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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Climate induced microbiome alterations increase cadmium bioavailability in agricultural soils with pH below 7

Climate change and metals independently stress soil microbiomes, but their combined effects remain unresolved. Here we show that future climate affects soil cadmium through altered soil microbiome and nutrient cycles, with soil pH as critical factor. In soils with pH<7 and during summer temperatures, future climate increased porewater cadmium, shifting total and potentially active taxonomic microbiome structures. Microbial ammonium oxidation released protons liberating cadmium through cation exchange from mineral surfaces. When porewater cadmium levels became toxic to non-cadmium-tolerant bacteria, microbial activity, and nutrient cycling decreased, reducing carbon and nitrogen emissions. In contrast, pH>7 soil show no climate impacts on cadmium mobilization, though imprints on microbiome structure were apparent. Subsequent nutrient cycling increased under future climate, stimulating soil respiration and nitrous oxide release. These findings underscore complex interactions between climate change and soil contaminants affecting the soil microbiome and its activity and highlights potential impacts on crop production, groundwater quality, and climate feedback.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Chemomechanical effect of reduced graphene oxide encapsulation on hydrogen storage performance of Pd nanoparticles

Primary chemomechanical impacts of confinement on hydrogen storage performance are studied using a nanolaminate structure where reduced graphene oxide (rGO) encapsulates palladium (Pd) nanoparticles. Three contributing factors are identified that can alter the reaction enthalpy: nanosizing, chemical interaction with the encapsulant, and mechanical stress induced strain from a combination of clamping force and lateral pulling force exerted on the Pd nanoparticles. The mechanical contributions are quantified by combining transmission electron microscopy, ab initio computation, and continuum elasticity theory, from which the encapsulation is found to exert an additional strain of 4.96% and 2.99% before and after hydrogen absorption, respectively, increasing the Pd and Pd hydride (PdH x ) reaction enthalpy by 1.3–2.8 kJ (mol H 2 ) -1 . The effect of the chemical interaction with rGO also raises the reaction enthalpy by up to 1.6 kJ (mol H 2 ) -1 , while the nanosizing effect decreases the reaction enthalpy. The three contributing factors to the reaction enthalpy are found to be similar in magnitude, where the net effect is in agreement with the measured enthalpy increase of 3.7 kJ (mol H 2 ) -1 from the bulk value. Hydrogen absorption kinetics and capacity also improved, which is attributed to facile nucleation of the hydrogen-rich phase enabled by the inhomogeneous strain distribution over the encapsulated PdHx nanoparticles. These results demonstrate that the chemomechanical effect can be controlled in the nanolaminate structure, providing an ideal template for tuning hydrogen storage performance.

08 HYDROGEN↗
DOE OSTI2021

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗
DOE OSTI2021

Assessing the ASME Section III, Division 5, Class A Primary Load Design Rules Against Creep Notch Effects

This report assesses the ASME Section III, Division 5, Subsection HB, Subpart B rules covering the design and construction of high temperature Class A nuclear reactor components for their robustness against creep notch effects. The creep notch effect combines the effect of multiaxial stresses on material creep deformation and damage. This report considers both effects, including the potential for creep mechanism shifts affecting the extrapolation of design data from high stress, short-time experimental data to low stress, long time operating component conditions. The report summarizes the history of and literature on multiaxial creep and surveys the current ASME design rules dealing with multiaxial effects. The report then describes the results of two dedicated numerical studies, one assessing the robustness of the ASME rules against uncertainty in extrapolating from uniaxial creep test data to multiaxial component conditions and a second study examining the potential effects of a mechanism shift from high stress, dislocation-mediated creep to diffusion-dominated creep at lower stresses. The final conclusion of the report is that the ASME rules adequately guard against multiaxial creep failure, though there are several aspects of the Code that could be optimized to provide less over-conservative design predictions or to provide a more consistent design margin as a function of temperature and stress. In a few areas, particularly the potential for mechanism shifts outside the currently-available experimental data, the Code rules should be revaluated as additional experimental data and new modeling and simulation results become available

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Network Models of Active Degradation Mechanisms and Pathways for Service Life Prediction of Indoor and Outdoor PV Modules

ct: PV service lifetime prediction (SLP) enables accurate calculation of levelized cost of energy (LCOE), which is crucial to rationalizing PV investment and installation. However, SLP is challeging since PV reliability in the field is affected by many combined factors, including various environmental stresses and module quality. In order to map out the active degradation mechanisms and pathways that best resemble real world conditions, we introduce the framework of a study protocol and use network models fitted to data, to enable analysis and SLP of complex PV systems with multiple active degradation mechanisms. The study protocol is the experimental design, including module variants and different exposure conditions, selection of evaluation methods, time-series data acquisition and training of network models to these data. We present SLP of minimodules in the lab and PV systems in the field. For lab SLP, minimodules with 8 variants based on manufacturer, architecture, and encapsulation were prepared and aged in modified damp heat with or without full spectrum light exposure. Stepwise I-V and Suns-Voc data acquisition tracks changes in electrical properties including Rs,IV, Isc,IV, Vmp,PIV providing insights into power loss of minimodules. Network structural equation modeling (netSEM) was utilized to construct degradation pathway models that identify active degradation mechanisms and predict power loss over time. For field SLP, datastreams of Pmp values and I-V curve datastreams of two types of modules installed in three distinctly different Köppen-Geiger climate zones for 9 years were acquired. With power loss modes corresponding to uniform current loss (ΔPIsc), recombination (ΔPVoc), series resistance (ΔPRs), and current mismatch (ΔPImis) determined, the performance loss rates (PLR) were determined using PVplr. We show how to establish a study protocol framework to ensure appropriate parametric variations and valid data collection from the variants of your complex systems. Then the data-driven netSEM model fitting provides a comprehensive mapping of multiple active degradation mechanisms, and accurate service life prediction.

network model, degradation, photovoltaic, solar↗
DOE OSTI2025

Self-healable Copolymer Composites for Extended Service H 2 Dispensing Hoses

In this project, we designed, synthesized and fabricated using X-winder technologies precommercialized novel, self-healingable commodity copolymer fiber-reinforced composites to extend the H 2 hose service life beyond the current target of 1000 fills. These studies demonstrated that these composites are able to withstand over 25,000 damage-repair cycles, which was the main objective of the proposed project, in the temperature range of -40 to +80 °C under variable pressures. When micro-cracks are formed after about 1,000 cycles/fueling per hose in the inner composite layer, these micro-cracks self-heal, thus extending the lifetime of a prototype inner layer of the hose. These composites were tested by exposure to H 2 fuel and demonstrated the ability to recover from mechanical damage. Thermomechanical testing combined with analysis of the stress and strain fields across the cross-section of the inner layer composite hoses also identified the ring-like stresses on the edge of inner layers arising from changes of the fiber winding angle directions from +45° to -45°. The developed novel concept that self-healing commodity copolymers can be used in the development of prototype composites for the extended service of H 2 dispensing hoses will have major implications for other energy-related technologies, where the extended service life in harsh environments is expected. In this project, we optimized, validated, and demonstrated novel copolymer fiber-reinforced composites for H 2 dispensing hose applications, which can be utilized in future manufacturing using commodity materials. The estimated cost of materials (exluding labor) is in the range of < $1.0/ft.

08 HYDROGEN↗
DOE OSTI2022

Sample Preparation and Experimental Design for In Situ Multi-Beam Transmission Electron Microscopy Irradiation Experiments

We discuss the need to understand materials exposed to overlapping extreme environments such as high temperature, radiation, or mechanical stress. When these stressors are combined there may be synergistic effects that enable unique microstructural evolution mechanisms to activate. Understanding of these mechanisms is necessary for the input and refinement of predictive models and critical for engineering of next generation materials. The basic physics and underlying mechanisms require advanced tools to be investigated. The in situ ion irradiation transmission electron microscope (I 3 TEM) is designed to explore these principles. To quantitatively probe the complex dynamic interactions in materials, careful preparation of samples and consideration of experimental design is required. Particular handling or preparation of samples can easily introduce damage or features that obfuscate the measurements. There is no one correct way to prepare a sample; however, many mistakes can be made. The most common errors and things to consider are highlighted within. The I 3 TEM has many adjustable variables and a large potential experimental space, therefore it is best to design experiments with a specific scientific question or questions in mind. Experiments have been performed on large number of sample geometries, material classes, and with many irradiation conditions. The following are a subset of examples that demonstrate unique in situ capabilities utilizing the I 3 TEM. Au nanoparticles prepared by drop casting have been used to investigate the effects of single ion strikes. Au thin films have been used in studies on the effects of multibeam irradiation on microstructure evolution. Zr films have been exposed to irradiation and mechanical tension to examine creep. Ag nanopillars were subjected to simultaneous high temperature, mechanical compression, and ion irradiation to study irradiation induced creep as well. These results impact fields including: structural materials, nuclear energy, energy storage, catalysis, and microelectronics in space environments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Acoustic-based monitoring and machine learning of component status for microreactor applications

This report provides a description and assessment of recent efforts to couple acoustic-based experimental measurements and characterization with machine learning models in order to enhance structural health monitoring capabilities for nuclear microreactors. With resilient embedded sensors in development by others supported by programs funded by the US Department of Energy’s Office of Nuclear Energy, the work described herein builds upon ongoing efforts to improve non-destructive testing technology that relates measured acoustic signatures to component stresses and/or structural defects, using a combination of new experimental measurements and machine learning architectures. The experimental procedure remained similar to that developed for the previous year’s demonstration of damage detection by the authors, with the same damaged sample tested under similar applied stress conditions. Notably, a new mounting fixture was designed and implemented to improve measurement consistency and a more sophisticated laser Doppler vibrometer was employed to make high-fidelity vibration measurements. Two nominally identical sets of training data were collected for each experimental setup to better understand the repeatability of the experiment and to better test the generality of trained neural network models. Additionally, we obtained new high-quality 3D mode shapes of the damaged test article at various stress and excitation levels, providing greater insights into the physical response of the sample during testing. Previously, we demonstrated that a machine learning model based on a convolutional neural network can predict structural details of an artificially introduced interface (intact, rough cut, smooth cut), and the applied torque level. In this study, we have transitioned to graph-based neural network architectures to better develop and test a flexible framework that is more suitable to being transferred away from controlled benchtop experiments and into more applied settings where less-structured data inputs may be expected. In general, performance testing of a graph neural network on frequency-domain representations of the data indicates strong and consistent identification of test conditions for datasets recorded on damaged components. With goals of predicting damage location and other changing experimental conditions using limited datasets, predictive models using a graph neural network architecture correctly predicted the applied torque level with an accuracy of 85% using only a single measurement point and predicted within one torque level in 95% of test windows. Predictions of damage location had limited success due to the symmetry and minimal number of the damage scenarios presented during model training. Results were ambiguous as to whether the model could detect the location of the artificial damage, or if it was instead learning the location of a given measurement point on the part and subsequently detecting which points were closest to the location of the damage. This finding will be factored into upcoming planned work on damaged graphite components, where new experimental tests with a larger number and variety of damage scenarios are expected to provide improved validation of recent developments in monitoring methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Experimental Investigation of Hydraulic Fracturing and Stress Sensitivity of Fracture Permeability Under Changing Polyaxial Stress Conditions

Understanding and predicting fracture propagation and subsequent fluid flow characteristics is critical to geoenergy technologies that engineer and/or utilize favorable geological conditions to store or extract fluids from the subsurface. Fracture permeability decreases nonlinearly with increasing normal stress, but the relationship between shear displacement and fracture permeability is less well understood. We utilize the new Geo–Reservoir Experimental Analogue Technology (GREAT cell), which can apply polyaxial stress states and realistic reservoir temperatures and pressures to cylindrical samples and has the unique capability to alter both the magnitude and orientation of the radial stress field by increments of 11.25° during an experiment. We load synthetic analogue materials and real rock samples to stress conditions representative of 500–1,000 m depth, investigate the hydraulic stimulation process, and then conduct flow experiments while changing the fluid pressure and the orientation of the intermediate and minimum principal stresses. High–resolution circumferential strain measurements combined with fluid pressure data indicate fracture propagation can be both stable (no fluid pressure drop) and unstable (fluid pressure drop). The induced fractures exhibit both opening and shear displacements during their creation and/or during fluid flow with changing radial stress states. Flow tests during radial stress field rotation reveal that fracture normal effective stress has first–order control on fracture permeability but increasing fracture offset can lead to elevated permeabilities at maximum shear stress. Here, the results have implications for our conceptual understanding of fracture propagation as well as fluid flow and deformation around fractures.

58 GEOSCIENCES↗
DOE OSTI2021

Dynamic flow stress of pure polycrystalline aluminum: Pressure-shear plate impact experiments and extension of dislocation-based modeling to large strains

The dynamic thermo-mechanical behavior of pure aluminum has attracted renewed interest lately due to experimental observations of an anomalous increase in Hugoniot Elastic Limit (HEL) at incipient plasticity and elevated temperatures in polycrystalline pure metals. In context of current dislocation-mediated plasticity models for metals, this increase in dynamic strength is indicative of a transition in the rate controlling mechanism for dislocation glide from being thermally assisted to phonon-drag restricted due to increase in phonon viscosity at elevated temperatures. Though these studies have helped to shed light on these important mechanisms operative in FCC metals at incipient plasticity, the extent to which they contribute to flow stress, particularly at larger strains, remains unclear. Here, we address these questions through a combined experimental and modeling effort focused on investigating the evolution of dynamic flow stress in polycrystalline aluminum using experimental data gathered from a series of combined pressure-and-shear plate impact (PSPI) experiments designed to reveal the flow stress of pure aluminum at strain rates ~ 10 5 /s, plastic strains of up to 40% and temperatures ranging from room to 866 K. In all cases, the flow stress of aluminum, as inferred from the measured transverse particle velocity histories at the free surface of an elastic tungsten carbide target plate, reveals saturation with increasing plastic strains at stress levels that decrease with increasing test temperatures. Numerical simulations are performed to correlate the experimentally observed temperature and strain rate dependence of flow stress at small and large plastic strains using the Austin-McDowell dislocation-mediated plasticity model parametrized to normal plate impact experiments conducted in an earlier study by Zaretsky and Kanel (2012). Extensions to the model are made to better represent dynamic behavior of pure aluminum at larger plastic strains as observed in elevated temperature split Hopkinson Pressure bar (SPHB) experiments of Samanta (1971) and Lindholm and Yeakly (1965), and the combined pressure-and-shear plate-impact experiments conducted in the present study. The main theoretical extension to the Austin-McDowell model made in this paper is the introduction of a new rate- and temperature- dependent dynamic recovery function, which can potentially allow for an effective reduction in the rate of accumulation of dislocations at large plastic strains. The numerical predictions of the revised and re-calibrated plasticity model are brought into agreement with the experimental observations, correlating sufficiently well with dynamic yield stress at incipient plasticity and the flow stress levels at larger plastic strains, plastic strain rates in the range 10 3 – 10 6 /s, and elevated temperatures up to near melt. The model, in concert with the experimental measurements, suggests that at incipient plasticity the rate governing mechanism for plastic flow is phonon-drag restricted dislocation glide, whereas, at higher magnitudes of plastic strain, it transitions to stress-assisted thermally activated glide. The transition between these two rate governing mechanisms is controlled by the evolution of dislocations throughout the deformation process.

36 MATERIALS SCIENCE↗
DOE OSTI2023

FINITE ELEMENT MODEL MESH REFINEMENT EFFECTS ON QUALIFICATION OF NUCLEAR GRADE GRAPHITE COMPONENTS

The American Society of Mechanical Engineers (ASME) provides the full and simplified design-by-analysis probabilistic assessments for determining acceptance of nuclear grade graphite core components. The assessments can be characterized by three parts: (1) a component stress distribution, often determined by a finite element (FE) model; (2) a Weibull probability density function (pdf) that characterizes the experimental tensile strength distribution; and (3) the post-processor, which combines the FE model and the Weibull strength distribution in accordance with the full and simplified assessments to determine component acceptance. It is known that the level of mesh refinement in FE models can affect the modeled component’s calculated stress distribution. Depending on the component geometry, the stress distribution may converge with sufficient refinement. It was previously unknown whether the acceptance decision resulting from the full and simplified assessments might change even with sufficient mesh refinement. This study explores that question using experimental strength results for a dog-bone geometry for two graphite grades, IG-110 and PCEA. The simplified assessment has two criteria that must be met, the first limits the combined membrane stress by the allowable stress and the second limits the peak equivalent stress by the allowable stress scaled by the ratio of flexural to tensile strength. In the application of the simplified assessment, convergence of the peak equivalent stress required extreme mesh refinement, however, the acceptance decision was not affected. It is hypothesized that more complex geometries with stress concentrations may present mesh refinement effects on the simplified assessment acceptance decision. Mesh refinement did affect the acceptance decision in the full assessment for the applied pressure loadings in this study. This work suggests component stress distribution convergence is not a sufficient criteria for POF convergence in the full assessment and that mesh refinement should continue until the POF has converged, especially where the resulting POF is bordering the SRC acceptable POF limit.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Initial Field Testing in the Deep Subsurface for the Thermal Breakout Project for Measuring In Situ Stress

The current state-of-the-art technology for in situ stress measurements involves an integrated approach that combines borehole breakout observations, drilling-induced tensile fractures, and hydraulic fracturing tests (i.e., mini-fracs); however, this methodology has several limitations that often prevent successful in situ stress measurements. One major limitation is that breakouts do not appear in every borehole and are generally a natural occurrence that cannot easily be controlled. Because borehole breakouts are used to measure the maximum horizontal in situ stress magnitude, the absence of borehole breakouts presents a major data gap for in situ stress measurements. As a response to this data gap a new thermal breakout technology is being developed that will provide a method for thermally inducing borehole breakouts and obtaining consistent measurements of the maximum horizontal stress magnitude. This thermal breakout technology involves heating the borehole and increasing the thermoelastic compressive stress in the rock until a breakout develops, which is directly correlated to the maximum horizontal stress magnitude. An initial component of the thermal breakout project involves developing a prototype downhole tool and performing field testing in the deep subsurface. The primary objective of the initial tool development and field testing is to provide a physical proof of concept for the thermal breakout technology. Three thermal breakout field tests were performed at approximately 4850 feet deep in the Sanford Underground Research Facility. Each test was performed in a borehole that had been previously used for overcoring stress measurements. The third and final test successfully created two diametrically opposed breakouts after deploying the thermal breakout tool for approximately 3 hours of continuous heating. Post-analysis of the thermally induced breakouts confirmed that the thermal breakout orientation directly corresponds to the known in situ stress orientation and magnitude.

Voegeli, Sam↗
DOE OSTI2021

Stepwise Dynamic Calibration of a Hydromechanical Simulation Using Time-Lapse Vertical Seismic Profile

This study aims to develop a methodology for calibrating subsurface stress changes through time-lapse Vertical Seismic Profiling (VSP) integration. The selected study site is the 13-10A injector well within the ongoing CO2-EOR operation of the Farnsworth Field Unit. The Time-lapse VSP dataset carries the combined effects of fluid substitution and mean effective stress changes, thereby providing a dataset amenable for the calibration of production and injection-induced stress changes. The concept is similar to calibrating a reservoir simulation model in that the process honor real field data to set up an inverse problem. The solution optimizes the independent and impactful geomechanical parameters that replicate the observed time-lapse seismic velocity changes. This stress calibration is enabled by 4D geomechanical modeling and the VSP Integration workflow. This calibration benefits from extensive geological, geophysical and geomechanical characterization through 3D seismic data, geophysical well logs, and core assessed as part of the 1D MEM conducted on the 13-10A subject well. These data are used to develop a site-specific rock physics model. The Biot Gassmann workflow combines rock physics and reservoir simulation outputs to determine the fluid substitution contribution to seismic velocity change. Additionally, modeled seismic velocity attributed to mean effective stress are determined from the geomechanical simulation outputs, and the stress-velocity relationship developed from the ultrasonic seismic velocity measurements on the extracted Morrow B core. A penalty function is then formed between the modeled seismic velocities and the observed time-lapse VSP dataset. Four independent and impactful geomechanical parameters have been determined. These are the bulk modulus and shear modulus for zero porosity and the shear and compressional seismic velocity to mean effective stress derivatives. The dataset of numerous coupled hydromechanical- geomechanical simulation realizations is built by combining variations of the four stated geomechanical parameters. A machine learning-assisted workflow comprised of an artificial neural network and a particle swarm optimizer are used to converge on the optimal geomechanical parameters. The successful execution of this workflow has affirmed the suitability of acoustic time-lapse measurements for 4D-VSP geomechanical stress calibration pending measurable stress sensitivities within the anticipated effective stress changes and the availability of suitable and reliable datasets for petroelastic modeling.

02 PETROLEUM↗
DOE OSTI2020

Deterministic and Statistical Modeling of a New Thermal Breakout Technology for Measuring the Maximum Horizontal In-Situ Stress

The current state-of-the-art technology for in-situ stress measurements involves an integrated approach that combines borehole breakout observations, drilling-induced tensile fractures, and hydraulic fracturing tests (i.e., “mini-fracs”). This methodology has achieved wide application in the oil and gas industry but has several limitations that often prevent successful in-situ stress measurements. One major limitation is that breakouts do not appear in all boreholes and are generally only a natural occurrence that cannot easily be controlled. Because borehole breakouts are used to directly measure the maximum horizontal in-situ stress magnitude, the absence of borehole breakouts presents a major data gap for in-situ stress measurements. In response to this data gap, a new US Department of Energy (US DOE)-sponsored thermal breakout technology that will provide a method for thermally inducing borehole breakouts and allow the consistent measurement of the maximum horizontal stress magnitude is currently in development. This thermal breakout technology involves heating the borehole and increasing the thermoelastic compressive stress in the rock until a breakout develops, which can be directly correlated to the maximum horizontal stress magnitude. The first step in this project was an analytical modeling study of the thermal breakout process. Based on the Kirsch solution (Kirsch 1898), a deterministic and statistical analysis was performed on the pertinent parameters that influence the maximum horizontal stress calculation. As a result of the analysis, the findings indicate that the thermal breakout technology is feasible and provides improved accuracy and/or an enhanced ability to measure the maximum horizontal stress. Future work as part of this US DOE-sponsored project includes additional validation through more detailed numerical modeling, laboratory testing, and field testing of the thermal breakout technology.

58 GEOSCIENCES↗
DOE OSTI2021

Analytical models of the strength and ductility of CNT reinforced metal matrix nano composites under elevated temperatures

Carbon nanotubes (CNTs) can greatly enhance the strength of metal matrix composites while resulting in ductility loss. This strength-ductility tradeoff dilemma always confines the development of material design and real-life applications. Here in this work, a temperature dependent strengthening analytical model is proposed for CNT reinforced metal matrix composites which considers three common strengthening mechanisms: Orowan looping effect, thermal expansion mismatch effect, and load bearing effect. The proposed model can predict composite material strength with different volume fractions of CNTs and under different temperatures. Combining the strengthening model with the stress based modified Mohr-Coulomb (sMMC) ductile fracture model, a ductility analytical model is then derived. This ductility analytical model includes the influences of temperature, multi-axial stress loading conditions, as well as the aforementioned three strengthening mechanisms. A good agreement has been achieved between literature published experimental data and analytical predictions for both composite material strength and ductility loss. The proposed two analytical models can provide a straightforward way to study the strength-ductility relationship for CNT reinforced metal matrix composites over a wide range of temperatures and different stress states, and then provide guidance on new material design and processing.

36 MATERIALS SCIENCE↗
DOE OSTI2026

3D probabilistic fracture mechanics / computational fluid dynamics simulation of a reactor pressure vessel under transient conditions

Reactor pressure vessels (RPVs) are safety-critical light-water-reactor components that, under irradiation, experience long-term material degradation in the form of embrittlement. This can increase their susceptibility to fracture under thermal-shock conditions, which could occur during off-normal transients such as loss-of-coolant accidents (LOCAs). During a LOCA, the most severe conditions for the RPV occur when emergency core cooling water is injected through the cold legs into the water-and-steam-filled RPV. The rapid cooling of the downcomer and internal RPV surface causes decreased temperature and elevated thermally driven tensile stresses in the RPV wall. This, combined with long-term material embrittlement, may cause fracture initiation at pre-existing flaws, challenging the integrity of the RPV. Assessing RPV integrity during transients with a large spatial variation in the coolant temperature requires a modeling approach that considers the effects of spatially varying coolant temperature on the fracture probability of a population of flaws distributed throughout the RPV, accounting for spatially varying embrittlement. Here, the present study addresses this need by demonstrating first-of-its-kind coupling of a high-fidelity 3D computational fluid dynamics code with 3D probabilistic fracture mechanics This was accomplished using representative models of a pressurized-water reactor subjected to small- and medium-break LOCA conditions, both of which can result in large spatial temperature variations. While the observed impact of accounting for 3D effects was minimal under the small-break LOCA this study indicates a significant increase in the probability of fracture initiation under the medium-break LOCA when 3D effects are considered, relative to a spatially uniform cooling scenario.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Sequential versus Simultaneous Aging of XLPE Nuclear Cable Insulation Subjected to Elevated Temperature and Gamma Radiation

Electrical cables constitute a critical component of nuclear power generation. The aging behavior of electrical cable insulation under combined exposure to thermal and radiation stress is not additive, complicating lifetime prediction of cable performance based on sequential accelerated aging. In this work we explore the relative effects of simultaneous and sequential thermal and gamma radiation aging on cross-linked polyethylene (XLPE), which is commonly found in commercial nuclear power plants in the United States. Samples of XLPE were subjected to up to 320 kGy of gamma irradiation at a dose rate of 300 Gy/hr in two heating scenarios. In the first, simultaneously-aged samples were heated at 150°C during irradiation. In the second, sequentially aged samples were heated at 150°C for designated durations followed by corresponding periods of irradiation without heating. The mass, total color difference, and density were characterized to quantify aging of the insulation polymer. Sequential aging is hypothesized to be more damaging to XLPE insulation due to an increased trend in mass gain, total color difference, and density.

Cross-linked polyethylene, XLPE, nuclear cable, ac↗
DOE OSTI2021

Towards Validation of Advanced Accelerated Stress Testing Protocols through Failure Analysis and Materials Characterization

As the lifetime of photovoltaic modules increases toward the goal of 50 years, accelerated stress testing is critical to assessing the viability of newer, improved, and often cheaper materials in the field. However, the validation of accelerated testing to reproduce field failure has remained elusive. The recent developments of more advanced stress testing protocols utilizing sequential and combined stressors have provided another opportunity for validation. Using a suite of mechanical, chemical, and structural characterization methods we report the development of our approach using a known bad backsheet “AAA.” We then apply this approach to PVDF-based backsheets to further confirm the generalizability of this approach. The outcome of this work is two-fold: (1) validation of advanced accelerated testing protocols which will enable the prediction of field failures in new materials, and (2) deeper insights into the degradation mechanisms observed through the extensive characterization allowing for improved materials engineering and development.

accelerated aging↗