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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Grassland-to-cropland conversion increased soil, nutrient, and carbon losses in the US Midwest between 2008 and 2016

After decades of declining cropland area, the United States (US) experienced a reversal in land use/land cover change in recent years, with substantial grassland conversion to cropland in the US Midwest. Although previous studies estimated soil carbon (C) loss due to cropland expansion, other important environmental indicators, such as soil erosion and nutrient loss, remain largely unquantified. In this study, we simulated the environmental impacts from the conversion of grassland to corn and soybeans for 12 US Midwestern states using the EPIC (Environmental Policy Integrated Climate) model. Between 2008 and 2016, over 2 Mha of grassland were converted to crop production in these states, with much less cropland concomitantly abandoned or retired from production. The net grassland-cropland conversion increased annual soil erosion by 7.9%, nitrogen (N) loss by 3.7%, and soil organic carbon loss by 5.6% relative to that of existing cropland, despite an associated increase in cropland area of only 2.5%. Notably, the above estimates represent the scenario of converting unmanaged grassland to tilled corn and soybeans, and impacts varied depending upon crop type and tillage regime. Corn and soybeans are dominant biofuel feedstocks, yet the grassland conversion and subsequent environmental impacts simulated in this study are likely not attributable solely to biofuel-driven land use change since other factors also contribute to corn and soybean prices and land use decisions. Nevertheless, our results suggest grassland conversion in the Upper Midwest has resulted in substantial degradation of soil quality, with implications for air and water quality as well. Additional conservation measures are likely necessary to counterbalance the impacts, particularly in areas with high rates of grassland conversion (e.g. the Dakotas, southern Iowa).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Recent Code Developments/Improvements to SAM Multi-dimensional Flow Model

The System Analysis Module (SAM) is under development at Argonne National Laboratory as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. In addition to its conventional one-dimensional flow network module, the multi-dimensional flow model of SAM offers significant benefits to its end-users, including the U.S. NRC, who uses it to develop reference models for advanced reactor concepts. This report provides a summary of the recent progress achieved under DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program in the continuous code development and improvements of the SAM code, specifically its multi-dimensional flow model. The improvements include enhancements to the physical model, code usability, addressing user feedback, and compliance with the SQA program standards that aim to enhance and maintain the quality of the software.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Agro-IBIS/THMB Modeled Yield, Nitrogen Loss, and Profitability Maps for the Raccoon River Basin, Iowa, USA

This data was used to assess the potential for improving water quality in this watershed when integrating miscanthus, a bioenergy perennial grass, on to areas of low profit under current corn-soybean management and areas of high nitrogen leaching under both current and future climate conditions. This dataset includes all observations (yield, streamflow, nitrogen loads) and model simulation data used from Dr. Kelsie Ferin’s (former PhD student with Dr. Andy VanLoocke, ISU Dept. of Agronomy) dissertation and publication in Global Change Biology – Bioenergy (DOI: 10.1111/gcbb.13078). Modeled output included in this dataset includes corn, soybean, and miscanthus yields, nitrogen leaching rates, net mineralization rates, land use cover fractions with and without the inclusion of miscanthus, profitability maps, additional soil property maps, and simulated streamflow and nitrogen loads near the outlet of the Raccoon River Basin (Van Meter, Iowa) for both historical and future climate conditions. This dataset includes a mixture of netCDF, .tiff, .csv, and .xlsx files. See README.pdf for more information.

Ferin, Kelsie↗
DOE OSTI2023

Impact of Flow Configurations on Response Time and Data Quality in Real-Time, In-Line Fourier Transform Infrared (FTIR) Monitoring of Viscous Flows

The real-time, in-line monitoring of continuous flow concentrations is widely conducted via infrared (IR) spectrometry by using a flow cell connected to a reactive flow stream. For protective purposes, the IR sensor tip is typically offset from the flow. This offset can cause the formation of a stagnant boundary layer above the sensor, especially when dealing with high-viscosity fluids. As a result, the IR signal response time is often controlled by the slow diffusional exchange of fluid in the boundary layer, as confirmed via 2D computational fluid dynamics (CFD) simulations. We evaluated several flow configuration modifications in a typical IR flow cell in order to identify the changes to the flow dynamics that enable improved response times with minimal changes to the cell configuration: the use of (i) vertical flow, where the standard horizontal flow over the sensor is redirected to contact vertically with the sensor, (ii) a static mixer to create radial flow momentum above the IR sensor, and (iii) horizontal or vertical nozzles to direct the flow toward the IR sensor. The vertical flow configuration did not show any significant improvement over the standard horizontal flow configuration. However, the static mixer, horizontal nozzle, and vertical nozzle configurations all resulted in markedly improved response times and signal quality, albeit at the expense of a higher pressure drop across the flow cell. These results point toward straightforward, user-accessible modifications of in-line IR flow cells that result in significant improvements in signal stability and acquisition times.

42 ENGINEERING↗
DOE OSTI2021

A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry–meteorology feedbacks on air quality

The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry–meteorology feedbacks. In this study, we present a comparative analysis of two-way (with consideration of both aerosol direct and indirect effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both offline and two-way coupling modes are carried out with anthropogenic emissions based on multiple years of the U.S. National Emission Inventory and chemical initial and boundary conditions derived from an advanced Earth system model (i.e., a modified version of the Community Earth System Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (O3) and fine particulate matter (PM 2.5 ). Due to the consideration of aerosol direct and indirect effects, two-way WRF-CMAQ shows improved performance over offline coupled WRF and CMAQ in terms of spatiotemporal distributions and statistics, especially for radiation, cloud forcing, O 3 , sulfate, nitrate, ammonium, elemental carbon, tropospheric O 3 residual, and column nitrogen dioxide (NO 2 ). For example, the mean biases have been reduced by more than 10 W m –2 for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h O 3 . However, relatively large biases still exist for cloud predictions, some PM 2.5 species, and PM 10 that warrant follow-up studies to better understand those issues. The impacts of chemistry–meteorological feedbacks are found to play important roles in affecting regional air quality in the US by reducing domain-average concentrations of carbon monoxide (CO), O 3 , nitrogen oxide (NO x ), volatile organic compounds (VOCs), and PM 2.5 by 3.1 % (up to 27.8 %), 4.2 % (up to 16.2 %), 6.6 % (up to 50.9 %), 5.8 % (up to 46.6 %), and 8.6 % (up to 49.1 %), respectively, mainly due to reduced radiation, temperature, and wind speed. The overall performance of the two-way coupled WRF-CMAQ model achieved in this work is generally good or satisfactory and the improved performance for two-way coupled WRF-CMAQ should be considered along with other factors in developing future model applications to inform policy making.

58 GEOSCIENCES↗
DOE OSTI2022

Ecosystem service benefits to water users from perennial biomass production

We report although many agree that a transition to renewable energy sources is needed to avoid the climate consequences of continued reliance on fossil sources, price is a barrier. For renewable energy sources, including bioenergy, penetrating energy markets depends on lowering prices to compete with the price of fossil sources, but the tools used in decision making, such as supply curves, exclude non-market benefits from ecosystem services. Here, we extend the economic concept of an economic supply curve to account for ecosystem services co-produced with perennial biomass. We developed three new types of supply curves to visualize the increased supply of biomass (‘sustainable supply’) with sufficient water-quality benefits to offset biomass production costs. Using these tools, we show that the value of water-quality improvements could significantly reduce the break-even price of perennial feedstocks if it were available to farmers. In the most optimistic case, nearly half of potential biomass supply in a large tributary of the Mississippi river basin carried water purification value exceeding the cost of biomass production. Furthermore, adding the value to swimmers and waders offset production cost for over 90% of potential supply. Simulated benefits were context specific. For example, total value for water drinkers peaked at an intermediate level of fertilizer application. Geographically, benefits were highest in the eastern portion of the river basin. This research shows where the sustainable supply is needed and can generate value; the next step is to match this supply with credit buyers. Efforts to internalize the values of ecosystem services into biomass prices could help to meet Biden administration targets to meet 100% of sustainable aviation fuels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Exascale granular microstructure reconstruction in 3D volumes of arbitrary geometries with generative learning

Reconstructing 3D granular microstructures within volumes of arbitrary geometries from limited 2D image data is crucial for predicting the material properties, as well as performances of structural components accounting for material microstructural effects. We present a novel generative learning framework that enables exascale reconstruction of granular microstructures within complex 3D geometric volumes. Building upon existing transfer learning techniques using pre-trained convolutional neural networks (CNN), we introduce several key innovations to overcome the difficulties inherent in arbitrary geometries. Our framework incorporates periodic boundary conditions using circular padding techniques, ensuring continuity and representativeness of the reconstructed microstructures. We also introduce a novel seamless transition reconstruction (STR) method that creates statistically equivalent transition zones to integrate multiple pre-existing 3D microstructure volumes. Based on STR, we propose a cost-effective strategy for reconstructing microstructures within complex geometric volumes, minimizing computational waste. Validation through numerical experiments using kinetic Monte Carlo simulations demonstrates accurate reproduction of grain statistics, including grain size distributions and morphology. A case study involving the reconstruction of a 4-blade propeller microstructure illustrates the method’s capability to efficiently handle complex geometries. In conclusion, the proposed framework significantly reduces computational demands while maintaining high reconstruction quality, paving the way for scalable microstructure reconstruction in materials design and analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗
DOE OSTI2022

How to support EV adoption: Tradeoffs between charging infrastructure investments and vehicle subsidies in California

Supporting the adoption of zero-emission vehicle (ZEVs), including plug-in electric vehicles (EVs), has become a priority for governments due to their ability to reduce petroleum demand, improve air quality, and reduce carbon dioxide (CO2) emissions. Optimal strategies to accelerate EV adoption must weigh the relative value of alternative policy mechanisms to consumers, including public charging infrastructure and vehicle purchase subsidies. We use a historically validated light-duty vehicle consumer choice tool, the ADOPT model, to simulate personal light-duty vehicle adoption and related emissions in California. ADOPT is updated to incorporate a quantification of the tangible value of public charging infrastructure, allowing us to simulate the impact of investments in public charging infrastructure and vehicle purchase subsidies under different scenarios. We show that both policies result in increased EV adoption, with the most effective policy varying depending on vehicle technology assumptions. Under conservative technology improvement assumptions, infrastructure investments are most effective in promoting EV sales and reducing CO2 emissions, while under optimistic technology improvement assumptions a combination of infrastructure and subsidies best supports EV sales and CO2 emission reductions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Experimental Studies of Single Invariant Quasi-Integrable Nonlinear Optics at IOTA

The Integrable Optics Test Accelerator is a research electron and proton storage ring recently commissioned at the Fermilab Accelerator Science and Technology facility. Its research program is focused on testing novel techniques for improving beam stability and quality, notably the concept of non-linear integrable optics. In this paper, we report on run 1 results of experimental studies of a quasi-integrable transverse focusing system with one invariant of motion, a Henon-Heiles type system implemented with octupole magnets. Good agreement with simulations is demonstrated on key parameters of achievable tune spread, dynamic aperture, and invariant conservation. We also outline current simulation and hardware improvement efforts for run 2, planned for fall of 2019.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Reservoir Thermal Energy Storage Benchmarking (Rev. 3)

A benchmarking analysis of RTES research funded by GTO through the Beyond Batteries projects was conducted against the ESGC to see where they fit within the identified ESGC Use Cases. The projects were found to advance knowledge in multiple ESGC use cases, either directly or in some cases, indirectly as enabling technologies. This analysis is helpful to understand where RTES and associated research fits into the larger discussion around energy storage technologies. Also, a retrospective analysis of the Beyond Batteries projects was conducted to evaluate what the projects learned and how the results can be applied to advance the value of RTES. Major results of each of the studies are summarized in Table 2. Additionally, a comparative metrics analysis for RTES was completed to understand where RTES lies within the energy storage industry. Metrics for evaluation of RTES and its comparison to other storage technologies were selected and ranges of their values compiled. The selected metrics – LCOE (levelized cost of energy), capital costs, roundtrip efficiency, energy storage capacity, and storage time – were chosen based on data availability and have a particularly strong influence on the potential deployment of a storage technology. Charts which compare the metrics are presented in section 4.3 and show ranges for each of the 10 selected technologies. However, due to a lack of domestic operational facilities, values for RTES and for portions of the remaining technologies are based on theoretical modeling and studies of best-case scenarios. LCOE estimates for RTES fall within the lower reaches of Figure 15, but nevertheless amount to 2 – 5 times the ESGC Roadmap goal for LCOE, for example in the Facilitating and Evolving Grid Use Case. Capital costs for RTES sit on the higher end (Figure 16) but are expected to decrease as new projects are developed and the technology is refined. The theoretical roundtrip efficiency reported for RTES varies from mid to high percentages (Figure 17) with efficiencies upwards of 93% in modeled scenarios in the Portland Basin (Bershaw et al.,2020). RTES is also expected to have the largest energy storage capacities and longest storage times, likely matched only by lower efficiency hydrogen storage. To better assess the role that RTES could play in energy storage we examined it’s potential in the U.S. The potential depends on many factors. Recently, many researchers have started looking at deep sedimentary basins, depleted oil and gas fields, and basalt formations as potential targets for RTES development. The United States Geological Survey (USGS) has analyzed various cities and shown substantial RTES potential in the cooling sector (Pepin et al., 2021). By modeling RTES in low-quality groundwater (e.g., brackish), it is shown to be favorable across the U.S. with particular suitability in the Illinois Basin, Coastal Plains, and Basin and Range regions. Seasonal RTES operations have also been modeled in the Portland Basin by those at the USGS and Portland State University to simulate an RTES system supplying heating loads needed for the Oregon Health and Science University. Simulations suggest that high conductive heat loss in the initial years exists but tends to decrease with increasing time and development of the resource due to self-insulating nature of the basalts (Burns et al., 2020). Other national laboratory efforts are taking a close look at many of the technical issues involved with RTES (McLing et al., 2019, McLing et al., 2022). These include difficulties in understanding geochemical, hydrogeological, mechanical, and microbiological changes at such elevated temperatures and operational scenarios. Major gaps in research are identified and suggested for future work. With this increased focus to understand how to make RTES successful in the U.S., this technology could be a potential solution to many of the nation’s energy storage problems. For the energy independence of this country, the DOE should prioritize de-risking this technology by making future investments in pilot-scale demonstrations to attract potential investors.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Effect of Surrogate Fission Products on Thermal Conductivity and Viscosity of NaCl-UCl 3

Thermophysical properties of salt systems relevant to molten salt reactors (MSRs) are experimentally measured in support of the US Department of Energy Office of Nuclear Energy (DOE-NE) MSR campaign within the Advanced Reactor Technology (ART) Program. These property measurements also support the development of the thermophysical arm of the Molten Salt Database (MSD) within DOE-NE’s Nu clear Energy Advanced Modeling and Simulation (NEAMS) Program. Several US Department of Energy (DOE) laboratories, including Oak Ridge National Laboratory (ORNL), have been capitalizing on modern methodologies and sample characterization techniques to conduct thermophysical property measurements to support these programs and to provide MSR developers and modelers with more recent and higher-quality data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A Framework to Analyze the Requirements of a Multiport Megawatt-Level Charging Station for Heavy-Duty Electric Vehicles

Widespread adoption of heavy-duty (HD) electric vehicles (EVs) will soon necessitate the use of megawatt (MW)-scale charging stations to charge high-capacity HD EV battery packs. Such a station design needs to anticipate possible station traffic, average and peak power demand, and charging/wait time targets to improve throughput and maximize revenue-generating operations. High-power direct current charging is an attractive candidate for MW-scale charging stations at the time of this study, but there are no precedents for such a station design for HD vehicles. We present a modeling and data analysis framework to elucidate the dependencies of a MW-scale station operation on vehicle traffic data and station design parameters and how that impacts vehicle electrification. This framework integrates an agent-based charging station model with vehicle schedules obtained through real-world vehicle telemetry data analysis to explore the station design and operation space. A case study applies this framework to a Class 8 vehicle telemetry dataset and uses Monte Carlo simulations to explore various design considerations for MW-scale charging stations and EV battery technologies. The results show a direct correlation between optimal charging station placement and major traffic corridors such as cities with ports, e.g., Los Angeles and Oakland. Corresponding parametric sweeps reveal that while good quality of service can be achieved with a mix of 1.2-megawatt and 100-kilowatt chargers, the resultant fast charging time of 35–40 min will need higher charging power to reach parity with refueling times.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Optimization-Based Fast-Frequency Estimation and Control of Low-Inertia Microgrids

The lack of inertial response from non-synchronous, inverter-based generation in microgrids makes the power system vulnerable to a large rate of change of frequency (ROCOF) and frequency excursions. Energy storage systems (ESSs) can be utilized to provide fast-frequency support to prevent such large excursions in the system. However, fast-frequency support is a power-intensive application that has a significant impact on the ESS lifetime. In this paper, a framework that allows the ESS operator to provide fast-frequency support as a service is proposed. The framework maintains the desired quality-of-service (limiting the ROCOF and frequency) while taking into account the ESS lifetime and physical limits. The framework utilizes moving horizon estimation (MHE) to estimate the frequency deviation and ROCOF from noisy phase-locked loop (PLL) measurements. These estimates are employed by a model predictive control (MPC) algorithm that computes control actions by solving a finite-horizon, online optimization problem. Additionally, this approach avoids oscillatory behavior induced by delays that are common when using low-pass filters as with traditional derivative-based (virtual inertia) controllers. MATLAB/Simulink simulations on a test system from Cordova, Alaska, show the effectiveness of the MHE-MPC approach to reduce frequency deviations and ROCOF of a low-inertia microgrid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

FGMS-poster

Idaho National Laboratory (INL) performs post irradiation examination (PIE) of tri-structural isotropic (TRISO)-coated particle fuel to help qualify it for high temperature gas cooled reactors. TRISO fuel compacts are re-irradiated in the Neutron Radiography Reactor (NRAD) to generate the short lived fission products needed for fission product release testing. The Fuel Accident Condition Simulator (FACS) furnace and newly added Screen Neutron Irradiated Fuel for Failure (SNIFF) furnace heat the compacts in helium to temperatures of up to 2,000°C, prompting fission product release—predominantly gaseous xenon and krypton isotopes and condensable products such as cesium—from failed particles. These released isotopes are transported to a fission gas monitoring system (FGMS 1 or FGMS 3), where they accumulate in cryogenic cold traps and are quantified using high-purity germanium (HPGe) detectors. The addition of SNIFF and FGMS 3 increases throughput by enabling simultaneous testing of multiple compacts. Furthermore, automated INL developed software provides continuous, near-real time monitoring of fission product inventories and manages the liquid nitrogen cooling of the traps. These system enhancements improve the efficiency, data quality, and testing capacity of TRISO fuel performance evaluations.

07 - ISOTOPES AND RADIATION SOURCES↗
DOE OSTI2020

Revealing transient powder-gas interaction in laser powder bed fusion process through multi-physics modeling and high-speed synchrotron x-ray imaging

Laser powder bed fusion (LPBF) is an emerging metal additive manufacturing process. The gas-driven powder motions in laser powder bed fusion have significant influence on the build quality. However, the transient powder-gas interaction has not been well understood due to the challenges in quantitative experiment measurements. In this work, the powder-gas interaction for a single pulse laser illuminating on the powder bed is studied. We establish a multi-physics model to simulate the complex liquid/gas flow as well as the gas-driven powder motions, which is substantiated by high-speed synchrotron x-ray imaging. We identify and quantify four characteristic modes of powder-gas interaction in LPBF. The motion of a powder is controlled by one or multiple interaction modes collectively. As revealed by simulations and confirmed by experiments, powders can merge into the molten pool from its rim, be ejected at different divergence angles (powder spattering), or dive into the molten pool to cause significant molten pool fluctuation. Overall, our results provide insights toward the driving forces controlling the dynamic powder behavior, which pave the way for reducing structure defects during the build process.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Isotherm modeling and techno-economic analysis of a TSA moving bed process using a tetraamine-appended MOF for NGCC applications

Tetraamine-appended metal-organic frameworks (MOF) are a new family of amine-functionalized MOF materials that show potential for CO 2 capture from flue gas conditions relevant to natural gas combined cycle (NGCC) power plants. This work presents isotherm modeling of the tetraamine-appended MOF Mg 2 (dobpdc)(3-4-3)(dobpdc 4- =4,4'-dioxidobiphenyl-3,3'dicarboxylate;3-4-3=N,N'bis(3-aminopropyl)-1,4-diaminobutane), process modeling, scale up, and a techno-economic optimization of a moving bed Temperature Swing Adsorption (TSA) process for carbon capture using this sorbent. This MOF exhibits a unique two-step CO 2 adsorption profile in three different pressure ranges. Thus, arctangent-based logistic functions and, quadratic and Langmuir models were employed to represent such isotherm behavior. The results of the isotherm model show good fitting vs the experimental data with an RMSE of 0.41. Here, to model the carbon capture process, the isotherm model was embedded into a moving bed contactor model, and this was used to simulate a TSA CO 2 capture cycle and evaluate cost-optimal designs considering flue gas from a -650 MWe NGCC power plant. The capital cost model consists of CAPEX correlations for reactors, compressors, ducting, etc., while the operating costs include steam, water, chemicals, and electricity (following NETL's quality guidelines for energy systems studies). A techno-economic optimization of the capture system was performed by using NETL's Framework for the Optimization and Quantification of Uncertainty and Surrogates tool (FOQUS). Results suggest that a moving bed carbon capture system with tetraamine-appended MOF can be competitive compared to conventional MEA solvent-based capture processes for NGCC plants, when a heat recovery efficiency of at least 40% is achieved, and MOF materials can be produced at a cost below -$9/kg.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Irradiation of ultrasonic sensors and adhesive couplants for application in light water reactor primary loop piping and components

The Electric Power Research Institute (EPRI) Nuclear Sector and US Department of Energy Light Water Reactor Sustainability Program are committed to engaging in research and development endeavors to address materials aging issues specific to long term operation of light water power reactors. To this effect, EPRI launched an industry initiative to develop nondestructive evaluation systems for online monitoring of existing cracks in light water reactor primary coolant loop piping and components. One of the goals of this initiative is to develop a sensor system (or systems) that can determine nondestructively if cracks are growing or arrested and, in the case of the former, to characterize their growth rates. A missing component of this initiative is an experimental assessment of how sensors and adhesive couplants will perform in service when exposed to chronic energetic neutron radiation, particularly at the primary coolant loop hot and cold leg dissimilar metal welds, which join the primary loop piping to the reactor pressure vessel and reside in the vicinity of the reactor core. The objective of this experimental study was to determine how ultrasonic transducers and adhesive couplants perform when exposed to irradiation in a test reactor to simulate and accelerate in-service exposure. Further, to achieve this objective, the signal stability of piezoelectric transducers and performance of adhesive couplants as a function of accumulated fast neutron fluence were characterized by collecting ultrasonic data in-situ during irradiation. Of particular interest were the ultrasonic signal quality and time decay of the amplitude of acoustic reflections as a function of fast neutron fluence. The results of the study showed that, of the 8 transducer/substrate sample assemblies tested, only 3 generated usable ultrasonic signals through the conclusion of the irradiation campaign. It was found that high temperature epoxy tends to ultrasonically couple the sensors to the substrates better than three types of refractory ceramic cements studied, as is supported by post irradiation examination. The results obtained through this experimental study will be utilized in the achievement of the overall goal of development of a sensor system to perform online monitoring of primary loop components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗