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Eddy-Dilek, Carol

Publications and source records attributed to Eddy-Dilek, Carol.

8 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Machine Learning Approach for Spatiotemporal Multivariate Optimization of Environmental Monitoring Sensor Locations

Abstract Long-term environmental monitoring is critical for managing the soil and groundwater at contaminated sites. Recent improvements in state-of-the-art sensor technology, communication networks, and artificial intelligence have created opportunities to modernize this monitoring activity for automated, fast, robust, and predictive monitoring. In such modernization, it is required that sensor locations be optimized to capture the spatiotemporal dynamics of all monitoring variables as well as to make it cost-effective. The legacy monitoring datasets of the target area are important to perform this optimization. In this study, we have developed a machine-learning approach to optimize sensor locations for soil and groundwater monitoring based on ensemble supervised learning and majority voting. For spatial optimization, Gaussian process regression (GPR) is used for spatial interpolation, while the majority voting is applied to accommodate the multivariate temporal dimension. Results show that the algorithms significantly outperform the random selection of the sensor locations for predictive spatiotemporal interpolation. While the method has been applied to a four-dimensional dataset (with two-dimensional space, time, and multiple contaminants), we anticipate that it can be generalizable to higher-dimensional datasets for environmental monitoring sensor location optimization.

Siddiquee, Masudur R.↗
DOE OSTI2022

Identifying Controlling Variables Related to Mercury Vapor Concentrations in Legacy Facilities: SRNL Technology Development For D&D

A suite of sensor packages has been installed in the Alpha-4 facility at Y-12 and preliminary data analysis to isolate the controlling variables has been performed after two months of data collection. In line with the conceptual model presented in Section 2.0, the preliminary analysis has demonstrated that temperature, barometric pressure, and relative humidity are the key controlling variables for mercury vapor releases within the building. The data analysis will continue to explore these controlling variables across the next several months to capture a more complete picture of the annual change in meteorological conditions at Y-12.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Reactive transport modeling for supporting climate resilience at groundwater contamination sites

Abstract. Climate resilience is an emerging issue at contaminated sites and hazardous waste sites, since projected climate shifts (e.g., increased/decreased precipitation) and extreme events (e.g., flooding, drought) could affect ongoing remediation or closure strategies. In this study, we develop a reactive transport model (Amanzi) for radionuclides (uranium, tritium, and others) and evaluate how different scenarios under climate change will influence the contaminant plume conditions and groundwater well concentrations. We demonstrate our approach using a two-dimensional (2D) reactive transport model for the Savannah River Site F-Area, including mineral reaction and sorption processes. Different recharge scenarios are considered by perturbing the infiltration rate from the base case as well as considering cap-failure and climate projection scenarios. We also evaluate the uranium and nitrate concentration ratios between scenarios and the base case to isolate the sorption effects with changing recharge rates. The modeling results indicate that the competing effects of dilution and remobilization significantly influence pH, thus changing the sorption of uranium. At the maximum concentration on the breakthrough curve, higher aqueous uranium concentration implies that sorption is reduced with lower pH due to remobilization. To better evaluate the climate change impacts in the future, we develop the workflow to include the downscaled CMIP5 (Coupled Model Intercomparison Project) climate projection data in the reactive transport model and evaluate how residual contamination evolves through 2100 under four climate Representative Concentration Pathway (RCP) scenarios. The integration of climate modeling data and hydrogeochemistry models enables us to quantify the climate change impacts, assess which impacts need to be planned for, and therefore assist climate resiliency efforts and help guide site management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Panel Session 45: Savannah River National Laboratory Advancing the EM Mission Through Technology

This panel focused on Savannah River National Laboratory (SRNL) activities and addressed: 1) Initial development work that SRNL performed to develop the technologies and processes, as well as design the equipment for the DOE EM HLW tank waste treatment and soil and groundwater mission, 2) Implemented technology and process improvements to the EM systems, and 3) Current technologies being evaluated for future implementation to improve throughput and reduce cost/schedule. Panelists with presentations: Advancing the EM Mission: SRNL Technology Approach (Connie Herman); Nuclear Materials Management (William Bates); Adjust, Adapt, Attest, and Adjudicate (Bruce Wiersma); SRNL Research and Development for Technological Advancements in the Liquid Waste Mission at SRS (Frank Pennebaker); EM TD Applies Solutions at SRS (Andrew Fellinger); Remediation of Complex Groundwater Plumes: Three Decades of Cleanup Success (Carol Eddy-Dilek)

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DOE OSTI2020

Session 058 - Panel: Ensuring Strong Return on Investment for DOE EM Technology Development: DOE Views (1/2) (R1.26)

The panel represented the views of US DOE National Laboratories and DOE Contractors and focused on DOE Technology Development Projects discussing how they approach tech development to maximize return on investment. Successful examples were discussed. Panelists with presentations: Ensuring a Strong ROI for DOE EM Technology Development (Jud Virden); The DOE EM Technology Development Technical Assistance Program (Carol Eddy-Dilek); SRR Liquid Waste Technology Development Program: Encouraging Creativity Maximize Return on Investment (Vijay Jain); Ensuring Strong Return on Investment for DOE EM Technology Development: A Vendor Perspective (Martin Williams)

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

The Challenge of Achieving Site Closure of a Complex Groundwater Plume - 20531

Over the last three decades, DOE has made substantial progress in nearly every area of nuclear waste cleanup and has closed and transitioned 91 of the 107 sites in the EM complex. Several of the remaining groundwater plumes at Hanford, Los Alamos, Paducah, Oak Ridge, and Savannah River are complex and tend to have unique site or contaminant characteristics which provide an almost impossible challenge to remediate to regulatory levels. As a result, these complex sites will require a large investment to remediate. In order for DOE to achieve regulatory closure, a technically sound case must be developed and presented to regulators and stakeholders that clearly demonstrates that remedial goals have been or will be irreversibly achieved or that there is an alternate acceptable end-state. Five lines of evidence are required: - A conceptual site model that is as complete as possible, with the knowledge that it may continue to evolve with time; - Demonstration that trends in contaminant concentrations, or flux, versus time indicate that remedial goals will be achieved on schedule or within a reasonable time thereafter and that trends that deviate from this path are explainable by the conceptual model; - Demonstration that remobilization of attenuated contaminants is unlikely to occur in the future; - Explicit consideration of remedial contingencies, should deviations in the path toward remedial goals occur; - Development of an effective long-term monitoring plan to detect any conditions that might alter the path toward remedial goals. SRS has made significant progress in the remediation of contamination associated with the F-area and H-Area Seepage Basins, and it is currently developing a strategic closure path that addresses each of these lines of evidence and identifies both basic and applied scientific issues that will need to be addressed in order to obtain regulatory closure. (authors)

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DOE OSTI2020

Big Data and AI at DoE's Legacy Sites - 20546

More than 30 years have passed since DOE started the decommissioning of nuclear weapon complexes and the clean-up of soil and groundwater. All the sites have been collecting and archiving soil and groundwater monitoring datasets; particularly contaminant concentration time-series. These datasets provide unparalleled opportunities to understand the system behavior (including more fundamental hydrological and geochemical processes, the response to various perturbations, the long-term trend and environmental decay rate towards the regulatory limit). This understanding is critical for providing multiple lines of evidences that can support site closure. In this study, we explore the machine learning (ML) and artificial intelligence (AI) applications to the long-term soil and groundwater management at DoE's legacy sites. ML can improve our understanding of the subsurface systems, which is critical for long-term monitoring and management of the sites, while AI can automate or support some of decision-making processes (e.g., anomaly detection, monitoring well placements). The particular focuses are to develop general algorithms to: (1) to identify distinct spatiotemporal patterns and to identify several groups that have similar temporal behaviors, using unsupervised clustering methods, (2) identify the different temporal scales of hydrological responses to climate perturbations by time-series analysis, and (3) reduce the number of monitoring wells by identifying the minimum sufficient number of wells to capture the heterogeneity of the groundwater contaminant plume and concentration distribution, using the Gaussian Process model. We demonstrate our methodology at the Savannah River Site F-Area. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗