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At least 631 records · Page 35

Modeling of stress/strain behavior of fiber-reinforced ceramic matrix composites including stress redistribution

A computational simulation procedure is presented for nonlinear analyses which incorporates microstress redistribution due to progressive fracture in ceramic matrix composites. This procedure facilitates an accurate simulation of the stress-strain behavior of ceramic matrix composites up to failure. The nonlinearity in the material behavior is accounted for at the constituent (fiber/matrix/interphase) level. This computational procedure is a part of recent upgrades to CEMCAN (Ceramic Matrix Composite Analyzer) computer code. The fiber substructuring technique in CEMCAN is used to monitor the damage initiation and progression as the load increases. The room-temperature tensile stress-strain curves for SiC fiber reinforced reaction-bonded silicon nitride (RBSN) matrix unidirectional and angle-ply laminates are simulated and compared with experimentally observed stress-strain behavior. Comparison between the predicted stress/strain behavior and experimental stress/strain curves is good. Collectively the results demonstrate that CEMCAN computer code provides the user with an effective computational tool to simulate the behavior of ceramic matrix composites.

Mital, Subodh K.↗

Dynamic fracture of tantalum under extreme tensile stress

The understanding of fracture phenomena of a material at extremely high strain rates is a key issue for a wide variety of scientific research ranging from applied science and technological developments to fundamental science such as laser-matter interaction and geology. Despite its interest, its study relies on a fine multiscale description, in between the atomic scale and macroscopic processes, so far only achievable by large-scale atomic simulations. Direct ultrafast real-time monitoring of dynamic fracture (spallation) at the atomic lattice scale with picosecond time resolution was beyond the reach of experimental techniques. We show that the coupling between a high-power optical laser pump pulse and a femtosecond x-ray probe pulse generated by an x-ray free electron laser allows detection of the lattice dynamics in a tantalum foil at an ultrahigh strain rate of Embedded Image ~2 × 10 8 to 3.5 × 10 8 s -1 . A maximal density drop of 8 to 10%, associated with the onset of spallation at a spall strength of ~17 GPa, was directly measured using x-ray diffraction. The experimental results of density evolution agree well with large-scale atomistic simulations of shock wave propagation and fracture of the sample. Our experimental technique opens a new pathway to the investigation of ultrahigh strain-rate phenomena in materials at the atomic scale, including high-speed crack dynamics and stress-induced solid-solid phase transitions.

36 MATERIALS SCIENCE↗

Mechanistic Study of Delamination Fracture in Al-Li Alloy C458 (2099)

Delamination fracture has limited the use of lightweight Al-Li alloys. In the present study, electron backscattered diffraction (EBSD) methods were used to characterize crack paths in Al-Li alloy C458 (2099). Secondary delamination cracks in fracture toughness samples showed a pronounced tendency for fracture between grain variants of the same deformation texture component. These results were analyzed by EBSD mapping methods and simulated with finite element analyses. Simulation procedures include a description of material anisotropy, local grain orientations, and fracture utilizing crystal plasticity and cohesive zone elements. Taylor factors computed for each grain orientation subjected to normal and shear stresses indicated that grain pairs with the largest Taylor factor differences were adjacent to boundaries that failed by delamination. Examination of matching delamination fracture surface pairs revealed pronounced slip bands in only one of the grains bordering the delamination. These results, along with EBSD studies, plasticity simulations, and Auger electron spectroscopy observations support a hypothesis that delamination fracture occurs due to poor slip accommodation along boundaries between grains with greatly differing plastic response.

Tayon, W. A.↗

Development of Nanoparticle-Stabilized Foams to Improve Performance of Water-less Hydraulic Fracturing

We have successfully created ultra dry carbon-dioxide-in-water and nitrogen-in-water foams (with water content down to 2-5% range), that are remarkably stable at high temperatures (up to 120 deg, C) and pressures (up to 3000psi) and viscous enough (100-200 cP tunable range) to carry proppant. Two generations of these ultra-dry foams have been developed; they are stabilized either with a synergy of surfactants and nanoparticle, or just with viscoelastic surfactants that viscosify the aqueous phase. Not only does this reduce water utilization and disposal, but it minimizes fluid blocking of hydrocarbon production. Further, the most recent development shows successful use of environmentally friendly surfactants at high temperature and pressure. We pay special attention to the role of nanoparticles in stabilization of the foams, specifically for high salinity brines. The preliminary numerical simulation for which shows they open wider fractures with shorter half-length and require less clean-up due to minimal water use. We also tested the stability and sand carrying properties of these foams at high pressure, room temperature conditions in sapphire cell. We performed on a preliminary numerical investigation of applicability for improved oil recovery applications. The applicability was evaluated by running multiphase flow injection simulations in a case-study oil reservoir. The results of this research thus expand the options available to operators for hydraulic fracturing and can simplify the design and field implementation of foamed fracturing fluids.

36 MATERIALS SCIENCE↗

THE ROLE OF FRACTURE PROPERTIES ON LAP JOINT STRENGTH OF FRICTION STIR WELDED AA7055-T6 SHEETS

Friction stir lap welded (FSLW) joints have weight-saving potential in aluminum-intensive automotive assembly. However, FSLW also modifies the material microstructure close to the joint. Optimizing the FSLW process requires understanding the relationship between the strength and the joint's microstructure. In previous studies, efforts have been dedicated to determining the effects of local softening, the shape of the oxide line, and porosity. However, the impact of changes to the fracture properties on the joint's strength has not been studied. In this work, strength testing, and simulations, aided by material characterization, were used to determine the role of fracture properties on the shear strength of a 3-sheet (aluminum alloys 7055-7055-6022) lap joint. Characterization involved testing for fracture properties in the weld region. This data was then implemented into finite element simulations. As a result, the joint strength was predicted with a deviation of less than 6% from the experimental value. Comparison with strength prediction using only the base metal properties indicates that fracture property in the nugget region determines the strength of AA7055 FSLW.

Finite element analysis, Friction stir welding, ma↗

Flowback Test Analyses at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) Site

Abstract In 2017 and 2019, injection testing was carried out in three zones in a vertical well in granite at the Frontier Observatory for Research in Geothermal Energy site near Milford, Utah, USA. In several injection cycles, flowback was implemented rather than shut-in. The goal was to explore an alternative to prolonged shut-in periods for inferring closure stress, formation compressibility, and formation permeability (permeability thickness product). The flowback procedures involved a cyclic flowback/shut-in, while pressure decreased. The flowback data are presented, and analyses are shown. The inferred closure stress(es) from flowback analyses are lower than for equivalent injection cycles that were strictly shut-in. Relatively high formation compressibility obtained from the flowback analyses indicates an extensive, fractured system. This study also includes numerical simulation of the flowback events. The numerical model shows that the rebound pressure is not necessarily the lower bound of the minimum principal stress. The signature of stiffness change can be identified as the process when the depletion mainly transitions from hydraulic fracture to natural fractures from numerical analysis. Overall, flowback potentially has advantages over shut-in because of the reduced time to closure.

15 GEOTHERMAL ENERGY↗

Osmotic Pressure Gradient Effects on Water Diffusion in Porous Rock: Can They Pervert Permeability Tests?

Abstract Generation of a large network of hydraulic cracks is of key importance not only for the success of fracking of shale but also for the recent scheme of sequestration of CO2 in deep formations of basalt and peridotite, which are mafic and ultramafic rocks that combine chemically with CO2. In numerical simulation of the creation of a fracture network in porous rock, an important goal is to enhance the rock permeability. The objective of this article is to calculate the effect of osmotic pressure gradients caused by gradients of concentration of the ions of Ca, Mg, Na, etc. on the effective permeability of the rock. The basic differential equations are formulated, and their explicit solutions for appropriate initial and boundary conditions are obtained under certain plausible simplifications. The main result is explicit approximate formulas for the critical time before which no water permeation through a test specimen can be observed. Depending on various parameters, this time can be unacceptably long, which is manifested as a zero water outflow. The solution may also explain the unreasonably small permeability values reported for some shales.

Mechanics↗

Numerical Modeling of CO 2 and Brine Leakage through Open Fracture in a Fault Zone: Open Channel Flow or Darcy Flow

Understanding fluids migration and leakage risk along the fault zone is necessary to guarantee the safety of CO 2 geological storage. The validity of Darcy’s law gets challenged in dealing with the flow in open fractures since the occurring of turbulence flow. In this study, we develop a 2D model with usage of T2Well, an integrated wellbore-reservoir simulator, to investigate the leakage problem along open fractures which are embedded in a fault zone from the deep injection reservoir to shallow aquifers. The results record a positive feedback of gas expansion and pressure response in fracture, which causes a quick downward propagation of highly gas saturated zone from the top of fracture and an easy gas breakthrough in the shallower aquifers. The decreasing of aperture size of fracture significantly enhances the leakage rates in fracture, but with less influences as aperture increases. In comparison, the Equivalent Porous Media models show a good approximation with the momentum model of large apertures but poor for the small one. Nevertheless, the differences are small in terms of final CO 2 distribution among various aquifers, suggesting that Darcy’s law may be still “effective” in solving flow problem along fractures in a constant injection system at a large time scale.

58 GEOSCIENCES↗

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells - increasing or decreasing the fluid flow rates across the wells - and drilling new wells at appropriate locations. The latter is expensive, time-consuming, and subject to many engineering constraints, but the former is a viable mechanism for periodic adjustment of the available fluid allocations. Data and supporting literature from a study describing a new approach combining reservoir modeling and machine learning to produce models that enable strategies for the mitigation of decreased heat and power production rates over time for geothermal power plants. The computational approach used enables translation of sets of potential flow rates for the active wells into reservoir-wide estimates of produced energy and discovery of optimal flow allocations among the studied sets. In our computational experiments, we utilize collections of simulations for a specific reservoir (which capture subsurface characterization and realize history matching) along with machine learning models that predict temperature and pressure timeseries for production wells. We evaluate this approach using an "open-source" reservoir we have constructed that captures many of the characteristics of Brady Hot Springs, a commercially operational geothermal field in Nevada, USA. Selected results from a reservoir model of Brady Hot Springs itself are presented to show successful application to an existing system. In both cases, energy predictions prove to be highly accurate: all observed prediction errors do not exceed 3.68% for temperatures and 4.75% for pressures. In a cumulative energy estimation, we observe prediction errors that are less than 4.04%. A typical reservoir simulation for Brady Hot Springs completes in approximately 4 hours, whereas our machine learning models yield accurate 20-year predictions for temperatures, pressures, and produced energy in 0.9 seconds. This paper aims to demonstrate how the models and techniques from our study can be applied to achieve rapid exploration of controlled parameters and optimization of other geothermal reservoirs. Includes a synthetic, yet realistic, model of a geothermal reservoir, referred to as open-source reservoir (OSR). OSR is a 10-well (4 injection wells and 6 production wells) system that resembles Brady Hot Springs (a commercially operational geothermal field in Nevada, USA) at a high level but has a number of sufficiently modified characteristics (which renders any possible similarity between specific characteristics like temperatures and pressures as purely random). We study OSR through CMG simulations with a wide range of flow allocation scenarios. Includes a dataset with 101 simulated scenarios that cover the period of time between 2020 and 2040 and a link to the published paper about this project, where we focus on the Machine Learning work for predicting OSR's energy production based on the simulation data, as well as a link to the GitHub repository where we have published the code we have developed (please refer to the repository's readme file to see instructions on how to run the code). Additional links are included to associated work led by the USGS to identify geologic factors associated with well productivity in geothermal fields. Below are the high-level steps for applying the same modeling + ML process to other geothermal reservoirs: 1. Develop a geologic model of the geothermal field. The location of faults, upflow zones, aquifers, etc. need to be accounted for as accurately as possible 2. The geologic model needs to be converted to a reservoir model that can be used in a reservoir simulator, such as, for instance, CMG STARS, TETRAD, or FALCON 3. Using native state modeling, the initial temperature and pressure distributions are evaluated, and they become the initial conditions for dynamic reservoir simulations 4....

15 GEOTHERMAL ENERGY↗

Predictive Data-driven Platform for Subsurface Energy Production

Subsurface energy activities such as unconventional resource recovery, enhanced geothermal energy systems, and geologic carbon storage require fast and reliable methods to account for complex, multiphysical processes in heterogeneous fractured and porous media. Although reservoir simulation is considered the industry standard for simulating these subsurface systems with injection and/or extraction operations, reservoir simulation requires spatio-temporal “Big Data” into the simulation model, which is typically a major challenge during model development and computational phase. In this work, we developed and applied various deep neural network-based approaches to (1) process multiscale image segmentation, (2) generate ensemble members of drainage networks, flow channels, and porous media using deep convolutional generative adversarial network, (3) construct multiple hybrid neural networks such as convolutional LSTM and convolutional neural network-LSTM to develop fast and accurate reduced order models for shale gas extraction, and (4) physics-informed neural network and deep Q-learning for flow and energy production. We hypothesized that physicsbased machine learning/deep learning can overcome the shortcomings of traditional machine learning methods where data-driven models have faltered beyond the data and physical conditions used for training and validation. We improved and developed novel approaches to demonstrate that physics-based ML can allow us to incorporate physical constraints (e.g., scientific domain knowledge) into ML framework. Outcomes of this project will be readily applicable for many energy and national security problems that are particularly defined by multiscale features and network systems.

58 GEOSCIENCES↗

Engineering the Interface: Advanced Surface Technologies for Lunar Dust Management and Equipment Longevity

Through the Artemis program, NASA intends to develop a sustainable human foothold on the Moon, ultimately paving the way for crewed exploration of Mars. The Moon's hostile environment poses numerous obstacles, including exposure to radiation, temperature extremes, micrometeoroid threats, and particularly the persistent problem of lunar dust. Lunar dust impacts nearly every aspect of surface operations through adhesion and abrasion mechanisms, with contamination from anthropogenic activities (landing, rovers) far outweighing natural phenomena. Multiple adhesion pathways contribute to surface contamination in the lunar environment, including van der Waals forces, electrostatic forces, chemical reaction, and magnetic forces from elemental iron deposits. Sharp asperities from micrometeoroid bombardment and atmospheric absence increase interaction potential and enable mechanical interlocking. Low cohesion between dust particles exacerbates these challenges, as minimal interaction potential between dust and nearby surfaces overcomes particle cohesion, causing contamination. Lunar dust adhesion mitigation technologies can be categorized as either active, requiring external energy, or passive, relying on intrinsic material properties. Ultrasonic and electrodynamic technologies have been developed to the highest technology readiness level for active approaches. Passive strategies primarily focus on surface chemistry and topography modifications. At NASA Langley Research Center, approaches include surface migration agents to reduce surface energy, topographical modification using laser ablation patterning, and tailored surface conductivity to reduce intrinsic adhesion force. Performance has been evaluated using custom-built ultrasonic and centrifuge instruments. Plume-surface interactions from lunar landers can propel micrometer-sized particles at velocities up to 1000 m s-1.8 These particles pose risks to landers, habitats and infrastructure, leading to erosion, degradation, and reduced component lifespan. A panel recovered from Surveyor III was determined to have been severely abraded because of lunar dust displaced from the Apollo 12 lunar module that landed 160 m away. The performance of metallic surfaces has been evaluated via high velocity single particle impact using the laser-induced project impact test (LIPIT) facility at the University of Utah. Peridynamics modeling, a form of continuum mechanics that uses a nonlocal approach enabling greater simulation capabilities of crack initiation and fracture, has also been utilized to gain greater insight into material response during impact events. Lunar dust contamination challenges extend to power generation systems and moving equipment. Cables, rotation stages, and other mechanisms may experience limited range of motion and reduced lifetime due to dust infiltration. NASA Langley Research Center has evaluated traditional aerospace alloys, softgoods, wear resistant ceramics, and several polymer and polymer composite materials. Test methods have included traditional techniques like Taber abrasion testing, as well as designed test configurations developed in the DUSTE (dust, ultraviolet radiation, and space thermal environmental) chamber that reproduce mechanism functions in operational environment. Beyond laboratory experiments, several flight experiments have been conducted. Materials were exposed to the low Earth orbit environment on the Materials International Space Station Experiment (MISSE) and to the lunar surface environment through the Aegis Aerospace Regolith Adherence Characterization (RAC) payload and the Honeybee Robotics PlanetVac payload. Determining lunar dust's impact on surface exploration and habitation requires comprehensive experimental and computational capabilities combined with lessons learned from initial lunar activities. Identifying the greatest environmental challenges and developing mitigation technologies provides the clearest path toward successfully, expeditiously, and efficaciously completing NASA's mission. This presentation will discuss ongoing efforts at NASA Langley Research Center and collaborator contributions to these critical objectives.

Surface Engineering↗

Optimization of Well Configuration for a Sedimentary Enhanced Geothermal Reservoir

The extraction of geothermal energy in the form of hot water from sedimentary rock formations could expand the current geothermal energy resources toward new regions. From previous work, we observed that sedimentary geothermal reservoirs with relatively low permeability would require the application of enhancement techniques (e.g., well hydraulic stimulation) to achieve commercial production/injection rates. In this paper we extend our previous work to develop a methodology to determine the optimum well configuration that maximizes the hydraulic performance of the geothermal system. The geothermal systems considered consist of one vertical well doublet system with hydraulic fractures, and three horizontal well configurations with open-hole completion, longitudinal fractures and transverse fractures, respectively. A commercial thermal reservoir simulation is used to evaluate the geothermal reservoir performance using as design parameters the well spacing and the length of the horizontal wells. The results obtained from the numerical simulations are used to build a response surface model based on the multiple linear regression method. The optimum configuration of the sedimentary geothermal systems is obtained from the analysis of the response surface model. The proposed methodology is applied to a case study based on a reservoir model of the Lyons sandstone formation, located in the Wattenberg field, Denver-Julesburg basin, Colorado.

15 GEOTHERMAL ENERGY↗

Investigating Performance of Geothermal Reservoirs With Bi-Directional Heat Transfer for Seasonal Thermal Storage Using Thermal-Hydraulic Reservoir Simulations

This paper presents initial simulation results of deep subsurface seasonal thermal storage of waste heat from a natural gas-fired power plant during the summer months for providing heating during winter months at the Cornell University main campus in Ithaca, New York. An injection temperature profile is calculated with the MEnU tool and numerical reservoir simulations are conducted with the simulator FALCON. Both a porous medium and large single fracture geothermal reservoir are considered at about 3 km depth with initial reservoir temperature of 75 degrees C. Simulations indicate that a much smaller reservoir - which is technically easier and less risky to develop - is sufficient when operating the reservoir for seasonal thermal storage instead of for continuous heat production. For example, storing 13 GWh of heat seasonally in a 100 m thick porous medium based on the Galway formation requires about 65 m of well spacing to limit the yearly variation in production temperature to 10 degrees C. Operating this reservoir for continuous heat production would require a well spacing of 365 m to limit the thermal decline to 10 degrees C after 10 years. Neglecting wellbore heat losses and assuming uniform and homogeneous properties, a round-trip thermal efficiency of 100% can be obtained if the yearly averaged injection temperature matches the initial reservoir temperature.

district heating↗

Progressive Fracture of Composite Structures

This report includes the results of a research in which the COmposite Durability STRuctural ANalysis (CODSTRAN) computational simulation capabilities were augmented and applied to various structures for demonstration of the new features and verification. The first chapter of this report provides an introduction to the computational simulation or virtual laboratory approach for the assessment of damage and fracture progression characteristics in composite structures. The second chapter outlines the details of the overall methodology used, including the failure criteria and the incremental/iterative loading procedure with the definitions of damage, fracture, and equilibrium states. The subsequent chapters each contain an augmented feature of the code and/or demonstration examples. All but one of the presented examples contains laminated composite structures with various fiber/matrix constituents. For each structure simulated, damage initiation and progression mechanisms are identified and the structural damage tolerance is quantified at various degradation stages. Many chapters contain the simulation of defective and defect free structures to evaluate the effects of existing defects on structural durability.

Minnetyan, Levon↗

Simulation and Analysis on Reactor Pressure Vessel (RPV) subjected to Pressurized Thermal Shock (PTS) under SBLOCA scenario by using Cardinal to support the fracture mechanics analyses

The structural components that comprise nuclear reactors and their supporting structures are subjected to harsh operating environments that can challenge their integrity, especially after exposure for extended durations or under accident condition. As one of the most significant components of a Reactor, the Reactor Pressure Vessel (RPV) is exposed to an aggressive environment during the operation time (e.g. more than 40 years). Ageing degradation mechanisms (e.g. thermos-fatigue) could grow initial defects up to a critical size, increasing the susceptibility to failure in the RPV. The conventional methods are mostly based on simple crack and structure geometries. Very limited studies consider the real conditions of the RPV subjected to a thermal shock due to a Loss of Coolant Accident (LOCA). During a LOCA event, the most severe conditions take place when the emergency core cooling (ECC) water is injected inside the cold legs filled initially with hotter water and/or steam. The rapid cooling of the down-comer and the internal RPV surface followed probably by re-pressurization of the RPV causes large temperature gradients and variation of pressure which induces thermal-mechanical stresses. In order to develop the model for integrity assessment of a reactor pressure vessel (RPV) subjected to pressurized thermal shock (PTS), a multi-physics simulation, which includes the thermo-hydraulic, thermo-mechanical and fracture mechanics analyses is necessary. The multi-physics simulations are performed using Cardinal, a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and other multi-physics sub-modules within the MOOSE framework. Cardinal now fully supports MOOSE stochastic perturbations of NekRS models with varying boundary conditions, initial conditions, material properties, and any other quantity which is defined by a kernel (such as coefficients in a momentum source model). The implementation is designed in a flexible manner so that scalar values are sent from MOOSE into a user scratch space in NekRS, which can then be applied for any purpose within the NekRS case files (both on the host and device). When modeling PTS, several factors can impact the results significantly. In this report, the impacts of the geometry of the model, Reynolds number and buoyancy effect are investigated. Two geometry, i.e., a simplified model and a realistic RPV model, with both laminar and turbulent flow condition are adopted for the PTS simulation with and without buoyancy effect. The purpose of the investigation is to understand the impact of these factors on the prediction of temperature history of RPV. The accurate prediction on the temperature evolution, which will be exported to Grizzly code for further analyses on the progression of aging mechanisms and their effects on the integrity of RPV structures, is very crucial. Based on the understanding of these factors, a more sophisticated model is built to analysis the PTS under SBLOCA scenario. A literature survey is conducted to pick the SBLOCA scenario for the multi-physics simulation. The analysis helps to explain the form and the transformation of the cold plum when the ECC is activated under SBLOCA. This model can be can be applied to study the PTS effect for different RPV configurations. The results can help to assess structural component degradation for advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Prediction and Monitoring Systems of Creep-Fracture Behavior of 9Cr-1Mo Steels for Teactor Pressure Vessels

A recent workshop on next-generation nuclear plant (NGNP) topics underscored the need for research studies on the creep fracture behavior of two materials under consideration for reactor pressure vessel (RPV) applications: 9Cr-1Mo and SA-5XX steels. This research project will provide a fundamental understanding of creep fracture behavior of modified 9Cr-1Mo steel welds for through modeling and experimentation and will recommend a design for an RPV structural health monitoring system. Following are the specific objectives of this research project: Characterize metallurgical degradation in welded modified 9Cr-1Mo steel resulting from aging processes and creep service conditions; Perform creep tests and characterize the mechanisms of creep fracture process; Quantify how the microstructure degradation controls the creep strength of welded steel specimens; Perform finite element (FE) simulations using polycrystal plasticity to understand how grain texture affects the creep fracture properties of welds; Develop a microstructure-based creep fracture model to estimate RPVs service life; Manufacture small, prototypic, cylindrical pressure vessels, subject them to degradation by aging, and measure their leak rates; Simulate damage evolution in creep specimens by FE analyses; Develop a model that correlates gas leak rates from welded pressure vessels with the amount of microstructural damage; Perform large-scale FE simulations with a realistic microstructure to evaluate RPV performance at elevated temperatures and creep strength; Develop a fracture model for the structural integrity of RPVs subjected to creep loads; and Develop a plan for a non-destructive structural health monitoring technique and damage detection device for RPVs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗