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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Securing the Modern Grid: Federal Investments, Digitization, and Supply Chain Strategy

Across the United States (U.S.) grid expansion and modernization is underway, paving the way for accelerated load growth and intelligent resource management. Digitization of the grid is supported by several state and federal programs, providing support for utilities installing advanced metering infrastructure (AMI), AI-powered analytics systems, battery energy storage systems (BESS), and distributed energy resource management systems (DERMS) to transform the grid from a one-way power delivery system into an intelligent, responsive network that will enable faster load growth and power expansion of data centers for advanced artificial intelligence (AI) applications. The digital transformation of America's grid presents opportunity for increased efficiency and resiliency but also introduces new digital risks that require careful management. Digital equipment often contains several vulnerabilities such as unencrypted communication protocols, and persistent remote access capabilities that could be exploited to manipulate device settings, coordinate service disruptions, or inject false data into grid operations. These digital risks become particularly important as the grid must rapidly scale to support AI-driven data centers, which the administration has identified as essential for maintaining U.S. technological leadership and economic competitiveness. These vulnerabilities are compounded by supply chain realities: Chinese manufacturers currently produce 70-90% of essential grid components including inverters, batteries, and control systems, with the U.S. lacking domestic manufacturing capacity for critical assets like extra-high voltage transformers. Recent federal legislation has established Foreign Entity of Concern (FEOC) restrictions to address these risks, requiring projects to achieve escalating thresholds of non-FEOC content to receive tax credits while utilities work to expand sourcing channels for their supply chains and strengthen security measures. These restrictions arrive precisely when utilities face unprecedented electricity demand growth driven by the rapid growth in data centers, creating a considerable challenge: rapidly expanding infrastructure while navigating complex compliance requirements while lacking viable alternatives for many critical components. Idaho National Laboratory (INL) and its partners have developed practical approaches to help utilities navigate these intersecting challenges as they leverage federal investment to strengthen and grow the grid. These solutions include Cyber-Informed Engineering (CIE) principles that build resilience directly into systems, the Cirrus tool for secure cloud migration, and enhanced procurement guidance that embeds security requirements throughout equipment lifecycles. Federal initiatives, such as the Technical Assistance for Digital Assurance (TADA) project, provide direct support to utilities implementing these approaches while facilitating knowledge sharing across the industry. While these tools and frameworks cannot eliminate all risks inherent in foreign supply chain dependencies, they offer pragmatic pathways for strengthening security posture without sacrificing the deployment momentum essential to meeting surging electricity demand. Ultimately, securing America's digital energy infrastructure demands dedicated coordination across multiple fronts: building domestic supply chains, implementing robust digital assurance practices, and maintaining the aggressive modernization timeline necessary for reliability, resilience, and energy independence.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Testing the efficacy of active pressure management as a tool to mitigate induced seismicity

Manipulation of subsurface stresses through fluid injection/extraction may induce seismicity through modulation of overpressure along faults. Globally, most industrial operations do not induce significant earthquakes. However, the possibility of inducing moderate to large earthquakes is recognized as a significant risk for basin-scale carbon dioxide (CO 2 ) storage operations (Niass et al., 2017). One possible method to reduce the occurrence of induced seismicity is to maintain only small (or zero) fluid overpressure changes in the subsurface through extraction of formation brine. For active pressure management (APM), operators may employ different procedures including extraction of various brine volumes and different configurations of injection/extraction well locations. However, the impact each these operational procedures on induced seismicity must be understood in order to develop management strategies. Here, we describe a numerical modeling workflow to evaluate the efficacy of APM techniques, that when applied to a specific site may be used to inform operational management strategies. We couple the multiphase reservoir model, NUFT, with the earthquake simulator, RSQSim and simulate seismicity induced by CO 2 injection into a hypothetical brine saturated reservoir. Reservoir overpressure is modified by co-extraction of brine at various fractions of the injected CO 2 volume from five potential wells. Our goal is to understand how the well-pair configuration and the extracted brine volume impact the total number and the maximum event magnitude. Additionally, the performance of each scenario is also evaluated in terms of the volume of CO 2 that can be stored before an earthquake above a tolerance threshold is induced.

58 GEOSCIENCES↗
DOE OSTI2025

Exploring Water System Vulnerabilities in California's Central Valley Under the Late Renaissance Megadrought and Climate Change

Abstract California faces cycles of drought and flooding that are projected to intensify, but these extremes may impact water users across the state differently due to the region's natural hydroclimate variability and complex institutional framework governing water deliveries. To assess these risks, this study introduces a novel exploratory modeling framework informed by paleo and climate‐change based scenarios to better understand how impacts propagate through the Central Valley's complex water system. A stochastic weather generator, conditioned on tree‐ring data, produces a large ensemble of daily weather sequences conditioned on drought and flood conditions under the Late Renaissance Megadrought period (1550–1580 CE). Regional climate changes are applied to this weather data and drive hydrologic projections for the Sacramento, San Joaquin, and Tulare Basins. The resulting streamflow ensembles are used in an exploratory stress test using the California Food‐Energy‐Water System model, a highly resolved, daily model of water storage and conveyance throughout California's Central Valley. Results show that megadrought conditions lead to unprecedented reductions in inflows and storage at major California reservoirs. Both junior and senior water rights holders experience multi‐year periods of curtailed water deliveries and complete drawdowns of groundwater assets. When megadrought dynamics are combined with climate change, risks for unprecedented depletion of reservoir storage and sustained curtailment of water deliveries across multiple years increase. Asymmetries in risk emerge depending on water source, rights, and access to groundwater banks.

Gupta, Rohini S. [School of Civil and Environmenta↗
DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗
DOE OSTI2020

Influence of physical and chemical hydrology on bioremediation of a U-contaminated aquifer informed by reactive transport modeling incorporating 238 U/ 235 U ratios

Microbially-catalyzed reductive immobilization of aqueous uranium (U) as a solid phase has been proposed as a U remediation technique. Both laboratory and field experiments have demonstrated that this reduction reaction alters the 238 U/ 235 U ratio, producing a 238 U-enriched U(IV) solid. In contrast, other major U reactive transport processes fractionate these isotopes much less. This suggests the potential to quantify the extent of bioreduction occurring in groundwater containing U using the 238 U/ 235 U ratio, which would substantially improve upon current practices largely relying on U concentration measurements alone. Current reactive transport models for uranium dynamics include only concentration measurements, which are strongly influenced by highly coupled reactive transformation and aqueous transport processes. The complex physical and chemical behavior of U potentially compromises such quantitative analysis of U storage and release. Here we report the first numerical reactive transport model which explicitly incorporates variations in the 238 U/ 235 U ratio of U and demonstrates improved interpretation of the principal chemical reactions and groundwater transport processes affecting the subsurface mobility and distribution of this widespread contaminant. Recent U bioreduction studies performed in a contaminated aquifer in Rifle, Colorado, USA applied Rayleigh distillation models to interpret U stable isotope fractionation observed as a result of acetate amendment. These simplified models were unable to resolve the spatiotemporal pattern of U isotope fractionation recorded in the aqueous solutes. Here, we employ the multi-component, isotope-enabled CrunchTope reactive transport software to interpret these measured U isotope ratios, and demonstrate accurate reproduction of observed trends in both geochemistry and 238 U/ 235 U ratios for two consecutive years of field experiments. Overall, our results indicate that accurately modeling both the U concentration and isotope ratio distributions greatly constrains the parameter space of the model. We find that the transport properties of U in the Rifle aquifer are governed by the presence of low-permeability regions, which the isotopes are uniquely sensitive to. When U reduction is spatially constrained by these low-permeability regions, the shift in the 238 U/ 235 U ratio becomes more muted. Accurate modeling of observed U isotope ratios thus provides a powerful means to better understand bioremediation, and the current study serves to advance the application of this novel method.

238U/235U↗
DOE OSTI2023

Shifts in bacterial traits under chronic nitrogen deposition align with soil processes in arbuscular, but not ectomycorrhizal-associated trees

Nitrogen (N) deposition increases soil carbon (C) storage by reducing microbial activity. These effects vary in soil beneath trees that associate with arbuscular (AM) and ectomycorrhizal (ECM) fungi. Variation in carbon C and N uptake traits among microbes may explain differences in soil nutrient cycling between mycorrhizal associations in response to high N loads, a mechanism not previously examined due to methodological limitations. Here, we used quantitative Stable Isotope Probing (qSIP) to measure bacterial C and N assimilation rates from an added organic compound, which we conceptualize as functional traits. As such, we applied a trait-based approach to explore whether variation in assimilation rates of bacterial taxa can inform shifts in soil function under chronic N deposition. We show taxon-specific and community-wide declines of bacterial C and N uptake under chronic N deposition in both AM and ECM soils. N deposition-induced reductions in microbial activity were mirrored by declines in soil organic matter mineralization rates in AM but not ECM soils. Our findings suggest C and N uptake traits of bacterial communities can predict C cycling feedbacks to N deposition in AM soils, but additional data, for instance on the traits of fungi, may be needed to connect microbial traits with soil C and N cycling in ECM systems. In conclusion, our study also highlights the potential of employing qSIP in conjunction with trait-based analytical approaches to inform how ecological processes of microbial communities influence soil functioning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Local Power: Comparing County-Level Renewable Energy Potential to Consumption Using the SLOPE Platform

Wide-scale deployment of renewable energy technologies has the potential to significantly reduce greenhouse gas emissions and mitigate the effects of climate change. Many communities have ambitious clean energy goals with targets for locally generated renewable energy. To inform state and local clean energy planning, analysts from the Joint Institute for Strategic Energy Analysis (JISEA) and National Renewable Energy Laboratory (NREL) used data from NREL's State and Local Planning for Energy (SLOPE) platform to compare annual technical generation potential of renewable energy technologies to modeled electricity consumption in every county of the contiguous United States. Annual costs were calculated to produce a 20% share of electricity consumed annually from each technology to examine localized cost effectiveness of a diversified mix of generation sources. For example, combining distributed and utility-scale wind and solar generation can offset the need for storage and nonintermittent fossil resources to achieve high deployment of renewables. This county-level analysis provides insight into where localized renewable energy generation could cost-effectively match annual electricity consumption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Deep Electrification Analysis: The Role of the U.S. Power Grid for Sustainable Transportation

This project attempts to quantify the size of electric generation for the entire nation to transition from a fossil fuel based transportation sector to a zero GHG emission-based energy source. The scope of this analysis is limited to decarbonizing the transportation sector, leaving the remaining sectors, such as power (for those that are still fossil based), industry, and building sectors, for later phases of study. The study year for this analysis is 2050, with expected escalation in transportation services and naturally occurring evolutions in the electric power sector and the entire economy. This analysis uses the projections of the Energy Information Administration’s (EIA’s) Annual Energy Outlook (AEO 2020) Reference Case for study year 2050 [EIA/AEO2020] as a base-case. The transportation sector is disaggregated by the following modes and classes: (1) on-road (divided into light-duty, medium-duty, heavy-duty vehicles), (2) aviation, (3) maritime, and (4) rail. The decarbonization case was based on only 2 pathways: (1) electrification of on-road transportation except for 30% of heavy-duty vehicles, and (2) power-to-liquid for the remaining transportation modes. The study estimated for 11 US regions what the additional wind and storage capacities requirements are to replace the fossil-based fuels with renewable wind capacity. Considered were the utilization of the existing idle capacity particularly during the load valley at night and any additional new generation capacity in EIA projections for the reference case. To balance the additional wind capacity required significant energy storage capabilities which were estimated in terms of power capacity (GW) and energy capacity (GWh). The paper further characterizes the energy requirements by a relation of power capacity to duration, allowing the analyst to gain insights into what the best technology portfolio might be to meet the new balancing or flexibility needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Battery Critical Materials Supply Chain Challenges and Opportunities: Results of the 2020 Request for Information (RFI) and Workshop

The purpose of this report is to outline and discuss the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE)’s findings related to EERE’s Request for Information (RFI) on Battery Critical Materials Supply Chain Research & Development (R&D) and the EERE R&D Battery Critical Materials Supply Chain Workshop. The United States has committed to achieving 50% or more reduction of greenhouse gas pollution by 2030, with a long-term goal to completely decarbonize the U.S. economy by 2050, and to limit global warming to 1.5 degrees Celsius (The White House, 2021a).

25 ENERGY STORAGE↗
DOE OSTI2022

HOPP - Hybrid Optimization and Performance Platform

The Hybrid Optimization and Performance Platform, HOPP, is a wind + solar + battery + X design software for optimizing co-located, utility-scale hybrid plants down to the component level for different markets and technoeconomic objectives. Key technology and financial inputs to the HOPP model that inform the objective to be optimized are presented. The layout and performance integration is combined with optimal dispatch and full financial modeling within an optimization framework. With an example scenario, optimal sizing and layout results are shown in a sensitivity analysis of prices for two hybrid configurations.

batteries↗
DOE OSTI2020

Smart Composite Pressure Vessels (SCPV) with Integrated Health Monitoring

The U.S. Department of Energy (DOE) is promoting and developing more energy efficient and environmentally friendly technologies that will enable America to use less petroleum. Hydrogen fuel cells – which directly convert the chemical energy in hydrogen to electricity with only water and heat as byproducts – are a very attractive solution that can enable this to happen. To date, DOE's efforts have culminated in commercial demonstration of on-board vehicular hydrogen storage systems that can allow for a driving range of greater than 300 miles. This requires storing 5 Kgs of hydrogen onboard a light vehicle. In order to store this quantity of hydrogen, the hydrogen gas needs to be stored in a composite overwrapped pressure vessel (COPV) at a very high internal pressure. The objective of the program was to demonstrate continuous and predictable health-monitoring of composite pressure vessels. A higher confidence in the operational safety of the vessels will lead to reduced burst factor of safety imposed by regulatory standards and hence will help reduce the structural wall thickness that drives the cost of the vessel. Highly optimized Type III (metal lined) and Type IV (polymer lined) COPVs that are manufactured using filament winding process have been designed and qualified for the above mentioned application. However, the main structural component of the COPVs is carbon fiber and the high cost of carbon fiber composite in a pressure vessel is a primary challenge in reducing the cost of gaseous hydrogen storage. Continuous and remote monitoring of structural health of the COPVs as well as optimization of the strength translation of carbon fibers have the potential to allow for reduced factor of safety, thereby reduced amount of carbon and associated cost of the vessel. In the current program, the project team including Steelhead Composites (SHC), University of Tennessee, Knoxville (UTK), Teijin Carbon America, Oak Ridge National Laboratory (ORNL) and LUNA designed, fabricated, and tested smart composite pressure vessels with integrated sensors. Iterative loops of design and testing using coupons, subscale STEB vessels and full size vessels proved that a new generation of high performance carbon fiber can be used for efficient design of Type 3 vessels for H2 storage. Novel analysis techniques were developed to predict the initiation and propagation of interlaminar damage inside the composite shell due to impact damage, a real threat in practical operation. Such an analysis scheme is typically not used in tank design but is an essential tool for health monitoring of composite vessels. Remote sensing of the key signatures of the tank’s operating parameters such as pressure, acceleration and humidity was demonstrated using a unique device that can wirelessly transmit and stream the data to a remote server. Fiber optic sensors were successfully integrated during fabrication of the tanks. These sensors provide a wealth of information regarding the structural health of the vessel when it is subsequently pressurized or subjected to impact damage. Excellent correlation was demonstrated between the fiber optic sensor and mechanical strain gage data, and between the measurements and analytical predictions.

08 HYDROGEN↗
DOE OSTI2023

The evaluation of aluminum and iron metal oxide settling behaviors for Hanford insoluble solids waste preprocessing

The Hanford site is currently one of the largest and most expensive cleanup sites for hazardous, radioactive waste. Over 20% of the waste found at the Hanford site is in the form of a high activity sludge. The insoluble solids in the sludge will need to be concentrated prior to vitrification in the high-level waste (HLW) melter. This will minimize the amount of liquid that will be evaporated during the melting process and expedite the melter processing rate. One proposed option for concentrating the insoluble solids is gravity settling in the storage tanks. Metal oxide compounds containing aluminum and iron make up the majority of the insoluble solids in the sludge, therefore understanding the behavior of these compounds in various tank waste matrices can facilitate sludge pretreatment options. A study of non-radioactive slurry solutions containing Al(OH) 3 (gibbsite), AlO(OH) (boehmite), and Fe 2 O 3 (iron (III) oxide) was conducted to determine the time dependent interface behavior and settling rates of these compounds. Variations in solids loading and sodium concentration were evaluated to represent waste processing conditions and the results of these settling studies were compared with prior tank waste settling tests. Information gathered from these studies can be used to inform future decisions on sludge treatment processes of the insoluble solids processed at the Hanford site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Computational investigation of hysteresis and phase equilibria of n-alkanes in a metal-organic framework with both micropores and mesopores

Abstract Adsorption hysteresis is a phenomenon related to phase transitions that can impact applications such as gas storage and separations in porous materials. Computational approaches can greatly facilitate the understanding of phase transitions and phase equilibria in porous materials. In this work, adsorption isotherms for methane, ethane, propane, and n-hexane were calculated from atomistic grand canonical Monte Carlo (GCMC) simulations in a metal-organic framework having both micropores and mesopores to better understand hysteresis and phase equilibria between connected pores of different size and the external bulk fluid. At low temperatures, the calculated isotherms exhibit sharp steps accompanied by hysteresis. As a complementary simulation method, canonical (NVT) ensemble simulations with Widom test particle insertions are demonstrated to provide additional information about these systems. The NVT+Widom simulations provide the full van der Waals loop associated with the sharp steps and hysteresis, including the locations of the spinodal points and points within the metastable and unstable regions that are inaccessible to GCMC simulations. The simulations provide molecular-level insight into pore filling and equilibria between high- and low-density states within individual pores. The effect of framework flexibility on adsorption hysteresis is also investigated for methane in IRMOF-1.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Blind Modeling Validation Exercises Using the Horizontal Dry Cask Simulator

The U.S. Department of Energy (DOE) established a need to understand the thermal-hydraulic properties of dry storage systems for commercial spent nuclear fuel (SNF) in response to a shift towards the storage of high-burnup (HBU) fuel (> 45 gigawatt days per metric ton of uranium, or GWd/MTU). This shift raises concerns regarding cladding integrity, which faces increased risk at the higher temperatures within spent fuel assemblies present within HBU fuel compared to low-burnup fuel (≤ 45 GWd/MTU). A dry cask simulator (DCS) was built at Sandia National Laboratories (SNL) in Albuquerque, New Mexico to produce validation-quality data that can be used to test the accuracy of the modeling used to predict cladding temperatures. These temperatures are critical to evaluating cladding integrity throughout the storage cycle of commercial spent nuclear fuel. A model validation exercise was previously carried out for the DCS in a vertical configuration. Lessons learned during the previous validation exercise have been applied to a new, blind study using a horizontal dry cask simulator (HDCS). Three modeling institutions – the Nuclear Regulatory Commission (NRC), Pacific Northwest National Laboratory (PNNL), and Empresa Nacional del Uranio, S.A., S.M.E. (ENUSA) – were granted access to the input parameters from the DCS Handbook, SAND2017-13058R, and results from a limited data set from the horizontal BWR dry cask simulator tests reported in the HDCS update report, SAND2019-11688R. With this information, each institution was tasked to calculate peak cladding temperatures and air mass flow rates for ten HDCS test cases. Axial as well as vertical and horizontal transverse temperature profiles were also calculated. These calculations were done using modeling codes (ANSYS/Fluent, STAR-CCM+, or COBRA-SFS), each with their own unique combination of modeling assumptions and boundary conditions. For this validation study, the ten test cases of the horizontal dry cask simulator were defined by three independent variables – fuel assembly decay heat (0.5 kW, 1 kW, 2.5 W, and 5 kW), internal backfill pressure (100 kPa and 800 kPa), and backfill gas (helium and air). The plots provided in Chapter 3 of this report show the axial, vertical, and horizontal temperature profiles obtained from the dry cask simulator experiments in the horizontal configuration and the corresponding models used to describe the thermal-hydraulic behavior of this system. The tables provided in Chapter 3 illustrate the closeness of fit of the model data to the experiment data through root mean square (RMS) calculations of the error in peak cladding temperatures (PCTs), PCT axial locations, axial temperature profiles, vertical and horizontal temperature profiles at two different axial locations, and air mass flow rates for the ten test cases, normalized by the experimental results. The model results are assigned arbitrary model numbers to retain anonymity. Due to the relatively flat axial temperature profiles, small temperature gradients resulted in large deviations of all models’ PCT axial location from the experimental PCT axial location. When the PCT axial location error is excluded in the calculation of the combined RMS of the normalized errors that considers PCT, the temperature profiles, and the air mass flow rates, the model data fits the experimental data to within 5%. When the vault information is excluded, the model data fits the experimental data to within 2.5%. An error analysis was developed further for one model, using the model and experimental uncertainties in each validation parameter to calculate validation uncertainties. The uncertainties for each parameter were used to define quantifiable validation criteria. For this analysis, the model was considered validated for a given comparison metric if the normalized error in that metric divided by the validation uncertainty was less than or equal to 1. When considering the combined RMS of the normalized errors of all metrics divided by their validation uncertainties, the model was found to have satisfied the criterion for model validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

RH-TRU Waste Streams: HFDA Crucibles Create New Complex Waste Stream

This project focuses on the removal of the Hot Fuel Dissolution Apparatus (HFDA) crucibles from the Hot Fuel Examination Facility’s (HFEF) hot cells to create space for upcoming projects. The project team has created a crucible and pyro-salt non-debris waste stream that can be disposed of at Waste Isolation Pilot Plant (WIPP). Chemical Compatibility Examinations (CCEs) must be performed on candidate waste by reviewing the types of chemicals used in the experiments, information found in INL Process Knowledge Summary Reports (PKSRs), and Environmental Protection Agency guides on chemical compatibility. The CCEs identify which chemicals can be safely combined to ensure adverse reactions do not occur in the waste packages. The CCEs are then used to update the PKSR, Basis of Knowledge, and Acceptable Knowledge documents and demonstrate compliance with the WIPP Waste Acceptance Criteria. Once documents are finalized, they are reviewed and approved by the WIPP Central Characterization Project (CCP) to ensure proper waste stream characterization. After the documents are approved, the crucibles can be packaged and shipped to the Idaho Nuclear Technical and Engineering Center for storage awaiting certification. CCP will certify the waste using the approved documents and a series of confirmatory testing before being shipped and disposed in WIPP’s deep geological repository. Currently, the CCE is in progress and the PKSRs are being updated.

Basis of Knowledge↗
DOE OSTI2023

High-Field Nuclear Magnetic Resonance (NMR) Spectroscopy

Nuclear magnetic resonance (NMR) is a non-destructive spectroscopic technique that provides detailed molecular structural information via the electronic environments of nuclei in materials. Higher magnetic field strengths enhance the resolution of NMR, enabling discernment of unique chemical environments that might not be possible at low fields. Herein, the application of high-field NMR to catalyst and electrochemical system characterization are detailed. A brief description of NMR and quadrupolar nuclei are presented where the effects of magnetic field are described. Examples of high-field NMR are provided with particular focus on employing NMR to elucidate the structure of oxides of aluminum and vanadium for catalyst applications. The role of high-field NMR to conduct challenging experiments for energy storage materials is also explored and numerous other nuclei which require high-field measurement are briefly summarized.

Catalyst, Spectroscopy, NMR, High-field, Quadrupol↗
DOE OSTI2023

Enabling site-specific well leakage risk estimation during geologic carbon sequestration using a modular deep-learning-based wellbore leakage model

Geologic carbon sequestration (GCS) is a promising technology for mitigating net carbon emissions and growing climate concern by storing CO 2 in reservoirs. Oil and gas brownfields are an attractive option for CO 2 storage, but these sites have many historical wellbores from petroleum production and can be a potential leakage pathway for CO 2 or formation brine. Therefore, risk management of GCS operations requires an assessment of potential well leakage. Due to the high uncertainty of the system, stochastic approaches are ideal for quantifying the range of risk behaviors, but they must be computationally efficient in the face of complex physics. Here, we develop a new physics-centric deep learning wellbore model to predict the leakage of CO 2 and brine through leaky wellbores. Multi-physics numerical simulations were used to generate data sets, and physics-informed features were introduced. Neural networks were optimized with an automated searching algorithm. Feature analysis quantifies the impact of each feature on model prediction and confirms the role of physics-inspired parameters. The model shows high predictive performance across a wide range of geologic and injection conditions and well attributes. In conclusion, a case study illustrates how the model is applied to assess well leakage in GCS operations.

58 GEOSCIENCES↗
DOE OSTI2021

ESPC ESA Webinar Series: ESPC ENABLE Contract Vehicle Overview

This webinar provides instructions and resources for financing distributed energy projects (e.g. on-site renewable energy, storage, and combined heat and power) using an energy savings performance contract (ESPC) energy sales agreement (ESA) through the U.S. Department of Energy's (DOE) ESPC ENABLE contract vehicle. The ESPC ENABLE contract vehicle is a streamlined procurement process that uses a standard investment grade audit tool and standard contract templates. Topics covered in the webinar include: An overview of the ESPC ENABLE contract vehicle; ESA-specific considerations for ENABLE contracts; and Case studies. This webinar also provides an overview of the resources available on the Federal Energy Management Program website, such as ESPC ENABLE templates. This webinar is the fourth of a series that provides information, best practices, and resources for implementing an ESPC ESA project. ESPC ESAs are a great option for federal sites that are motivated to reduce site costs, have no capital investment funding, and cannot use the U.S. Department of Defense 10 USC 2922a authority for long-term contracting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗