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At least 1,333 records · Page 74

Packaging printed circuit boards: A production application of interactive graphics

The structure and use of an Interactive Graphics Packaging Program (IGPP), conceived to apply computer graphics to the design of packaging electronic circuits onto printed circuit boards (PCB), were described. The intent was to combine the data storage and manipulative power of the computer with the imaginative, intuitive power of a human designer. The hardware includes a CDC 6400 computer and two CDC 777 terminals with CRT screens, light pens, and keyboards. The program is written in FORTRAN 4 extended with the exception of a few functions coded in COMPASS (assembly language). The IGPP performs four major functions for the designer: (1) data input and display, (2) component placement (automatic or manual), (3) conductor path routing (automatic or manual), and (4) data output. The most complex PCB packaged to date measured 16.5 cm by 19 cm and contained 380 components, two layers of ground planes and four layers of conductors mixed with ground planes.

Perrill, W. A.↗

A hybrid M-algorithm/sequential decoder for convolutional and trellis codes

The Viterbi Algorithm (VA) is optimum in the sense of being maximum likelihood for decoding codes with a trellis structure. However, since the VA is in fact an exhaustive search of the code trellis, the complexity of the VA grows exponentially with the constraint length upsilon. This limits its application to codes with small values of upsilon and relatively modest coding gains. The M-Algorithm (MA) is a limited search scheme which carries forward M paths in the trellis, all of the same length. All successors of the M paths are extended at the next trellis depth, and all but the best M of these are dropped. Since a limited search convolutional decoder will flounder indefinitely if one of the paths in storage is not the correct one, the data are usually transmitted in blocks. It has been shown that the performance of the MA approaches the VA at high signal to noise ratios (SNR's) with an M which is far less than the 2 sup upsilon states in the full trellis. Thus the MA can be used with larger values of upsilon, making larger coding gains possible at high SNR's. However, it still requires a relatively large fixed computational effort to achieve good performance.

Wang, Fu-Quan↗

A hybrid finite element-boundary integral for the analysis of cavity-backed antennas of arbitrary shape

This is the final report on this project which was concerned with the analysis of cavity-backed antennas and more specifically spiral antennas. The project was a continuation of a previous analysis, which employed rectangular brick elements, and was, thus, restricted to planar rectangular patch antennas. A total of five reports were submitted under this project and we expect that at least four journal papers will result from the research described in these reports. The abstracts of the four previous reports are included. The first of the reports (028918-1-T) is over 75 pages and describes the general formulation using tetrahedral elements and the computer program. Report 028918-2-T was written after the completion of the computer program and reviews the capability of the analysis and associated software for planar circular rectangular patches and for a rectangular planar spiral. Measurements were also done at the University of Michigan and at Mission Research Corp. for the purpose of validating the software. We are pleased to acknowledge a partial support from Mission Research Corp. in carrying out the work described in this report. The third report (028918-3-T) describes the formulation and partial validation (using 2D data) for patch antennas on a circular platform. The 3D validation and development of the formulation for patch antennas on circular platforms is still in progress. The fourth report (028918-4-T) is basically an invited journal paper which will appear in the 'J. Electromagnetic Waves and Applications' in early 1994. It describes the application of the finite element method in electromagnetics and is primarily based on our work here at U-M. This final report describes the culmination of our efforts in characterizing complex cavity-backed antennas on planar platforms. The report describes for the first time the analysis of non-planar spirals and non-rectangular slot antennas as well as traditional planar patch antennas. The comparisons between measurements and calculations are truly impressive. Another unique aspect of this work is the incorporation of the FFT as part of the BiCG solver by overlaying a structured triangular mesh over the unstructured mesh. The implementation of this BiCG-FFT solution algorithm is important in minimizing the CPU and storage requirements. This final report will be submitted for publication in a refereed journal.

Gong, Jian↗

Wide-bandwidth high-resolution search for extraterrestrial intelligence

A third antenna was added to the system. It is a terrestrial low-gain feed, to act as a veto for local interference. The 3-chip design for a 4 megapoint complex FFT was reduced to finished working hardware. The 4-Megachannel circuit board contains 36 MByte of DRAM, 5 CPLDs, the three large FFT ASICs, and 74 ICs in all. The Austek FDP-based Spectrometer/Power Accumulator (SPA) has now been implemented as a 4-layer printed circuit. A PC interface board has been designed and together with its associated user interface and control software allows an IBM compatible computer to control the SPA board, and facilitates the transfer of spectra to the PC for display, processing, and storage. The Feature Recognizer Array cards receive the stream of modulus words from the 4M FFT cards, and forward a greatly thinned set of reports to the PC's in whose backplane they reside. In particular, a powerful ROM-based state-machine architecture has been adopted, and DRAM has been added to permit integration modes when tracking or reobserving source candidates. The general purpose (GP) array consists of twenty '486 PC class computers, each of which receives and processes the data from a feature extractor/correlator board set. The array performs a first analysis on the provided 'features' and then passes this information on to the workstation. The core workstation software is now written. That is, the communication channels between the user interface, the backend monitor program and the PC's have working software.

Horowitz, Paul↗

Colorimetric Solid Phase Extraction (CSPE): Using Color to Monitor Spacecraft Water Quality

In August 2009, an experimental water quality monitoring kit based on Colorimetric Solid Phase Extraction (CSPE) technology was delivered to the International Space Station (ISS). The kit, called the Colorimetric Water Quality Monitoring Kit (CWQMK), was launched as a Station Development Test Objective (SDTO) experiment to evaluate the suitability of CSPE technology for routine use monitoring water quality on the ISS. CSPE is a sorption-spectrophotometric technique that combines colorimetric reagents, solid-phase extraction, and diffuse reflectance spectroscopy to quantify trace analytes in water samples. In CSPE, a known volume of sample is metered through a membrane disk that has been impregnated with an analyte-specific colorimetric reagent and any additives required to optimize the formation of the analyte-reagent complex. As the sample flows through the membrane disk, the target analyte is selectively extracted, concentrated, and complexed. Formation of the analyte-reagent complex causes a detectable change in the color of the membrane disk that is proportional to the amount of analyte present in the sample. The analyte is then quantified by measuring the color of the membrane disk surface using a hand-held diffuse reflectance spectrophotometer (DRS). The CWQMK provides the capability to measure the ionic silver (Ag +) and molecular iodine (I2) in water samples on-orbit. These analytes were selected for the evaluation of CSPE technology because they are the biocides used in the potable water storage and distribution systems on the ISS. Biocides are added to the potable water systems on spacecraft to inhibit microbial growth. On the United States (US) segment of the ISS molecular iodine serves as the biocide, while the Russian space agency utilizes silver as a biocide in their systems. In both cases, the biocides must be maintained at a level sufficient to control bacterial growth, but low enough to avoid any negative effects on crew health. For example, the presence of high levels of iodine in water can cause taste and odor issues that result in decreased water consumption by the crew. There are also concerns about potential impacts on thyroid function following exposure to high levels of iodine. With silver, there is a risk of developing argyria, an irreversible blue-gray discoloration of the skin, associated with long term consumption of water containing high concentrations of silver. The need to ensure that safe, effective levels of biocide are maintained in the potable water systems on the ISS provides a perfect platform for evaluating the suitability of CSPE technology for in-flight water quality monitoring. This paper provides an overview of CSPE technology and details on the silver and iodine methods used in the CWQMK. It also reports results obtained during in-flight analyses performed with the CWQMK and briefly discusses other potential applications for CSPE technology in both the spacecraft and terrestrial environments.

Gazda, Daniel B.↗

Disruptive Technologies and Their Putative Impacts Upon Society and Aerospace- Entering The Virtual Age

Developments in technology over the recent decades have been extraordinary. They include the IT, bio, nano, and now quantum and energetics technology arenas and their many combinatorial interactions and impacts. In the main, these are at the frontiers of the small and in a combinational, synergistic feeding frenzy with each other. They fall under the broad category of Disruptive Technologies and have greatly altered society. The outlook for the runout of these and other technology developments augers mid-term to later alterations in components of the human existence theorem, including the requirement to work for our living and our physiological makeup and longevity (Ref 1). The IT revolution began in the 1950s with the development of solid-state electronics. The biologics revolution began later in the 1960s and 1970s with DNA and genomics, and the nano revolution in the 1990s with self-forming nano systems and carbon nanotubes. Quantum technology is now developing rapidly, aided by enabling nano systems, and the energetics revolution is providing ever more efficient and less expensive renewable energy sources. The IT revolution has produced improvements of an astounding eleven orders of magnitude in computing speed since the late 1950s. As we shift from silicon to biological, optical, nano, molecular, and atomic computing, improvements of some 4 orders of magnitude are evidently possible from either optical or DNA computing [Refs 2and 3], then there are combinatorials. Then there is quantum computing, under development worldwide for an increasing number of applications and proffering phenomenal capabilities. The current fastest computers are considerably beyond human brain speed. Machine intelligence is developing well after decades of inadequate machine capability, now no longer the case, and a detour into expert systems. Researchers in machine intelligence are now pursuing deep learning approaches using neural nets, which are proving to be extremely useful. Some believe the frontier of potential human-level machine intelligence may be found in biomimetics and brain-emulation approaches. There is even a possibility of “emergence”—i.e., when the machine intelligence is complex enough that it “wakes up,” as when human intelligence emerged via evolution during the million-plus years of the hunter-gatherer epoch [ Ref 4]. In fact, some posit that human intelligence can be improved upon and is only a cul-de-sac of what is conceivable. The IT revolution has produced massive changes in human society and economics—from the Internet, enabling the rapid expansion of knowledgeability (and even what is knowable), to an increasingly pervasive trend of “tele-everything.” The extraordinary compilation, storage, and availability of truly massive amounts of information could, when combined with AI and under the mantra of “big data,” greatly improve many of our technical and commercial processes and their content including elucidating new heuristic governing laws.

Dennis M. Bushnell↗

Functionalized Magnetic Nanoparticles for Technetium Sequestration from Groundwater

Technetium 99 (Tc) is among the most common environmental contaminants at DOE sites and one of the most common risk drivers in low- and high-level waste disposal sites. The majority of Tc is generated from anthropogenic sources, such as nuclear power plants, global weapons, nuclear storage facilities and medical applications. Through these sources, Tc contamination has been unintentionally introduced in to the environment. The most common chemical form of Tc is Tc(VII)O{sub 4}{sup -}. Due to its high solubility and mobility, Tc can enter the food chain and cause adverse health effects to humans. Currently, ion exchange resins and reduction processes are the most common approaches for Tc immobilization. Although these techniques have shown to be effective, they also possess major drawbacks, such as high cost, low adsorption capacity, and complex creation and maintenance. Therefore, development of more efficient and simple technologies for the remediation of Tc-contaminated systems are needed. Functionalized magnetic nanoparticles have been used to remove organic and inorganic contaminants from water resources. These nanoparticles have attracted extensive attention as an adsorbent material due to their large surface area, high efficiency, low-cost, easy functionalization and separation with a magnet. This study seek to develop functionalized magnetic iron oxide nanoparticles for the efficient removal of Tc and other heavy metal contaminants from water resources under ambient conditions. Objectives: Synthesize magnetic iron oxide nanoparticles and functionalize their surface with Cetyltrimethylammonium Bromide (CTAB) and tetraethyl-orthosilicate (TEOS). Characterize the synthesized nanoparticles using scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDS), Dynamic Light Scattering (DLS) and Zeta PALS. Perform adsorption studies to evaluate their adsorption behavior and capacity for (a) Technetium using Rhenium (ReO{sub 4}{sup -}) as a surrogate and (b) heavy metals, e.g. Cu{sup 2+}. Conclusions: Magnetic iron oxide nanoparticles were successfully functionalized with CTAB and TEOS. The functionalization of the iron oxide nanoparticles affects their surface charge and their hydrodynamic diameter. The addition of CTAB or TEOS decreased the hydrodynamic diameter of the nanoparticles due to repulsive and steric forces. The SEM micrographs show spherical nanoparticles of different sizes. The EDX analysis shows the presence of iron and oxygen from the iron oxide crystalline structure, and the different constituents of the CTAB and TEOS molecules. Proof-of-concept shows the successful adsorption of rhenium (ReO{sub 4}{sup -}) and copper Cu{sup 2+}) onto CTAB-Fe{sub 2}O{sub 3} and TEOS-Fe{sub 2}O{sub 3} respectively.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Rapid determination of supercritical CO 2 and brine relative permeability using an unsteady-state flow method

In this study, relative permeability of supercritical CO 2 (scCO 2 ) and brine was determined in reactive and non-reactive rock cores using a combination of unsteady-state methodology and computed tomography. Experiments were conducted using a medical grade CT scanner to determine saturation using a custom Python script. The saturation and differential pressure across the core were then used to derive four empirical constants to calculate relative permeability. This methodology increases temporal efficiency while reducing experimental complexity. Additionally, we show that the method can be used to determine scCO 2 relative permeability in a wide range of lithologies and flow rates, and with the ability to account for matrix dissolution during scCO 2 flooding.

54 ENVIRONMENTAL SCIENCES↗

Enhancing durability of polymer electrolyte membrane using cation size selective agents

Radical species generated during proton exchange membrane fuel cell operation considerably limit the achievable durability, particularly for heavy-duty vehicle applications. A promising solution to the problem is the incorporation of radical scavenger additives such as cerium which mitigates chemical attacks on the membrane. However, these additives migrate during fuel cell operation causing a loss in durability and performance due to detrimental interaction with various components of the fuel cell. Here, we study cation size selective agents as a means to immobilize cerium within perfluorosulfonic acid (PFSA) membranes. We synthesized an organometallic complex of cerium with 15-Crown-5 and investigated the effectiveness of this complex to immobilize cerium. Over 300% increase in cerium retention and an 80% increase in chemical durability were observed owing to the stabilization effect of crown ethers on cerium. Migration under a potential gradient can be eliminated while the complex also contributes to the enhancement in cerium radical scavenging activity. In conclusion, current challenges with the proposed solution are highlighted and future work is discussed.

25 ENERGY STORAGE↗

Site demonstration and performance evaluation of MPC for a large chiller plant with TES for renewable energy integration and grid decarbonization

Thermal energy storage (TES) for a cooling plant is a crucial resource for load flexibility. Traditionally, simple, heuristic control approaches, such as the storage priority control which charges TES during the nighttime and discharges during the daytime, have been widely used in practice, and shown reasonable performance in the past benefiting both the grid and the end-users such as buildings and district energy systems. However, the increasing penetration of renewables changes the situation, exposing the grid to a growing duck curve, which encourages the consumption of more energy in the daytime, and volatile renewable generation which requires dynamic planning. The growing pressure of diminishing greenhouse gas emissions also increases the complexity of cooling TES plant operations as different control strategies may apply to optimize operations for energy cost or carbon emissions. This paper presents a model predictive control (MPC), site demonstration and evaluation results of optimal operation of a chiller plant, TES and behind-meter photovoltaics for a campus-level district cooling system. The MPC was formulated as a mixed-integer linear program for better numerical and control properties. Compared with baseline rule-based controls, the MPC results show reductions of the excess PV power by around 25%, of the greenhouse gas emission by 10%, and of peak electricity demand by 10%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Variable rate neural compression for sparse detector data

Particle colliders produce data at extraordinary rates, posing major challenges for transmission and storage. High-throughput compression algorithms are therefore essential. In the sPHENIX experiment taking data at the Relativistic Heavy Ion Collider, a time projection chamber records three-dimensional (3D) particle trajectories that are highly sparse, making conventional learning-free lossy compression ineffective. Convolutional neural networks have surpassed traditional methods in compression ratio and accuracy. However, they fail to exploit sparsity for efficiency. To address these gaps, we present BCAE-VS, a bicephalous convolutional autoencoder with variable compression ratio for sparse data, which adapts compression to input complexity through key-point identification and sparse convolution. BCAE-VS achieves higher accuracy and compression ratios than prior neural approaches while being orders of magnitude smaller. Moreover, its throughput increases with sparsity—a property not observed in other methods. Although it was developed for collider experiments, BCAE-VS readily extends to other sparse data domains, such as light detection and ranging (LiDAR) sensing and 3D microscopy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Using Big Data Technologies with Earth Science Data in HDF5: HDF5 Scalable Solutions

HDF5 (Hierarchical Data Format 5) is open-source, high-performance software that consists of an abstract data model, library, and fileformat used for storing and managing extremely large and/or complex data collections. NASA Earth Observing System (EOS) Data and Information Systems use HDF5 as an archival format to store remote sensing data from EOS satellites. HDF5 is also used to store other types of Geoscience and Strophysical data, e.g., seismic data and data from Low-Frequency Array (LOFAR) radio telescopes. Data stored in HDF5 has reached tens of petabytes and is growing at an accelerated rate.With the growing amout of HDF5 Earth Science data to analyze and process, scientists need to adopt big data technologies including new storage paradigms such as cloud and object storage. To run models and perform data analysis they also need to utilizied efficient and diverse ways to access data, from high-performance computing's (HPC) Message Passing Interface (MPI) I/O and deep memory hierarchies (DMH) to non-HPC frameworks such as Apache Hadoop, Spark, and Drill. The HDF Group continually works to enable usage of big data technologies in HDF software.

Knox, Larry↗

Development of a Testbed for Pipeline Flushing - 20425

Pipelines which carry high-level waste within the DOE complex should be properly flushed in the cases where stationary or moving beds of solid sediment occur, or lines are prone to hydrogen gas buildup. Present guidelines establish a minimum for the amount of water (flush volume) and flush velocity values used for post-transfer flushing operations to achieve satisfactory cleaning of pipelines. However, further studies are needed to find optimal operating velocity modes/values in order to minimizing the flush volume and consequent downstream waste. These efforts are significantly helpful to DOE waste remediation sites by preserving tank storage, preventing additional waste processing, and minimizing dilution and changes in waste chemistry. An experimental test loop was recently developed for study of non-Newtonian slurry flushing at the Florida International University (FIU). This loop was designed to create sediment beds of various materials and bed heights and investigate parameters that effect the efficiency of flushing operations. The objective is to find flush velocity values/modes which lead to satisfactory cleaning of transport lines with a minimum amount of water usage. A 165 ft experimental test loop made of 3-inch carbon steel pipes was constructed and used in initial testing campaigns. This pipe loop was equipped with real-time monitoring instruments to record variation of pressure, density, mass flow rate, and temperature during testing. Post-flush in-situ no-flow evaluations were performed using ultrasonic, endoscopy, and visual inspection. Additional post-flush evaluations were conducted using filtration and density monitoring of residuals within a designated circulations loop. These provisions enable comparison of pipeline cleanness before the start and after termination of flushing operations for efficiency evaluation. This paper presents efforts associated with flushing of kaolin-water mixtures at different concentrations and with various flush volume and flush velocity values/modes. In initial testing, efforts focused on creating repeatable sediment beds inside the pipeline in both fully-flooded (no pre-flush drainage) and gravity-drained (pre-flush drained) systems. Bed characterization (i.e., measurement of sediment height and solids concentration) was conducted to ensure about consistency of initial conditions between tests. Preliminary results for flushing study of 10% vol. kaolin-water mixtures starting from a fully-flooded initial condition showed that flushing with 1-line volume (65 gallons) could remove up to 72 percent of solids from the pipeline. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects

This is the conference paper accompanying an oral presentation “Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects” at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24 , 2024. Carbon capture and storage (CCS) technology is critical for mitigating climate change but requires effective subsurface reservoir management to ensure safe containment of injected CO2. Accurate predictions of reservoir pressure and saturation are essential for assessing long-term CCS performance. Traditional numerical simulations, while effective, are computationally intensive, time-consuming, and constrained by data discretization. Previous work has shown the effectiveness of MeshGraphNets (MGN), a graph-based machine learning framework, as an innovative alternative for predicting reservoir behavior. MGN leverages graph neural networks (GNNs) and mesh representations to model complex geological formations, offering superior adaptability across different discretizations and reservoir configurations. Classic MGN implementations utilize an autoregressive technique to predict future behavior based on current predictions, but this technique is hampered by error accumulation over time. To enhance the model accuracy in time-series predictions, this study implemented a multi-step rollout strategy that integrates autoregressive predictions during training to stabilize prediction of saturation over time. Using the Illinois Basin – Decatur Project (IBDP) dataset, comprising 100 simulations of CO2 injection, pressure, and saturation changes, the framework demonstrated its ability to learn spatial dependencies and temporal dynamics. With inputs including permeabilities, porosities, and injection rates, MGN accurately predicted CO2 plume evolution over time, even with limited training data. Moreover, the addition of a multi-step rollout procedure during training improved the ability of MGN to predict stably over time by ~15%. This research positions MGN, enhanced with multi-step rollout capabilities, as a robust and efficient tool for CCS applications. It advances the field by enabling precise, computationally efficient predictions of reservoir behavior, providing a foundation for the broader adoption of machine learning frameworks in CCS and other geoscience domains.

Holcomb, Paul↗

A Method to Access Absolute fIPAR fo Vegetation in Spatially Complex Ecosystems

Arid and semi-arid lands compose a large fraction of the earth's terrestrial vegetation, and thereby contribute significantly to global atmospheric-biospheric interactions. The thorny shrubs and small trees in these semi-arid shrub lands have counterparts throughout much of the world's tropical and subtropical zones and have captured substantial areas of the world's former grasslands. The objective of our field and remotely sensed measurements in the semi-arid shrublands of Texas is to monitor interannual variability and directional change in landscape structure, ecosystem processes and atmosphere-biosphere exchanges. To understand the role ecosystems play in controlling the composition of the atmosphere, it is necessary to quantify processes such as photosynthesis and primary production, decomposition and soil carbon storage, and trace gas exchanges. Photosynthesis is the link whereby surface-atmosphere exchanges such as the radiation balance and exchange of heat, moisture, and gas can be inferred. It also describes the efficiency of carbon dioxide exchange and is directly related to the primary production of vegetation. Our efforts in this paper focus on the indirect, quantification of photosynthesis, and thereby carbon flux and net primary production, via remote sensing and direct measurements of intercepted photosynthetically active radiation (IPAR).

Wessman, Carol A.↗

A Co-design Framework for Online Data Analysis and Reduction

Science applications preparing for the exascale era are increasingly exploring in situ computations comprising of simulation-analysis-reduction pipelines coupled in-memory. Efficient composition and execution of such complex pipelines for a target platform is a codesign process that evaluates the impact and tradeoffs of various application- and system-specific parameters. In this article, we describe a toolset for automating performance studies of composed HPC applications that perform online data reduction and analysis. We describe Cheetah, a new framework for composing parametric studies on coupled applications, and Savanna, a runtime engine for orchestrating and executing campaigns of codesign experiments. Furthermore, this toolset facilitates understanding the impact of various factors such as process placement, synchronicity of algorithms, and storage versus compute requirements for online analysis of large data. Ultimately, we aim to create a catalog of performance results that can help scientists understand tradeoffs when designing next-generation simulations that make use of online processing techniques. We illustrate the design of Cheetah and Savanna, and present application examples that use this framework to conduct codesign studies on small clusters as well as leadership class supercomputers.

97 MATHEMATICS AND COMPUTING↗

Understanding Cation Selectivity in Carbon Nanopores with Hybrid First-Principles/Continuum Simulations: Implications for Water Desalination and Separation Technologies

Understanding ion adsorption in porous carbons is crucial for a range of technologies, including water desalination and energy storage. In this work, we combined density functional theory with a continuum solvation model to investigate thermodynamics and kinetics of the adsorption process of alkali metal ions from aqueous solutions into carbon nanopores with different sizes and geometries. We found that cations with a larger ionic radius are more favorable to enter the nanopores because of a lower energy penalty of dehydration. In addition, the pore size and geometry were found to have a significant impact on the ion–pore interaction under confinement and cation selectivity. Our study highlights a complex interplay among nanopore geometry, ion size, and hydration on the cation adsorption selectivity, suggesting that tuning the porosity could represent a general strategy for improving ion separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Workflow for Characterizing Legacy Wells as Potential Leakage Pathways for Integration to NRAP-Open-IAM

Carbon capture and storage is a crucial component of climate change mitigation strategies, involving the capture of carbon dioxide (CO2) from point sources and its injection into permeable subsurface formation. Many suitable CO2 storage sites coincide with legacy wells since the conditions that kept hydrocarbons in-situ for thousands of years are also ideal for storage of carbon dioxide. To protect underground sources of drinking water (USDW) during greenhouse gas injection, the Environmental Protection Agency (EPA) mandates area of review evaluations. These evaluations ensure that drinking water sources would not be contaminated by injected fluids. They include identification of legacy wellbores, integrity assessments, and implementing any necessary corrective action. Previous assessment approaches of legacy wells include high-level scoring of regional data and well construction and abandonment evaluation. This work describes a novel methodology that evaluates well construction and abandonment, ranks them based on complexity, and performs a risk assessment with NRAP-Open-IAM. A workflow of the methodology is presented, highlighting its capabilities and limitations.

Wise, Jarrett↗