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At least 109 records · Page 6

Autonomous Inversion of In Situ Deformation Measurement Data for Injection-Induced Stress Change

Geologic carbon storage (GCS) is likely to play a key part of the global effort to dramatically reduce CO2 emissions and perhaps even reduce atmospheric CO2 concentrations through carbon negative operations. A critical part of effort to commercialize and widely deploy this technology is developing the capability to rapidly assimilate real-time monitoring data into a form that will enable site operators to make decisions to manage the safe and efficient operations. Two of the risks associate with GCS are the risk of inducing fractures in the sealing formations that can create leakage pathways and the risk of inducing earthquakes of sufficient magnitude to cause public concern, property damage, or safety risks. To properly manage these risks the site operator needs to know the initial state of stress, the change in stress induced by injection, and the relationship between operational parameters such as injection rate and pressure and the change in stress. Current methods of estimating the change in stress require choosing the type of constitutive model and the model parameters based on core, log, and geophysical data during the characterization phase, with little feedback from operational observations to validate or refine these choices. These characterization methods interrogate the geologic formations using length scales, loading rates or magnitudes that are quite different from those encountered by the actual storage system. It is shown that errors in the assumed constitutive response, even when informed by laboratory tests on core samples, are likely to be common, large, and underestimate the magnitude of stress change caused by injection. Recent advances in borehole-based strain instruments and borehole and surface-based tilt and displacement instruments have now enabled monitoring of the deformation of the storage system throughout its operational lifespan. This data can enable validation and refinement of the knowledge of the geomechanical properties and state of the system, but brings with it a challenge to transform the raw data into actionable knowledge. We demonstrate a method that uses automatic differentiation and a finite-element based geomechanical model perform a gradient-based deterministic inversion of geomechanical monitoring data. This approach allows autonomous integration of the instrument data without the need for time consuming manual interpretation and selection of updated model parameters. Furthermore, only isotropic linear elasticity is considered in this paper, the approach presented is very flexible as to what type of geomechanical constitutive response can be used. The approach is easily adaptable to nonlinear physics-based constitutive models to account for common rock behaviors such as creep and plasticity. The approach also enables training of machine learning-based constitutive models by allowing back propagation of errors through the finite element calculations. This enables strongly enforcing known physics, such as conservation of momentum and continuity, while allowing data-driven models to learn the truly unknown physics such as the constitutive or petrophysical responses.

Burghardt, Jeffrey A.↗

Normal-Incidence Soft-X-Ray Mirror

Multilayered interference structure has about 6 percent reflectivity. Normal-incidence X-Ray Mirror, bent into spherical surface of radius 1.1mm used to image electroformed-nickel grid onto photographic film sensitive to soft X-rays. Grid set at distance of 1,067 mm from mirror, illuminated by simple Coolidge-type X-ray tube with carbon anode operated from 1.5KV supply. Film set at distance of 1,186 mm from mirror with resultant magnification of 1.11.

Underwood, J. H.↗

Catalytic autothermal reforming increases fuel cell flexibility

Experimental results are presented for the autothermal reforming (ATR) of n-hexane, n-tetradecane, benzene and benzene solutions of naphthalene. The tests were run at atmospheric pressure and at moderately high reactant preheat temperatures in the 800-900 K range. Carbon formation lines were determined for paraffinic and aromatic liquids. Profiles were determined for axial bed temperature and composition. Space velocity efforts were assessed, and the locations and types of carbon were recorded. Significant reactive differences between hydrocarbons were identified. Carbon formation characteristics were hydrocarbon specific. The differing behavior of paraffinic and aromatic fuels with respect to their carbon formation may be important in explaining the narrow range of carbon-free operating conditions found in the ATR of number two fuel oil.

Flytzani-Stephanopoulos, M.↗

Anaerobic reduction of elemental sulfur by Chromatium vinosum and Beggiatoa alba

The effect of sulfur globules on the buoyant density of Chromatium vinosum and Beggiatoa alba was examined. The potential use of sulfur as a terminal electron acceptor in the anaerobic metabolism of Beggiatoa alba is also examined. The effect of the reduction of intracellular sulfur was investigated during dark metabolism on the buoyant density of C. vinosum. It is hypothesized from the results that the sulfur reduction to sulfide is part of an anaerobic energy operating system. Carbon stored as PHB can be oxidized with the concomitant reduction of sulfur to sulfide.

Schmidt, T. M.↗

Quantifying the Value of Grid-Interactive Efficient Buildings through Field Study: Preprint

Quantifying the annual energy impacts of efficient technologies in commercial buildings has been well established by the building science field. As we move toward enabling grid-interactive efficient buildings (GEB) targeting flexible building operation and carbon reduction, quantification methods to evaluate time-sensitive peak load and emissions impact are much less defined. A number of national laboratories are working to field validate four different GEB software solutions that provide the capability to control multiple building end-use systems in multiple load flexibility modes (i.e., energy efficiency, load shed, load shift, and possible load modulation at the second to sub-second level). To guide the laboratory leads in effective measurement and verification (M&V) practices, two of the laboratories collaborated to define metrics to quantify the impacts of flexible load control on building demand, utility costs, carbon emissions, facility management, and occupant comfort. This paper summarizes the proposed metrics to quantify peak load and emission impacts in the field, decision parameters, approaches to accurately conduct M&V, lessons learned, and outstanding needs and next steps.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

Quantifying the Value of Grid-Interactive Efficient Buildings through Field Study

Quantifying the annual energy impacts of efficient technologies in commercial buildings has been well established by the building science field. As we move toward enabling grid-interactive efficient buildings (GEB) targeting flexible building operation and carbon reduction, quantification methods to evaluate time-sensitive peak load and emissions impact are much less defined. A number of national laboratories are working to field validate four different GEB software solutions that provide the capability to control multiple building end-use systems in multiple load flexibility modes (i.e., energy efficiency, load shed, load shift, and possible load modulation at the second to sub-second level). To guide the laboratory leads in effective measurement and verification (M&V) practices, two of the laboratories collaborated to define metrics to quantify the impacts of flexible load control on building demand, utility costs, carbon emissions, facility management, and occupant comfort. This paper summarizes the proposed metrics to quantify peak load and emission impacts in the field, decision parameters, approaches to accurately conduct M&V, lessons learned, and outstanding needs and next steps.

Langner, Rois↗

Flexible Gasification of Coal and Biomass to Generate Carbon Free Electric Power and Hydrogen

This paper describes the development of a coal and biomass-fed plant concept to co-produce electric power and hydrogen with net-negative CO2 emissions under the aegis of the 21st Century Power Plant initiative of the U.S. Department of Energy (DOE), whose goal is to advance innovative power plant concepts that are capable of flexible, net-zero carbon emission operations while producing cost-effective “blue” hydrogen to support economy-wide decarbonization goals. The proposed standalone plant will be in Nebraska, USA. The specified design feedstock is a hybrid blend of Powder River Basin (PRB) subbituminous coal from Wyoming and local Nebraska biomass (corn stover), 50 wt.% each (dry basis). Other potential feedstocks, including woody biomass (eastern red cedar) and waste plastic (auto shredder residue) were evaluated or reviewed as alternates. The proposed process block comprises a high-pressure, oxygen-blown fluidized bed gasifier (GTI Energy U-GAS® process) coupled with water gas shift, the Selexol process for acid gas (H2S and CO2) removal, and pressure-swing adsorption (PSA) to yield 8,500 kg/h of high-purity hydrogen. The off gas from the PSA unit is used in the power block (gas turbine combined cycle) to generate electric power to support the gasification process, hydrogen production, and 50 MWe net electric power to the grid. All major plant equipment including the gasifier, gas cleanup system, and power generation are commercially available and proven in other applications and considered at TRL 8-9. However, gasification of corn stover biomass is considered at TRL 6. Overall thermal efficiency of the plant is 50% (net HHV) with net atmospheric CO2 removal at a rate of 250-300,000 tpa. Design activities necessary to provide input to a FEED study (Phase II of the project), including the development of the Environmental Information Volume (EIV) for the host site, and an investment case, based on a pro-forma pre-FEED level cost estimate, have been completed and are described in detail in this paper.

Gülen, S. Can↗

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

Siriwardane, Hema↗

Analysis of Waste Material Feedstocks Using Laser-Induced Breakdown Spectroscopy and Machine Learning

Predicting properties such as heating value, ash fusion temperature, and mineral ash composition from Laser-Induced Breakdown Spectroscopy (LIBS) data can make gasifiers more flexible to different feedstocks. Understanding these feedstock properties in-situ improves feedstock conversion modelling methods that allow for consistent operation, higher carbon conversion, and reduced fouling and erosion rates. The purpose of this study is to demonstrate methods for model creation that take LIBS data as predictor features and estimate higher order material properties as a function of feedstock material properties. Six samples were chosen to represent a mixture of abundant and carbon rich waste materials. LIBS measurements were performed on these samples for elemental wavelengths and intensity values. Laboratory analytical results were obtained for each sample’s heating value, proximate and ultimate analysis, mineral ash composition, ash fusion temperatures, and viscosity temperatures. Thermal conductivity was measured using a HotDisk TPS 2500S. LIBS measurements were processed and used as predictor features for machine learning (ML) models to predict the sample’s material properties. Predictor feature selection algorithms, particularly minimum redundancy maximum relevance (mRMR), reduced the dimensionality of ML models. Many modelling methods such as Gaussian process regression (GPR), regression tree, neural networks (NN), and support vector machines (SVM) were demonstrated to be effective at predicting higher order properties; however, mRMR with GPR stood out as a clear winning combination.

01 COAL, LIGNITE, AND PEAT↗

Enhanced carbon-transfer and -utilization efficiencies achieved using membrane carbonation with gas sources having a range of CO 2 concentrations

The economic viability of microalgal biofuels relies on increasing productivity in a cost-effective manner. As microalgal biomass contains > 50% carbon, a high rate of CO 2 delivery is required for high productivity, and inefficient CO 2 delivery amplifies operating costs. Membrane carbonation using non-porous hollow fiber membranes can ideally deliver CO 2 without bubble formation and high carbon transfer efficiency. Because CO 2 streams from industrial resources are not 100% CO 2 , the buildup of inert gasses can significantly lower the CO 2 delivery rate when the distal end of the membrane is closed. To overcome the buildup of inert gases, we managed the distal end of the membranes with three different approaches: fully open end, restricted bleed valve, and restricted bleed valve with pH-actuated venting. For all approaches, CO 2 was delivered to membranes ondemand based on a pH set point. Evaluating a wide range of CO 2 concentrations (10% to 100%), we found that all approaches eliminated the buildup of inert gases, could maintain target pH values and gave the same biomass productivities and carbon distributions. However, carbon transfer efficiency depended on the operation of the distal end. Fully open-end operation gave a poor carbon transfer efficiency because of excessive loss of CO 2 from the distal end. However, restricting the exit flow rate to ≤4 cm 3 /min mitigated the problems of excessive CO 2 loss, but without incurring a large loss of CO 2 -delivery flux. For the continuous cultivation, combining a restricted bleed valve with pH-actuated venting improved the carbon-transfer efficiency and -utilization efficiencies up to 85% and 67%, respectively, with a sufficient CO 2 delivery flux.

42 ENGINEERING↗

Advanced Anode for Internal Reforming and Thermal Management in Solid Oxide Fuel Cells

Solid oxide fuel cell (SOFC) is an efficient and clean electrical power generation system compared to conventional combustion based technologies with energy efficiency reaching as high as 85-90% in co-generation mode (electricity and heat). Other advantages of SOFCs are hybridization, modularity of construction, small CO 2 foot print per kWh of generated electricity and fuel flexibility. Hydrocarbons present in the gaseous fuel is utilized in SOFCs by internal or external reforming. There are two different internal reforming concepts: Direct Internal Reforming (DIR) and Indirect Internal Reforming (IIR). For DIR operation, the endothermic reforming reaction and the exothermic reaction from the oxidation reaction are operated together in the single unit eliminating the requirement for a separate fuel reformer. This configuration also simplifies the overall system design, making SOFC more attractive and efficient means of producing electrical power. The main advantage of the DIR type of operation is that the H 2 or CO consumption by the electrochemical reaction could directly promote the conversion of methane at the anode side of the fuel cell resulting in high conversion and high efficiency. The DIR operation, however, requires an anode material that has desired dual catalytic (hetero and electro) properties for reforming reaction and electrochemical reactions. The anode materials also need to remain resistant to carbon formation at the operating temperature and atmosphere with stable cell performance. Another requirement is to match the reforming reactions and electrochemical reactions to avoid local cooling or overheating, which can result in mechanical failure due to thermally induced stresses. Direct internal reforming (DIR) of hydrocarbon fuels simplifies the overall SOFC system design making it more attractive and efficient for producing electrical power. Low cost alloy anodes for distributed internal reforming of methane and other hydrocarbon fuels offer increased fuel-flexibility, reliability, and long term performance stability of solid oxide fuel cells (SOFC). The research program examined modification of the chemical compositions and microstructure of high entropy alloy (HEA) anode materials using thermochemical calculations and process simulation and modeling to achieve distributed reforming over the entire anode to eliminate hot zones. Cell fabrication and testing of the HEA anodes using button cell configuration has been performed to demonstrate the advantages of new anode over traditional Ni-YSZ anodes for distributed reforming and carbon free operation. Technical accomplishments include identification and synthesis of HEA carbon-resistant anode, demonstration of reduction in reforming rate confirmed by GC and modelling data validating effectiveness for thermal management in cell/stacks, electrochemical testing of HEA anode in single cell (HEA-GDC||YSZ||LSM-YSZ) and Characterization of pretest and posttest anode materials by TEM and SEM-EDS confirming carbon-free operation.

30 DIRECT ENERGY CONVERSION↗

Measuring thermal diffusivity and gap conductance in uranium nitride and Zircaloy relevant for microreactor applications

Heat transfer across nuclear fuels and structural interfaces is an important factor for evaluating the performance of nuclear power systems. Specifically, heat generated as nuclear fuel fissions must be transported through the cladding material and through the reactor to reach the steam turbine for power generation. As new microreactor designs emerge, maximizing the efficiency of this heat transfer process becomes crucial to make them commercially viable. This article examines thermal diffusivity and gap conductance in uranium nitride (UN) fuel and Zircaloy-4 (Zry4) cladding using light flash analysis (LFA). Thermal diffusivity measurements were made on monolithic UN pellets and Zry4 exposed to carbon at peak operating temperatures of microreactors and show that carbon ingress has a minimal effect on thermal diffusivity when compared with identical materials not exposed to carbon. Evaluation of gap conductance at the UN-Zry4 interface was done using one-dimensional two-layer thermal transport models as a function of applied pressure. Here the results show that increasing pressure on the UN-Zry4 interface leads to gains in gap conductance per unit area in fuel-cladding assemblies at microreactor operating temperatures. While many other variables are expected to influence UN-Zry4 interfacial gap conductance (e.g. contact surface roughness, porosity, localized heating, environmental gas pressure), the work offers a demonstration of using a conventional LFA apparatus to determine this parameter at elevated temperatures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗