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At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Potential Formation Damage: An Integrated Reservoir Characterization Study of the Naturally Fractured Carbonate Middle Duperow Formation at the Kevin Dome, Montana

In this study, we integrate geologic and engineering data of a naturally fractured carbonate reservoir at the Kevin Dome, Montana. Well test data are correlated with core description, geochemical and lithology study to determine the flow behavior and communication within the injection test interval and to the surrounding area. Based on a dual-continuum geologic model, numerical brine injection simulations are carried out to validate the interpretation results from our well test analytical models and forecast the probability of CO 2 injection success using current reservoir properties. As a result, our well test analytical models as well as lithology/core description suggest that fluid flow may be mainly restricted to the injection interval and the assumption of radial (horizontal) flow may be appropriate. The well test models also indicate that there is potentially formation damage with a positive skin factor although prior to brine injection well tests, well stimulation through acid treatment was performed. Our numerical simulation results appear to confirm this formation damage by showing additional pressure buildup in the injection data during later test periods. To explain this, acid may have dissolved dolomite then dolomite or calcite may have been formed again further into the matrix/fracture system. Another possible explanation is mechanical clogging of the fractures due to acid dissolving dolomite and dislodging fine grains. Our work also predicts that if no additional well stimulation is performed, the project will have a lower probability of successfully injecting 1 million tons of CO 2 into the Middle Duperow formation over 4 years.

42 ENGINEERING↗
NASA NTRS2014

NDE and SHM Simulation for CFRP Composites

Ultrasound-based nondestructive evaluation (NDE) is a common technique for damage detection in composite materials. There is a need for advanced NDE that goes beyond damage detection to damage quantification and characterization in order to enable data driven prognostics. The damage types that exist in carbon fiber-reinforced polymer (CFRP) composites include microcracking and delaminations, and can be initiated and grown via impact forces (due to ground vehicles, tool drops, bird strikes, etc), fatigue, and extreme environmental changes. X-ray microfocus computed tomography data, among other methods, have shown that these damage types often result in voids/discontinuities of a complex volumetric shape. The specific damage geometry and location within ply layers affect damage growth. Realistic threedimensional NDE and structural health monitoring (SHM) simulations can aid in the development and optimization of damage quantification and characterization techniques. This paper is an overview of ongoing work towards realistic NDE and SHM simulation tools for composites, and also discusses NASA's need for such simulation tools in aeronautics and spaceflight. The paper describes the development and implementation of a custom ultrasound simulation tool that is used to model ultrasonic wave interaction with realistic 3-dimensional damage in CFRP composites. The custom code uses elastodynamic finite integration technique and is parallelized to run efficiently on computing cluster or multicore machines.

Leckey, Cara A. C.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-32227-DND

The ability of a recently proposed cohesive fatigue model to predict the initiation and propagation of skin/stiffener separation was evaluated using a three-point bend (3PB) configuration. The 3PB specimen consists of a quasi-isotropic laminate representing the skin of a fuselage. A shorter doubler representing the flange of a stiffener is co-cured at the center of the specimen. A simplified modeling technique was applied, in which the complex damage mechanisms involved in the separation, such as delamination migration, matrix cracking, bridging, and crack delving are represented by a mixed-mode trilinear cohesive law at the interface between the skin and the doubler. The quasi-static properties of the trilinear law were characterized. The main advantage of the proposed fatigue model is that it relies on quasi-static properties as well as engineering assumptions to compose the shape of the S-N diagram. The model does not require Paris law data, and it is capable of predicting the initiation of separation, the rate of propagation, as well as the effects of crack resistance curves and the stress ratio.

Carlos G Davila↗
NASA NTRS2018

Comparison of Test Methods to Determine Failure Parameters for MAT162 Calibration

MAT162, a laminated composite failure material model developed by The Material Sciences Corporation for the commercial finite element software LS-Dyna, is widely used within the aerospace industry to predict damage events under a range of dynamic conditions. The material model involves numerous inputs consisting of both physical material properties and numerical calibration parameters. Due to the large number material card inputs, often there is a lack of uniqueness to MAT162 material cards that limits the predictive capability to only the directly calibrated space. To expand this space, MAT162 requires a prudent and robust calibration process in which significant parameters are calibrated to high confidence damage events observed in experiment. Critical to this success is fully defining the material properties correctly, namely the fiber crush (SFC) and fiber shear (SFS) values, prior to calibrating the numerical parameters. In this paper, the effect of the determination of SFS and SFC on subsequent calibration steps is examined using two different experimental techniques.

Molitor, Matthew↗
DOE OSTI2024

Calibration of the 2-Phase Bubble Tracking Model for Liquid Mercury Target Simulation with Machine Learning Surrogate Models

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory is one of the most powerful accelerator-driven neutron sources in the world. The intense protons strike on SNS's mercury target to provide bright neutron beams, which also leads to severe fluid-structure interactions inside the target. Prediction of resultant loading on the target is difficult particularly when helium gas is injected into mercury to reduce the loading and mitigate the pitting damage on vessel walls. A 2-phase material model that incorporates the Rayleigh-Plesset (R-P) model is expected to address this multi-physics problem. However, several uncertain parameters in the R-P model require intensive simulations to determine their optimal values. With the help of machine learning and the measured target strain, we have studied the major uncertain parameters in this R-P model and developed a framework to identify optimal parameters that significantly reduce the discrepancy between simulations and experimental strains. The preliminary results show the possibility of using this mercury/helium mixture and surrogate models to predict a better match of target strain response when the helium gas is injected.

Lin, Lianshan↗
NASA NTRSDate not supplied

Effects Of Five-Ion Galactic Cosmic Radiation Simulation On Immune Function, Brain, And Behavior In Male And Female Mice

Exposure to galactic cosmic radiation is a principal consideration of spaceflight missions, and with upcoming missions to the Moon and Mars, it is increasingly imperative to elucidate the effects of space travel beyond the lower Earth orbit. Additionally, with the first female astronaut to soon travel to the Moon there is a strong need to understand the biological sex differences to adaptation to the deep space environment. While the effects of spaceflight on the nervous system are not fully known, studies in animal models have shown that exposure to ionizing radiation can cause neuronal damage and lead to downstream cognitive and behavioral deficits. To simulate the type of radiation exposure occurring during spaceflight, model organisms can be exposed to relevant doses via Five-Ion Galactic Cosmic Radiation Simulation at the NASA National Space Radiation Laboratory at Brookhaven National Laboratory. We have investigated the neurobehavioral responses to space environment-like radiation exposure. Male and female 23–24-week-old mice (age-matched to average astronaut age) were exposed to 5, 15 and 50 cGy. Following exposure, immune, brain and behavioral (sensorimotor, risk-taking and cognitive) measures were acquired at ‘Acute’ (IR+24hrs, IR+72hrs), ‘Intermediate’ (IR+14 days) and ‘Delayed’ (IR+28 to IR+124 days) to inform biological responses anticipated during a transit to Moon and Mars. There were pronounced sex differences observed in all outcome measurements, while very few radiation induced effects were observed. Those dose effects that were observed were primarily in cytokine expression and less so in behavioral measurements. Further studies will investigate if radiation, microgravity and social isolation combine synergistically to trigger an oxidative stress response that alters immune homeostasis, brain structure/function, and neurobehavioral/cognitive performance, ultimately to characterize risks and identify appropriate countermeasures in both women and men in anticipation of future deep space missions.

Stephanie Puukila↗
DOE OSTI2025

Advancing Multi-Hazard Risk and Safety Considerations for Aging Nuclear Facilities (Revision 1)

This project will demonstrate a multi-hazard time-dependent probabilistic risk assessment (PRA) approach for nuclear facilities considering aging-related deterioration of structures. A generic pressurized water reactor (PWR) reactor subjected to seismic mainshock-aftershock sequences considering the aging of the containment structure will be used as a case study to demonstrate the multi-hazard PRA approach. Using advanced modeling and simulation, seismic mainshock-aftershock fragility functions will be simulated for the containment structure considering aging effects. A multi-hazard PRA model for a generic PWR reactor will be built to quantify the multi-hazard core damage frequency (CDF) and large early release frequency (LERF) with explicit time-dependent modeling of event sequences. To date, the cascading impacts of multi-hazards are not adequately accounted for in the PRA models for nuclear facilities. In addition, for both initial and periodic evaluation of facilities to withstand natural phenomena hazards (NPH), deterioration of the SSCs due to aging and other effects is not adequately considered. By advancing multi-hazard considerations accounting for aging effects, this project will contribute to improved understanding of the safety of aging nuclear facilities. Project outcomes such as the multi-hazard CDF and LERF will also allow facility owners to optimize upgrade and retrofit protocols. This project is divided into two components: (1) advanced modeling and simulations; and (2) multi-hazard PRA. For the first component, Idaho National Laboratory’s (INL) Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON) and BlackBear codes will be used to simulate the seismic response and damage of a containment structure under cascading mainshock-aftershock sequences with aging effects. Uncertainties related to the seismic inputs, material parameters, and environmental factors such as temperature and humidity will be identified and propagated to the fragility functions. These fragility functions, which consider aging effects, will be time dependent. The second component will take the fragility information from the first component to build a multi-hazard time-dependent PRA model starting from a generic PWR model to evaluate the multi-hazard CDF and LERF and characterize the associated consequences. For this component, OpenPRA Web Application and SAPHIRE code will be used. Events such as the Fukushima Daiichi accident have highlighted the importance of considering the cascading impacts of multi-hazards for PRA. Moreover, many of the reactors in the current nuclear fleet in the United States (US) are already operating well beyond their initially planned design life, and applications for further extensions to operating licenses are being considered. Therefore, considering multi-hazard effects and aging deterioration in the NPH risk assessment process will contribute to the safety of both existing and future nuclear facilities. Outcomes of this project will thus directly benefit the standards DOE-STD-1020-16 and DOE-HDBK-1224-18.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2022

Milwaukee Urban Development: Assessing the Drivers of Urban Flooding Vulnerability in Milwaukee Using NASA Earth Observations

Milwaukee County has experienced an increase in flooding due to climate change and urbanization. The frequency and severity of flooding vary spatially due to differences in land cover, surface permeability, and infrastructure. Marginalized communities tend to experience disproportionately high flooding and damage due to infrastructural inequalities and limited access to resources. To quantify these differences, we used the Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model to calculate and create maps of runoff retention, nominal flood depth, and economic damage to buildings in Milwaukee. Our model inputs included land cover, surface permeability, and rainfall. To inform our precipitation inputs, we used NASA’s Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) and National Weather Service (NWS) data. We assessed the relationship between flood risk and social and environmental spatial data including redlining, racial demographics, greenspace, and community resilience. The data demonstrate that flood risk is higher in historically redlined neighborhoods, majority Hispanic and Black census block groups, areas that lack parks and trees, and areas of low community resilience as measured by the Census Bureau’s Community Resilience Estimates (CRE). These findings will support our partners, Groundwork Milwaukee and Groundwork USA, in their efforts to promote the equitable distribution of resources and support environmental health in urban spaces. The end products of this project provide our partners with tools to assess urban flooding vulnerability, guide future intervention projects, quantify the effects of environmental injustice, and improve stakeholder access to data.

Madeleine Tango↗
DOE OSTI2022

Machine learning in nuclear materials research

Nuclear materials are often demanded to function for extended time in extreme environments, including high radiation fluxes with associated transmutations, high temperature and temperature gradients, mechanical stresses, and corrosive coolants. They also have a wide range of microstructural and chemical makeups, resulting in multifaceted and often out-of-equilibrium interactions. Machine learning (ML) is increasingly being used to tackle these complex time-dependent interactions and aid researchers in developing models and making predictions, sometimes with better accuracy than traditional modeling that focuses on one or two parameters at a time. Conventional practices of acquiring new experimental data in nuclear materials research are often slow and expensive, limiting the opportunity for data-centric ML, but new methods are changing that paradigm. Here we review high-throughput computational and experimental data approaches, especially robotic experimentation and active learning that is based on Gaussian process and Bayesian optimization. We show ML examples in structural materials (e.g., reactor pressure vessel (RPV) alloys and radiation detecting scintillating materials) and highlight new techniques of high-throughput sample preparation and characterizations, and automated radiation/environmental exposures and real-time online diagnostics. Herein, this review suggests that ML models of material constitutive relations in plasticity, damage, and even electronic and optical responses to radiation are likely to become powerful tools as they develop. Finally, we speculate on how the recent trends of using natural language processing (NLP) to aid the collection and analysis of literature data, interpretable artificial intelligence (AI), and the use of streamlined scripting, database, workflow management, and cloud computing platforms that will soon make the utilization of ML techniques as commonplace as the spreadsheet curve-fitting practices of today.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Phase instabilities in austenitic steels during particle bombardment at high and low dose rates

Disruption of phase stability by energetic particle bombardment is a major challenge in designing advanced radiation-tolerant alloys and ion beam processing of nanocomposites. Particularly, ballistic dissolution susceptibility of different solute nanocluster species in alloys is poorly understood. Here, low dose rate neutron irradiations were conducted on a Fe-Cr-Ni based austenitic steel in the BOR-60 reactor (9.4 × 10 -7 dpa/s, 318 °C) followed by accelerated dose rate ion irradiations at multiple temperatures ( 10 -3 dpa/s, 380 – 420 °C). Using atom probe tomography, the stability of radiation-enhanced Cu-rich and radiation-induced Ni-Si-Mn-rich nanoclusters was evaluated. During neutron irradiation, Cu-rich clusters nucleated with their core concentrations progressively increasing with dose, while Ni-Si-Mn-rich clusters formed and evolved into G-phase precipitates. Ion irradiations dramatically altered the nanoclusters. Cu-rich clusters were ballistically dissolved, but Ni-Si-Mn-rich clusters remained stable and coarsened with dose at 400 and 420 °C, highlighting that different nanocluster species in a single microstructure can have innately distinct ballistic dissolution susceptibilities. Solute-specific recoil rates were incorporated into the Heinig precipitate stability model, which shows that in addition to radiation-enhanced diffusion, recovery from ballistic dissolution depends on solute concentration gradient near cluster interfaces. Finally, the combined experimental-modeling study quantified the critical temperatures and damage rates where ballistic dissolution dominates for each cluster species.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Perspective on Scalable AI on High-Performance Computing and Leadership Class Supercomputing Facilities [Industrial and Governmental Activities]

Many scientific applications that support the mission of the US Department of Energy (US-DoE) require modeling complex engineering and/or physical systems. Here, examples of such complex systems arise from: (a) materials science to develop new compounds with exceptional mechanical and thermodynamical properties (e.g., resistance to mechanical stresses and high temperatures), (b) structural and nuclear engineering to model the temporal evolution of the structural damage of concrete shields exposed to continuous neutron and gamma radiations emitted by the nuclear reactor core, (c) urban sciences (e.g., transportation and smart buildings), and (d) power grid systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Computational Study of the Shear Behavior of Reinforced Concrete Beams Affected from Alkali–Silica Reactivity Damage

In this study, an investigation of the shear behavior of full-scale reinforced concrete (RC) beams affected from alkali–silica reactivity damage is presented. A detailed finite element model (FEM) was developed and validated with data obtained from the experiments using several metrics, including a force–deformation curve, rebar strains, and crack maps and width. The validated FEM was used in a parametric study to investigate the potential impact of alkali–silica reactivity (ASR) degradation on the shear capacity of the beam. Degradations of concrete mechanical properties were correlated with ASR expansion using material test data and implemented in the FEM for different expansions. The finite element (FE) analysis provided a better understanding of the failure mechanism of ASR-affected RC beam and degradation in the capacity as a function of the ASR expansion. The parametric study using the FEM showed 6%, 19%, and 25% reduction in the shear capacity of the beam, respectively, affected from 0.2%, 0.4%, and 0.6% of ASR-induced expansion.

36 MATERIALS SCIENCE↗
NASA NTRS1978

An engineering approach to the prediction of fatigue behavior of unnotched/notched fiber reinforced composite laminates

An engineering approach is proposed for predicting unnotched/notched laminate fatigue behavior from basic lamina fatigue data. The fatigue analysis procedure was used to determine the laminate property (strength/stiffness) degradation as a function of fatigue cycles in uniaxial tension and in plane shear. These properties were then introduced into the failure model for a notched laminate to obtain damage growth, residual strength, and failure mode. The approach is thus essentially a combination of the cumulative damage accumulation (akin to the Miner-Palmgren hypothesis and its derivatives) and the damage growth rate (similar to the fracture mechanics approach) philosophies. An analysis/experiment correlation appears to confirm the basic postulates of material wearout and the predictability of laminate fatigue properties from lamina fatigue data.

Kulkarni, S. V.↗
NASA NTRS1980

Three year performance of the NTS-2 solar cell experiment

Twelve different solar cell modules from the NTS 2 experiment are functioning after more than three years in a severe trapped radiation orbit of 20,367 km (10,990 nm) circular, 63 deg inclination. The rate of maximum power degradation may be fit to a predicted rate which is based on twice the value of 1 MeV electron equivalent damage fluence calculated from the space electron model AEI 7. The photovoltaic parameters of the cells are compared to their original values to demonstrate rank order of performance.

Statler, R. L.↗
NASA NTRS1982

The effects of microcracking on the thermal expansion of graphite-epoxy composites

A study of the effects of thermal environment and microcracking in graphite epoxy composites was made. Research indicates that microcracking does affect the thermal expansion of composite laminates. The amount of reduction in thermal expansion was a function of the crack density. A maximum reduction of approximately 25% occurred in a quasi-isotropic specimen with a crack density of 2.05 mm 1 in the 90 deg plies. Laminate analysis with appropriate reductions in E sub 2 and Alpha sub 2 of the damaged plies appears to be capable of modeling the observed

Bowles, D. E.↗
NASA NTRS1984

Fatigue behavior of continuous fiber silicon-carbide-aluminum composites

Four lay-ups of continuous fiber silicon carbide (SCS2) fiber/aluminum matrix composites were tested to assess fatigue mechanisms including stiffness loss when cycled below their respective fatigue limits. The lay-ups were 0 (sub 8), 0(sub 2)/ + or - 45 (sub 2s), 0/90 (sub 2s),and 0/ + or 45/90 (subs). The data were compared with predictions from the author's previously published shakedown model which predicts fatigue-induced stiffness loss in metal matrix composites. A fifth lay-up, + or - 45 (sub 2s), was tested to compare shakedown and fatigue limits. The particular batch of silicon-carbide fibers tested in this program had a somewhat lower modulus (340 GPa) than expected and displayed poor bonding to the aluminum matrix. Good agreement was obtained between the stiffness loss model and the test data. The fatigue damage below the fatigue limit was primarily in the form of matrix cracking. The fatigue limit corresponded to the laminate shakedown for the + or - 45 (sub 2s) laminate.

Johnson, W. S.↗
NASA NTRS1984

Effect of ion sputtering on interface chemistry and electrical properties of Au GaAs(100) Schottky contacts

The effects of sputtering n-type (100)GaAs with 1 to 5 keV argon ions have been studied in ultrahigh vacuum. Auger electron and X-ray photoelectron spectroscopies have been used to characterize the surface before and after sputtering. Gold Schottky contacts were prepared in situ to avoid contamination at the metal/semiconductor interface. The data show that sputtering depletes the surface in As, and the extent of depletion increased as the ion energy was increased. However, angular-resolved photoelectron data showed As was enriched on the outer atom layer by 5 keV but depleted by 1 keV Ar(+) sputtering. Current and capacitance versus voltage data showed that sputtering always lowered the Schottky barrier height and generally increased the ideality factor. However, the barrier height after 3 keV sputtering was higher than after 1 keV sputtering. Those effects are explained based on a combined effective work function model and creation of a donorlike surface damage layer. The donor layer was correlated with As depletion by sputtering. Deep level trap formation and annealing of sputtering effects were studied.

Wang, Y.-X.↗
NASA NTRS1986

Fatigue behavior of continuous-fiber silicon carbide/aluminum composites

Four lay-ups of continuous fiber silicon carbide (SCS2) fiber/aluminum matrix composites were tested to assess fatigue mechanisms including stiffness loss when cycled below their respective fatigue limits. The lay-ups were 0 (sub 8), 0(sub 2)/ + or - 45 (sub 2s), 0/90 (sub 2s), and 0/ + or - 45/90 (subs). The data were compared with predictions from the author's previously published shakedown model which predicts fatigue-induced stiffness loss in metal matrix composites. A fifth lay-up, + or - 45 (sub 2s), was tested to compare shakedown and fatigue limits. The particular batch of silicon-carbide fibers tested in this program had a somewhat lower modulus (340 GPa) than expected and displayed poor bonding to the aluminum matrix. Good agreement was obtained between the stiffness loss model and the test data. The fatigue damage below the fatigue limit was primarily in the form of matrix cracking. The fatigue limit corresponded to the laminate shakedown for the + or - 45 (sub 2s) laminate.

Johnson, W. S.↗