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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Performance of an Isobaric Hybrid Compressed Air Energy Storage System at Minimum Entropy Generation

Efficient, large-scale, and cost-effective energy storage systems provide a means of managing the inherent intermittency of renewable energy sources and drastically increasing their utilization. Compressed air energy storage (CAES) and its derivative architectures have received much attention as a viable solution; however, optimization objectives for these systems have not been thoroughly investigated in the literature. In this work, a hybrid thermal and compressed air energy storage (HT-CAES) system is investigated that mitigates the shortcomings of the otherwise attractive conventional CAES systems and its derivatives—shortcomings such as strict geological locations, low energy densities, and the production of greenhouse gas emissions. The HT-CAES system allows a portion of the available energy to operate a compressor and the remainder to be converted and stored in the form of heat through joule/resistive heating in a high-temperature, sensible, thermal energy storage medium. Internally reversible and irreversible HT-CAES system assumptions were investigated, in addition to regenerative and non-regenerative design configurations. Several system optimization criteria were examined—including maximum energy efficiency, maximum exergy efficiency, maximum work output, and minimum entropy generation—with a focus on whether the latter may lead to conclusive design guidelines in a real system. It is shown that an HT-CAES system designed based on a minimum entropy generation objective may operate at a lower energy and exergy efficiency as well as lower output power than otherwise achievable. Furthermore, optimization objective equivalence is shown to be limited to certain design conditions.

25 ENERGY STORAGE↗
DOE OSTI2018

Thermodynamic performance and cost optimization of a novel hybrid thermal-compressed air energy storage system design

Compressed Air Energy Storage (CAES) can potentially allow renewable energy sources to meet electricity demands as reliably as coal-fired power plants. However, conventional CAES systems rely on the combustion of natural gas, require large storage volumes, and operate at high pressures, which possess inherent problems such as high costs, strict geological locations, and the production of greenhouse gas emissions. A novel and patented hybrid thermal-compressed air energy storage (HT-CAES) design is presented which allows a portion of the available energy, from the grid or renewable sources, to operate a compressor and the remainder to be converted and stored in the form of heat, through joule heating in a sensible thermal storage medium. The HT-CAES design incudes a turbocharger unit that provides supplementary mass flow rate alongside the air storage. The hybrid design and the addition of a turbocharger have the beneficial effect of mitigating the shortcomings of conventional CAES systems and its derivatives by eliminating combustion emissions and reducing storage volumes, operating pressures, and costs. Storage efficiency and cost are the two key factors, which upon integration with renewable energies would allow the sources to operate as independent forms of sustainable energy. The potential of the HT-CAES design is illustrated through a thermodynamic optimization study, which outlines key variables that have a major impact on the performance and economics of the storage system. The optimization analysis quantifies the required distribution of energy between thermal and compressed air energy storage, for maximum efficiency, and for minimum cost. This study provides a roundtrip energy and exergy efficiency map of the storage system and illustrates a trade off that exists between its capital cost and performance.

25 ENERGY STORAGE↗
DOE OSTI2018

Theoretical Performance Limits of an Isobaric Hybrid Compressed Air Energy Storage System

Furthermore, the desire to increase power production through renewable sources introduces a number of problems due to their inherent intermittency. One solution is to incorporate energy storage systems as a means of managing the intermittent energy and increasing the utilization of renewable sources. A novel hybrid thermal and compressed air energy storage (HT-CAES) system is presented which mitigates the shortcomings of the otherwise attractive conventional compressed air energy storage (CAES) systems and its derivatives, such as strict geological locations, low energy density, and the production of greenhouse gas emissions. The HT-CAES system is investigated, and the thermodynamic efficiency limits within which it operates have been drawn. The thermodynamic models considered assume a constant pressure cavern. It is shown that under this assumption the cavern acts just as a delay time in the operation of the plant, whereas an adiabatic constant volume cavern changes the quality of energy through the cavern. The efficiency of the HT-CAES system is compared with its Brayton cycle counterpart, in the case of pure thermal energy storage (TES). It is shown that the efficiency of the HT-CAES plant is generally not bound by the Carnot efficiency and always higher than that of the Brayton cycle, except for when the heat losses following compression rise above a critical level. The results of this paper demonstrate that the HT-CAES system has the potential of increasing the efficiency of a pure TES system executed through a Brayton cycle at the expense of an air storage medium.

25 ENERGY STORAGE↗
DOE OSTI2015

Geothermally Coupled Well-Based Compressed Air Energy Storage

Previous work by McGrail et al. (2013, 2015) has evaluated the possibility of pairing compressed air energy storage with geothermal resources in lieu of a fossil-fired power generation component, and suggests that such applications may be cost competitive where geology is favorable to siting both the geothermal and CAES components of such a system. Those studies also note that the collocation of subsurface resources that meet both sets of requirements are difficult to find in areas that also offer infrastructure and near- to mid-term market demand for energy storage. This study examines a novel application for the compressed air storage portion of the project by evaluating the potential to store compressed air in disused wells by amending well casings to serve as subsurface pressure vessels. Because the wells themselves would function in lieu of a geologic storage reservoir for the CAES element of the project, siting could focus on locations with suitable geothermal resources, as long as there was also existing wellfield infrastructure that could be repurposed for air storage. Existing wellfields abound in the United States, and with current low energy prices, many recently productive fields are now shut in. Should energy prices remain stagnant, these idle fields will be prime candidates for decommissioning unless they can be transitioned to other uses, such as redevelopment for energy storage. In addition to the nation’s ubiquitous oil and gas fields, geothermal fields, because of their phased production lifetimes, also may offer many abandoned wellbores that could be used for other purposes, often near currently productive geothermal resources. These existing fields offer an opportunity to decrease exploration and development uncertainty by leveraging data developed during prior field characterization, drilling, and production. They may also offer lower-cost deployment options for hybrid geothermal systems via redevelopment of existing well-field infrastructure. This project assessed the technical and economic feasibility of implementing geothermally coupled well-based CAES for grid-scale energy storage. Based on an evaluation of design specifications for a range of casing grades common in U.S. oil and gas fields, a 5-MW CAES project could be supported by twenty to twenty-five 5,000-foot, 7-inch wells using lower-grade casing, and as few as eight such wells for higher-end casing grades. Using this information, along with data on geothermal resources, well density, and potential future markets for energy storage systems, The Geysers geothermal field was selected to parameterize a case study to evaluate the potential match between the proven geothermal resource present at The Geysers and the field’s existing well infrastructure. Based on calculated wellbore compressed air mass, the study shows that a single average geothermal production well could provide enough geothermal energy to support a 15.4-MW (gross) power generation facility using 34 to 35 geothermal wells repurposed for compressed air storage, resulting in a simplified levelized cost of electricity (sLCOE) estimated at 11.2 ¢/kWh (Table S.1). Accounting for the power loss to the geothermal power project associated with diverting geothermal resources for air heating results in a net 2-MW decrease in generation capacity, increasing the CAES project’s sLCOE by 1.8 ¢/kWh.

25 ENERGY STORAGE↗
DOE OSTI2021

Hybrid simulations of sub-cyclotron compressional and global Alfvén eigenmode stability in spherical tokamaks

A comprehensive numerical study has been conducted in order to investigate the stability of beam-driven, sub-cyclotron-frequency compressional Alfvén eigenmodes (CAEs) and global Alfvén eigenmodes (GAEs) in low-aspect-ratio plasmas for a wide range of beam parameters. The presence of CAEs and GAEs has previously been linked to anomalous electron temperature profile flattening at high beam powers in NSTX experiments, prompting a further examination of the conditions necessary for their excitation. Linear simulations have been performed with the hybrid MHD–kinetic initial value code HYM in order to capture the general Doppler-shifted cyclotron resonance that drives the modes. Additionally, three distinct types of modes were found in the simulations—co-CAEs, cntr-GAEs, and co-GAEs—with differing spectral and stability properties. The simulations revealed that unstable GAEs are more ubiquitous than unstable CAEs, which is consistent with experimental observations, as they are excited at lower beam energies and generally have larger growth rates. Local analytic theory is used to explain key features of the simulation results, including the preferential excitation of different modes based on beam injection geometry and the growth rate dependence on the beam injection velocity, critical velocity, and degree of velocity space anisotropy. The background damping rate is inferred from the simulations and analytically estimated for relevant sources absent from the simulation model, indicating that co-CAEs are closer to marginal stability than modes driven by the cyclotron resonances.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Hybrid simulations of sub-cyclotron compressional and global Alfven Eigenmode stability in spherical tokamaks

A comprehensive numerical study has been conducted in order to investigate the stability of beam-driven, sub-cyclotron frequency compressional (CAE) and global (GAE) Alfven Eigenmodes in low aspect ratio plasmas for a wide range of beam parameters. The presence of CAEs and GAEs has previously been linked to anomalous electron temperature profile flattening at high beam power in NSTX experiments, prompting further examination of the conditions for their excitation. Linear simulations are performed with the hybrid MHD-kinetic initial value code HYM in order to capture the general Doppler-shifted cyclotron resonance that drives the modes. Three distinct types of modes are found in simulations -- co-CAEs, cntr-GAEs, and co-GAEs -- with differing spectral and stability properties. The simulations reveal that unstable GAEs are more ubiquitous than unstable CAEs, consistent with experimental observations, as they are excited at lower beam energies and generally have larger growth rates. Local analytic theory is used to explain key features of the simulation results, including the preferential excitation of different modes based on beam injection geometry and the growth rate dependence on the beam injection velocity, critical velocity, and degree of velocity space anisotropy. The background damping rate is inferred from simulations and estimated analytically for relevant sources not present in the simulation model, indicating that co-CAEs are closer to marginal stability than modes driven by the cyclotron resonances.

Compressional Alfven Eigenmodes↗
DOE OSTI2015

Geothermally Coupled Well-Based Compressed Air Energy Storage

Previous work by McGrail et al. (2013, 2015) has evaluated the possibility of pairing compressed air energy storage with geothermal resources in lieu of a fossil-fired power generation component, and suggests that such applications may be cost competitive where geology is favorable to siting both the geothermal and CAES components of such a system. Those studies also note that the collocation of subsurface resources that meet both sets of requirements are difficult to find in areas that also offer infrastructure and near- to mid-term market demand for energy storage. This study examines a novel application for the compressed air storage portion of the project by evaluating the potential to store compressed air in disused wells by amending well casings to serve as subsurface pressure vessels. Because the wells themselves would function in lieu of a geologic storage reservoir for the CAES element of the project, siting could focus on locations with suitable geothermal resources, as long as there was also existing wellfield infrastructure that could be repurposed for air storage. Existing wellfields abound in the United States, and with current low energy prices, many recently productive fields are now shut in. Should energy prices remain stagnant, these idle fields will be prime candidates for decommissioning unless they can be transitioned to other uses, such as redevelopment for energy storage. In addition to the nation’s ubiquitous oil and gas fields, geothermal fields, because of their phased production lifetimes, also may offer many abandoned wellbores that could be used for other purposes, often near currently productive geothermal resources. These existing fields offer an opportunity to decrease exploration and development uncertainty by leveraging data developed during prior field characterization, drilling, and production. They may also offer lower-cost deployment options for hybrid geothermal systems via redevelopment of existing well-field infrastructure. This project assessed the technical and economic feasibility of implementing geothermally coupled well-based CAES for grid-scale energy storage. Based on an evaluation of design specifications for a range of casing grades common in U.S. oil and gas fields, a 5-MW CAES project could be supported by twenty to twenty-five 5,000-foot, 7-inch wells using lower-grade casing, and as few as eight such wells for higher-end casing grades. Using this information, along with data on geothermal resources, well density, and potential future markets for energy storage systems, The Geysers geothermal field was selected to parameterize a case study to evaluate the potential match between the proven geothermal resource present at The Geysers and the field’s existing well infrastructure. Based on calculated wellbore compressed air mass, the study shows that a single average geothermal production well could provide enough geothermal energy to support a 15.4-MW (gross) power generation facility using 34 to 35 geothermal wells repurposed for compressed air storage, resulting in a simplified levelized cost of electricity (sLCOE) estimated at 11.2 ¢/kWh (Table S.1). Accounting for the power loss to the geothermal power project associated with diverting geothermal resources for air heating results in a net 2-MW decrease in generation capacity, increasing the CAES project’s sLCOE by 1.8 ¢/kWh.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Final TCF Report for Earth Battery: Storing Energy with Compressed Air and Heated Brine in Porous Rock

Cost-effective reductions in greenhouse gas (GHG) emissions are best achieved when all low-carbon energy resources are fully utilized. This includes base-load power: nuclear energy (NE) and fossil energy (FE), integrated with CO 2 capture, use, and storage (CCUS), and variable renewable energy (VRE) (wind and solar); but, current CCUS options don’t justify CO 2 -capture costs and existing energy-storage approaches lack the capacity and storage duration needed to fully utilize all forms of low-carbon energy without curtailment. The Earth Battery is designed to meet these challenges by synergistically integrating conventional- and renewable-energy resources, allowing each to contribute more efficiently to the grid than if operated independently. The Earth Battery stores energy underground as pressure and heat, using compressed air and/or CO 2 , together with heated brine. These fluids are stored in either saline aquifers used for CO 2 or natural gas (NG) storage or in oil and gas reservoirs, making deployment possible over much of the U.S. We can provide enormous energy-storage capacity and duration. The main goal of this study was to assess the techno-economic feasibility of the versions of the Earth Battery that use compressed air energy storage (CAES). Current CAES systems use NG turbines and store air in salt caverns, which limits geographic deployment. Conventional CAES wastes much of the heat of air compression, comprising half of the compression energy. Our technology addresses these deficiencies by using permeable sedimentary rock to store air and the heat of compression as heated brine. When electricity is needed, air and hot brine are produced, with hot brine used to pre-heat air before it is fed into the expanders. Key factors affecting round-trip efficiency are (1) pressure loss in the air-storage reservoir, which depends on permeability (> 100 mD being needed for efficient operations) and (2) temperature loss in the hot-brine storage reservoir, which decreases with time as the storage formation heats up. The original scope of this project was to conduct a techno-economic assessment of diurnal storage with the CAES Earth Battery, including (1) Adiabatic CAES, which requires no fossil fuel and (2) NG/CAES, where one or more of the expansion stages are NG fueled. During its assessment, we found NG/CAES, generates excess heat of compression that can be put into long-term (seasonal) storage and be utilized in a combined-cycle fashion with the addition of steam turbines. This resulted in our developing a new Earth Battery technology, which we call the Thermal Earth Battery. We conducted energy-system analyses for the Thermal Earth Battery for various combinations of heat sources: (1) heat of FE combustion, (2) excess heat of compression from NG/CAES, and (3) solar thermal energy (STE). The other Earth Battery class we developed compresses CO 2 , rather than air; hence, it is called Compressed CO 2 Energy Storage (CCES). Finally, we developed an improved, more efficient, more versatile version of the Allam cycle, which uses pressurized CO 2 , and developed various options for integrating renewable energy and energy storage. Our improved Allam-cycle technology minimizes cooling-water consumption, while enabling reliable, dispatchable renewable energy. Although not anticipated in our original scope of work, our Topic 1 project evolved into a highly productive discovery process wherein we developed a portfolio of Earth Battery configuration options and use cases. Our ultimate objective was to evaluate those options and use cases and determine the most optimal first best use options for our Earth Battery technology. That process resulted in identifying seasonal energy storage as a niche where no other energy storage technology could compete with us. As a result, we have identified the Thermal Earth Battery, which uses conventional steam-turbine components, and our improved Allam-cycle integrated with renewable energy and energy storage as the most promising technologies to commercialize in our Topic 2 proposal. Finally, our scope included finding a commercialization team for a Topic 2 continuation of this project, which we have successfully completed.

25 ENERGY STORAGE↗
NASA NTRS1994

Analytical Design Package (ADP2): A computer aided engineering tool for aircraft transparency design

The Analytical Design Package (ADP2) is being developed as a part of the Air Force Frameless Transparency Program (FTP). ADP2 is an integrated design tool consisting of existing analysis codes and Computer Aided Engineering (CAE) software. The objective of the ADP2 is to develop and confirm an integrated design methodology for frameless transparencies, related aircraft interfaces, and their corresponding tooling. The application of this methodology will generate high confidence for achieving a qualified part prior to mold fabrication. ADP2 is a customized integration of analysis codes, CAE software, and material databases. The primary CAE integration tool for the ADP2 is P3/PATRAN, a commercial-off-the-shelf (COTS) software tool. The open architecture of P3/PATRAN allows customized installations with different applications modules for specific site requirements. Integration of material databases allows the engineer to select a material, and those material properties are automatically called into the relevant analysis code. The ADP2 materials database will be composed of four independent schemas: CAE Design, Processing, Testing, and Logistics Support. The design of ADP2 places major emphasis on the seamless integration of CAE and analysis modules with a single intuitive graphical interface. This tool is being designed to serve and be used by an entire project team, i.e., analysts, designers, materials experts, and managers. The final version of the software will be delivered to the Air Force in Jan. 1994. The Analytical Design Package (ADP2) will then be ready for transfer to industry. The package will be capable of a wide range of design and manufacturing applications.

Wuerer, J. E.↗
NASA NTRS2024

Sensor Fault Detection in Smart Extraterrestrial Habitats Using Unsupervised Learning

Various types of sensors are needed to monitor the health state of smart deep-space habitats. However, measured data can be affected by sensor faults, which influence the health management system and consequently the decision-making. In this paper, an unsupervised learning approach based on convolutional autoencoders (CAEs) is developed to detect anomalies in temperature and pressure sensors. The proposed method is systematically investigated using a habitat simulator (HabSim). Several illustrative examples are demonstrated in the nominal and hazardous states of the habitat, including micrometeorite impact and fire scenarios. The performance of the proposed method using CAEs is compared with that of existing methods using auto-associative neural networks (AANNs) and variational autoencoders. This comparison is based on typical evaluation metrics, including precision, recall, F1 score, training time, and testing time. The effect of temperature–pressure coupling on the detection performance of CAEs and AANNs is explored by training different data-driven models, including one with temperature sensors, one with pressure sensors, and one with both temperature and pressure sensors. The effect of the number of faulty sensors on the performance of CAEs is studied, as with an increase in the number of faulty sensors, redundant information among the sensors is reduced. The capability of CAEs to change the number of sensors without redesigning the network architecture and retraining the neural network is investigated and demonstrated. The capabilities and limitations of the proposed solution are discussed.

Zixin Wang↗
DOE OSTI2025

Techno-Economic Analysis of Compressed Air Energy Storage and Hydrogen Production from Variable Renewable Energy

This study presents the techno-economic analysis (TEA) results of integrating electrolysis hydrogen (H 2 ) production, compressed air energy storage (CAES), and H 2 -fired combustion turbines in a high variable renewable energy (VRE) market environment. The inconsistent nature of VRE creates challenges for power producers in maintaining a stable electrical grid as it is increasingly utilized. The mission of the National Energy Technology Laboratory (NETL) is driving innovation and delivering energy solutions, and a multiangle approach involving H 2 production, energy storage, and next-level H 2 -fired combustion turbine generator (CTG) technologies could provide one solution for the nation’s growing electrical grid issues with increasing VRE sources. The H 2 production and CAES concept were investigated due to its ability to provide utility-scale H 2 -fueled power generation with large-scale energy storage capabilities. Two facilities with CAES and natural gas-fired CTGs (in McIntosh, Alabama, and Huntorf, Germany) have been operating for decades. In contrast, this study investigates the potential to replace the natural gas fuel with H 2 fuel. This concept has been publicly presented by both Siemens Energy and Bechtel Global Engineering, Construction & Project Management (Bechtel) at two different power generating levels. The CAES and air expansion/combustion turbine power generation in this study are primarily based on the Siemens Energy system (Bailie, Aug. 10-11, 2021) (Scheller, Feb. 21, 2023). The inclusion of a H 2 turboexpander generator is from Bechtel (Gülen, Sep. 6, 2022). A block flow diagram of the proposed process is illustrated in Exhibit ES-1.

08 HYDROGEN↗
DOE OSTI2017

Numerical investigation of a joint approach to thermal energy storage and compressed air energy storage in aquifers

Different from conventional compressed air energy storage (CAES) systems, the advanced adiabatic compressed air energy storage (AA-CAES) system can store the compression heat which can be used to reheat air during the electricity generation stage. Thus, AA-CAES system can achieve a higher energy storage efficiency. Similar to the AA-CAES system, a compressed air energy storage in aquifers (CAESA) system, which is integrated with an aquifer thermal energy storage (ATES) could possibly achieve the same objective. In order to investigate the impact of ATES on the performance of CAESA, different injection air temperature schemes are designed and analyzed by using numerical simulations. Key parameters relative to energy recovery efficiencies of the different injection schemes, such as pressure distribution and temperature variation within the aquifers as well as energy flow rate in the injection well, are also investigated in this study. The simulations show that, although different injection schemes have a similar overall energy recovery efficiency (~97%) as well as a thermal energy recovery efficiency (~79.2%), the higher injection air temperature has a higher energy storage capability. Our results show the total energy storage for the injection air temperature at 80 °C is about 10% greater than the base model scheme at 40 °C. Sensitivity analysis reveal that permeability of the reservoir boundary could have significant impact on the system performance. However, other hydrodynamic and thermodynamic properties, such as the storage reservoir permeability, thermal conductivity, rock grain specific heat and rock grain density, have little impact on storage capability and the energy flow rate. Our study suggests that the combination of ATES and CAESA can help keep the high efficiency of energy storage so as to make CAESA system more efficiency.

25 ENERGY STORAGE↗
DOE OSTI2021

De-noising drift chambers in CLAS12 using convolutional auto encoders

Modern Nuclear Physics experimental setups run experiments with higher beam intensity resulting in increased noise in detector components used for particle track reconstruction. Increased uncorrelated signals (noise) result in decreased particle reconstruction efficiency. In this paper, we investigate the usage of Machine Learning, specifically Convolutional Neural Network Auto-Encoders (CAE), for de-noising raw hits from drift chambers in the CLAS12 detector. To the best of our knowledge, this is the first time CAE is employed to perform such an operation in this field. During the de-noising phase, it is important to remove as much noise as possible while retaining the valid hits to avoid losing crucial information about the experiment. Here, we show that using CAE, it is possible to remove noise hits while retaining up to 94% of valid tracks for a beam current of 110nA while for lower beam currents (45-55nA), we get up to 98% efficiency. Studies on experimental conditions with increasing noise show that CAE performs better than conventional tracking algorithms in isolating hits belonging to tracks. Specifically, the de-noising algorithm results in tracking efficiency improvements greater than 15%, in real data production procedures with nominal conditions, and up to two times better efficiency in synthetically generated data with high luminosity conditions (90-110nA), indicating that machine learning can lead to significantly shorter times for conducting physics experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Efficacy of Midazolam and Ketamine Combination Therapy over Midazolam Monotherapy against Soman Exposure in Carboxylesterase Knockout Mice

Introduction Chemical warfare nerve agents (CWNAs) inhibit acetylcholinesterase (AChE), which leads to status epilepticus (SE), spontaneous recurrent seizures (SRS) and severe neuropathology when treatment is delayed. In addition to binding to AChE, some organophosphorus (OP) CWNAs such as soman (GD) also inhibit carboxylesterase (CaE), which acts as a bioscavenger and can thus reduce the severity of the toxicity of OP agent exposure. Unlike humans, rodents have plasma CaE activity. The CaE knockout (ES1−/−) mouse specifically lacks plasma CaE and might better model human GD exposure compared to wildtype rodents. Delayed treatment of CWNA‐induced SE with midazolam leads to benzodiazepine‐refractory SE. We evaluated combination therapy of midazolam and the NMDA antagonist ketamine in male and female mice for efficacy against soman‐induced lethality, SE and epileptogenesis. Methods Mice implanted with telemetry transmitters for electroencephalography (EEG) seizure identification were exposed to 82 μg/kg GD (~4LD 50 ) and treated with an admix (ip) of atropine sulfate (4 mg/kg) and HI‐6 (50 mg/kg) 1 min after exposure, and with midazolam (3 mg/kg; ip) alone or in combination with ketamine (30 mg/kg, ip) at 40 min after seizure onset. Mice were continuously recorded to evaluate initial seizure duration and SRS and then euthanized 2 weeks after exposure for neuropathology assessment. Results Delayed treatment with midazolam resulted in poor survival, was unable to rapidly terminate behavioral or EEG seizure activity and did not prevent the development of SRS or neuronal loss following GD exposure. Combination therapy of midazolam and ketamine resulted in improved outcome, including an increase in survival from 30% to 78% in female and from 57% to 77% in males compared to midazolam monotherapy. In addition, the incidence of epileptogenesis was lower in mice treated with ketamine and midazolam dual therapy compared to midazolam monotherapy. Conclusions This study demonstrates that delayed treatment of SE with midazolam is not fully protective against the GD‐induced epileptogenesis and neuropathology, exemplifying the need for adjunct treatment to midazolam to prevent or reduce effects of GD‐induced SE. Ketamine combination with midazolam improves outcome. Support or Funding Information Research was supported by the CounterACT Program, NIH OD, and the NINDS (Grant 1R21NS103820‐01 to LA Lumley‐Lange) and by DTRA‐JSTO. Erica Kundrick, Katie Walker, and Sean O'Brien were supported in part by an appointment to the Research Participation Program for the U.S. Army Medical Research and Materiel Command administered by the Oak Ridge Institute for Science and Education through an agreement between the U.S. Department of Energy and U.S. Army Medical Research and Materiel Command. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Marrero‐Rosado, Brenda↗
DOE OSTI2022

Illinois Compressed Air Energy Storage

Compressed Air Storage Energy (CAES) is one of the few mid- technology readiness level (TRL) energy storage technologies that can address the long-duration infrastructure needed for dealing with variable electric output from renewable energy sources and be reliable backup source for replacing natural gas during supply interruptions. In CAES the goal is to capture and store compressed air in subsurface sedimentary strata when off-peak power is available, or there is a need for grid balancing. The stored high-pressure air is returned to the surface and used to power turbines during reductions in either renewable energy or supply issues with fossil fuels. The Illinois CAES project evaluates the feasibility of capturing surplus electrical energy from renewable sources and off-peak energy at a fossil fuel power plant at the University of Illinois Urbana - Champaign (UIUC) campus. The UIUC Abbott Power Plant uses natural gas and coal to generate electricity (capacity: 35 MWe by coal and 49 MWe by NG). UIUC receives additional electricity from on campus solar farm, and off-campus wind farm. Also, UIUC offsets electricity usage by integrating geothermal energy systems into building heating Also, UIUC offsets steam, hot and chilled water usage by integrating geothermal energy systems into building heating and cooling systems. Furthermore, the two UIUC solar farms (Solar Farm 1 is 21 acres and Solar Farm 2 is 54 acres) to generate 4.68 megawatts (MW) and 12.1 MW, respectively. Campus receives 8.6% of the wind-generated electricity from the Rail Splitter Wind Farm. The project objectives were to design an integrated system to 1) capture surplus electrical energy from renewable sources and the Abbott Power Plant using a CAES system, 2) store both the compressed air and the thermal heat generated by compression in the subsurface as part of an adiabatic system, 3) simulate the movement of the air and heat in the subsurface, 4) recover the compressed air and stored thermal heat to rotate turbine generators during sustained interruption due to weather events or fossil fuel disruptions.

03 NATURAL GAS↗
DOE OSTI2022

Benchmark Exercise for the Control Rod Swelling Evaluation

The VTR core has six reactivity control assemblies and three safety assemblies. The control assemblies or primary control rods are adjusted during the normal operation to balance the core reactivity and to control the reactor power. A typical control assembly radial layout is presented in Figure 1. The figure shows the swelled absorber (B 4 C) rod. Initially, helium gas fills the gap between the pin and the cladding before irradiation swelling takes place. For VTR, HT9 steel was selected as the cladding and duct material. The main neutron absorbing material used in the VTR is B 4 C. When residing in the core, the neutronics, thermophysical, and mechanical properties of the materials used in a control assembly will degrade due to accumulated neutron damage. Material degradation limits how long a control assembly can reside in the core. Many phenomena affect the control assembly lifetime, such as the loss of reactivity worth due to B 4 C depletion, the mechanical interaction of the absorber rod and the cladding due to B 4 C swelling, the helium gas buildup in the pin due to B-10 capture, etc. B 4 C swelling, which causes closure of the gap between the absorber rod and the cladding, is usually considered as the main limiting factor from past experience. An initial study was conducted at PNNL to evaluate the irradiation behavior of a VTR control assembly. The evaluation was performed using the CNRD2 code that was initially developed for the FFTF. The study also included an assessment of the VTR control assembly and focused on a 61-pin control assembly design, which is different from that used (37-pin design) in the core design study. The study conducted by PNNL was reviewed independently by ANL. A Python script referred to as the Control Assembly Evaluation Script (CAES) was developed for the independent review and additional assessment of 37-pin control assembly design. The script has focused on the assessment of the absorber rod swelling for its importance in determining the control assembly lifetime. CAES uses geometry, neutronics, materials data as input to predict the swelling of the absorber rod during its residence in the reactor core. The results from CAES showed some non-negligible differences against the PNNL results. Some of the differences can be attributed to the different interpretation of the control rod assembly dimensions. To resolve this issue, a benchmark exercise was proposed. The benchmark specification was developed by PNNL. The benchmark exercise was performed independently at PNNL and ANL using different codes/scripts (CRND2 and CAES). This memo documents the results calculated using the different codes. However, this report is limited to presenting the results obtained. Further investigation of the cause of the observed difference will be performed as part of future activities, pending continuation of the VTR program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Techno-Economic Analysis of a Thermally Integrated Solid Oxide Fuel Cell and Compressed Air Energy Storage Hybrid System

Natural-gas-fueled solid oxide fuel cell (SOFC) systems have the potential for high-efficiency conversion of carbon to power due to the underlying electrochemical conversion process while readily facilitating carbon capture through the separation of the fuel and oxidant sources. Compressed air energy storage (CAES) technology can potentially store significant quantities of energy for later use with a high round-trip efficiency and lower cost when compared with state-of-the-art battery technology. The base load generation capability of SOFC can be coupled with CAES technology to provide a potentially flexible, low-carbon solution to meet the fluctuating electricity demands imposed by the increasing share of intermittent variable renewable energy (VRE) production. SOFC and CAES can be hybridized through thermal integration to maximize power output during periods of high electrical demand and then store power when either demand is low or renewable generation reduces power prices. The techno-economics of a low-carbon hybrid SOFC and CAES system was developed and investigated in the present study. The proposed hybrid system was found to be cost-competitive with other power-generating base-load facilities when power availability was considered. The hybrid system shows increased resilience to changes in a high VRE grid market scenario.

25 ENERGY STORAGE↗
DOE OSTI2022

A comparison of neural network architectures for data-driven reduced-order modeling

The popularity of deep convolutional autoencoders (CAEs) has engendered new and effective reduced-order models (ROMs) for the simulation of large-scale dynamical systems. Despite this, it is still unknown whether deep CAEs provide superior performance over established linear techniques or other network-based methods in all modeling scenarios. To elucidate this, the effect of autoencoder architecture on its associated ROM is studied through the comparison of deep CAEs against two alternatives: a simple fully connected autoencoder, and a novel graph convolutional autoencoder. Through benchmark experiments, it is shown that the superior autoencoder architecture for a given ROM application is highly dependent on the size of the latent space and the structure of the snapshot data, with the proposed architecture demonstrating benefits on data with irregular connectivity when the latent space is sufficiently large.

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