first sites in the municipality to be remediated with the waste being safety removed and transferred to the newly constructed LTWMF. This paper discusses the challenges associated with the clean-up activities for these three sites and the strategies employed to address those challenges. These included weather-related challenges, owing to the seasons over which the work was conducted as well as those associated with working within a closely-knit community. Canadian Nuclear Laboratories (CNL), working on behalf of the federal government, has worked diligently to develop a positive and trusting relationship with the community. Consequently, the successful execution of this project needed to be sensitive to, and respectful of the needs of the community. In addition to the usual Health, Safety and Environment training, project staff received community awareness training that spoke to the history of this community-based initiative and the expected behavior when working within the community. Transportation routes were defined based on safety and the need to minimize disruption to local traffic while haul-times where scheduled around school bus hours to enhance public safety. The successful completion of this first of many remediation projects to be completed under the Port Hope Area Initiative reflected years of careful planning. Nevertheless, there were a number of 'lessons learned' that have been applied on other ongoing projects be completed under the Port Hope Area Initiative. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Results of a Soil Flushing Treatability Test for Hanford Site Hexavalent Chromium Removal - 20446

U.S. Department of Energy contractor CH2M Hill Plateau Remediation Company has made significant progress remediating hexavalent chromium in groundwater near the Columbia River through the operation of pump and treat facilities and source removal activities. To mitigate risks associated with hexavalent chromium contamination, which was identified in a CERCLA interim action record of decision as the primary groundwater contaminant of concern for the 100-KR-4 Operable Unit from discharging to the Columbia River, three ion-exchange pump and treat systems were installed between 1997 and 2009. Between 2010 and 2016, operation of the K West pump and treat system, located near the former 105K West plutonium production reactor, reduced concentrations below the groundwater remediation target for hexavalent chromium. In 2016, a rebound study was performed to evaluate the effectiveness of the pump and treat remedy and assess the potential for any residual hexavalent chromium sources continuing to contribute to groundwater contamination. As a result of the rebound study, a source of continued groundwater contamination was identified. To address this condition, a soil flushing treatability test was written and approved by the U.S. Department of Energy and the U.S. Environmental Protection Agency. The test included saturating about a 1-acre area of soil with treated water with the goal of forcing the residual hexavalent chromium to groundwater where existing extraction wells could remove it for treatment, accelerating the cleanup process. In spring and summer 2019, CH2M Hill Plateau Remediation Company installed and began operating a shallow underground leach system to support the treatability test. Preliminary sampling data show the test was effective in removing the residual contamination. Following further evaluation and analysis from the initial test, the process will be considered for implementation elsewhere on the Hanford Site, particularly at locations where there is a known or suspected continuing contamination source in the soil column. The paper will cover the goals of the study, as well as more details about the following: - Overview of pump and treat exit strategy (using U.S. Environmental Protection Agency guidance); - The design and installation of the soil flushing technology in the 100-K Area; - The testing process and results of sampling data; - Post-study evaluation and potential for implementation in other locations at the Hanford Site. Innovative solutions for cleanup, such as the soil flushing technology, have resulted in substantial progress in the removal of groundwater contaminants at the Hanford Site, potentially shortening the time frame required to meet cleanup goals and resulting in significant cost savings. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Satellite remote sensing for environmental sustainable development goals: A review of applications for terrestrial and marine protected areas

With few years left to achieve the vital United Nations Sustainable Development Goals (SDGs), member nations must urgently leverage technological advancements in environmental monitoring to succeed. Remote sensing now provides decades of global observations at a variety of spatio-temporal scales and a litany of data products to guide comprehensive measures for climate action, and aquatic and terrestrial biota preservation. Protected areas, such as national parks and wildlife preserves, represent largely untapped resources for both applying robust conservation measures and testing ambitious new approaches to sustainable development that could jumpstart the much-needed adoption of strategies to efficiently pursue global sustainability. This review summarizes recent demonstrated utilities of remotely sensed data applied to protected areas for research related to SDG goals 13, 14, and 15: “Climate Action”, “Life below Water”, and “Life on Land”. We identify successful uses of such data for each SDG, identify areas for improvement, and provide recommendations from the literature on how to expand what others have done to achieve lofty goals with global impact. We demonstrate that remote sensing provides a valuable tool for achieving SDGs as it facilitates monitoring vegetation health, water quality and condition, and climate variables at large spatial and fine temporal scales, while also evaluating the effectiveness of management and conservation practices. Issues remain, however, in that there is currently no reference from which to relate goal progress to human livelihoods. Further, the current relationship between remotely sensed indices and ecological services that determine sustainable development omit steps that would establish this connection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Assessment of Cloud-based Applications for Enabling a Scalable Riskinformed Predictive Maintenance Strategy

The current light-water reactor fleet uses time-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging artificial intelligence (AI) and cloud computing technologies to achieve a cost-effective, predictive-maintenance strategy. This paper presents discussion and results on the application of cloud computing in the nuclear industry. The technical viability of cloud computing was analyzed using data from a boiling-water reactor’s safety relief valve. The models were hosted on three different systems: a local personal computer, Idaho National Laboratory’s high-performance computer system, and Microsoft Azure. The data were loaded and processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was determined that cloud computing affords adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, the benefit is that the plants no longer need to manage their own servers, software, cybersecurity, and information technology support staff for in-house data analytics purpose. Many of these features can be offloaded to the cloud provider for a potential cost savings. Demonstrating how AI can improve the maintenance and operation of non-safety-related systems seems the likely path forward for implementing AI and cloud computing resources inside nuclear power plants.

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DOE OSTI2023

Development of a Scalable Risk-informed Predictive Maintenance Cloud-based Strategy at Nuclear Power Plants

The fact that light-water reactor operation and maintenance costs are prohibitively expensive and contribute to the premature decommissioning of nuclear power plants is partly due to how the equipment is monitored. In recent years, cloud computing has emerged as a dominant technology, as its low cost, computing and storage adaptability, and ability to host applications across numerous virtual infrastructures potentially make it a cost-effective alternative to onsite storage and diagnostics. In this paper, a technological assessment is carried out on a provisional cloud deployment architecture for a nuclear power plant predictive monitoring system. This cloud-based monitoring system would enable maintenance and diagnostic analysts and other authorized plant users to remotely monitor equipment functionality, thus enabling early fault detection and effective predictive maintenance practices. To provide data processing and storage, sensor device networking, and database management, the Microsoft Azure cloud platform is utilized as part of the proposed cloud architecture; however, this analysis could be extended to other cloud computing service providers as well. The focus of this paper is on application of cloud resources for enabling predictive maintenance, identification of technological hurdles associated with moving to a cloud-computing-based architecture, and potential benefits from moving to a centralized cloud system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗