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DOE OSTI2017

Geothermal reservoir characterization using distributed temperature sensing at Brady Geothermal Field, Nevada

Distributed temperature sensing (DTS) systems provide near real-time data collection that captures borehole spatiotemporal temperature dynamics. For this study, temperature data was collected in an observation well at an active geothermal site for a period of eight days under geothermal production conditions. Collected temperature data showcase the ability of DTS systems to detect changes to the location of the steam-water interface, visualize borehole temperature recovery — following injection of a coldwater “slug” — and identify anomalously warm and/or cool zones. The high sampling rate and spatial resolution of DTS data also shows borehole temperature dynamics that are not captured by traditional pressure-temperature survey tools. Inversion of thermal recovery data using a finite-difference heat-transfer model produces a thermal-diffusivity profile that is consistent with laboratorymeasured values and correlates with identified lithologic changes within the borehole. Used alone or in conjunction with complementary data sets, DTS systems are useful tools for developing a better understanding of both reservoir rock thermal properties as well as within and near borehole fluid movement.

15 GEOTHERMAL ENERGY↗

DOE OSTI2022

Overview of the COMPASS results *

COMPASS addressed several physical processes that may explain the behaviour of important phenomena. This paper presents results related to the main fields of COMPASS research obtained in the recent two years, including studies of turbulence, L–H transition, plasma material interaction, runaway electron, and disruption physics: Tomographic reconstruction of the edge/SOL turbulence observed by a fast visible camera allowed to visualize turbulent structures without perturbing the plasma. Dependence of the power threshold on the X-point height was studied and related role of radial electric field in the edge/SOL plasma was identified. The effect of high-field-side error fields on the L–H transition was investigated in order to assess the influence of the central solenoid misalignment and the possibility to compensate these error fields by low-field-side coils. Results of fast measurements of electron temperature during ELMs show the ELM peak values at the divertor are around 80% of the initial temperature at the pedestal. Liquid metals were used for the first time as plasma facing material in ELMy H-mode in the tokamak divertor. Good power handling capability was observed for heat fluxes up to 12 MW m –2 and no direct droplet ejection was observed. Partial detachment regime was achieved by impurity seeding in the divertor. The evolution of the heat flux footprint at the outer target was studied. Runaway electrons were studied using new unique systems—impact calorimetry, carbon pellet injection technique, wide variety of magnetic perturbations. Radial feedback control was imposed on the beam. Forces during plasma disruptions were monitored by a number of new diagnostics for vacuum vessel (VV) motion in order to contribute to the scaling laws of sideways disruption forces for ITER. Current flows towards the divertor tiles, incl. possible short-circuiting through PFCs, were investigated during the VDE experiments. The results support ATEC model and improve understanding of disruption loads.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Smart Proxy Modeling of SACROC CO2-EOR

Large CO2-enhanced oil recovery (EOR) projects usually contain an abundance of geological and good performance data. While this volume of data leads to robust models, it often results in difficult to manage, slow-running numerical flow models. To dramatically reduce the numerical run-times associated with the traditional simulation techniques, this work investigated the feasibility of using artificial intelligence and machine learning technologies to develop a smart proxy model of the Scurry Area Canyon Reef Operators Committee (SACROC) oilfield, located in the Permian Basin, TX, USA. Smart proxy models can be used to facilitate injection-production optimization for CO2-EOR projects. The use of a coupled grid-based, and well-based surrogate reservoir model (SRM) (also known as smart proxy modeling) was investigated as the base of the optimization. A fit-for-purpose coupled SRM, which executes in seconds, was built based on high-resolution numerical reservoir simulation models of the northern platform of the SACROC oilfield. This study is unique as it is the first application of coupled SRM at a large oilfield. The developed SRM was able to identify the dynamic reservoir properties (pressure, saturations, and component mole-fraction) at every grid-block, along with the production characteristics (pressure and rate) at each well. Recent attempts to use machine learning and pattern recognition to build proxy models have been simplistic, with limited predictive capabilities. The geological model used in this study is comprised of more than nine million grid blocks. The high correlation between the actual component and SRM, which can be visualized by mapping the properties, along with the fast footprint of the developed model demonstrate the successful application of this methodology.

Vida, Gholami↗

DOE OSTI2020

BWR Spent Nuclear Fuel Acquisition and Testing to Support DOE-NE High Burnup Spent Fuel Data Project

The Office of Spent Fuel and Waste Disposition (SFWD) within the US Department of Energy (DOE) Office of Nuclear Energy (NE) established the Spent Fuel and Waste Science and Technology (SFWST) campaign to conduct research and development (R&D) activities related to the storage, transportation, and disposal of spent nuclear fuel (SNF) and high-level radioactive waste. The SFWST program was created within SFWD to address issues of extended or long-term SNF storage and transportation. Some near-term objectives of SFWST are to use a science-based, engineering-driven approach to: Support the enhancement of the technical bases to support the continued safe and secure dry storage of SNF for extended periods; Support the enhancement of the technical bases for retrieving SNF after extended dry storage; Support the enhancement of the technical bases for transporting high burnup (HBU) fuel and transporting low burnup fuel and HBU fuel after dry storage DOE-NE, in partnership with the Electric Power Research Institute, developed the High Burnup Spent Fuel Data Project to perform a large-scale demonstration and laboratory-scale testing of HBU pressurized water reactor (PWR) fuels (exceeding 45 gigawatt-days per metric ton of uranium [GWd/MTU]). Under this project, 25 sister rods—which are rods that have the same design, power histories, and other characteristics—were removed from assemblies at the North Anna Nuclear Power Station and sent to Oak Ridge National Laboratory (ORNL) in January 2016. ORNL performed detailed nondestructive examination (NDE) on all 25 rods. The NDE consisted of visual examinations, gamma and neutron scanning, profilometry and rod length measurements, and eddy current examinations. After completing the NDE, 10 of the sister rods were delivered to Pacific Northwest National Laboratory (PNNL) in a NAC International, Inc. legal-weight truck cask in September 2018 for destructive examination (DE). To date, SFWD work has focused on the PWR fuel that is part of the Sister Rod Test program. No boiling water reactor (BWR) fuel has been tested in the program, and the data needs that were identified for the PWR fuel have not been collected for BWR fuel. The goal to obtain six to nine BWR rods and test them at ORNL will support closing this important data gap. BWR fuel comprises approximately 56% of the total fuel assemblies currently in storage at nuclear power plants in the United States. BWR nuclear fuel and cladding designs and manufacturing are significantly different from PWRs. Differences include the following: BWR fuel pellets are larger than PWR pellets; Variations of Zircaloy-2 (including liners) are used instead of the Zircaloy-4 cladding materials used in PWRs; Clad manufacturing and stress-relief processes are different between PWRs and BWRs; The fuel rod dimensions are different because larger rod diameters and thicker cladding are used in BWRs; BWR fuel typically has lower internal rod pressures and sees vastly different operating conditions than PWR fuel (i.e., two-phase flow); BWR assemblies are “canned,” meaning each assembly is surrounded by a metal fuel channel; BWR cladding is often composed of an inner pure Zr liner that has widely different mechanical properties than the Zircaloy-2 alloy and exhibits a stronger affinity for hydrogen; The BWR SNF generally has more total hydrogen in the cladding/liner than typical PWR fuel; The construction of the PWR and BWR assemblies is vastly different; BWR rods are solidly attached to the assembly nozzles and experience a much different vibration and shock load than PWR rods, which are “floating” within a grid system attached to guide tubes, and the rods sit loosely on the bottom end plates. These numerous differences will affect the way the BWR SNF responds under dry storage preparation processes (e.g., vacuum drying) and during transportation. The results collected in the PWR experimental program must be compared with a subset of similar data collected on BWR SNF to establish a technical basis for whether the larger PWR database is sufficient to bound the BWR SNF end-of-life conditions as is currently assumed for several fuel/clad properties. Changes that occur in both fuel types at HBU could exacerbate any mechanical property differences. As the fuel burnup increases, several changes occur that might affect the performance of the fuel, cladding, and assembly hardware in storage and transportation. These changes include increased cladding corrosion layer thickness, increased cladding hydrogen content, increased cladding creep strains, increased fission gas release, and the formation of the HBU structure at the surface of the fuel pellets. The Nuclear Regulatory Commission (NRC) limits the current maximum rod-averaged burnup to 62 GWd/MTU due to these changes and the lack of data at higher burnups.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2014

SU-E-J-61: Electrodynamics and Nano-Scale Fluid Dynamics in Protein Localization of Nuclear Pore Complexes

Purpose: To develop a simulation to catalyze a reevaluation of common assumptions about 3 dimensional diffusive processes and help cell biologists gain a more nuanced, intuitive understanding of the true physical hurdles of protein signaling cascades. Furthermore, to discuss the possibility of intracellular electrodynamics as a critical, unrecognized component of cellular biology and protein dynamics that is necessary for optimal information flow from the cell membrane to the nucleus. Methods: The Unity 3D gaming physics engine was used to build an accurate virtual scale model of the cytoplasm within a few hundred nanometers of the nuclear membrane. A cloud of simulated pERK proteins is controlled by the physics simulation, where diffusion is based on experimentally measured values and the electrodynamics are based on theoretical nano-fluid dynamics. The trajectories of pERK within the cytoplasm and through the 1250 nuclear pores on the nuclear surface is recorded and analyzed. Results: The simulation quickly demonstrates that pERKs moving solely by diffusion will rarely locate and come within capture distance of a nuclear pore. The addition of intracellular electrodynamics between charges on the nuclear pore complexes and on pERKs increases the number of successful translocations by allowing the electro-physical attractive effects to draw in pERKs from the cytoplasm. The effects of changes in intracellular shielding ion concentrations allowed for estimation of the “capture radius” under varying conditions. Conclusion: The simulation allows a shift in perspective that is paramount in attempting to communicate the scale and dynamics of intracellular protein cascade mechanics. This work has allowed researchers to more fully understand the parameters involved in intracellular electrodynamics, such as shielding anion concentration and protein charge. As these effects are still far below the spatial resolution of currently available measurement technology this simulation is invaluable to researchers to visualize and study current hypotheses concerning protein dynamics.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Dramatic Demand Reduction In The Desert Southwest

This report summarizes a project that was funded to the University of Nevada Las Vegas (UNLV), with subcontractors Pulte Homes and NV Energy. The project was motivated by the fact that locations in the Desert Southwest portion of the US demonstrate very high peak electrical demands, typically in the late afternoons in the summer. These high demands often require high priced power to supply the needs, and the large loads can cause grid supply problems. An approach was proposed through this contact that would reduce the peak electrical demands to an anticipated 65% of what code-built houses of the similar size would have. It was proposed to achieve energy reduction through four approaches applied to a development of 185 homes in northwest part of Las Vegas named Villa Trieste. First, the homes would all be highly energy efficient. Secondly, each house would have a PV array installed on it. Third, an advanced demand response technique would be developed to allow the resident to have some control over the energy used. Finally, some type of battery storage would be used in the project. Pulte Homes designed the houses. The company considered initial cost vs. long-term savings and chose options that had relatively short paybacks. HERS (Home Energy Rating Service) ratings for the homes are approximately 43 on this scale. On this scale, code-built homes rate at 100, zero energy homes rate a 0, and Energy Star homes are 85. In addition a 1.764 Wp (peak Watt) rated PV array was used on each house. This was made up of solar shakes that were in visual harmony with the roofing material used. A demand response tool was developed to control the amount of electricity used during times of peak demand. While demand response techniques have been used in the utility industry for some time, this particular approach is designed to allow the customer to decide the degree of participation in the response activity. The temperature change in the residence can be decided by the residents by adjusting settings. In a sense the customer can choose between greater comfort and greater money savings during demand response circumstances. Finally a battery application was to be considered. Initially it was thought that a large battery (probably a sodium-sulfur type) would be installed. However, after the contract was awarded, it was determined that a single, centrally-located battery system would not be appropriate for many reasons, including that with the build out plan there would not be any location to put it. The price had risen substantially since the budget for the project was put together. Also, that type of battery has to be kept hot all the time, but its use was only sought for summer operation. Hence, individual house batteries would be used, and these are discussed at the end of this report. Many aspects of the energy use for climate control in selected houses were monitored before residents moved in. This was done both to understand the magnitude of the energy flows but also to have data that could be compared to the computer simulations. The latter would be used to evaluate various aspects of our plan. It was found that good agreement existed between actual energy use and computed energy use. Hence, various studies were performed via simulations. Performance simulations showed the impact on peak energy usage between a code built house of same size and shape compared to the Villa Trieste homes with and without the PV arrays on the latter. Computations were also used to understand the effect of varying orientations of the houses in this typical housing development, including the effect of PV electrical generation. Energy conservation features of the Villa Trieste homes decreased the energy use during peak times (as well as all others), but the resulting decreased peak occurred at about the same time as the code-built houses. Consideration of the PV generation decreases the grid energy use further during daylight hours, but did not extend long enough many days to decrease the peak. Hence, a demand response approach, as planned, was needed. With participation of the residents in the demand response program developed does enable the houses to reduce the peak demand between 66% and 72%, depending on the built years. This was addressed fully in the latter part the study and is described in the latter part of this report.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

In situ multimodal imaging for nanoscale visualization of tribofilm formation

A third of the energy from fuel combustion in passenger car gasoline engines is lost due to friction. Carefully designed engine lubricants can recover some of these losses by reducing friction and wear by forming a nanometer-scale chemico-physico tribofilm between surfaces. Accordingly, attention has focused on developing oil formulations that form low-friction tribofilms. However, analyses of resultant tribofilms are typically conducted after tribo-tests with conventional characterization tools and do not offer insights into tribofilm formation and evolution, precluding information critical to tuning tribofilm properties. In this work, we developed a unique multimodal methodology based on Atomic Force Microscopy (AFM) with local probe heating for in situ tribological studies that activates friction modifiers and simultaneously captures the evolution of friction and surface roughness, with nanometer resolution. As a platform to demonstrate the ability of this methodology to visualize dynamics of tribofilm formation in situ, we apply it to molybdenum-based friction modifiers to distinguish key factors in their functionality and correlate nanoscale AFM and Friction Force Microscopy data to bench tribo-tests used in the industry. To decode the formation mechanisms observed in situ and underlying chemistry of tribofilms, we performed ab initio Molecular Dynamics (AIMD) simulations at comparable conditions. AIMD simulations confirmed both nanoscale and bench tribo-test results and showed deviations in molecular organization in tribofilms that are formed from different molybdenum-based friction modifiers that corroborates with surface functionality. With this innovative methodology, we demonstrate proof-of-principle in situ formation of molybdenum-based tribofilms directly on steel surfaces that could be applied generally to studying tribofilm formation.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Novel Infiltration Diagnostics based on Laser-line Scanning and Infrared Temperature Field Imaging

This project targets the building energy efficiency problems induced by building infiltration/leaks. The current infiltration inspection techniques often require extensive visual inspection and/or whole building pressure test. These current techniques cannot meet more than three of the below five criteria of ideal infiltration diagnostics: 1. location and extent diagnostics, 2. building-level application, 3. least surface preparation, 4. weather-proof, and 5. non-disruption to building occupants. These techniques are either too expensive or time consuming, and often lack accuracy and repeatability. They are hardly applicable to facades/facades section. The goal of the project was to develop a novel infiltration diagnostics technology based on laser line-scanning and simultaneous infrared temperature imaging. A laboratory scale experimental setup was designed to mimic a model house of well-defined pressure difference below or above the outside pressure. Algorithms and Matlab-based programs had been developed for recognition of the hole location in infrared images. Our experiment based on laser wavelengths of 450 and 1550 nm and laser beam diameters of 4-25 mm showed that the location of the holes could be identified using laser heating; the diagnostic approach however could not readily distinguish between infiltration and non-infiltration points. To significantly improve the scanning throughput and recognition accuracy, a second approach was explored, developed, and extensively tested. It incorporates a liquid spray on the surface to induce extra phase change cooling effect. In this spray method, we termed it as PECIT (Phase-change Enhanced Cooling Infrared Thermography), phase-change enhanced cooling was used, which significantly amplifies the effect of air flow (infiltration and exfiltration). This heat transfer method worked extremely well to identify infiltration and exfiltration locations with high accuracy and increased throughput. The PECIT technique was systematically developed and tested for through holes with diameters 1 mm to 2 mm, and diagonal lines of 0.5 mm width at different camera-wall distances of 46 cm to 200 cm, under different pressure differences from 5 Pa to 20 Pa, and under different wind conditions. The PECIT technique had either met or exceeded the goals proposed in the project. For exfiltration, we achieved 100% accuracy under a much lower pressure difference of 10 Pa (proposed one: 50 Pa with stretch goal of 15 Pa). For infiltration, we achieved >90% accuracy under a much lower pressure difference of 10 Pa (proposed one: 50 Pa with stretch goal of 15Pa). For exfiltration, we achieved 100% accuracy under a much lower pressure difference of 10 Pa. For infiltration, we achieved 100% accuracy under a much lower pressure difference of 10 Pa. The PECIT technique can reach a throughput of 120 m2/h, which is 4 times the proposed goal for the laser line-scanning and simultaneous infrared temperature imaging approach. For commercialization and market penetration, we had meetings with two companies for feedback collection and further improvement for practical use. Also, we have interacted with Office of Intellectual Property and Technology Transfer of Iowa State University for idea disclosure and patent application.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Development of Strong Anaerobic Fluorescent Reporters for Clostridium acetobutylicum and Clostridium ljungdahlii Using HaloTag and SNAP-tag Proteins

One of the biggest limitations in the study and engineering of anaerobic Clostridium organisms is the lack of strong fluorescent reporters capable of strong and real-time fluorescence. Recently, we developed a strong fluorescent reporter system for Clostridium organisms based on the FAST protein. Here, we report the development of two new strong fluorescent reporter systems for Clostridium organisms based on the HaloTag and SNAP-tag proteins, which produce strong fluorescent signals when covalently bound to fluorogenic ligands. These new fluorescent reporters are orthogonal to the FAST ligands and to each other, allowing for simultaneous labeling and visualization. We used HaloTag and SNAP-tag to label the strictly anaerobic organisms Clostridium acetobutylicum and Clostridium ljungdahlii. We have also identified a new strong promoter for protein expression in C. acetobutylicum, based on the phosphotransacetylase gene (pta) from C. ljungdahlii. Furthermore, the HaloTag and the SNAP-tag, in combination with the previously described FAST system, were successfully used to measure cell populations in bacterial mixed cultures and showed the simultaneous orthogonal labeling of HaloTag and SNAP-tag together with the FAST protein reporter. Finally, we show the expression of recombinant fusion protein of FAST and the ZapA division protein (from C. acetobutylicum) in C. ljungdahlii. The availability of multiple strong fluorescent reporters is a major addition to the genetic toolkit of Here, Clostridium and other anaerobes that will lead to better understanding of these unique organisms.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

Analyzing Dynamic Probabilistic Risk Assessment Data through Topology-Based Clustering

We investigate the use of a topology-based clustering technique on the data generated by dynamic event tree methodologies. The clustering technique we utilizes focuses on a domain-partitioning algorithm based on topological structures known as the Morse-Smale complex, which partitions the data points into clusters based on their uniform gradient flow behavior. We perform both end state analysis and transient analysis to classify the set of nuclear scenarios. We demonstrate our methodology on a dataset generated for a sodium-cooled fast reactor during an aircraft crash scenario. The simulation tracks the temperature of the reactor as well as the time for a recovery team to fix the passive cooling system. Combined with clustering results obtained previously through mean shift methodology, we present the user with complementary views of the data that help illuminate key features that may be otherwise hidden using a single methodology. By clustering the data, the number of relevant test cases to be selected for further analysis can be drastically reduced by selecting a representative from each cluster. Identifying the similarities of simulations within a cluster can also aid in the drawing of important conclusions with respect to safety analysis.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Consistent Feature Extraction From Vector Fields: Combinatorial Representations and Analysis Under Local Reference Frames

This dissertation presents research on addressing some of the contemporary challenges in the analysis of vector fields—an important type of scientific data useful for representing a multitude of physical phenomena, such as wind flow and ocean currents. In particular, new theories and computational frameworks to enable consistent feature extraction from vector fields are presented. One of the most fundamental challenges in the analysis of vector fields is that their features are defined with respect to reference frames. Unfortunately, there is no single “correct” reference frame for analysis, and an unsuitable frame may cause features of interest to remain undetected, thus creating serious physical consequences. This work develops new reference frames that enable extraction of localized features that other techniques and frames fail to detect. As a result, these reference frames objectify the notion of “correctness” of features for certain goals by revealing the phenomena of importance from the underlying data. An important consequence of using these local frames is that the analysis of unsteady (time-varying) vector fields can be reduced to the analysis of sequences of steady (timeindependent) vector fields, which can be performed using simpler and scalable techniques that allow better data management by accessing the data on a per-time-step basis. Nevertheless, the state-of-the-art analysis of steady vector fields is not robust, as most techniques are numerical in nature. The residing numerical errors can violate consistency with the underlying theory by breaching important fundamental laws, which may lead to serious physical consequences. This dissertation considers consistency as the most fundamental characteristic of computational analysis that must always be preserved, and presents a new discrete theory that uses combinatorial representations and algorithms to provide consistency guarantees during vector field analysis along with the uncertainty visualization of unavoidable discretization errors. Together, the two main contributions of this dissertation address two important concerns regarding feature extraction from scientific data: correctness and precision. The work presented here also opens new avenues for further research by exploring more-general reference frames and more-sophisticated domain discretizations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Chemosaturation Percutaneous Hepatic Perfusion (CS-PHP) with Melphalan: Evaluation of 2D-Perfusion Angiography (2D-PA) for Leakage Detection of the Venous Double-Balloon Catheter

Purpose: To evaluate the feasibility of 2D-perfusion angiography (2D-PA) for detecting leakage of the double-balloon catheter used for chemosaturation percutaneous hepatic perfusion (CS-PHP). Materials and Methods: Overall, 112 CS-PHP (09/2015-09/2018) in 52 patients were retrospectively screened for leakage alongside the double-balloon catheter on standard venograms. Finally, 18 procedures with visually detected leakage were included. Fifteen consecutive procedures without leakage served as control. To evaluate 2D-PA for leakage detection, the acquired digital subtraction venograms were post-processed. For each balloon, two different target ROIs were evaluated to assess a possible impact of localization and shape of the ROIs. Time to peak (TTP), peak density (PD), area under the curve (AUC), and ratios of target ROI/reference ROIs (PD{sub tROI}/PD{sub REF}; AUC{sub tROI}/AUC{sub REF}; and TTP{sub tROI}/TTP{sub REF}) were calculated. Results: Leakages were located as follows: 15/18 cranial and 3/18 caudal. At the cranial balloon both ROIs showed a significant decrease in PD{sub tROI}/PD{sub REF} and AUC{sub tROI}/AUC{sub REF} (ROI1: p < 0.0001; p < 0.0001; ROI2: p < 0.0001; p < 0.0001) and a significant increase in TTP{sub tROI}/TTP{sub REF} (ROI1: p = 0.0009; ROI2: p = 0.0003) after double-balloon correction. Following balloon adjustment, the 2D-PA ratios (PD and AUC) of the tested ROIs differed significantly (p < 0.05). The inter-individual comparison of the 2D-PA parameters of the group with leakage before balloon correction and the non-leakage group showed significantly different 2D-PA values for the cranial balloon in both ROIs (p < 0.05). No significant differences were found for the caudal balloon. Conclusion: 2D-PA provides a feasible tool for detecting leakages alongside the cranial portion of the double-balloon catheter used in CS-PHP. The shape and position of the ROIs used to assess perfusion and flow have an impact on the measurements.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2021

The Circular Economy Lifecycle Assessment and Visualization Framework: A Case Study of Wind Blade Circularity in Texas

Moving the current linear economy toward circularity is expected to have environmental, economic, and social impacts. Various modeling methods, including economic input-output modeling, life cycle assessment, agent-based modeling, and system dynamics, have been used to examine circular supply chains and analyze their impacts. This work describes the newly developed Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework, which is designed to model how the impacts of supply chains might change as circularity increases. We first establish the framework with a discussion of modeling capabilities that are needed to capture circularity transitions; these capabilities are based on the fact that supply chains moving toward circularity are dynamic and therefore not at steady state, may encompass multiple industrial sectors or other interdependent supply chains and occupy a large spatial area. To demonstrate the capabilities of CELAVI, we present a case study on end-of-life wind turbine blades in the U.S. state of Texas. Our findings show that depending on exact process costs and transportation distances, mechanical recycling could lead to 69% or more of end-of-life turbine blade mass being kept in circulation rather than being landfilled, with only a 7.1% increase in global warming potential over the linear supply chain. We discuss next steps for framework development.

17 WIND ENERGY↗

DOE OSTI2020

Savannah River Site H-Canyon Advancing Technologies for Remote Inspections - 20345

In 2017, the DOE Environmental Management Office of Technology Development (DOE-EM TD) sponsored the H-Canyon Advanced Technology Demonstration (ATD) to demonstrate to DOE facilities the value of using new commercial-off-the-shelf (COTS) and near-ready technologies to solve difficult problems and enhance worker safety. The DOE Savannah River Site (SRS) H-Canyon Air Exhaust Tunnel (HCAEX) inspection task was identified as representative of the hazardous, human denied environments which could benefit from advanced technologies. The HCAEX underground concrete tunnel is visually inspected biannually using a camera mounted on a remotely operated vehicle (ROV) designed and built by SRNL. While tunnel images have provided valuable visual information, it is desirable to have a higher order of understanding of the environment to support a more thorough structural integrity (SI) analysis and for long term planning purposes. As part of the ATD, the Concrete Integrated Product Team (CIPT) was formed to identify and evaluate available sensors and methods mature enough to remotely obtain tunnel concrete characterization data of high value and with a high probability of success. The team included SMEs and H-Canyon stakeholders in the field of concrete, nondestructive examination (NDE), structural integrity, sensors and remote systems from SRNL, SRNS, LANL, DOE-SR and the Army Corps of Engineering. The CIPT completed an in-depth identification of customer concrete inspection needs and potential technology solutions. Sensors and methods were evaluated on performance, data usefulness, cost and the feasibility of a successful deployment given the unique tunnel access challenges and environment. Two technologies were identified as promising by the CIPT for near term demonstration and evaluation: Lidar (Light Detection and Ranging) 3-dimensional (3D) mapping and remote robotic deployment of NDE instrumentation. Laser spectroscopy to characterize tunnel surface chemical changes was also of interest, but presently cost prohibitive. This paper will include a discussion of the two efforts underway to evaluate and implement the CIPT recommendations. First, the status of the November 2019 deployment of Lidar at a single location into the tunnel is presented. This initial deployment provided the team a learning curve and lessons learned on the challenges of tunnel deployment to include remote operation and data collection, stabilization of the sensor in high air flow (∼30 mph), ability to achieve a tolerance accuracy of 0.25-inches, and the probability to identify change in tunnel dimensions over time. Secondly, a discussion on the development of the Robotic Arm Concrete Inspection Test Bed capable of deploying NDE instruments to examine custom concrete forms will be presented. Concrete forms simulating the rough concrete surfaces, strength, composition and potential structural defects that can be found at our DOE EM facilities have been designed and built for the test bed. Two state-of-the art concrete NDE instruments have been identified as having potential to work on rough concrete walls, they are being tested and characterized as to their ability to provide desired structural integrity data to include wall thickness and defect identification on the developed test beams. Lastly, lessons learned, and the path forward will be presented. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Final Report: Non-Visible, Automated Target Acquisition and Tracking

The Roadside Tracker (RST) represents a new approach to radiation portal monitors. It uses a combination of gamma-ray and visible-light imaging to localize gamma-ray radiation sources to individual vehicles in free-flowing, multi-lane traffic. Deployed as two trailers that are parked on either side of the roadway (Fig. 1); the RST scans passing traffic with two large gamma-ray imagers, one mounted in each trailer. The system compensates for vehicle motion through the imager’s fields of view by using automated target acquisition and tracking (TAT) software applied to a stream of video images. Once a vehicle has left the field of view, the radiation image of that vehicle is analyzed for the presence of a source, and if one is found, an alarm is sounded. The gamma-ray image is presented to the operator together with the video image of the traffic stream when the vehicle was approximately closest to the system (Fig. 2). The offending vehicle is identified with a bounding box to distinguish it from other vehicles that might be present at the same time. The system was developed under a previous grant from the Department of Homeland Security’s (DHS’s) Domestic Nuclear Detection Office (DNDO). This report documents work performed with follow-on funding from DNDO to further advance the development of the RST. Specifically, the primary thrust was to extend the performance envelope of the system by replacing the visible-light video cameras used by the TAT software with sensors that would allow operation at night and during inclement weather. In particular, it was desired to allow operation after dark without requiring external lighting. As part of this work, the system software was also upgraded to allow the use of 64-bit computers, the current generation operating system (OS), software development environment (Windows 7 vs. Windows XP, and current Visual Studio.Net), and improved software version controls (GIT vs. Source Safe.) With the upgraded performance allowed by new computers, and the additional memory available in a 64-bit OS, the system was able to handle greater traffic densities, and this also allowed addition of the ability to handle stop-and-go traffic.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2018

Calculating Trajectories Associated With Solute Transport in a Heterogeneous Medium

Here, we present a trajectory-based technique for calculating solute transport in a porous medium that has several advantages over existing methods. Unlike streamlines, the extended trajectories are influenced by each of the important parameters governing transport, including molecular diffusion and transverse dispersion. The approach is complete and does not require any additional techniques, such as operator splitting or particle tracking, in order to account for the full dispersion tensor. The semianalytic expressions make it clear how the flow field, the concentration distribution, and the dispersion tensor contribute to the velocity field of an injected solute. The equations are valid for an arbitrary porous medium, including those with rapid spatial variations in properties, overcoming limitations faced by previous approaches based upon asymptotic techniques. A test on a layered model with sharp boundaries indicates that the extended trajectories are compatible with the results of a numerical simulator and differ from streamlines. We also describe a new form of the dispersion tensor that incorporates a known asymmetry. The trajectories indicate that the modifications of the dispersion tensor lead to more focused transport within regions of high conductivity. The trajectories are used to define a semianalytic relationship between solute travel times and variations in solute velocities along a path that may be used for tomographic imaging. In an application to the injection of a radioactive tracer into a Berea sandstone core, monitored using micropositron emission tomographic (micro-PET) observations, the sensitivities are used to map the spatial variations of permeability within the core.

42 ENGINEERING↗

DOE OSTI2026

Model Data Archive for Manuscript Titled "Evaluation of a Coupled Surface–Subsurface Hydrologic Model Using Dense Water‑Level Sensors in a Mixed Urban–Rural Watershed"

This archive provides scripts, input files, and datasets used for the implementation and evaluation of a fully coupled surface–subsurface hydrologic model in the Neches River Basin, southeast Texas. The study uses the Advanced Terrestrial Simulator (ATS) to simulate coupled surface–subsurface hydrologic processes over a mixed urban–rural watershed and evaluates model performance using a dense network of 136 in situ water-level sensors, nine U.S. Geological Survey (USGS) stream gauges, and SSEBop-derived evapotranspiration estimates during the period October 2014–June 2024. The workflow is implemented primarily in Python 3 using the Watershed Workflow package. The Jupyter notebooks can be executed using open-source software such as Anaconda JupyterLab or Visual Studio Code. Other data files include TXT, CSV, XML, SHP, TIF, NetCDF, HDF5, and ExodusII files, which can be processed using the provided Python scripts. ATS input files are provided in XML format and can be edited using any commonly used text editor. This archive contains: *Scripts and input files used to generate the ATS model setup, including watershed discretization, mesh generation, parameter mapping, and model configuration. *Jupyter notebooks used for preprocessing observational data, evaluating streamflow, water levels, and evapotranspiration, computing performance metrics, and generating the figures presented in the manuscript. *ATS simulation outputs and processed observational datasets, including OneRain and DD6 water-level sensors, USGS streamflow observations, GIS data, and supporting spatial datasets used throughout the study.

Dense water-level sensor network↗

DOE OSTI2021

Machine learning to discover mineral trapping signatures due to CO 2 injection

Mineral trapping is pursued as a geological CO 2 sequestration (GCS) mechanism because it permanently stores CO 2 in solid phases or minerals. However, CO 2 mineral-trapping mechanisms are poorly understood due to (1) lack of sufficient field and laboratory data characterizing these complex processes, and (2) challenges to develop site-specific reactive-transport models coupling fluid flow and geochemical reactions occurring at various temporal (from milliseconds to years) and spatial (from pore (millimeters) to field (kilometers)) scales. Reactive transport with additional complexities such as heterogeneity can make the simulation outputs even more difficult to interpret because of complex nonlinearity and multi-scale interdependencies. Furthermore, the values of model outputs such as concentrations can vary by several orders of magnitude, making it harder to correlate and characterize the impact of the variables via traditional data interpretation techniques such as exploratory data analyses. Recently, machine learning (ML) has shown promise in feature discovery and in highlighting hidden mechanisms that cannot be obtained by existing data-analytics and statistical methods. In this study, we applied an unsupervised ML approach, non-negative matrix factorization with custom -means clustering (NMF) to the data generated by reactive-transport simulations of GCS. The reactive-transport data consisted of 19 attributes, including four physio-chemical variables (pH, porosity, aqueous CO 2 , and sequestered CO 2 ), six chemical species (K + , Na + , HCO, Ca 2+ , Mg 2+ , Fe 2+ ), and four carbonate minerals (calcite, dolomite, siderite, and ankerite), a feldspar mineral (albite), and four clay minerals (illite, clinochlore, kaolinite, and smectite) over a period of 200 years of simulation time. Furthermore, the simulation data used was for Morrow B sandstone at the Farnsworth hydrocarbon unit in Texas. Data are sampled at two locations within the model domain: (1) at the injection well and (2) 200 m west of the injection well. The injection was performed for a period of 10 years. Using NMF, we estimated the temporal interdependencies among the 19 attributes over a span of 200 years. We found that NMF was able to identify four reaction stages and their dominant attributes; these cannot be directly discerned through traditional visualization (e.g., line plots, Pareto analysis, Glyph-based visualization methods) or exploratory data analysis tools of the simulation data. The four stages were: reactions in the injection phase followed by short-, mid-, and long-term reactions. The NMF analysis also revealed that 10 among the 19 attributes are dominant. These dominant attributes for mineral trapping include calcite, dolomite at injection well, siderite at 200 m away from the injection well, clinochlore, kaolinite, Na + , K + , Ca 2+ , Mg 2+ , pH, and aqeuous CO 2 . Finally, at late times (65–200 years), our results showed that calcite plays a major role in mineral trapping with insignificant contribution from siderite, ankerite, and clay minerals. These findings make the proposed unsupervised ML-model attractive for reactive-transport sensing towards real-time GCS monitoring.

54 ENVIRONMENTAL SCIENCES↗