Multi-scale modeling and simulation of a novel membrane reactor (MR)/adsorptive reactor (AR) process
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Energy & Fuels↗
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Results for “Model based development”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Lead Slowing-Down Spectrometry for Spent Fuel Assay: FY11 Status Report
Executive Summary Developing a method for the accurate, direct, and independent assay of the fissile isotopes in bulk materials (such as used fuel) from next-generation domestic nuclear fuel cycles is a goal of the Office of Nuclear Energy, Fuel Cycle R&D, Material Protection and Control Technology (MPACT) Campaign. To meet this goal, MPACT supports a multi-institutional collaboration to study the feasibility of Lead Slowing Down Spectroscopy (LSDS). This technique is an active nondestructive assay method that has the potential to provide independent, direct measurement of Pu and U isotopic masses in used fuel with an uncertainty considerably lower than the approximately 10% typical of today’s confirmatory assay methods. This document is a progress report for FY2011 collaboration activities. Progress made by the collaboration in FY2011 continues to indicate the promise of LSDS techniques applied to used fuel. PNNL developed an empirical model based on calibration of the LSDS to responses generated from well-characterized used fuel. The empirical model demonstrated the potential for the direct and independent assay of the sum of the masses of 239Pu and 241Pu to within approximately 3% over a wide used fuel parameter space. Similar results were obtained using a perturbation approach developed by LANL. Benchmark measurements have been successfully conducted at LANL and at RPI using their respective LSDS instruments. The ISU and UNLV collaborative effort is focused on the fabrication and testing of prototype fission chambers lined with ultra-depleted 238U and 232Th, and uranium deposition on a stainless steel disc using spiked U3O8 from room temperature ionic liquid was successful, with improving thickness obtained. In FY2012, the collaboration plans a broad array of activities. PNNL will focus on optimizing its empirical model and minimizing its reliance on calibration data, as well continuing efforts on developing an analytical model. Additional measurements are planned at LANL and RPI. LANL measurements will include a Pu sample, which is expected to provide more counts at longer slowing-down times to help identify discrepancies between experimental data and MCNPX simulations. RPI measurements will include the assay of an entire fresh fuel assembly for the study of self-shielding effects as well as the ability to detect diversion by detecting a missing fuel pin in the fuel assembly. The development of threshold neutron sensors will continue, and UNLV will calibrate existing ultra-depleted uranium deposits at ISU.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Uncertainty characterization in a coupled human-natural system: Modeling agricultural adaptation in the Great Lakes Region
The Great Lakes Region's water quality and ecological health are threatened by the export of nutrients from agricultural lands, which causes eutrophication, hypoxia, and destructive algal blooms. The intensification of hydrologic cycles brought about by climate change is expected to exacerbate nutrient loading in the region, and, at the same time, agricultural adaptation to changing conditions is also expected to affect loading through shifting amounts and timing of fertilization. Quantifying these future effects and their interactions necessitates modeling both the human and natural processes as a coupled system, by pairing land use and agricultural management with hydrologic modeling. At the same time, compounding uncertainties arising from the complex interactions in both systems significantly limit our predictive understanding of the region's impacts. This study utilizes the Soil and Water Assessment Tool (SWAT), developed for simulating the impact of various farmer decisions on watershed functions in Western Lake Erie watersheds, and an under-development agent-based model (ABM) for agricultural management decisions. The aim of this study is to use global sensitivity analysis on the coupled ABM and SWAT models to quantify how uncertainty in both models interactively affects nutrient loading. To do so, we will conduct Sobol sensitivity analysis experiments at different levels of coupling assumptions to quantify how various uncertain factors (e.g., soil moisture and crop choice) and their interactions affect our estimates of nutrient loading. The results of this analysis will allow us to quantify how complex interactions and dependencies between both systems amplify the effect of uncertainties. Insights gained from this study will have broader implications for modeling the adaptive co-evolution of human and natural systems under climate change and can inform effective management of nutrient loading in the Great Lakes Region.
Climate Change↗
A Reactor Scale-Up Methodology from Lab-Scale to Pilot-Scale Operations: Numerical Modeling of THFA Dehydration to DHP in Packed-Bed Reactors
This manuscript discusses developing a model-based scale-up methodology for a successful technology transfer of gas-phase catalytic reactors from a lab-scale to a pilot-scale operation. The manuscript demonstrates the methodology for gas-phase dehydration of tetrahydrofurfuryl alcohol (THFA) to dihydropyran (DHP) process over commercial Al 2 O 3 catalysts. A two-dimensional reactor model was developed using COMSOL Multiphysics 6.1 software. The model solves heat and mass transport equations in bed-scale and particle scales simultaneously. This powerful feature enables accurate prediction of the heat and mass transfer limitations in pilot-scale reactors, if any exists. Further, the model uses isothermal lab-scale experimental data to derive and validate the reaction chemistry, flow fields and boundary conditions. The model was then scaled-up to project conversion, selectivity, yield and formation rate of DHP in a pilot-scale reactor. The results highlight the complex nature of chemistry, heat, and mass transfer effects in lab-scale and pilot-scale reactors. The model results inform the possible operational limitations of the pilot-scale reactor and design strategies to improve process efficiency. Although the scale-up approach is explained through the THFA dehydration process, the methodology is applicable to any catalytic packed-bed reactor models for a successful process scale-up.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Unsteady thermotechnical model of a closed flat plate solar collector–storage tank system
The main provisions of the developed numerical unsteady model of the flat plate solar collector–storage tank (SC–ST) system are given. The model takes into account all of the main parameters of the SC (receiver parameters, radiative properties of the transparent fence for solar radiation, and thermophysical properties of the thermal insulation of the bottom) and the ST (thermophysical parameters of thermal insulation). An algorithm and a program for calculating the thermal properties of a closed SC–ST system have been developed based on this model in the Delphi language. The results of the calculated estimates of the time variation of water heating temperatures in the ST and the efficiency of the closed SC–ST system as a function of the ST volume are given for the case where the water temperature at the SC inlet is equal to the mean water temperature in the ST. The model and the program also make it possible to determine the time variation of temperatures of SC elements and water in individual sections along the length of the SC as well as the thermal losses of the SC sections. The model makes it possible to estimate the effect of the thermal properties of SC elements and the water velocity on the thermal properties of the SC–ST system. The program can be modified for the case of the open SC–ST system, i.e., where the water temperature at the SC inlet does not depend on the water temperature in the ST.
14 SOLAR ENERGY↗
Development and Validation of Resistance-Capacitance Model for Phase Change Material Embedded in Porous Media
A simple and effective way to enhance PCM thermal conductivity is by embedding porous materials with high thermal conductivities. In this work, CFD was used to evaluate the melting of PCM embedded in metal foam supplied with constant heat flux. Good agreement between experimental and numerical results has been found with a mean PCM local temperature deviation of 1.62K and 2.97K in two locations. The CFD simulation time was 56 hours for 6.5 hours of flow time. A computationally efficient resistance capacitance-based model (RCM) was developed to improve simulation speed. The proposed RCM exhibited mean local temperature deviations of 1.86K and 2.96K when compared against the experimental data for two thermocouple positions, however, it was approximately 2.5x10 5 times faster than CFD. The charging time deviation was less than 1% compared to CFD, and no significant change in thermal energy stored was observed since the temperature differences were small enough to result in insignificant sensible heat deviation. A simulation cost-effectiveness index (CEI) considering accuracy and computational affordability was introduced; the CEI of the RCM solver is 10 3 times better compared to CFD for the prediction of local PCM temperature.
25 ENERGY STORAGE↗
Resilience-Motivated Distribution System Restoration Considering Electricity-Water-Gas Interdependency
A major outage in the electricity distribution system may affect the operation of water and natural gas supply systems, leading to an interruption of multiple services to critical customers. Therefore, enhancing resilience of critical infrastructures requires joint efforts of multiple sectors. In this paper, a distribution system service restoration method considering the electricity-water-gas interdependency is proposed. The objective is maximizing the supply of electricity, water, and gas to critical customers after an extreme event. The operational constraints of electricity, water, and natural gas networks are considered. Additionally, the characteristics of electricity-driven coupling components, including water pumps and gas compressors, are also modeled. Relaxation techniques are applied to non convex constraints posed by physical laws of those networks. Consequently, the restoration problem is formulated as a mixed-integer second-order cone program, which can readily be solved by the off-the-shelf solvers. The proposed method is validated by numerical simulations on an electricity-water-gas integrated system, developed based on benchmark models of the subsystems. The results indicate that considering the interdependency refines the allocation of limited generation resources and demonstrate the exactness of the proposed convex relaxation
24 POWER TRANSMISSION AND DISTRIBUTION↗
2D-imaging of sampling-probe perturbations in laminar premixed flames using Kr X-ray fluorescence
The perturbation of the temperature field caused by a quartz sampling probe has been investigated in a fuel-rich low-pressure premixed ethylene/oxygen/argon/krypton flame using X-ray fluorescence. The experiments were performed at the 7-BM beamline at the Advanced Photon Source (APS) at the Argonne National Laboratory where a continuous beam of X-rays at 15 keV was used to excite krypton atoms that were added to the unburnt flame gases in a concentration of 5% (by volume). The resulting krypton X-ray fluorescence at 12.65 keV was collected and the spatially resolved signal was subsequently converted into the local temperature of the imaged spot. One and two dimensional scans of the temperature field were obtained by translating the entire flame chamber through a pre-programmed sequence of positions on high precision translation stages and measuring the X-ray fluorescence at each location. Multiple measurements were performed at various separations between the burner surface and probe tip, representing sampling positions from the preheat, reaction, and postflame zones of the low-pressure flame. Distortions of up to 1000 K of the burner-probe centerline flame temperature were found with the tip of the probe in the preheat zone and distortions of up to 500 K were observed with it in the reaction and postflame zones. Furthermore, perturbations of the temperature field have been revealed that radially reach as far as 20 mm from the burner-probe centerline and about 3 mm in front of the probe tip. Finally, these results clearly reveal the limitations of one-dimensional models for predicting flame-sampling experiments and comments are made with regard to model developments and validations based on quantitative speciation data from low-pressure flames obtained via intrusive sampling techniques.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
CHIRP-Like Signals: Estimation, Detection and Processing A Sequential Model-Based Approach
Chirp signals have evolved primarily from radar/sonar signal processing applications specifically attempting to estimate the location of a target in surveillance/tracking volume. The chirp, which is essentially a sinusoidal signal whose phase changes instantaneously at each time sample, has an interesting property in that its correlation approximates an impulse function. It is well-known that a matched-filter detector in radar/sonar estimates the target range by cross-correlating a replicant of the transmitted chirp with the measurement data reflected from the target back to the radar/sonar receiver yielding a maximum peak corresponding to the echo time and therefore enabling the desired range estimate. In this application, we perform the same operation as a radar or sonar system, that is, we transmit a “chirp-like pulse” into the target medium and attempt to first detect its presence and second estimate its location or range. Our problem is complicated by the presence of disturbance signals from surrounding broadcast stations as well as extraneous sources of interference in our frequency bands and of course the ever present random noise from instrumentation. First, we discuss the chirp signal itself and illustrate its inherent properties and then develop a model-based processing scheme enabling both the detection and estimation of the signal from noisy measurement data.
42 ENGINEERING↗
SU-E-J-03: A Comprehensive Comparison Between Alpha and Beta Emitters for Cancer Radioimmunotherapy
Purpose: The purpose of this study is to perform a comprehensive comparison of the therapeutic efficacy and cytotoxicity of alpha and beta emitters for Radioimmunotherapy (RIT). For each stage of cancer development, specific models were built for the separate objectives of RIT to be addressed:a) kill isolated cancer cells in transit in the lymphatic and vascular circulation,b) regress avascular cell clusters,c) regress tumor vasculature and tumors. Methods: Because of the nature of short range, high LET alpha and long energy beta radiation and heterogeneous antigen expression among cancer cells, the microdosimetric approach is essential for the RIT assessment. Geant4 based microdosimetric models are developed for the three different stages of cancer progression: cancer cells, cell clusters and tumors. The energy deposition, specific energy resulted from different source distribution in the three models was calculated separately for 4 alpha emitting radioisotopes ({sup 211}At, {sup 213}Bi, {sup 223}Ra and {sup 225}Ac) and 6 beta emitters ({sup 32}P, {sup 33}P, {sup 67}Cu, {sup 90}Y, {sup 131}I and {sup 177}Lu). The cell survival, therapeutic efficacy and cytotoxicity are determined and compared between alpha and beta emitters. Results: We show that internal targeted alpha radiation has advantages over beta radiation for killing isolated cancer cells, regressing small cell clusters and also solid tumors. Alpha particles have much higher dose specificity and potency than beta particles. They can deposit 3 logs more dose than beta emitters to single cells and solid tumor. Tumor control probability relies on deep penetration of radioisotopes to cancer cell clusters and solid tumors. Conclusion: The results of this study provide a quantitative understanding of the efficacy and cytotoxicity of RIT for each stage of cancer development.
60 APPLIED LIFE SCIENCES↗
Novel Approach to PV Inverter Modeling and Simulation Leveraging Experiments, Learning Based Modeling and Co-Simulation: Preprint
Photovoltaic inverter (PV) inverter manufacturers use custom, proprietary control approaches and topologies in their inverter design. Due to this proprietary nature, it is not possible to share EMT domain models for system studies. This research work presents a novel approach in experimental design, high fidelity data collection, use of learning-based modeling, and co-simulation to enhance the PV inverter modeling. We used a 20 kW off-the-shelf grid following PV inverter and subjected the inverter to controlled tests including voltage and frequency step changes, as well as solar irradiance variations. The recorded high frequency data was used in learning-based model training. This learning-based model was imported into an Electromagnetic Transient (EMT) simulation tool using co-simulation techniques to complete the modeling effort and integrate the model into an EMT simulation tool. The three key components in this research work are the design of experimental setup, use of learning-based approach for model development and use of co-simulation to complete the approach. The proposed approach will allow users to develop a model in a really short period of time and achieve reasonable inverter models.
artificial intelligence↗
Arctic Shrub Expansion, Plant Functional Trait Variation, and Effects on Belowground Carbon Cycling (Final Technical Report)
Terrestrial ecosystems are undergoing dramatic changes in response to climate warming, and these changes are expected to feedback to the atmosphere, potentially altering the trajectory of future climate change. Feedbacks from Arctic ecosystems are a major concern because the Arctic is projected to warm significantly in the 21 st century and because >50% of global belowground organic carbon is stored in permafrost and overlying soils. Warming-driven release of this carbon could drastically increase atmospheric greenhouse gas concentrations and accelerate climate warming. Plant communities are also responding to warming, as evidenced by the widely documented increase in woody-shrub growth and “greening” across much of the Arctic tundra biome. This vegetation shift may offset or amplify warming by altering carbon cycling. The direction and magnitude of shrub effects remain highly uncertain, however, due to limited understanding of the consequences of shrub expansion for belowground carbon cycling and simplification of these relationships in models. The major shrubs expanding in the Arctic (Betula, Salix, and Alnus) vary widely with respect to aboveground and belowground traits (e.g., tissue production and chemistry, rooting depth, microbial symbionts), and may also exhibit substantial intraspecific variation in these traits in response to environmental conditions. Such variation is likely to have profound implications for soil carbon cycling. The overarching goal of this project was to improve process-based understanding of the influence of shrub expansion on carbon cycling to enable improved representation of carbon dynamics in ecosystem and Earth system models. We investigated how plant functional traits vary among shrub genera, respond to environmental conditions, and affect belowground carbon and nutrient cycling by quantifying relationships among functional traits and biogeochemical cycling along edaphic gradients nested within a climate gradient in the Alaskan tundra. We found consistent differences in leaf and root traits among shrub genera and between shrubs and a widespread sedge species, indicating diverse nutrient acquisition strategies and belowground impacts among different arctic shrubs. We also found striking differences in trait values among individuals within the same species or genera within sites. Soil parameters were more important than climate parameters for predicting size and leaf trait variation, and root trait responses were less dependent on climate overall. For all but one root trait, including parameters representing aboveground traits improved the predictive ability of models. These results demonstrate that tundra shrub traits vary considerably at local scales and soil factors drive this variation, especially belowground. Furthermore, leveraging information about aboveground traits and soil conditions can improve predictions of how belowground traits will respond to climate change. Despite these differences, soil carbon and nitrogen pools in the active layer did not vary among plots dominated by different shrub or sedge genera. Instead, pool sizes generally decreased from warmer to colder sites, consistent with a productivity gradient. Patterns of isotopic N composition indicate that shrubs tighten nitrogen cycling via nitrogen resorption or immobilization of shrub litter. Overall, these results suggest that further identifying the specific shrub genera in the tundra landscape will ultimately provide better predictions of belowground dynamics across the changing arctic. We also performed simulation experiments with the Terrestrial Ecosystem Model (TEM) incorporated in the Predictive Ecosystem Analyzer (PEcAn) framework, treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We performed simulations across different types of tundra, including shrub tundra. One key finding was that both model sensitivity and uncertainty to a given parameter could vary within the same type of tundra, but in a different geographical location, such as over the climate gradient of shrub tundra described above. We organized a special session at the annual meeting of the Ecological Society of America in August 2019 to disseminate our results, refine recommendations for model improvement, and initiate collaborations to implement these recommendations in existing models of tundra carbon dynamics at ecosystem to Earth system scales. Our results support DOE near-term priorities by providing mechanistic insights into the role of vegetation change in the terrestrial carbon cycle in a region that is inadequately represented in Earth system models. Current models reduce the complexity of Arctic vegetation to a small number of plant functional types (PFTs). This approach implicitly assumes that each PFT represents the average ecological function of its constituent species, thus ignoring the effects of trait variation on biogeochemical cycling and potentially leading to large uncertainty in the sign and magnitude of ecosystem feedbacks to climate. By quantifying variation of plant functional traits across broad gradients of climatic and edaphic conditions and elucidating the linkages of such variation with carbon and nutrient cycling, our results illustrate the need and create a foundation for further developing trait-based modeling approaches that allow the traits of PFTs to vary as a function of environmental conditions. These approaches should improve the capacity of simulation models to offer insights into ecosystem carbon dynamics associated with novel plant communities in a rapidly changing Arctic.
54 ENVIRONMENTAL SCIENCES↗
Results from a synthetic model of the ITER XRCS-Core diagnostic based on high-fidelity x-ray ray tracing
A high-fidelity synthetic diagnostic has been developed for the ITER core x-ray crystal spectrometer diagnostic based on x-ray ray tracing. This synthetic diagnostic has been used to model expected performance of the diagnostic, to aid in diagnostic design, and to develop engineering tolerances. The synthetic model is based on x-ray ray tracing using the recently developed xicsrt ray tracing code and includes a fully three-dimensional representation of the diagnostic based on the computer aided design. The modeled components are: plasma geometry and emission profiles, highly oriented pyrolytic graphite pre-reflectors, spherically bent crystals, and pixelated x-ray detectors. Plasma emission profiles have been calculated for Xe 44+ , Xe 47+ , and Xe 51+ , based on an ITER operational scenario available through the Integrated Modelling & Analysis Suite database, and modeled within the ray tracing code as a volumetric x-ray source; the shape of the plasma source is determined by equilibrium geometry and an appropriate wavelength distribution to match the expected ion temperature profile. All individual components of the x-ray optical system have been modeled with high-fidelity producing a synthetic detector image that is expected to closely match what will be seen in the final as-built system. Particular care is taken to maintain preservation of photon statistics throughout the ray tracing allowing for quantitative estimates of diagnostic performance.
47 OTHER INSTRUMENTATION↗
A general peridynamics model for multiphase transport of non-Newtonian compressible fluids in porous media
Herein a general state-based peridynamics model is developed to simulate transport of fluids in an arbitrary heterogeneous porous medium. The generality encompasses modeling of multiphase, multi-component flow of non-Newtonian and compressible fluids, which is often encountered in but not limited to subsurface reservoirs. Peridynamic model is especially useful for solving non-local problems, such as crack propagation, since it does not assume spatial continuity of field variables. Thus, the formulation presented here, combined with peridynamics-based damage model, can be used to simulate hydraulic fracturing with complex fluids. To demonstrate its capability to simulate multi-phase flow in porous media, the derived model is verified against the analytical Buckley-Leverett solution for immiscible Newtonian two-phase flow. Further, the non-Newtonian two-phase fluid flow in porous media is verified by simulating the polymer flood process involving immiscible displacement of a Newtonian fluid by a non-Newtonian fluid against a generalized solution obtained by Wu et al. The non-local solutions are shown to be consistent with the corresponding local solutions in limiting cases. Moreover, mass conservation of all the phases is satisfied, irrespective of discretization and extent of non-locality.
42 ENGINEERING↗
Fusion Fuel Cycle Inventory Reduction Studies Using a Processing-Time–Based Discrete-Time Interval Model
Developing a Fusion Pilot Plant (FPP) design that minimizes risks due to tritium in-process inventory (IPI) is an important concern for the operation of commercial devices. This becomes even more of concern since an FPP will be breeding more tritium than is burned in the reactor for sustainability. The IPI is the tritium moving through the system that is not in the storage and delivery subsystem. Here a process model that solves time-dependent differential equations based on processing times was used to investigate the reduction of the IPI of a potential fuel cycle design. The impact of new and more efficient technologies such as direct internal recycling (DIR), metal foil pumps, continuous pumping, improved isotope separation, and hydrogen separating continuous pumps on IPI was investigated by adjusting subsystem processing times and material flow streams. It was shown that any of the insertions of DIR studied in this paper caused a reduction in the total IPI of the system and proved to be the optimal way to reduce the IPI in the system. Fuel cycle modifications near the torus, such as a coupled DIR and improved pumping systems, produced the largest reductions in tritium inventory.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Multisensor Agile Adaptive Sampling of Convective Storms Driven by Real-time Analytics
Convective storms vertically transport water vapor and condensate from Earth’s surface to the upper troposphere. Life on Earth is fundamentally linked to this transport which determines the hydrological cycle, and the intensity of severe weather responsible for the destruction of life and property. Despite advances in high-resolution modeling and better observational capabilities, the scientific community continues to be confronted with knowledge gaps about convective storms that limit our predictive capabilities. The ongoing developments in the high-resolution Energy Exascale Earth System Model (E3SM), large eddy simulations, and AI-based analytics to evaluate uncertainties are expected to provide a comprehensive framework for new scientific discovery. The model-experiment (MODEX) approach suggests that the aforementioned advancements in model development and AI-based inference techniques should be complemented by similar advancements in the experimental (observational) side so that the former does not outstrip the ability of the latter to provide meaningful constraints. What are the recent advancements in observations that will provide the necessary leap forward in improving our predictive capabilities? To address this question, we propose a new experimental paradigm called Multisensor Agile Adaptive Sampling (MAAS) that capitalizes on advancements in communications (5G), computational resources (edge/fog computing), sensor capabilities, and machine learning (ML) and AI techniques (Kollias et al., 2020). The MAAS framework allows for the collection of higher spatiotemporal resolution and quality observations of convective storms than is traditionally possible. The MAAS framework is scalable and applicable to atmospheric observatories such as those operated by the Department of Energy (DoE) Atmospheric Radiation Measurement (ARM) facility.
54 ENVIRONMENTAL SCIENCES↗
Innovative Use of Cr(VI) Plume Depictions and Pump-and-Treat Capture Analysis to Estimate Risks of Contaminant Discharge to Surface Water at Hanford Reactor Areas
The Hanford Site nuclear reactor operations required large quantities of high-quality cooling water, which was treated with chemicals including sodium dichromate dihydrate for corrosion control. Cooling water leakage, as well as intentional discharge of cooling water to ground during upset conditions, produced extensive groundwater recharge mounds consisting largely of contaminated cooling water and resulted in wide distribution of hexavalent chromium (Cr[VI]) contamination in the unconfined aquifer. The 2013 Cr(VI) groundwater plumes in the 100 Areas cover approximately 6 km2 (1500 acres), primarily in the 100-HR-3 and 100-KR-4 groundwater operable units (OUs). The Columbia River is a groundwater discharge boundary; where the plumes are adjacent to the Columbia River there remains a potential to discharge Cr(VI) to the river at concentrations above water quality criteria. The pump-and-treat systems along the River Corridor are operating with two main goals: 1) protection of the Columbia River, and 2) recovery of contaminant mass. An evaluation of the effectiveness of the pump-and-treat systems was needed to determine if the Columbia River was protected from contamination, and also to determine where additional system modifications may be needed. In response to this need, a technique for assessing the river protection was developed which takes into consideration seasonal migration of the plume and hydraulic performance of the operating well fields. Groundwater contaminant plume maps are generated across the Hanford Site on an annual basis. The assessment technique overlays the annual plume and the capture efficiency maps for the various pump and treat systems. The river protection analysis technique was prepared for use at the Hanford site and is described in detail in M.J. Tonkin, 2013. Interpolated capture frequency maps, based on mapping dynamic water level observed in observation wells and derived water levels in the vicinity of extraction and injection wells, are developed initially. Second, simulated capture frequency maps are developed, based on transport modelling results. Both interpolated and simulated capture frequency maps are based on operation of the systems over a full year. These two capture maps are then overlaid on the plume distribution maps for inspection of the relative orientation of the contaminant plumes with the capture frequency. To quantify the relative degree of protection of the river from discharges of Cr(VI) (and conversely, the degree of threat) at any particular location, a systematic method of evaluating and mapping the plume/capture relationship was developed. By comparing the spatial relationship between contaminant plumes and hydraulic capture frequency, an index of relative protectiveness is developed and the results posted on the combined plume/capture plan view map. Areas exhibiting lesser degrees of river protection are identified for remedial process optimization actions to control plumes and prevent continuing discharge of Cr(VI) to the river.
Miller, Chuck W.↗