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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Bridging Equipment Reliability Data and Risk Informed Decisions in a Plant Operation Context

Industry equipment reliability and asset management programs are essential elements that help ensure the safe and economical operation of nuclear power plants. The effectiveness of these programs is addressed in several industry-developed and regulatory programs. The Risk-Informed Asset Management (RIAM) project is tasked to develop tools in support of the equipment reliability and asset management programs at nuclear power plants. These tools are designed to create a direct bridge between component health/lifecycle data and decision making (e.g., maintenance scheduling and project prioritization). The goal of this article is to provide a guide for specific use cases that the RIAM project is targeting. We have grouped uses cases into three main areas. The first area focuses on the analysis of equipment reliability data with a particular emphasis on condition-based data, such as test/surveillance reports and component monitoring data. The second area focuses on the integration of equipment reliability into system/plant reliability models to determine system/plant health and identify the components that are critical to maintain an operational system. Lastly, the third area manages plant resources, such as maintenance activities and replacement scheduling using optimization methods. Here the primary focus is on supporting typical system engineer decisions regarding maintenance activity scheduling and component aging management. This is performed in a risk-informed context where the term “risk” is broadly constructed to include both plant reliability and economics. This framework combines data analytics tools to analyze equipment reliability data with risk-informed methods designed to support system engineer decisions (e.g., maintenance and replacement schedules, optimal maintenance posture) in a customizable workflow.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A Data-Driven Workflow Approach to Optimization of Fracture Spacing in Multi-Fractured Shale Oil Wells

A data-driven workflow approach is presented in this study for optimizing fracture spacing of multifractured horizontal wells (MFHW) in shale oil reservoirs. The workflow employs a simple well productivity model for the initial design of hydraulic fracturing well completions. This provides a transparent approach to the identification of key fracturing parameters affecting well productivity. The workflow uses transient pressure or production data to identify fracture interference. This offers a reliable and cost-effective means for assessment of well production potential in terms of optimization of fracture spacing in the MFHW. Result of a field case study indicated that three wells were drilled in an area with dense natural fractures, and the fracture spacing of MFHW in this area was short enough to effectively drain the stimulated reservoir volume (SRV), while the other three wells were drilled in an area with less natural fractures, and the fracture spacing of MFHW in this area could be shortened to double well productivity.

58 GEOSCIENCES↗
DOE OSTI2015

Adsorbent Alkali Conditioning for Uranium Adsorption from Seawater. Adsorbent Performance and Technology Cost Evaluation

The Fuel Resources program of the Fuel Cycle Research and Development program of the Office of Nuclear Energy (NE) is focused on identifying and implementing actions to assure that nuclear fuel resources are available in the United States. An immense source of uranium is seawater, which contains an estimated amount of 4.5 billion tonnes of dissolved uranium. This unconventional resource can provide a price cap and ensure centuries of uranium supply for future nuclear energy production. NE initiated a multidisciplinary program with participants from national laboratories, universities, and research institutes to enable technical breakthroughs related to uranium recovery from seawater. The goal is to develop advanced adsorbents to reduce the seawater uranium recovery technology cost and uncertainties. Under this program, Oak Ridge National Laboratory (ORNL) has developed a new amidoxime-based adsorbent of high surface area, which tripled the uranium capacity of leading Japanese adsorbents. Parallel efforts have been focused on the optimization of the physicochemical and operating parameters used during the preparation of the adsorbent for deployment. A set of parameters that need to be optimized are related to the conditioning of the adsorbent with alkali solution, which is necessary prior to adsorbent deployment. Previous work indicated that alkali-conditioning parameters significantly affect the adsorbent performance. Initiated in 2014, this study had as a goal to determine optimal parameters such as base type and concentration, temperature, and duration of conditioning that maximize the uranium adsorption performance of amidoxime functionalized adsorbent, while keeping the cost of uranium production low. After base-treatment at various conditions, samples of adsorbent developed at ORNL were tested in this study with batch simulated seawater solution of 8-ppm uranium concentration, batch seawater spiked with uranium nitrate at 75-100 ppb uranium, and continuous-flow natural seawater at the Pacific Northwest National Laboratory (PNNL). Fourier Transform Infrared (FTIR) spectroscopy, Nuclear Magnetic Resonance (NMR) spectroscopy, Scanning Electron Microscopy (SEM), and elemental analysis were used to characterize the adsorbent at different stages of adsorbent preparation and treatment. The study can be divided into two parts: (A) investigation of optimal parameters for KOH adsorbent conditioning and (B) investigation of other possible agents for alkali conditioning, including cost analysis on the basis of uranium production. In the first part of the study, tests with simulated seawater containing 8 ppm uranium showed that the uranium adsorption capacity increased with an increase in the KOH concentration and conditioning time and temperature at each of the KOH concentrations used. FTIR and solid state NMR studies indicated that KOH conditioning converts the amidoxime functional groups into more hydrophilic carboxylate. The longer the KOH conditioning time, up to three hours, the higher was the loading capacity from the simulated seawater solution which is composed of only uranyl, sodium, chloride, and carbonate ions. Marine testing with natural seawater, on the other hand, showed that the uranium adsorption capacity of the adsorbent increased with KOH conditioning temperature, and gradually decreased with increasing KOH conditioning time from one hour to three hours at 80 C. This behavior is due to the conversion of amidoxime to carboxylate. The carboxylate groups are needed to increase the hydrophilicity of the adsorbent; however, conversion of a significant amount of amidoxime to carboxylate leads to loss in selectivity toward uranyl ions. Thus, there is an optimum KOH conditioning time for each temperature at which an optimum ratio between amidoxime and carboxylate is reached. For the case of base conditioning with 0.44 M KOH at 80 C, the optimal conditioning time is 1 hour, with respect to the highest uranium loading capacity from natural seawater. Uptake of other metal ions such as V, Fe, and Cu follows the same trend as that of uranium. Also, the uptake of Ca, Mg, and Zn ions increased with increasing KOH conditioning time, probably due to formation of more carboxylates, which leads to conversion of uranium-selective binding sites to less selective sites. In the second part of the study, inorganic based reagents such as sodium hydroxide (NaOH), sodium carbonate (Na 2 CO 3 ), cesium hydroxide (CsOH), as well as organic based reagents such as ammonium hydroxide (AOH), tetramethylammonium hydroxide (TMAOH), tetraethylammonium hydroxide (TEAOH), triethylmethylammonium hydroxide (TEMAOH), tetrapropylammonium hydroxide (TPAOH) and tetrabutylammonium hydroxide (TBAOH), in addition to KOH, were used for alkaline conditioning. NaOH has emerged as a better reagent for alkaline conditioning of amidoxime-based adsorbent because of higher uranium uptake capacity, higher uranium uptake selectivity ...

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Surface-Enhanced Raman Scattering (SERS) Studies of Disc-on-Pillar (DOP) Arrays: Contrasting Enhancement Factor with Analytical Performance

The use of nanomachining methods capable of reproducible construction of nano-arrayed devices have revolutionized the field of plasmonic sensing by the introduction of a diversity of rationally engineered designs. Significant strides have been made to fabricate plasmonic platforms with tailored interparticle gaps to improve their performance for surface-enhanced Raman scattering (SERS) applications. Over time, a dichotomy has emerged in the implementation of SERS for analytical applications, the construction of substrates, optimization of interparticle spacing as a means to optimize electromagnetic field enhancement at the localized surface plasmon level, and the substrate sensitivity over extended areas to achieve quantitative performance. Here, we assessed the enhancement factor of plasmonic Ag/SiO 2 /Si disc-on-pillar (DOP) arrays of variable pitch with its analytical performance for quantitative applications. Experimental data were compared with those from finite-difference time-domain (FDTD) simulations used in the optimization of the array dimensions. A self-assembled monolayer (SAM) of benzenethiol rendered highly reproducible signals (RSD ~4–10%) and SERS substrate enhancement factor (SSEF) values in the orders of 10 6 –10 8 for all pitches. Furthermore, spectra corresponding to rhodamine 6G (R6G) and 4-aminobenzoic acid demonstrated the advantages of using the more densely packed DOP arrays with a 160 nm pitch (gap= 40 nm) for quantitation in spite of the strongest SSEF was attained for a pitch of 520 nm corresponding to a 400 nm gap.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A new strategy to engineer polymer bulk heterojunction solar cells with thick active layers via self-assembly of the tertiary columnar phase

Here, we report that the addition of a non-photoactive tertiary polymer phase in the binary bulk heterojunction (BHJ) polymer solar cell leads to a self-assembled columnar nanostructure, enhancing the charge mobilities and photovoltaic efficiency with surprisingly increased optimal active blend thicknesses over 300 nm, 3–4 times larger than that of the binary counterpart. Using the prototypical poly(3-hexylthiophene) (P3HT):fullerene blend as a model BHJ system, we discover that the inert poly(methyl methacrylate) (PMMA) added in the binary BHJ blend self-assembles into vertical columns, which not only template the phase segregation of electron acceptor fullerenes but also induce the out-of-plane rotation of the edge-on-orientated crystalline P3HT phase. Using complementary interrogation methods including neutron reflectivity, X-ray scattering, atomic force microscopy, transmission electron microscopy, and molecular dynamics simulations, we show that the enhanced charge transport originates from the more randomized molecular stacking of the P3HT phase and the spontaneous segregation of fullerenes at the P3HT/PMMA interface, driven by the high surface tension between the two polymeric components. The results demonstrate a potential method for increasing the thicknesses of high-performance polymer BHJ solar cells with improved photovoltaic efficiency, alleviating the burden of stringently controlling the ultrathin blend thickness during the roll-to-roll-type large-area manufacturing environment.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

In-flight performance of S PIDER'S 280-GHz receivers

S PIDER is a balloon-borne instrument designed to map the cosmic microwave background at degree-angular scales in the presence of Galactic foregrounds. S PIDER has mapped a large sky area in the Southern Hemisphere using more than 2000 transition-edge sensors (TESs) during two NASA Long Duration Balloon flights above the Antarctic continent. During its first flight in January 2015, S PIDER observed in the 95 GHz and 150 GHz frequency bands, setting constraints on the B-mode signature of primordial gravitational waves. Its second flight in the 2022-23 season added new receivers at 280 GHz, each using an array of TESs coupled to the sky through feedhorns formed from stacks of silicon wafers. Here, these receivers are optimized to produce deep maps of polarized Galactic dust emission over a large sky area, providing a unique data set with lasting value to the field. In this work, we describe the instrument’s performance during S PIDER'S second flight.

280 GHz cosmology↗
DOE OSTI2023

Optimizing training trajectories in variational autoencoders via latent Bayesian optimization approach *

Unsupervised and semi-supervised ML methods such as variational autoencoders (VAE) have become widely adopted across multiple areas of physics, chemistry, and materials sciences due to their capability in disentangling representations and ability to find latent manifolds for classification and/or regression of complex experimental data. Like other ML problems, VAEs require hyperparameter tuning, e.g. balancing the Kullback–Leibler and reconstruction terms. However, the training process and resulting manifold topology and connectivity depend not only on hyperparameters, but also their evolution during training. Because of the inefficiency of exhaustive search in a high-dimensional hyperparameter space for the expensive-to-train models, here we have explored a latent Bayesian optimization (zBO) approach for the hyperparameter trajectory optimization for the unsupervised and semi-supervised ML and demonstrated for joint-VAE with rotational invariances. We have demonstrated an application of this method for finding joint discrete and continuous rotationally invariant representations for modified national institute of standards and technology database (MNIST) and experimental data of a plasmonic nanoparticles material system. The performance of the proposed approach has been discussed extensively, where it allows for any high dimensional hyperparameter trajectory optimization of other ML models.

42 ENGINEERING↗
DOE OSTI2018

Risk-Informed Systems Analysis (RISA) Dynamic Fire PRA Roadmap

Modeling and implementing fire safety for nuclear power plants is a costly activity. Because of the complexity of fire phenomenon and multiple operational procedures, it is difficult to computationally provide assurance that the mitigation methods are adequate for critical areas using current analysis methods. An economical method to provide more accurate modeling and optimize mitigation methods is needed to improve nuclear power viability. This report describes the initial investigation into modeling and simulation tools for application of fire as part of the Risk-Informed Systems Analysis (RISA), formerly Risk-Informed Safety Margin Characterization (RISMC). The report provides a framework of how 3D modeling and simulation techniques could be combined with a dynamic Probabilistic Risk Analysis (PRA) to reduce compounding conservatism present in current Fire PRA methods. Electrical Power Research Institute has analyzed current Fire PRA practices and identified the most significant contributors to risk and areas for improving analysis. This framework describes how to apply dynamic PRA and simulation methods for key contributors/scenarios, credit missing factors of manual fire suppression, and applying conditional probabilities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Decision-Dependent Uncertainty-Aware Distribution System Planning Under Wildfire Risk

The interaction between power systems and wildfires can be dangerous and costly. Distribution grids can be liable for the outbreak of wildfires during extreme weather. In wildfire-prone areas, investment planning should consider the impact of operational actions on wildfire-related uncertainties affecting line failure likelihood. Here, in this case, endogenous-based uncertainty modeling should comprise the backbone of the investment planning model viz-a-viz the inability of standard exogenous-based uncertainty modeling. Therefore, we propose a decision-dependent uncertainty (DDU) aware methodology to optimize investment portfolios for distribution systems, considering that high power-flow levels in high-threat areas can ignite wildfires and increase line failure probability. The methodology identifies the best combination of upgrades (new lines, hardening existing lines, and placing switching devices). Methodologically, we propose a two-stage distributionally robust planning optimization problem with DDU that considers the distribution system's multiperiod operation. The first stage determines optimal switching actions and line investments, and the second stage evaluates the worst-case expected operational cost under a DDU framework designed to account for the endogenous impact of power-flow levels and hardening investment decisions in the line failure probabilities. An iterative method is tailored to handle the problem and numerical experiments demonstrate a more prepared grid to deal with wildfire risk.

Power systems investment planning↗
DOE OSTI2017

Characterization and photocatalytic activity of Bi{sub 3}TaO{sub 7} prepared by hydrothermal method

In this paper, Bi{sub 3}TaO{sub 7} nanoparticles with visible light response have been prepared via a facile hydrothermal route and solid-state reaction. The photocatalytic performance of as-prepared samples was evaluated by the degradation of Tetracycline hydrochloride (TC). It was observed that the sample obtained by hydrothermal method showed an enhanced photocatalytic activity in contrast to the sample prepared by solid-state method. This could be ascribed to the efficient separation of photogenerated electrons and holes in the sample prepared via hydrothermal process, which is certified by the photoluminescence spectroscopy (PL) and transient photocurrent analysis. Moreover, the result of nitrogen adsorption-desorption isotherm indicated the existence of mesoporous structure in as-prepared sample with hydrothermal process, and specific surface area is significantly higher than the sample obtained by solid-state method. The optimal conditions involved in the photocatalytic reaction, such as TC concentration, catalyst concentration and pH value were investigated. - Graphical abstract: The preparation process of Bi{sub 3}TaO{sub 7} photocatalyst by hydrothermal method. Display Omitted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

FY25 Electric Grid Security Annual Report

Sandia’s Electric Grid Security program advances a national vision of energy dominance and accessibility, while applying our national security -emphasis on ensuring of a secure, resilient, and affordable electric system for all users. Our achievements reflect a strategic approach combining technology development; modeling, simulation, and data analytics; and partnered demonstrations and outreach to further the adoption of advanced grid and storage technologies. Our FY25 efforts leverage the strengths of our partnerships—spanning Sandia’s core science and technology competencies as well as external technology leaders—to develop the solutions today which enable the grid of tomorrow. Key accomplishments in this report that support our strategy span our technical program areas and include: • New open-source analytical tools for systems -level planning and optimization, including significant advances to the QuESt analytical environment; • Further advancement of artificial intelligence and machine learning to enhanced grid operations and planning as we rise to the challenge of new large loads; • Development of solid-state power conversion technologies and a new medium-voltage research lab; • New technologies to assess wildfire vulnerabilities and mitigate potential impacts; • Advanced applications of new cybersecurity technologies with industry partners; • Contributions to understanding the impacts of electromagnetic pulses and geomagnetic disturbances on grid components; and • Digital twin development for hybrid microgrids with multiple generators, storage, and loads. This report indicates key areas of research and engagement and summarizes the impact of Sandia’s contributions through notable accomplishments, journal publications, patents, and technical conferences and presentations. It is provided with the hope that readers discover ways we can further team to create our modern grid and apply the outcomes of our efforts. The bulk of work described herein is funded by several offices within the U.S. Department of Energy (USDOE), including the Office of Electricity (OE); Cybersecurity, Energy Security, and Emergency Response (CESER); former offices such as the Office of Energy Efficiency and Renewable Energy (EERE), the Grid Deployment Office (GDO), the Office of Clean Energy Demonstrations (OCED), and other key programs at USDOE. As we continue to state in these annual reports, the contributors to our successes are too numerous to name here, though our team wishes to express our deep gratitude to the numerous program and project sponsors at the US Department of Energy, who often function equally as technical collaborators; our many partners in industry, academia, utilities, and other national labs; and fellow researchers and business partners at Sandia whose leadership and creativity have enabled the accomplishments described herein.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Large area planar photocathode for MCP-based photodetectors

We report on the principle, design, fabrication, and characterization of a large-area planar bialkali photocathode. Herein, sequential photocathode growth process was investigated, and the growth parameters, especially the initial antimony layer thickness, were optimized. The source arrangement and configuration were also simulated and the preferred configuration was chosen for numerical and experimental studies. Photocathode with average QE of 18% and activation area of similar to 40 square inches was experimentally demonstrated, making it a candidate for MCP-based photodetector applications. Further improvements were also discussed to enhance the uniformity and QE value of the photocathodes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

Influence of starting precursors and synthesis methods on the physiochemical properties of zirconia

Graphical abstract: Crystallite size of tetragonal phase of the zirconia samples prepared using different synthesis parameters and precursors as a function of calcination temperature. Surface area values of the zirconia samples calcined at 500 and 700 °C are in given brackets. - Highlights: • Zirconia prepared with modified sol–gel method is less stable compared with zirconia prepared by precipitation method. • Optimized synthesis conditions shifted the glow exotherm to higher temperature range indicating better thermal stability. • Tetragonal-zirconia could be synthesized in cost-effective manner using zirconium oxy-nitrate. • In our studies no co-relation between the surface area and crystallite size was observed. - Abstract: Under identical and judiciously pre-optimized synthesis conditions, the influence of different combinations of zirconium sources and/or post treatment conditions on structural properties, thermal stability, phase composition and morphology of zirconia has been investigated. High surface area tetragonal zirconia could be synthesized in a cost-effective manner from 1 M solution of zirconium oxy-nitrate at pH 11 using aqueous ammonia solution as a precipitant when calcined at 400 °C for 3 h. Irrespective of the preparation method, pH and starting precursor, zirconia samples prepared without digestion contained dominant monoclinic phase with some traces of tetragonal phase when calcined at 700 °C. Even though there is linear decrease in surface area with increase in the crystallite size for each sample as a function of calcination temperature, no co-relation between the surface area and crystallite size could be achieved. SEM images show agglomerated and irregular shape particles between 10 to 20 μm.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Artificial Intelligence for Multiphysics Nuclear Design Optimization with Additive Manufacturing

The geometric flexibility of additively manufactured metals and ceramics generates a very large and open design space that requires advanced modeling and simulation tools for physics simulations and the rigorous definition of design problems. This effort deploys artificial intelligence (AI) and machine learning (ML) algorithms to understand the design space, evaluate potential designs, and more efficiently generate optimized results. The Transformational Challenge Reactor (TCR) program is leveraging advances in several scientific areas—including materials, manufacturing, sensors and control systems, data analytics, and high-fidelity modeling and simulation—to accelerate the design, manufacturing, qualification, and deployment of advanced nuclear energy systems. Through a manufacturing-informed design approach, the TCR program seeks to integrate digital data for rapid nuclear innovation; accelerate the adoption of advances in manufacturing, materials, and computational sciences for nuclear applications; and dramatically reduce deployment costs and timelines for new nuclear reactor technologies. This report documents efforts under the TCR program to leverage advanced modeling and simulation techniques driven by AI/ML algorithms on high-performance computing (HPC) systems to yield more optimized TCR core designs. A multiphysics ML surrogate model was developed to run on the HPC architectures. The surrogate model is trained on high-fidelity simulation data of coupled neutronics and thermofluidics and is used to quickly evaluate thousands of candidate core designs in parallel, which drives the evolution of the cooling channel shapes to minimize temperature peaking and material stress. Outcomes from these activities provide design information and feedback into the core design efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Synthesis of CS/PVA Biodegradable Composite Nanofibers as a Microporous Material with Well Controllable Procedure Through Electrospinning

In this study, we have showed a facile route for fabrication of a novel microporous material based on chitosan (CS) and poly(vinyl alcohol) (PVA) biodegradable nanofibers that have high specific surface area, considerable porosity, and small diameter. Scanning electron microscopy, thermogravimetric analysis, differential scanning calorimetry, fourier transform infrared spectroscopy, Brunauer–Emmett–Teller surface area analysis, and CHNS/O elemental analyser were applied to characterize the fabricated CS/PVA composite nanofibers. Moreover, the influences of spinning conditions including concentration, voltage, electrospinning distance, and flow rate, on size distribution and pore diameter of the final product were systematically studied using 2{sup k−1} factorial design experiments, and the response surface optimization was used for determining the best synthesis parameter. The results obtained from 2{sup K−1} factorial design experiments showed that electrospinning parameters influenced the size distribution and pore diameter of the CS/PVA microporous material. Based on the response surface methodology, the CS/PVA product could be obtained with a high microporous diameter of 1.8 nm and a small diameter distribution of 15.0 nm under optimized conditions. The obtained results showed that the fabricated samples could be utilized in different applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2013

Optimization of Nano-Carbon Materials for Hydrogen Sorption

Research undertaken has added to the understanding of several critical areas, by providing both negative answers (and therefore eliminating expensive further studies of unfeasible paths) and positive feasible options for storage. Theoretical evaluation of the early hypothesis of storage on pure carbon single wall nanotubes (SWNT) has been scrutinized with the use of comprehensive computational methods (and experimental tests by the Center partners), and demonstrated that the fundamentally weak binding energy of hydrogen is not sufficiently enhanced by the SWNT curvature or even defects, which renders carbon nanotubes not practical media. More promising direction taken was towards 3-dimensional architectures of high porosity where concurrent attraction of H2 molecule to surrounding walls of nano-scale cavities can double or even triple the binding energy and therefore make hydrogen storage feasible even at ambient or somewhat lower temperatures. An efficient computational tool has been developed for the rapid capacity assessment combining (i) carbon-foam structure generation, (ii) accurate empirical force fields, with quantum corrections for the lightweight H2, and (iii) grand canonical Monte Carlo simulation. This made it possible to suggest optimal designs for carbon nanofoams, obtainable via welding techniques from SWNT or by growth on template-zeolites. As a precursor for 3D-foams, we have investigated experimentally the synthesis of VANTA (Vertically Aligned NanoTube Arrays). This can be used for producing nano-foams. On the other hand, fluorination of VANTA did not show promising increase of hydrogen sorption in several tests and may require further investigation and improvements. Another significant result of this project was in developing a fundamental understanding of the elements of hydrogen spillover mechanisms. The benefit of developed models is the ability to foresee possible directions for further improvement of the spillover mechanism.

08 HYDROGEN↗
DOE OSTI2021

Combined Land Use of Solar Infrastructure and Agriculture for Socioeconomic and Environmental Co-Benefits in the Tropics

Solar photovoltaics (PV) are on the rise even in areas of low solar insolation. However, in developing countries with limited capital, land scarcity, or with geographically isolated agrarian communities, large solar infrastructures are often impractical. In these cases, implementation of low-density PV over existing crops may be required to integrate renewable energy services into rural communities. Here, using Indonesia as a model system, we investigated the land use, energy, greenhouse gas emissions, economic feasibility, and the environmental co-benefits associated with off-grid solar PV when combined with high value crop cultivation. The life cycle analyses indicate that small-scale dual land-use systems are economically viable in certain configurations and have the potential to provide several co-benefits including rural electrification, retrofitting diesel electricity generation, and electricity for processing agricultural products locally. A hypothetical full-density off-grid solar PV for a model village in Indonesia shows that electricity output (1907.5 GJ yr-1) is much higher than the total residential consumption (678 GJ yr-1), highlighting the opportunity to downscale the PV infrastructure by half to lower capital cost, to co-locate crops, and to support secondary income generating activities. Economic analysis shows that the 30-year net present cost of electricity from the half-density co-located PV system (12,257 million IDR) is significantly lower than that of the flat cost of diesel required to generate equivalent electricity (14,702 million IDR). Our analysis provides insights for smarter energy planning by optimizing the efficiency of land use and limiting conversion of agricultural and forested areas for energy production.

agrivoltaics↗
DOE OSTI2012

Reservoir Characterization of Bridgeport and Cypress Sandstones in Lawrence Field Illinois to Improve Petroleum Recovery by Alkaline-Surfactant-Polymer Flood

Within the Illinois Basin, most of the oilfields are mature and have been extensively waterflooded with water cuts that range up to 99% in many of the larger fields. In order to maximize production of significant remaining mobile oil from these fields, new recovery techniques need to be researched and applied. The purpose of this project was to conduct reservoir characterization studies supporting Alkaline-Surfactant-Polymer Floods in two distinct sandstone reservoirs in Lawrence Field, Lawrence County, Illinois. A project using alkaline-surfactantpolymer (ASP) has been established in the century old Lawrence Field in southeastern Illinois where original oil in place (OOIP) is estimated at over a billion barrels and 400 million barrels have been recovered leaving more than 600 million barrels as an EOR target. Radial core flood analysis using core from the field demonstrated recoveries greater than 20% of OOIP. While the lab results are likely optimistic to actual field performance, the ASP tests indicate that substantial reserves could be recovered even if the field results are 5 to 10% of OOIP. Reservoir characterization is a key factor in the success of any EOR application. Reservoirs within the Illinois Basin are frequently characterized as being highly compartmentalized resulting in multiple flow unit configurations. The research conducted on Lawrence Field focused on characteristics that define reservoir compartmentalization in order to delineate preferred target areas so that the chemical flood can be designed and implemented for the greatest recovery potential. Along with traditional facies mapping, core analyses and petrographic analyses, conceptual geological models were constructed and used to develop 3D geocellular models, a valuable tool for visualizing reservoir architecture and also a prerequisite for reservoir simulation modeling. Cores were described and potential permeability barriers were correlated using geophysical logs. Petrographic analyses were used to better understand porosity and permeability trends in the region and to characterize barriers and define flow units. Diagenetic alterations that impact porosity and permeability include development of quartz overgrowths, sutured quartz grains, dissolution of feldspar grains, formation of clay mineral coatings on grains, and calcite cementation. Many of these alterations are controlled by facies. Mapping efforts identified distinct flow units in the northern part of the field showing that the Pennsylvanian Bridgeport consists of a series of thick incised channel fill sequences. The sandstones are about 75-150 feet thick and typically consist of medium grained and poorly sorted fluvial to distributary channel fill deposits at the base. The sandstones become indistinctly bedded distributary channel deposits in the main part of the reservoir before fining upwards and becoming more tidally influenced near their top. These channel deposits have core permeabilities ranging from 20 md to well over 1000 md. The tidally influenced deposits are more compartmentalized compared to the thicker and more continuous basal fluvial deposits. Fine grained sandstones that are laterally equivalent to the thicker channel type deposits have permeabilities rarely reaching above 250 md. Most of the unrecovered oil in Lawrence Field is contained in Pennsylvanian Age Bridgeport sandstones and Mississippian Age Cypress sandstones. These reservoirs are highly complex and compartmentalized. Detailed reservoir characterization including the development of 3-D geologic and geocellular models of target areas in the field were completed to identify areas with the best potential to recover remaining reserves including unswept and by-passed oil. This project consisted of tasks designed to compile, interpret, and analyze the data required to conduct reservoir characterization for the Bridgeport and Cypress sandstones in pilot areas in anticipation of expanded implementation of ASP flooding in Lawrence Field. Geologic and geocellular modeling needed for reservoir characterization and reservoir simulation were completed as prerequisites for design of efficient ASP flood patterns. Characterizing the complex reservoir geology that identifies the geologic conditions that will optimize oil recoveries for expansion of the ASP pilots in the Bridgeport and Cypress sandstones to other areas of Lawrence Field is the primary objective of this project. It will permit evaluation of efficiency of oil recovery from Bridgeport and Cypress sandstone reservoirs using ASP technology. Additionally evaluation of similar Pennsylvanian and Chesterian reservoirs shows that it is likely that ASP flood technology can be successfully applied to similar reservoirs in the Illinois Basin as well as to other U.S. reservoirs. Chemical flooding was introduced in stages with the first flood initiated in 2010 and a second offset pilot project initiated during 2011. Rex Energy Corporation is reporting a positive response on its ASP Middagh pilot project in the Pennsylvanian Bridgeport B reservoir, Lawrence Field. Oil response in the 15 acre flood has continued to show an increase in oil cut from 1% to 12%. Total pattern production increased from 16 BOPD and stabilized at a range of 65-75 BOPD in the last three months of 2011. Peak production rose to 100 + BOPD. Oil cut in the pilot increased for 1.0% to ~ 12.0% with an individual well showing oil cuts greater than 20%. A second, 58 acre pilot (Perkins-Smith) adjacent to and likely in communication with the Middagh pilot has been initiated. Preliminary brine injection has been implemented and ASP injection was initiated in mid-2012. Response is expected by mid-2013 with peak recovery expected by late 2013. Rex Energy is projecting full scale expansion with the next step of development being a 351 acre project scheduled to begin in mid-2013. Preliminary development has been initiated in this Delta Unit area located in the south half of section 32, T4N, R12W.

02 PETROLEUM↗