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At least 55 records · Page 3

Co-optimizing water-alternating-carbon dioxide injection projects using a machine learning assisted computational framework

In this report, a robust machine-learning-based computational framework that couples multi-layer neural network (MLNN) proxies and a multi-objective particle swarm optimizer (MOPSO) to design water-alternating-carbon dioxide injection (CO 2 -WAG) projects is presented. The proposed optimization protocol considers various objectives, including oil recovery and CO 2 storage volume. Expert MLNN systems are trained and employed as surrogate models of the high-fidelity compositional simulator in the optimization workflow. When multiple objective functions are considered, two approaches are employed to treat the objectives: the weighted sum method and the Pareto-front-based scheme. A field-scale implementation focusing on tertiary recovery in the Morrow B formation at Farnsworth Unit (FWU) is presented. The developed Pareto-optimal solutions indicate the maximal available oil production can be 1.64 × 10 7 barrels and maximal carbon storage can achieve 2.35 × 10 7 tons. Trade-offs factor is defined to divide the constructed Pareto front into 4 sections with the trade-off factors’ value ranges from 0.35 to 49.9. This work also compares the optimum solution found by the aggregative objective function and the solution repository covered by the Pareto front that considers the physical and operational constraints and reduces uncertainties involved by the multi-objective optimization process. Our comparison indicates multiple solutions exist to satisfy the objective criteria of the WAG design, and these results cannot be found using the traditional weighted sum method. The Pareto front solution can provide more options for project designers, but decisions regarding necessary trade-offs must be made using the solution repository to balance the project economics and CO 2 storage amount.

10 SYNTHETIC FUELS↗

Development and application of a machine learning based multi-objective optimization workflow for CO 2 -EOR projects

Carbon dioxide-Enhanced Oil Recovery (CO 2 -EOR) is known as one of techniques for hydrocarbon production improvement as wells as an important candidate to reduce greenhouse gas emissions. Thus, an ideal development strategy for a CO 2 -EOR project would consider multiple objectives including to maximize oil recovery, CO 2 storage volume and project economic outcomes. This work proposes a robust computational framework that couples artificial neural network (ANN) and multi-objective optimizers to optimize the aforementioned objectives in CO 2 -EOR processes simultaneously. Expert ANN systems are trained and employed as surrogate models of the high-fidelity compositional simulator in the optimization workflow. The robustness of the development optimization protocol is confirmed via a synthetic injection-pattern-base case study. Afterward a field implementation to Morrow-B formation to optimize the tertiary recovery stage of the field development is discussed. This work compares the optimum solution found using an aggregate objective function and the solution repository (Pareto front) generated by the multi-objective optimization process. The comparison indicates the existence of potential multi-solutions satisfying certain criteria in a CO 2 -EOR project designing, which cannot be found using traditional weighted sum method. The optimization results provide significant insight into the decision-making process of CO 2 -EOR project when multiple objective functions are considered.

02 PETROLEUM↗

Analyzing the effect of misalignment on single-filament carbon fiber tensile testing via stereoscopic computer vision imaging

An understanding of the constitutive properties of carbon fibers (CF) is critical to the accuracy of high-resolution composite simulations and to the development of CF derived from low-cost alternative precursor materials. Single-fiber tensile testing is a capable tool to measure CF properties and is well suited to research efforts where only a small number of fibers may be available. However, single-fiber tensile tests are challenging to conduct due to the difficulty in handling small diameter fibers (5-15 μm), the brittleness of single fibers, and the required nanoscale/microscale resolution of testing equipment. The accuracy of the measured properties depends on several factors, but a critical factor is fiber misalignment, especially at short gauge lengths. Current standards do not address the effect of tensile specimen misalignment on measured properties. Furthermore, this work presents a robust method of fiber alignment using stereoscopic computer vision that enables users to align fibers vertically for tensile testing to improve the accuracy of resulting mechanical properties. Additionally, an analytical relationship between fiber misalignment angle and measured properties is developed and validated against the experimental results. As a result, new best practices for single-fiber tensile testing of CF are recommended.

47 OTHER INSTRUMENTATION↗

Microwave-specific heating of crystalline species in nuclear waste glass

Here, the microwave heating of a crystal-free and a partially trevorite-crystallized nuclear waste glass simulant was evaluated. Our results show that a 500-mg monolith of partially crystallized waste glass can be heated from room temperature to above 1600°C within 2 min using a single-mode, highly focused, 2.45 GHz microwave, operating at 300 W. Using X-ray diffraction measurements, we show that trevorite is no longer detectable after irradiation and thermal quenching. When a crystal-free analog of the same waste glass simulant composition was exposed to the same microwave radiation, it could not be heated above 450°C regardless of the heating time. The reduction in crystalline content achieved by selectively heating spinels in the presence of glass suggests that microwave-specific heating should be further explored as a technique for remediating crystal accumulation in a glass melt.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Fracture mechanisms of sodium silicate glasses

Reactive classical molecular dynamics simulations of sodium silicate glasses, xNa 2 O–(100 – x)SiO 2 (x = 10–30), under quasi-static loading, were performed for the analysis of molecular scale fracture mechanisms. Mechanical properties of the sodium silicate glasses were consistent with experimentally reported values, and the amount of crack propagation varied with reported fracture toughness values. The most crack propagation occurred in NS20 systems (20-mol% Na 2 O) compared with the other simulated compositions. Dissipation via two mechanisms, the first through sodium migration as a lower activation energy process and the second through structural rearrangement as a higher activation energy process, was calculated and accounted for the energy that was not stored elastically or associated with the formation of new fracture surfaces. Here, a correlation between crack propagation and energy dissipation was identified, with systems with higher crack propagation exhibiting less energy dissipation. Sodium silicate glass compositions with lower energy dissipation also exhibited the most sodium movement and structural rearrangement within 10 Å of the crack tip during loading. Therefore, high sodium mobility near the crack tip may enable energy dissipation without requiring formation of structural defects. Therefore, the varying mobilities of the network modifiers near crack tips influence the brittleness and the crack growth rate of modified amorphous oxide systems.

36 MATERIALS SCIENCE↗

Reducing Uncertainties in Model Predictions via History Matching of CO 2 Migration and Reactive Transport Modeling of CO 2 Fate at the Sleipner Project

An important question for the Carbon Capture, Storage, and Utility program is “can we adequately predict the CO 2 plume migration?” For tracking CO 2 plume development, the Sleipner project in the Norwegian North Sea provides more time-lapse seismic monitoring data than any other sites, but significant uncertainties still exist for some of the reservoir parameters. In Part I, we assessed model uncertainties by applying two multi-phase compositional simulators to the Sleipner Benchmark model for the uppermost layer (Layer 9) of the Utsira Sand and calibrated our model against the time-lapsed seismic monitoring data for the site from 1999 to 2010. Approximate match with the observed plume was achieved by introducing lateral permeability anisotropy, adding CH 4 into the CO 2 stream, and adjusting the reservoir temperatures. Model-predicted gas saturation, CO 2 accumulation thickness, and CO 2 solubility in brine—none were used as calibration metrics—were all comparable with the interpretations of the seismic data in the literature.

20 FOSSIL-FUELED POWER PLANTS↗

Evaluating the Microwave Heating of Spinel Crystals in High-Level Waste Glass

In this report, the microwave heating of a crystal-free and a partially (24 wt%) trevorite-crystallized waste glass simulant were evaluated. The results show that a 500 mg piece of partially crystallized waste glass can be heated from room-temperature to above 1600 °C (as measured by infrared radiometry) within 2 minutes using a single mode, highly focused, 2.45 GHz microwave, operating at 300 W. X-ray diffraction measurements show that the partially crystallized glass experiences an 87 % reduction in trevorite following irradiation and thermal quenching. When a crystal-free analogue of the same waste glass simulant composition is exposed to the same microwave radiation it could not be heated above 450 °C regardless of the heating time.

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Defense Waste Processing Facility Nitric- Glycolic Flowsheet Chemical Process Cell Chemistry: Part 2

The conversions of nitrite to nitrate, the destruction of glycolate, and the conversion of glycolate to formate and oxalate were modeled for the Nitric-Glycolic flowsheet using data from Chemical Process Cell (CPC) simulant runs conducted by Savannah River National Laboratory (SRNL) from 2011 to 2016. The goal of this work was to develop empirical correlation models to predict these values from measureable variables from the chemical process so that these quantities could be predicted a-priori from the sludge or simulant composition and measurable processing variables. The need for these predictions arises from the need to predict the REDuction/OXidation (REDOX) state of the glass from the Defense Waste Processing Facility (DWPF) melter. This report summarizes the work on these correlations based on the aforementioned data. Previous work on these correlations was documented in a technical report covering data from 2011-2015. This current report supersedes this previous report. Further refinement of the models as additional data are collected is recommended.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Petronius Offshore Oil Field Case Study

This document is one of three offshore post-primary CO 2 enhanced oil recovery project case studies that compares the modeling results from an industry standard compositional simulator (“GEM”) and a variant of the FE/NETL CO 2 Prophet Model (CO 2 Prophet Model), which determined the CO 2 Prophet Model was able to reasonably represent the performance of the CO 2 flood modeled using the more sophisticated GEM. This case study uses the Petronius oil field J-2 Sand using a quarter of a five-spot pattern design (one CO 2 injector well and five production wells), for a 40-year injection scenario. A version of the CO 2 Prophet Model is available on NETL’s website under the Collection Name: FE/NETL CO 2 Prophet Model.

02 PETROLEUM↗

Cognac Offshore Oil Field Case Study

This document is one of three offshore post-primary CO 2 enhanced oil recovery project case studies that compares the modeling results from an industry standard compositional simulator (“GEM”) and a variant of the FE/NETL CO 2 Prophet Model (CO 2 Prophet Model), which determined the CO 2 Prophet Model was able to reasonably represent the performance of the CO 2 flood modeled using the more sophisticated GEM. This case study uses the Cognac oil field J Sand, in the field’s Northeast fault block, using a line drive pattern design (one CO 2 injector and two production wells), for 10-year and 20-year injection scenarios. A version of the CO 2 Prophet Model is available on NETL’s website under the Collection Name: FE/NETL CO 2 Prophet Model.

02 PETROLEUM↗

Horn Mountain Offshore Oil Field Case Study

This document is one of three offshore post-primary CO 2 enhanced oil recovery project case studies that compares the modeling results from an industry standard compositional simulator (“GEM”) and a variant of the FE/NETL CO 2 Prophet Model (CO 2 Prophet Model), which determined the CO 2 Prophet Model was able to reasonably represent the performance of the CO 2 flood modeled using the more sophisticated GEM. This case study uses the Horn Mountain oil field NFB M Sand, in the field's North fault block, using three pairs of wells. Each pair of wells is a line drive pattern design (one CO 2 injector and one production well). Four 20-year injection scenarios were assessed, varying CO 2 injector well placements. A version of the CO 2 Prophet Model is available on NETL’s website under the Collection Name: FE/NETL CO 2 Prophet Model.

02 PETROLEUM↗

Field Laboratory for Emerging Stacked Unconventional Plays in Central Appalachia

The goal of the Field Laboratory for Emerging Stacked Unconventional Plays (ESUP) in Central Appalachia project was to investigate and characterize the resource potential for multi-play production of emerging unconventional reservoirs in Central Appalachia. Project activities included drilling, logging and coring of a vertical characterization well drilled to basement to approximately 15,000 feet in depth. The data from drilling and well logs as well recovered core samples were used by the research team to support characterization of the geology and potential pay zones within the Nora Gas Field of southwestern Virginia and the greater Central Appalachian Basin. This project was led by Dr. Nino Ripepi of the Virginia Center for Coal and Energy Research (VCCER) in close collaboration with EnerVest Operating LLC (EnerVest). VCCER is housed in the Department of Mining and Minerals Engineering at Virginia Tech and was created by an Act of the Virginia General Assembly on March 30, 1977, as an interdisciplinary study, research, information, and resource facility for the Commonwealth of Virginia. EnerVest is a top tier, low-cost oil and natural gas company with a long history of traditional operating relationships with institutional investors as well as public and private companies. This report summarizes two major research activities: 1) Log and Core Analysis and 2) Numerical Modeling. Core analysis comprises the characterization efforts of the ESUP Field Laboratory and includes a discussion of the well logs run in the deep characterization wells, an initial analysis of those, the number, size and location of cores recovered, core testing and analysis done to date as well as plans for future analysis. Numerical modeling is comprised of seven major modeling efforts, including (1) Multiphysics shale transport modeling work, (2) the developed in-house compositional simulator studies, (3) reservoir modeling studies using GEM software, (4) fracture modeling work using EFRAC3D software and (5) numerical modeling efforts with ABAQUS software, (6) Numerical modeling efforts using FLAC3D and PFC3D, and (7) Automatic Machine Learning (AutoML) Studies.

02 PETROLEUM↗

Integrative Modeling and Analysis of Fungal Central Carbon Metabolism

Over a thousand fungal genomes have been sequenced, yet manually curated genome-scale metabolic models (GEMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, Mucoromycota, and both Crabtree-positive and Crabtree-negative yeasts. We harmonized metabolites and reactions into a non-redundant shared ModelSEED ontological space, standardized compartmentalization, and refined gene–protein–reaction (GPR) rules. Using pathway-level visualization and systematic gap detection, we further improved the integrated network through literature-guided curation to correct stoichiometry, stereospecificity, and pathway architecture. Orthologous protein family reconstruction and functional annotation workflows were used to validate and inform GPR associations, with particular emphasis on ambiguous enzyme superfamilies and membrane-associated components. Using the resulting CFCMM, we built high-quality central carbon core models for each fungus and performed flux balance analysis to quantify ATP-yield variation under aerobic and anaerobic conditions, explicitly evaluating scenarios driven by differences in electron transport chain (ETC) composition. Simulations reproduced the expected fermentative yield of approximately 2 mmol ATP per mmol glucose under anaerobic conditions and separated the thirteen fungi into two bioenergetic groups under aerobic respiration based on Complex I status, with predicted yields of approximately 30 versus 22 mmol ATP per mmol glucose. Forcing flux through the alternative oxidase bypass further reduced ATP yields to approximately 12 and 4 mmol ATP per mmol glucose in Complex I-containing and Complex I-lacking fungi, respectively. Collectively, this work provides a manually curated, ModelSEED-consistent, and extensible fungal core metabolic template, deployed in DOE KBase as a resource for automated reconstruction of central carbon core models from any sequenced fungal genome. In addition, the CFCMM provides modular components for developing GEMs with more accurate energy predictions and enables robust comparative analyses of fungal bioenergetics and core metabolic diversity

59 BASIC BIOLOGICAL SCIENCES↗

Simplified Physics Based Models Research Topical Report on Task #2

We present a simplified-physics based approach, where only the most important physical processes are modeled, to develop and validate simplified predictive models of CO2 sequestration in deep saline formation. The system of interest is a single vertical well injecting supercritical CO2 into a 2-D layered reservoir-caprock system with variable layer permeabilities. We use a set of well-designed full-physics compositional simulations to understand key processes and parameters affecting pressure propagation and buoyant plume migration. Based on these simulations, we have developed correlations for dimensionless injectivity as a function of the slope of fractional-flow curve, variance of layer permeability values, and the nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. Similar correlations are also developed to predict the average pressure within the injection reservoir, and the pressure buildup within the caprock.

Mishra, Srikanta↗

SIMPLIFIED PREDICTIVE MODELS FOR CO₂ SEQUESTRATION PERFORMANCE ASSESSMENT RESEARCH TOPICAL REPORT ON TASK #3 STATISTICAL LEARNING BASED MODELS

We compare two approaches for building a statistical proxy model (metamodel) for CO₂ geologic sequestration from the results of full-physics compositional simulations. The first approach involves a classical Box-Behnken or Augmented Pairs experimental design with a quadratic polynomial response surface. The second approach used a space-filling maxmin Latin Hypercube sampling or maximum entropy design with the choice of five different meta-modeling techniques: quadratic polynomial, kriging with constant and quadratic trend terms, multivariate adaptive regression spline (MARS) and additivity and variance stabilization (AVAS). Simulations results for CO₂ injection into a reservoir-caprock system with 9 design variables (and 97 samples) were used to generate the data for developing the proxy models. The fitted models were validated with using an independent data set and a cross-validation approach for three different performance metrics: total storage efficiency, CO₂ plume radius and average reservoir pressure. The Box-Behnken–quadratic polynomial metamodel performed the best, followed closely by the maximin LHS–kriging metamodel.

Mishra, Srikanta↗

Low Temperature Waste Form for Supplemental Immobilization of Hanford Low Activity Waste - 17485

The Hanford site has approximately 56 million gallons of radioactive waste stored in 177 underground storage tanks. The Hanford Waste Treatment and Immobilization Plant (WTP) is being constructed to treat the waste but will only have sufficient capacity to treat about one-third of the Low Activity Waste (LAW) portion within the anticipated time-frame for completing the waste treatment mission. The LAW vitrification facility will need to be supplemented with additional LAW vitrification capacity or an alternate LAW immobilization technology. The LAW immobilization technologies considered must be capable of treating approximately 65% of Hanford's LAW and will be evaluated with respect to facilities required, quantity of final waste forms and secondary wastes produced, waste form performance data, technical viability, and life cycle cost and schedule estimates. A low temperature (i.e. non-thermal) waste form and treatment process is being evaluated to provide the additional LAW immobilization capacity. Low temperature, cementitious waste forms have been evaluated previously for immobilizing Hanford tank waste but were not further developed for various reasons. Over the past few years the Hanford Tank Operations Contractor has conducted a technology development program to evaluate a low temperature waste form for immobilization of Hanford LAW including formulation development and testing with a range of simulant compositions spiked with radioactive and hazardous contaminants of concern (COCs). The objectives of this program include; developing a low temperature waste form formulation that is robust with respect to both waste form performance and processing properties over a range of LAW compositions, demonstrating waste form performance with real waste, and conducting Engineering Scale testing to advance the technical maturity of the low temperature immobilization process. The purpose of this paper is to report progress toward these objectives, in particular testing with real waste including additives to enhance technetium and iodine retention. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Development of a Testbed for Pipeline Flushing - 19409

Pipelines which carry radioactive waste within the DOE complex should be properly flushed, particularly 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 used for post-transfer flushing operations to achieve satisfactory cleaning of pipelines. However, further studies are needed to limit the amount of water used for flushing operations, thus minimizing the 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 pipe loop designed for study of non-Newtonian slurry flushing is currently being developed at the Florida International University (FIU). The testbed is designed to 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. The developed methodologies will be streamlined according to the demands from both Hanford and Savannah River sites. A test matrix containing parameters such as pipeline length, flow rate, and simulant composition (solid concentration, rheology, particle size and density) has been developed. In the initial phase of testing, material composition and loop length will be fixed to a mixture of 17 wt% kaolin in water (to attain density, viscosity, and yield stress in the applicable range to operations at Savannah River and Hanford sites) and 165 feet, respectively. This matrix provides a parametric study on the flush velocity. Prescribed velocities in this test matrix comply with the maximum and minimum recommended flush velocity values by the flushing guidelines for Hanford waste (RPP-RPT-59600, Rev. 0, SRNL-STI-2015-00014, TFC-ENG-STD-26, REV C-1). Efforts will focus on creating repeatable sediment beds inside the pipeline in both fully-flooded and gravity-drained systems. Bed characterization (i.e., measurement of sediment height, solids concentration, and rheology) will be conducted to ensure consistency of initial conditions between tests. A combination of Pulse-Echo technique, Coriolis meter, and optical inspections will be used to accomplish initial bed characterization (ensuring consistency between tests), control/monitor density variations (initial bed creation, flush velocity control, and post-flush evaluations), and serve as reference (validation of PulseEcho and pipe surface cleanness evaluation), respectively. This paper will present the details of the development of the test loop and the test matrix. (authors)

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Implementation of the Glycolate Destruction Process with Sodium Permanganate in the Defense Waste Processing Facility (DWPF) - 20141

The Savannah River Site (SRS) seeks to replace formic acid with glycolic acid as a chemical reductant in the Defense Waste Processing Facility (DWPF), where borosilicate glass is mixed with high-level radioactive waste, melted at high temperatures, then poured into stainless steel canisters for safe storage. Prior research and development have demonstrated the feasibility and advantages of the new nitric-glycolic acid flowsheet over the current nitric-formic acid flowsheet to chemically adjust the radioactive sludge slurry waste in the Sludge Receipt and Adjustment Tank (SRAT) prior to vitrification. Use of glycolic acid reduces hydrogen and ammonia generation during the reduction process, thus reducing flammability hazards and purge requirements in the DWPF processing vessels. In addition, glycolic acid will support the new Salt Waste Processing Facility (SWPF) by allowing for receipt of higher volumes of waste due to reduction of flammable gases, increased boil-up rates in the vessels, and easing the processing of future sludge batches containing high levels of mercury. However, during DWPF operations, trace amounts of glycolate are anticipated to be entrained in the recycle stream and sent to the Concentration, Storage, and Transfer Facilities (CSTF) via the Recycle Collection Tank (RCT). The RCT receives condensate from the Slurry Mix Evaporator Condensate Tank (SMECT) and Off-gas Condensate Tank (OGCT) that may contain unreacted glycolate. A literature review found the potential for hydrogen generation due to thermolysis of glycolate in caustic CSTF conditions. Savannah River National Laboratory (SRNL) conducted several tests on simulant and radioactive waste from various tanks at SRS and confirmed that glycolate added to waste at concentrations of approximately 1000 mg/L and higher generates hydrogen through thermolysis. There are potential operating scenarios in the future where glycolate concentration could exceed 1000 mg/L in the 2H Evaporator Drop Tank, the highest accumulation point for DWPF organics received via recycle. These findings presented a need to develop another process to mitigate the impact of glycolic acid to the CSTF. Several DWPF compatible options were evaluated for their ability to destroy glycolate in the DWPF recycle stream under various processing conditions, thereby mitigating its introduction to the CSTF. Downselection testing identified sodium permanganate as the most promising and simplest option to oxidize glycolate. It has been demonstrated to be effective in various RCT simulant compositions, operating temperatures, oxidant addition rates, solution pH, and initial glycolate concentrations. A feasibility study identified existing tanks within the facility that could be used for receiving and storing the commercially available sodium permanganate, as well as feeding it to the RCT for processing. The use of existing equipment as well as the ability to purchase the pre-mixed chemical reduces implementation and operational complexity. The downstream impacts of the sodium permanganate reaction were also evaluated and demonstrated to have minimal impact on other chemical species present in the RCT and CSTF, as well as on the materials of construction of the RCT and CSTF vessels and associated piping and instrumentation. Future work is in progress to validate the glycolate destruction process with testing in actual radioactive RCT waste before implementation in DWPF. (authors)

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