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At least 379 records · Page 21

Numerical Predictions of Damage and Failure in Carbon Fiber Reinforced Laminates Using a Thermodynamically-Based Work Potential Theory

A thermodynamically-based work potential theory for modeling progressive damage and failure in fiber-reinforced laminates is presented. The current, multiple-internal state variable (ISV) formulation, referred to as enhanced Schapery theory (EST), utilizes separate ISVs for modeling the effects of damage and failure. Consistent characteristic lengths are introduced into the formulation to govern the evolution of the failure ISVs. Using the stationarity of the total work potential with respect to each ISV, a set of thermodynamically consistent evolution equations for the ISVs are derived. The theory is implemented into a commercial finite element code. The model is verified against experimental results from two laminated, T800/3900-2 panels containing a central notch and different fiber-orientation stacking sequences. Global load versus displacement, global load versus local strain gage data, and macroscopic failure paths obtained from the models are compared against the experimental results.

composite materials↗

Transgenic Mouse Model for Reducing Oxidative Damage in Bone

Exposure to musculoskeletal disuse and radiation result in bone loss; we hypothesized that these catabolic treatments cause excess reactive oxygen species (ROS), and thereby alter the tight balance between bone resorption by osteoclasts and bone formation by osteoblasts, culminating in bone loss. To test this, we used transgenic mice which over-express the human gene for catalase, targeted to mitochondria (MCAT). Catalase is an anti-oxidant that converts the ROS hydrogen peroxide into water and oxygen. MCAT mice were shown previously to display reduced mitochondrial oxidative stress and radiosensitivity of the CNS compared to wild type controls (WT). As expected, MCAT mice expressed the transgene in skeletal tissue, and in marrow-derived osteoblasts and osteoclast precursors cultured ex vivo, and also showed greater catalase activity compared to wildtype (WT) mice (3-6 fold). Colony expansion in marrow cells cultured under osteoblastogenic conditions was 2-fold greater in the MCAT mice compared to WT mice, while the extent of mineralization was unaffected. MCAT mice had slightly longer tibiae than WT mice (2%, P less than 0.01), although cortical bone area was slightly lower in MCAT mice than WT mice (10%, p=0.09). To challenge the skeletal system, mice were treated by exposure to combined disuse (2 wk Hindlimb Unloading) and total body irradiation Cs(137) (2 Gy, 0.8 Gy/min), then bone parameters were analyzed by 2-factor ANOVA to detect possible interaction effects. Treatment caused a 2-fold increase (p=0.015) in malondialdehyde levels of bone tissue (ELISA) in WT mice, but had no effect in MCAT mice. These findings indicate that the transgene conferred protection from oxidative damage caused by treatment. Unexpected differences between WT and MCAT mice emerged in skeletal responses to treatment.. In WT mice, treatment did not alter osteoblastogenesis, cortical bone area, moment of inertia, or bone perimeter, whereas in MCAT mice, treatment increased these parameters. Taken together, this typically catabolic treatment (disuse and irradiation) appeared to stimulate cortical expansion in MCAT mice but not WT mice. In conclusion, these results reveal the importance of mitochondrial ROS generation in skeletal remodeling and show that MCAT mice provide a useful animal model for bone studies.

trandgenic↗

A Multiphysics Thermoelastoviscoplastic Damage Internal State Variable Constitutive Model including Magnetism

We present a macroscale constitutive model that couples magnetism with thermal, elastic, plastic, and damage effects in an Internal State Variable (ISV) theory. Previous constitutive models did not include an interdependence between the internal magnetic (magnetostriction and magnetic flux) and mechanical fields. Although constitutive models explaining the mechanisms behind mechanical deformations caused by magnetization changes have been presented in the literature, they mainly focus on nanoscale structure–property relations. A fully coupled multiphysics macroscale ISV model presented herein admits lower length scale information from the nanoscale and microscale descriptions of the multiphysics behavior, thus capturing the effects of magnetic field forces with isotropic and anisotropic magnetization terms and moments under thermomechanical deformations. For the first time, this ISV modeling framework internally coheres to the kinematic, thermodynamic, and kinetic relationships of deformation using the evolving ISV histories. For the kinematics, a multiplicative decomposition of deformation gradient is employed including a magnetization term; hence, the Jacobian represents the conservation of mass and conservation of momentum including magnetism. The first and second laws of thermodynamics are used to constrain the appropriate constitutive relations through the Clausius–Duhem inequality. The kinetic framework employs a stress–strain relationship with a flow rule that couples the thermal, mechanical, and magnetic terms. Experimental data from the literature for three different materials (iron, nickel, and cobalt) are used to compare with the model’s results showing good correlations.

36 MATERIALS SCIENCE↗

A Multiphysics Thermoelastoviscoplastic Damage Internal State Variable Constitutive Model including Magnetism

We present a macroscale constitutive model that couples magnetism with thermal, elastic, plastic, and damage effects in an Internal State Variable (ISV) theory. Previous constitutive models did not include an interdependence between the internal magnetic (magnetostriction and magnetic flux) and mechanical fields. Although constitutive models explaining the mechanisms behind mechanical deformations caused by magnetization changes have been presented in the literature, they mainly focus on nanoscale structure–property relations. A fully coupled multiphysics macroscale ISV model presented herein admits lower length scale information from the nanoscale and microscale descriptions of the multiphysics behavior, thus capturing the effects of magnetic field forces with isotropic and anisotropic magnetization terms and moments under thermomechanical deformations. For the first time, this ISV modeling framework internally coheres to the kinematic, thermodynamic, and kinetic relationships of deformation using the evolving ISV histories. For the kinematics, a multiplicative decomposition of deformation gradient is employed including a magnetization term; hence, the Jacobian represents the conservation of mass and conservation of momentum including magnetism. The first and second laws of thermodynamics are used to constrain the appropriate constitutive relations through the Clausius–Duhem inequality. The kinetic framework employs a stress–strain relationship with a flow rule that couples the thermal, mechanical, and magnetic terms. Experimental data from the literature for three different materials (iron, nickel, and cobalt) are used to compare with the model’s results showing good correlations.

36 MATERIALS SCIENCE↗

Space Plasma Ion Processing of the Lunar Soil: Modeling of Radiation-Damaged Rim Widths on Lunar Grains

Chemically and microstructurally complex altered rims around grains in the finest size fraction (<20 micron) of the lunar regolith are the result of multi-stage processes involving both solar ion radiation damage and nanoscale deposition of impact or sputter-derived vapors. The formation of the rims is an important part of the space weathering process, and is closely linked to key changes in optical reflectance and other bulk properties of the lunar surface. Recent application of field-emission scanning transmission electron microscope techniques, including energy dispersive X-ray spectral imaging, is making it easier to unravel the "nano-stratigraphy" of grain rims, and to delineate the portions of rims that represent Radiation-Amorphized (RA) host grain from overlying amorphous material that represents vapor/sputter deposits. For the portion of rims formed by host grain amorphization (henceforth called RA rims), we have been investigating the feasibility of using Monte Carlo-type ion-atom collision models, combined with experimental ion irradiation data, to derive predictive numerical models linking the width of RA rims to the grain s integrated solar ion radiation exposure time.

Chamberlin, S.↗

Analysis of the Influence of Layer Shifting on the Elastic Response and Damage Nucleation and Growth in Woven Composite Laminates

The influence of relative layer shifting on the elastic and damage response of plain weave composite laminates is analyzed using a continuum damage mechanics approach in combination with the finite element method. First, the homogenized properties of the woven composite as a function of the number of layers and of layer shifting are presented. Next, the damage development in various shifting configurations is studied using different damage constitutive models for the matrix and the fiber bundles. It is shown that the impact of layer shifting on both the elastic response and the nonlinear damage response is significant. Most notably, the model captures changes in the damage mechanisms within the woven composite that occur due to layer shifting, resulting in stiffer, more brittle behavior, which has been shown experimentally in the literature. Model results in the linear and nonlinear regimes are shown to be consistent with both an independent analytical model and reported experiments.

layer shifting↗

Phase-field modeling of thermally-grown oxide and damage evolution in environmental barrier coatings

Silicon carbide-based ceramic matrix composites protected by environmental barrier coatings (EBCs) present a promising materials solution for next-generation gas turbines. Developing more robust and efficient EBCs is therefore of significant technological importance. During the service in high-temperature oxidative environments, there is a thermally grown oxide (TGO) layer, spontaneously formed in the EBC system. TGO is recognized as a critical factor for the degradation and failure of EBCs, yet the detailed mechanisms of TGO growth and its effect on EBC failure remain unclear. In this study we develop a comprehensive chemo-mechano-phase-field model to simulate growth of the TGO in EBCs, factoring in creep and deformation, and especially the cracking behaviors. The volume expansion due to TGO growth and the resulting large inelastic deformation are addressed by using our recently developed, so-called incremental realization of inelastic deformation (IRID) algorithm, in combination with an adapted Hu-Chen spectral solver for elasticity. Simulations of TGO growth are performed considering different growth modes of TGOs determined mainly by the ratio of oxidant permeability in the topcoat to that in the TGO itself. Large-scale three-dimensional (3D) simulations are performed to model the formation of interconnecting vertical/channel cracks (often called ‘mud cracks’). The simulated crack morphology are in excellent agreement with the experimental observations from the literature. The simulations also provide insights into the cracking of EBCs and its dependence on the structure and constituent properties of the coating system. Furthermore, these results demonstrate the developed damage model can be a useful tool for design of more durable EBCs.

Cracking↗

Feasibility of an Accelerometer-Based Structural Health Monitoring System for the LANL Blast Tube

A modeling- and simulation-based study was conducted on the feasibility of implementing an accelerometer-based SHM system on the Los Alamos National Laboratory blast tube. A blast tube experiment was modeled using the Abaqus explicit finite element solver. A custom user subroutine was written to apply test-like pressure loading to the inside surface of the blast tube. The subroutine applies analytically defined pressure loads derived from tracer output taken from a Compressible Flow Computational Fluid Dynamics Solver model of the blast tube. Five unique versions of the model were created: an undamaged reference model at 65°F was used as the baseline and compared to equivalent models at 10°F and 100°F. These three models were compared to models with small damage at the reference temperature. The two types of damage considered were a radial (circumferential) crack in the main tube body and a longitudinal crack in the supports. Acceleration outputs were extracted from accelerometer bodies included in the model and were post processed using a variety of standard SHM techniques. Different potential features signaling failure were extracted and compared using statistical methods in the time and frequency domains. A method was identified that clearly shows that differences in structural response resulting from the modeled damage can be differentiated from the structural response resulting from changing environmental conditions. However, the amount of damage applied to create observable differences in the accelerometer data was so large that simpler methods of damage detection would be more cost effective in locating damage.

42 ENGINEERING↗

A parameter sensitivity study for simulating DNA damage after proton irradiation using TOPAS-nBio

Monte Carlo (MC) track structure simulation tools are commonly used for predicting radiation induced DNA damage by modeling the physical and chemical reactions at the nanometer scale. However, the outcome of these MC simulations is particularly sensitive to the adopted parameters which vary significantly across studies. In this study, a previously developed full model of nuclear DNA was used to describe the DNA geometry. The TOPAS-nBio MC toolkit was used to investigate the impact of physics and chemistry models as well as three key parameters (the energy threshold for direct damage, the chemical stage time length, and the probability of damage between hydroxyl radical reactions with DNA) on the induction of DNA damage. Our results show that the difference in physics and chemistry models alone can cause differences up to 34% and 16% in the DNA double strand break (DSB) yield, respectively. Additionally, changing the direct damage threshold, chemical stage length, and hydroxyl damage probability can cause differences of up to 28%, 51%, and 71% in predicted DSB yields, respectively, for the configurations in this study.

60 APPLIED LIFE SCIENCES↗

Revealing low-temperature plasma efficacy through a dose-rate assessment by DNA damage detection combined with machine learning models

Low-temperature plasmas have quickly emerged as alternative and unconventional types of radiation that offer great promise for various clinical modalities. As with other types of radiation, the therapeutic efficacy and safety of low-temperature plasmas are ubiquitous concerns, and assessing their dose rates is crucial in clinical settings. Unfortunately, assessing the dose rates by standard dosimetric techniques has been challenging. To overcome this difficulty, we proposed a dose-rate assessment framework that combined the predictive modeling of plasma-induced damage in DNA by machine learning with existing radiation dose-DNA damage correlations. Our results indicated that low-temperature plasmas have a remarkably high dose rate that can be tuned by various process parameters. This attribute is beneficial for inducing radiobiological effects in a more controllable manner.

59 BASIC BIOLOGICAL SCIENCES↗

Development of Graphite Thermal and Mechanical Modeling Capabilities in Grizzly

Nuclear-grade graphites are used extensively in the core designs of multiple types of advanced nuclear reactors. In the reactor environment, graphite is exposed over long durations to extreme conditions, including high temperatures, radiation and potentially molten salt and oxygen. Exposure to these conditions can cause several degradation mechanisms in graphite, including nonuniform volumetric strains induced by irradiation and thermal expansion, which lead to stresses that can compromise the performance of graphite components. Evaluating component integrity, predicting component performance over the reactor lifetime, and developing design standards all require robust tools for predicting fracture initiation and propagation in graphite structural components in nuclear reactors. This report documents progress in an ongoing effort to develop modeling and simulation tools in the Grizzly code for predicting the performance of graphite exposed to reactor conditions. Recent developments include a set of thermal and mechanical models that now include the IG-110, NBG-18, and H-451 graphite grades. Improvements have also been made to a nonlinear damaged plasticity model applicable to predicting damage under tension and compression to quasibrittle materials, including graphite. In addition, enhancements have been made to the extended finite element method implementation targeted at simulating graphite fracture. These include new capabilities for crack nucleation in the interior of a solid body, improved treatment of crack nucleation on free surfaces, and more robust modeling approaches for crack growth approaching free surfaces or other cracks.

36 MATERIALS SCIENCE↗

Model-Based Fatigue Prognosis of Fiber-Reinforced Laminates Exhibiting Concurrent Damage Mechanisms

Prognostics of large composite structures is a topic of increasing interest in the field of structural health monitoring for aerospace, civil, and mechanical systems. Along with recent advancements in real-time structural health data acquisition and processing for damage detection and characterization, model-based stochastic methods for life prediction are showing promising results in the literature. Among various model-based approaches, particle-filtering algorithms are particularly capable in coping with uncertainties associated with the process. These include uncertainties about information on the damage extent and the inherent uncertainties of the damage propagation process. Some efforts have shown successful applications of particle filtering-based frameworks for predicting the matrix crack evolution and structural stiffness degradation caused by repetitive fatigue loads. Effects of other damage modes such as delamination, however, are not incorporated in these works. It is well established that delamination and matrix cracks not only co-exist in most laminate structures during the fatigue degradation process but also affect each other's progression. Furthermore, delamination significantly alters the stress-state in the laminates and accelerates the material degradation leading to catastrophic failure. Therefore, the work presented herein proposes a particle filtering-based framework for predicting a structure's remaining useful life with consideration of multiple co-existing damage-mechanisms. The framework uses an energy-based model from the composite modeling literature. The multiple damage-mode model has been shown to suitably estimate the energy release rate of cross-ply laminates as affected by matrix cracks and delamination modes. The model is also able to estimate the reduction in stiffness of the damaged laminate. This information is then used in the algorithms for life prediction capabilities. First, a brief summary of the energy-based damage model is provided. Then, the paper describes how the model is embedded within the prognostic framework and how the prognostics performance is assessed using observations from run-to-failure experiments

Prognostics↗

Search-based model identification of smart-structure damage

This paper describes the use of a combined model and parameter identification approach, based on modal analysis and artificial intelligence (AI) techniques, for identifying damage or flaws in a rotating truss structure incorporating embedded piezoceramic sensors. This smart structure example is representative of a class of structures commonly found in aerospace systems and next generation space structures. Artificial intelligence techniques of classification, heuristic search, and an object-oriented knowledge base are used in an AI-based model identification approach. A finite model space is classified into a search tree, over which a variant of best-first search is used to identify the model whose stored response most closely matches that of the input. Newly-encountered models can be incorporated into the model space. This adaptativeness demonstrates the potential for learning control. Following this output-error model identification, numerical parameter identification is used to further refine the identified model. Given the rotating truss example in this paper, noisy data corresponding to various damage configurations are input to both this approach and a conventional parameter identification method. The combination of the AI-based model identification with parameter identification is shown to lead to smaller parameter corrections than required by the use of parameter identification alone.

Glass, B. J.↗

An Integrated Approach to Damage Accommodation in Flight Control

In this paper we present an integrated approach to in-flight damage accommodation in flight control. The approach is based on Multiple Models, Switching and Tuning (MMST), and consists of three steps: In the first step the main objective is to acquire a realistic aircraft damage model. Modeling of in-flight damage is a highly complex problem since there is a large number of issues that need to be addressed. One of the most important one is that there is strong coupling between structural dynamics, aerodynamics, and flight control. These effects cannot be studied separately due to this coupling. Once a realistic damage model is available, in the second step a large number of models corresponding to different damage cases are generated. One possibility is to generate many linear models and interpolate between them to cover a large portion of the flight envelope. Once these models have been generated, we will implement a recently developed-Model Set Reduction (MSR) technique. The technique is based on parameterizing damage in terms of uncertain parameters, and uses concepts from robust control theory to arrive at a small number of "centered" models such that the controllers corresponding to these models assure desired stability and robustness properties over a subset in the parametric space. By devising a suitable model placement strategy, the entire parametric set is covered with a relatively small number of models and controllers. The third step consists of designing a Multiple Models, Switching and Tuning (MMST) strategy for estimating the current operating regime (damage case) of the aircraft, and switching to the corresponding controller to achieve effective damage accommodation and the desired performance. In the paper present a comprehensive approach to damage accommodation using Model Set Design,MMST, and Variable Structure compensation for coupling nonlinearities. The approach was evaluated on a model of F/A-18 aircraft dynamics under control effector damage, augmented by nonlinear cross-coupling terms and a structural dynamics model. The proposed approach achieved excellent performance under severe damage effects.

Boskovic, Jovan D.↗

Progressive Damage Analysis of Laminated Composite (PDALC)-A Computational Model Implemented in the NASA COMET Finite Element Code

A method for analysis of progressive failure in the Computational Structural Mechanics Testbed is presented in this report. The relationship employed in this analysis describes the matrix crack damage and fiber fracture via kinematics-based volume-averaged variables. Damage accumulation during monotonic and cyclic loads is predicted by damage evolution laws for tensile load conditions. The implementation of this damage model required the development of two testbed processors. While this report concentrates on the theory and usage of these processors, a complete list of all testbed processors and inputs that are required for this analysis are included. Sample calculations for laminates subjected to monotonic and cyclic loads were performed to illustrate the damage accumulation, stress redistribution, and changes to the global response that occur during the load history. Residual strength predictions made with this information compared favorably with experimental measurements.

Lo, David C.↗