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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Biofouling and Corrosion Study for a Novel Linear Guided Wave Energy Converter (Post Access Report)

The overall objective of this project was to examine the reliability and performance of antibiofouling coatings used for a wave energy converter (WEC) developed by E-Wave Technologies. The particular coatings were selected for their low toxicity and potential compatibility with aquaculture. The aim of this work was to 1) test coating solutions to prevent biofouling growth and saltwater corrosion on the static (paddle and attachment frame surface) components of the WEC that are submerged, 2) determine adhesion of the coatings to system components, and 3) assess the ease and effectiveness of biofouling cleaning to insure long term performance of the system. An analysis of commercial coatings was performed using methods to examine the prevention of biofouling and coating adhesion properties on two key materials of the WEC, which were 316L low carbon marine grade stainless steel (SS) and Ultra High Molecular Weight Polyethylene (PE). Three marine antifouling paints were selected based on their unique properties to test how different paint styles perform on different materials. The selected paints were ePaint Ecominder self-polishing paint with Zinc Omadine for slime control, Pettit ECO HRT Copper-Free ablative antifouling with Econea biocide, and Intersleek 1100SR foul release. Pacific Northwest National Laboratory (PNNL) prepared PE and SS substrates coated with the three paints and compared the performance against uncoated substrates when submerged in raw seawater for 3-, 6-, and 9-month (m) time periods. Results in adhesion testing indicated that Pettit and ePaint materials clearly bonded strongly to SS, but did not bond comparably well to PE. It was noted during adhesion testing that the Intersleek surfaces were especially difficult to test as the paint highly resists bonding to the epoxy adhesives used with the adherence testing platform. The wear rate of the coatings was not measured under this study; however, based on adhesion testing, coatings in the sliding regions of the Ewave device are expected to wear rapidly. Sandia National Laboratories (SNL) evaluated the adhesion of three different paints to PE and SS substrates which were exposed to a marine environment for time intervals of 0, 3, 6, and 9 months. From qualitative visual analysis of the 3 in2 coupons when pulled from the tank, the 3 in2 coupons generally only appeared to have biofouling consisting of filamentous algae or diatoms, which all have relatively low mass and can be easily wiped from the surface of coupons. Qualitative visual analysis indicated that ECO HRT and Unpainted were consistently worse than Intersleek and Ecominder at all time points. Results provide insight to aid with down-selection of commercial coatings under static conditions to support reliability of the WEC and potential maintenance schedules. This investigation was conducted using small coupon samples suspended in seawater and the development of testing rigs for dynamic component level testing is needed for future work. In addition, the potential toxicity of these commercial coatings on aquaculture has not been determined by this study. One recommendation is to conduct toxicity investigations at the Environmental Toxicity Laboratory at Oak Ridge National Laboratory.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

A long-term pilot-scale algal cultivation on power plant flue gas – Cultivation stability and biomass accumulation

A long-term culture of a selected freshwater microalgal assemblage on power plant flue gas was realized using a pilot-scale photobioreactor. Different culture conditions of light cycle, harvesting amount, pH stabilization, and sulfur addition were tested during a 12-month continuous operation at a natural gas fired power plant. The results concluded that the daily harvesting amount of 60% with no light-cycle and NH 4 NO 3 as the nitrogen source and pH stabilization agent, resulted in optimal cultivation performance. Biomass concentration and biomass productivity reached 1.07 ± 0.23 g L -1 and 0.43 ± 0.14 g L -1 d -1 , respectively. During the year-long cultivation period, the algal assemblage was relatively stable with average abundances of 88 ± 4% and 12 ± 4% for algae and bacteria, respectively, and no significant differences between individual case scenarios. The stable culture fostered a stable biomass composition. Protein, carbohydrate, and lipid contents of the algal biomass were 58.60 ± 2.41%, 19.5 ± 2.44%, and 9.70 ± 1.68%, respectively.

09 BIOMASS FUELS↗
DOE OSTI2021

Regional Subsidence Analysis Through a Multi-Scale Modeling Framework Based on Breakage Mechanics

Although poroelastic models are often used to explain the delay between subsurface fluid depletion and ground subsidence, inelastic compaction involving permanent changes of rock microstructure may exacerbate hydro-mechanical coupling, thus influencing the interpretation of measurements and long-term forecasts. Here, a multi-scale modeling approach is discussed, which accounts for the inherent connection between rock microstructure, hydraulic conductivity, and pore compaction. A constitutive model built within the framework of breakage mechanics is proposed to link the hydraulic conductivity of granular rocks with inelastic deformations and changes in grading caused by injection-depletion cycles at stress levels far from yielding. The proposed model has been incorporated into large-scale simulation frameworks, thus enabling the spatiotemporal mapping of regional subsidence through a hybrid, semi-analytical approach. Numerical results based on this strategy show that the model allows isolating near-field and far-field effects into the computation of land subsidence and can generate forecasts for different modeling scenarios (e.g., elastic and inelastic compaction, constant permeability, and concurrent change of compressibility and permeability). In particular, examples of simulations for the case of the Groningen gas field are discussed, showing the model capabilities to use both field measurements and laboratory tests for the generation of reasonable subsidence maps, without expensive computational costs. Results indicate that ignoring coupled inelastic effects has major consequences on the predicted timescale of subsidence. Specifically, while all the model scenarios produced similar long-term ground settlements, those ignoring breakage-dependent permeability changes result in a variation of the temporal window of residual subsidence of the order of several decades.

58 GEOSCIENCES↗
DOE OSTI2022

Simulation, Challenge Testing and Validation of Solutions for Residential and Commercial Occupancy Sensing/Counting and CO2 Sensing (Final Report)

Carbon dioxide sensors used for monitoring and control applications in buildings are known to be sensitive to long term drift and can be affected by variations in temperature, humidity, other gas interferents, pressure and other factors that cannot be corrected through the typical auto-calibration methods often embedded in the sensor electronics. This investigation was part of the Category D defined in the ARPA-E Saving Energy Nationwide in Structures With Occupancy Recognition (SENSOR) Financial Assistance Funding Opportunity Announcement No. DE-FOA-0001737, FFDA No. 81.135, January 18, 2017. The FOA defined target criteria for the evaluation of the Category C commercial CO2 sensors selected for review and development through the ARPA-E SENSOR program and charged the Iowa State Category D team with developing an evaluation methodology for Category C sensors in accordance with these criteria. As part of the work, the Iowa State team chose to engage the standards community in the development of the evaluation methodology. Standard development work in the D22.05 Indoor Air and D22.03 Ambient Atmospheres and Source Emissions subcommittees of ASTM International Committee D22 on Air Quality on the evaluation of low cost sensors and provision of guidance for using indoor carbon dioxide concentrations to evaluate indoor air quality and ventilation is of particular relevance to the Category D efforts. To date, three draft standards with specific input by the Iowa State Category D team have passed the subcommittee balloting stage and are being balloted in December 2022 and January 2023 in the main D22 committee. In addition to the aforementioned standards to which the PI was a contributing author, intellectual property developed in this project pertaining to “An Automated System for Evaluation of the Long Term Performance of Carbon Dioxide Sensors” and “An Automated Ground Truth System for Real-Time Reliability Assessment, Capture of Control Decisions and Energy Savings Measurements for Occupancy Recognition Systems and Other Applications” are the other major deliverables of the project. These standards and the developed intellectual property are expected to benefit the public in a number of ways stemming from their provision of means to benchmark the performance of carbon dioxide and other sensor systems. In particular, there is high interest in techniques to demonstrate the performance of low-cost carbon dioxide sensors which can be used for typical HVAC applications (e.g., demand controlled ventilation, outdoor and indoor air monitoring, estimation of occupancy, etc.).

42 ENGINEERING↗
DOE OSTI2020

Field Test Bed for Vadose-Zone Monitoring Approaches - 20404

In the Central Plateau at the U.S. Department of Energy Hanford Site, a large inventory of contaminants resides in unsaturated sediments within the approximately 100-meter-thick vadose zone, posing a potential continuing risk to groundwater. Vadose zone remedies used to address these contaminants will require performance monitoring to provide feedback during implementation and for long-term verification that remedial action objectives have been met. Passive approaches may also need long-term monitoring to demonstrate that the flux of contaminants from the vadose zone to the groundwater are below thresholds established to meet groundwater protection goals. Collection of physical (e.g., groundwater or sediment) samples is a common method for identifying contaminant concentration distributions, but this approach is limited by the number of locations and the frequency with which data can be collected. In situ vadose zone measurements have evolved over the past few years to include key measurements of water content, soil water pressure, temperature, and chemical concentration. However, the current generation of sensors is designed for relatively short-term use in near-surface soils or sediments. Geophysical methods have been evolving but are also limited in that they have not been designed for the specific long-term vadose zone monitoring needs at the Hanford Site. Overall, monitoring under unsaturated conditions can be difficult due to the need to install and maintain instrumentation over a large area and depth and the need to identify preferential flow pathways due to geologic and chemical heterogeneities over long periods. Thus, a vadose zone monitoring test bed was initiated to address these challenges and identify cost-effective approaches for implementation and postclosure monitoring of the deep vadose zone. The monitoring test bed is expected to provide valuable field-scale information for the design of vadose zone monitoring systems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Development and Testing of a new Current-Regulated Arc Modulator for the LINAC

In this study, the performance of a current-regulated arc modulator was investigated with a focus on its role in initiating and sustaining plasma discharge within the Magnetron Body of the LINAC system. The analysis centered on how switching components, circuit topology, and feedback loop architecture influence critical factors such as energy efficiency, discharge stability, and long-term plasma containment. Particular attention was given to variations in pulse termination behavior, as observed through oscilloscope traces, which revealed inconsistencies affecting the duty factor and cathode temperature. These fluctuations have downstream effects on the cesium-coated cathode surface, thereby impacting H⁻ ion production and beam reliability. Simulation-based testing in LTspice was used to evaluate noise suppression techniques and arc current regulation schemes, revealing how optimized snubber networks, improved pulse shaping, and feedback stability can mitigate modulator-induced noise. The results identified hardware level parameters that significantly enhance discharge repeatability and improve overall plasma performance under operational conditions.

Campos, Nathan [Unlisted, US; Fermilab]↗
DOE OSTI2023

Modeling DOE Standard Canister Configurations with Updated Surface Chemistry

Road-ready and final disposition packaging configurations for the advanced test reactor (ATR) fuel currently specifies storage within helium backfilled DOE sealed standard canisters. The aluminum cladding of the ATR fuel contains an oxyhydroxide layer of boehmite/bayerite that generates hydrogen when subjected to irradiation. Understanding the effect of this hydrogen buildup over time to important for long term storage considerations. Previous modeling efforts have built a coupled CFD-chemical model to simulate the temperature gas phase concentrations within the DOE sealed standard canisters. These models have coupled the temperature conditions to both the gas phase radiolysis chemistry and the surface chemistry associated with the oxyhydroxide layer. Continued experimental work has identified trends for aluminum surrogate samples with oxyhydroxide layers for tests done at higher dose rates. At low initial doses a fast generation rate of hydrogen occurs which starts to roll over to a lower generation rate as the total dose applied in increased. A previous study created a small-scale chemical model was built to replicate a mini-canister surrogate system at SRNL as well as for the smaller capsule tests performed at INL. The previous iteration of the model utilized step function for its G-values for the hydrogen generation over a 200-year period. This model makes an update to the surface chemistry to account for theorized surface chemistry reactions allowing for oxygen to remain bounded to the oxyhydroxide layer. As additional experiments continue, the kinetic fits may be adjusted to adapt to new data. Three canister configurations are modeled – the base 18-inch, 15-foot DOR standard canister with 30 ATR fuel elements, an 18-inch, 10-foot DOE standard canister with 32 ATR fuel elements and a 24-inch, 10-foot DOE standard canister with 40 ATR fuel elements. In previous reports, the primary sensitivity of the canister conditions was identified as the decay heat of the fuel and the dried condition of the fuel. Only these parameters are studied in the report. For the nominal case with dried fuel, the hydrogen generation is only about 2%, so it is even less than the flammability limit if it were exposed to oxygen. For the densely packed 18-inch case the total hydrogen concentration is only around 4% with the nominal decay heat. For the densely packed 24-inch case the total hydrogen concentration is only 2.5%, roughly 20% higher than the original packing design, and still under flammability conditions if exposed to oxygen.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Control of a Three-Phase Grid-Connected Voltage-Sourced Converter Using Long Short-Term Memory Networks

With the rise of inverter-based resources (IBRs) within the power system, the control of grid-connected converters (GCCs) has become pertinent due to the fact they interface IBRs to the grid. The conventional method of control for a GCC such as the voltage-sourced converter (VSC) is through a decoupled control loop in the synchronous reference frame. However, this model-based control method is sensitive to parameter changes causing deterioration in controller performance. Data-driven approaches such as machine learning can be utilized to design controllers that are capable of operating GCCs in various system conditions. This work explores a deep learning-based control method for a three-phase grid-connected VSC, specifically utilizing a long short-term memory (LSTM) network for robust control. Simulations of a conventional controlled VSC are conducted using Simulink to collect data for training the LSTM-based controller. The LSTM model is built and trained using the Keras and TensorFlow libraries in Python and tested in Simulink. The performance of the LSTM-based controller is evaluated under different case studies and compared to the conventional method of control. Simulation results demonstrate the effectiveness of this approach by outperforming the conventional controller and maintaining stability under different system parameter changes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Recalibration of missing low-frequency variability and trends in the North Atlantic Oscillation

Abstract Multi-decadal trends in the wintertime North Atlantic Oscillation (NAO) are under-represented by coupled general circulation models (CGCMs), consistent with a lack of autocorrelation in their NAO index series. This study proposes and tests two simple “reddening” approaches for correcting this problem in simulated indices based on simple one parameter short-term (AR; Auto-Regressive order 1) and long-term (FD; Fractional-Difference) time series filters. Using CGCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6), the FD filter successfully improves the autocorrelation structure of the NAO, and in turn the simulation of extreme trends, while the AR filter is less successful. The 1963–1993 NAO trend is the maximum 31-year trend in the historical period. Raw CGCMs underestimate the likelihood of this trend by a factor of ten but this discrepancy is corrected after reddening. CMIP6 future projections show that long-term (2024–2094) NAO ensemble mean trends systematically increase with the magnitude of radiative forcing: -2.4 to 3.5 hPa/century for low-to-high forcing after reddening (more than double the range using raw output). The related likelihood of future maximum 31year trends comparable to 1963–1993 ranges from 3 to 7% whereas none of these CMIP6 projections simulate this without reddening. Near-term projections of the next 31 years (2024–2054) are less sensitive than long term trends to the future scenario, showing weak-to-no forced trend. However, reddening increases the ensemble range by 74% (to +/-1 standard deviation/decade), which could increase/decrease regional climate change signals in the Northern Hemisphere by magnitudes that are underestimated when using raw CGCM output.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Neural-based time series forecasting of loss of coolant accidents in nuclear power plants

During the last few years, deep learning in neural networks has demonstrated impressive successes in the areas of computer vision, speech and image recognition, text generation, and many others. However, sensitive engineering areas such as nuclear engineering benefited less from these efficient techniques. In this work, deep learning expert systems are utilized to model and predict time series progression of a design-basis nuclear accident, featuring a loss of coolant accident. Two major findings are accomplished in this work. First, the ability to train expert systems with high accuracy, which could help nuclear power plant operators to figure out plant responses during the accident. Second, building fast, efficient, and accurate deep models to simulate nuclear phenomena, which could be valuable to nuclear computational science. In this work, large amount of time series data is obtained from simulation tools by simulating different conditions of the base-case/nominal accident scenario. Four critical outputs/responses are monitored during the accident (e.g. temperature, pressure, break flow rate, water level). Two approaches are adopted in this work. The first approach is to use feedforward deep neural networks (DNN) to fit all time steps and outputs in a single model. The second approach is to use long short-term memory (LSTM) to fit all time steps together for each reactor response separately. Both DNN and LSTM demonstrate very good performance in predicting the test and base-case scenarios, with accuracy as low as 92% and as high as 99%, where these test scenarios are unknown to the expert systems and are not included in the model training. In addition, both approaches demonstrate a significant reduction in computational costs, as the deep expert system is able to accurately predict the accident 100,000 times faster than the original simulation tool. Given sufficient data, the methodology adopted in this study demonstrates that DNN/LSTM expert systems can be used as a decision support system to model advanced time series phenomena within nuclear power plants with high accuracy and negligible computational costs.

42 ENGINEERING↗
DOE OSTI2021

Modelling yield cap evolution in sandstone based on brittle creep experiments

The Zenifim Formation is being considered as a potential disposal formation for a deep borehole nuclear repository concept in Israel. Site selection and repository construction are intended to ensure that waste is separated from circulating groundwater, but long-term deformation of the wellbore could potentially create fluid flow pathways. To understand how time-dependent rock strength could affect wellbore stability, here we conducted creep tests under low to moderate confining pressures on retrieved core from the Zenifim formation. During creep, samples strain slowly as gradual damage accumulation progressively weakens the samples. Failure eventually occurred through the near-instantaneous formation of a shear fracture. Experimental results were used to calibrate a continuum damage poro-elastic model for sandstones. The calibrated damage-poro-elastic model successfully simulates different types of loading experiments including quasi-static and creep. The state of strain in experiments is close to yield during loading as the yield cap continuously evolves with damage accumulation. For creep tests, most damage occurs during triaxial loading. Minor damage accumulation occurs under constant load until the final stage of creep, where damage accelerates and promotes unstable fracturing.

58 GEOSCIENCES↗
DOE OSTI2022

Interaction of beryllium with 316H stainless steel in molten Li 2 BeF 4 (FLiBe)

The increased demand in renewable energy resources has led to a renewed interest in nuclear reactors including a new generation of molten salt reactors. One of the issues encountered in handling of molten chloride or fluoride salts is the inability of metals to form and retain a protective oxide surface layer, generally chromium oxide. The low chromium content, nickel-based alloy INOR-8, later marketed as Hastelloy N, was specifically developed to contain molten fluorides. This alloy had some deficiencies, but its composition resulted in it incurring far less chromium depletion by the molten fluoride salts than alloys like 316 stainless steel. For the next generation of molten salt reactors, an alloy with pressure vessel code approval and higher temperature capability than Hastelloy N is required. Consequently, several reactor designers have reportedly chosen to build the reactor containment vessel from 316H stainless steel. In order to minimize corrosion of the stainless steel by the molten fluoride salt (2LiF-BeF 2 ), it is proposed to add beryllium metal to the salt to react with impurities and provide a means to lower the oxidation potential thus making the salt less corrosive. Even so, there is a concern whether the beryllium would react with components of the stainless steel. To address this concern, static capsule tests were conducted in which selected amounts of beryllium were added to capsules containing 2LiF-BeF 2 (FLiBe) salt and 316H stainless steel and Hastelloy N samples. Following exposure, the samples were cleaned and examined using a variety of analysis techniques including, optical microscopy, SEM-EDS, XPS, LIBS, XRD and EPMA. Tensile samples were also exposed in capsules, and those were subjected to tensile testing. Notably, It was found that for the level of beryllium additions used in this study, intermetallic compounds were formed which could be detrimental to the long-term performance of the 316H stainless steel.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Joint effects of climate, tree size, and year on annual tree growth derived from tree–ring records of ten globally distributed forests

Tree rings provide an invaluable long-term record for understanding how climate and other drivers shape tree growth and forest productivity. However, conventional tree-ring analysis methods were not designed to simultaneously test effects of climate, tree size, and other drivers on individual growth. This has limited the potential to test ecologically relevant hypotheses on tree growth sensitivity to environmental drivers and their interactions with tree size. Here, we develop and apply a new method to simultaneously model nonlinear effects of primary climate drivers, reconstructed tree diameter at breast height (DBH), and calendar year in generalized least squares models that account for the temporal autocorrelation inherent to each individual tree's growth. We analyze data from 3811 trees representing 40 species at 10 globally distributed sites, showing that precipitation, temperature, DBH, and calendar year have additively, and often interactively, influenced annual growth over the past 120 years. Growth responses were predominantly positive to precipitation (usually over ≥3-month seasonal windows) and negative to temperature (usually maximum temperature, over ≤3-month seasonal windows), with concave-down responses in 63% of relationships. Climate sensitivity commonly varied with DBH (45% of cases tested), with larger trees usually more sensitive. Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently reached maxima at intermediate DBH. Accounting for climate and DBH, growth rate declined over time for 92% of species in secondary or disturbed stands, whereas growth trends were mixed in older forests. These trends were largely attributable to stand dynamics as cohorts and stands age, which remain challenging to disentangle from global change drivers. By providing a parsimonious approach for characterizing multiple interacting drivers of tree growth, our method reveals a more complete picture of the factors influencing growth than has previously been possible.

generalized least squares (GLS)↗
DOE OSTI2020

Plug-In Electric Vehicle Showcases: Consumer Experience and Acceptance

In 2016 the U.S. Department of Energy's (DOE) Office of Energy Efficiency and Renewable Energy's Vehicle Technologies Office (VTO) announced three awardees to hold plug-in electric vehicle (PEV) showcases to demonstrate available technologies and provide a hands-on consumer experience at conveniently located, brand-neutral settings. The events varied in style from long term stationary storefront settings to weekend events at a variety of regional venues. Attendees could interact with the technology through ride-and-drives and longer-term test drives. The events began in the spring of 2017 and continued through 2019.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

2022 Long-Term Hydrologic Monitoring Program Report for the Rio Blanco, Colorado Site

This report presents the monitoring data collected by the U.S. Department of Energy (DOE) Office of Legacy Management (LM) during the 2022 sampling event at the Rio Blanco, Colorado, Site, where an underground nuclear test was conducted in 1973. The test resulted in residual radionuclide contamination at the detonation depth. The 2022 sampling event included the collection of samples from onsite groundwater wells to monitor for any potential contamination that might be attributed to the Rio Blanco nuclear tests. This report summarizes the laboratory results obtained from the sampling along with the historical results since monitoring began in the 1970s. This annual report and previous reports are available on the LM public website at https://www.energy.gov/lm/rio-blanco-colorado-site. Data collected during this and previous monitoring events are available on the Geospatial Environmental Mapping System (GEMS) website at https://gems.lm.doe.gov/#site=RBL.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Low-Yield Nuclear Monitoring (LYNM) Experimental Science Plan

The Low-Yield Nuclear Monitoring (LYNM) Program is a long-term NNSA research and development effort designed to improve the United States’ explosion monitoring capabilities, particularly with respect to low-yield and potentially evasive underground nuclear testing. The LYNM Program focuses on researching, discovering, and exploiting unique and useful signatures, from all available technologies and sensors (e.g., seismic, acoustic, electromagnetic, gases, and particulates (both stable and radioactive)). Four Department of Energy laboratories participate in LYNM and together are referred to as the ‘quad-lab’. The R&D program execution is performed under NNSA defined structures known as “ventures”. Four science ventures were established: 1) Explosion Source Functions; 2) Containment of Low-Yield Underground Tests; 3) Local Signatures; 4) Dynamic Monitoring Networks. To organize and execute the large field scale experiment a fifth venture was established: 5) Physics Experiment One (PE-1). As part of the LYNM Program, a series of experiments are planned at various scales and levels of venture involvement. These vary from those that involve a subset of labs and/or LYNM ventures (e.g., small experiments), to full quad-lab LYNM Program field-scale integrated experiments. Such experiments may involve chemical explosions with tracer materials or other means of simulating the expected signals from a nuclear explosion. The LYNM Program does not conduct actual nuclear explosions. Since 1992, the U.S. has observed a moratorium on underground nuclear explosions. This document is intended to provide the underlying scientific basis for the LYNM planned experimental work. Each specific LYNM experiment will develop a goals, objectives, and requirements (GOR) plan following the guidance in this document. The LYNM technical staff will define the numbers and types of experiments required over the course of the Program based on technical needs and within funding constraints. As with any scientific experiment series, the number and types of experiments may change based upon the experimental results obtained. An experiment that agrees with models/codes/software signature predictions may need fewer repetitions/variations, depending upon the level of statistical rigor desired, as compared to one in which the predictions and experimental data do not match. The large LYNM field-scale integrated experiments require the longest lead-time for planning, and these are discussed in more detail near the end of this document.

58 GEOSCIENCES↗
DOE OSTI2022

Modeling Chemo-Mechanics with Electrolyte Infiltration to Quantify Degradation of Cathode Particles

One of the main goals in modeling lithium-ion batteries is to improve/predict longevity and resilience of new chemistries. To that end, this talk investigates the formation of stress-induced fracture within polycrystalline cathode particles and the impact on capacity loss. Physically based cathode aging dynamics is simulated in a 3D, continuum-level chemo-mechanical model. The model captures anisotropic Li diffusion within a single polycrystalline particle comprised of hundreds to thousands of randomly oriented grains. A recent addition to this model includes electrolyte infiltration, which occurs when the electrolyte seeps into surface cracks within the particle. The model predicts that particle fracture is primarily due to non-ideal grain interactions with slight dependence on high-rate charge demands. Essentially, when neighboring grains are misaligned, they expand a different rates relative to one another leading to high stresses and ultimately the formation of intraparticle cracks. The model predicts that small particles with large grains develop significantly less damage than larger particles with small grains. Finally, the model predicts most of the chemo-mechanical damage accumulates in the first charge after formation. This chemo-mechanical "damage saturation" effect indicates that initial particle fracture occurs within the first few cycles, while long-term cathode degradation is not solely chemo-mechanically induced. The principle contribution of this research is the use of an anisotropic chemo-mechanical model to test how particle geometry affect capacity fade, which predicts that particle size has a stronger effect on capacity fade than grain size and ultimately that small particles with large grains have the least capacity fade.

cathode↗
DOE OSTI2022

Development Of Thermodynamic and Kinetic Simulation Tools and Testing Procedures for Enhanced Durability of Concrete Containing Industrial By-Products

This project developed screening tools that enable evaluation of alternative cementitious binders that create concretes to significantly reduce energy and emissions while remaining cost competitive on both initial and long-term costs. The team began with the viewpoint that acceptance of new cementitious binder products has a substantially greater chance of successful implementation when capital investment is not excessive and the end product has customers that have experience and resources to use this. As such, a binder system that is based on portland cement with blended using industrial by-products (alternative cementitious materials) has the potential for dramatic and meaningful impact. The team has focused on developing implementable solutions in specifications and current practice. This however requires three main factors: 1) ability to screen byproducts and alternative materials for success, 2) ability to ‘treat’ materials chemically to enhance kinetics, and 3) ability to provide predictions of performance of both binders and concrete from first principles. The project developed/refined a state of the art and scientifically based screening test for SCM called the pozzolanic reactivity test. The team developed kinetic models to simulate these materials as well as experimental approaches to alter selected reactions. Simulation tools were developed that enable the performance of concrete to be predicted based on the chemistry and reactivity of the cement and alternative SCM. Specifically, this project: • enhanced the kinetic reactivity models for use in multi-scale computational programs that use thermodynamics to predict reaction products. 2 • developed scaling models to extend thermodynamic modeling to link these models with pore structure. This enables strength, transport property, and coupled transport prediction. • developed tools to predict performance of cementitious materials using the pozzolanic reactivity test and chemical composition. The predicted properties are consistent with AASHTO R101 and the CEB-FIP model code and can be measured using associated test procedures. • demonstrated mechanical and fracture based modeling tools that thermodynamic predictions and inputs to predict concrete service life. These results have been used to demonstrate the value of enabling specifications to include ASTM C 595 cement as well ASTM C150 cement. In addition, these products are being used to expedite the evaluation of alternative SCM to aide in determining which materials have potential value and what ‘compositions’ of blended cements merit further investment.

42 ENGINEERING↗