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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Probabilistic Damage Characterization Using the Computationally-Efficient Bayesian Approach

This work presents a computationally-ecient approach for damage determination that quanti es uncertainty in the provided diagnosis. Given strain sensor data that are polluted with measurement errors, Bayesian inference is used to estimate the location, size, and orientation of damage. This approach uses Bayes' Theorem to combine any prior knowledge an analyst may have about the nature of the damage with information provided implicitly by the strain sensor data to form a posterior probability distribution over possible damage states. The unknown damage parameters are then estimated based on samples drawn numerically from this distribution using a Markov Chain Monte Carlo (MCMC) sampling algorithm. Several modi cations are made to the traditional Bayesian inference approach to provide signi cant computational speedup. First, an ecient surrogate model is constructed using sparse grid interpolation to replace a costly nite element model that must otherwise be evaluated for each sample drawn with MCMC. Next, the standard Bayesian posterior distribution is modi ed using a weighted likelihood formulation, which is shown to improve the convergence of the sampling process. Finally, a robust MCMC algorithm, Delayed Rejection Adaptive Metropolis (DRAM), is adopted to sample the probability distribution more eciently. Numerical examples demonstrate that the proposed framework e ectively provides damage estimates with uncertainty quanti cation and can yield orders of magnitude speedup over standard Bayesian approaches.

Warner, James E.↗
NASA NTRS2016

Strain-Based Damage Determination Using Finite Element Analysis for Structural Health Management

A damage determination method is presented that relies on in-service strain sensor measurements. The method employs a gradient-based optimization procedure combined with the finite element method for solution to the forward problem. It is demonstrated that strains, measured at a limited number of sensors, can be used to accurately determine the location, size, and orientation of damage. Numerical examples are presented to demonstrate the general procedure. This work is motivated by the need to provide structural health management systems with a real-time damage characterization. The damage cases investigated herein are characteristic of point-source damage, which can attain critical size during flight. The procedure described can be used to provide prognosis tools with the current damage configuration.

Hochhalter, Jacob D.↗
NASA NTRS2016

Applications of Earth Remote Sensing for Identifying Tornado and Severe Weather Damage

NASA SPoRT (Short-term Prediction Research and Transition Center) provided MODIS (Moderate Resolution Imaging Spectrometer) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) imagery to WFOs (Weather Forecast Offices) in Alabama to support April 27th, 2011 damage assessments across the state. SPoRT was awarded a NASA Applied Science: Disasters Feasibility award to investigate the applicability of including remote sensing imagery and derived products into the NOAA/NWS (National Oceanic and Atmospheric Administration/National Weather System) Damage Assessment Toolkit (DAT). Proposal team was awarded the 3-year proposal to implement a web mapping service and associate data feeds from the USGS (U.S. Geological Survey) to provide satellite imagery and derived products directly to the NWS thru the DAT. In the United States, NOAA/NWS is charged with performing damage assessments when storm or tornado damage is suspected after a severe weather event. This has led to the development of the Damage Assessment Toolkit (DAT), an application for smartphones, tablets and web browsers that allows for the collection, geo-location, and aggregation of various damage indicators collected during storm surveys.

Satellite Remote Sensing↗
NASA NTRS2017

Damage Detection Sensor System for Aerospace and Multiple Applications

The damage detection sensory system is an intelligent damage detection ‘skin’ that can be embedded into rigid or flexible structures, providing a lightweight capability for in-situ health monitoring for applications such as spacecraft, expandable or inflatable structures, extravehicular activities (EVA) suits, smart wearables, and other applications where diagnostic impact damage monitoring might be critical. The sensor systems can be customized for detecting location, damage size, and depth, with velocity options and can be designed for particular environments for monitoring of impact or physical damage to a structure. The operation of the sensor detection system is currently based on the use of parallel conductive traces placed on a firm or flexible surface. Several detection layers can be implemented, where alternate layers are arranged in orthogonal direction with respect to the adjacent layers allowing for location and depth calculations. Increased flexibility of the damage detection sensor system designs will also be introduced.

Williams, M.↗
NASA NTRS2018

Plasticity and Damage Modeling of Stress Asymmetry and Dynamic Behavior of AFS Additive Manufactured Aluminum Alloy 2219

The Solid State Additive Manufacturing (AM) process referred as MELD that fabricated the samples in this study, provides a new path for repairing, coating, joining and additive manufacturing metals and metal matrix composites. This research will be the first application of a physics-based microstructure dependent internal state variable (ISV) plasticity and damage material model to capture the mechanical response of an AM Aluminum Alloy (AA) 2219 via the MELD process. In this research, a microstructure-based internal state variable (ISV) plasticity-damage model was used to capture the mechanical behavior of AFS 2219 aluminum alloy. Aeroprobe Corporation, creator and patent holder for the MELD process, fabricated the material by pushing a solid filler rod of AA2219-T861 material through a hollow rotating tool onto an AA2219 T851 plate substrate. As feedstock, solid or powder precursor metals are pushed through a nonconsumable rotating cylindrical tool. Herein, added layers are deposited and metallurgically bonded to substrate material or previously deposited layers by the heat generated from the rotating tool through plastic deformation of the filler material. Once a layer has been added, the tool height increases, and starts the deposition of the next layer. This process results in beneficial properties such as grain refinement, homogenization and reduced porosity (fully dense). This process will experience temperatures similar to those in the weld nugget zone (WNZ) in friction stir welding (FSW), ranging from 0.6-0.9 Tm, with Tm being the melting point of the material. MELD is highly scalable with AA deposition rates reaching over 1000 cm3/hr, which allows for MELD being used for repairs, coatings, and building components. A motivating factor driving the research for physics-based history dependent material modeling of MELD components is the ability to accurately capture the stress-state and strain rate dependence in the material caused by variations in material microstructure from the MELD processing of new or repaired components. The ISV model incorporates microstructural content and is consistent with continuum level kinematics, kinetics, and thermodynamics. These features allow the ISV model to capture large deformations at the structural scale using the kinematic and isotropic hardening, while microscale damage is obtained from the microstructural features. The benefits of the ISV model arise from the inclusion of structure-property relationships identified from microstructural characterization and experimentation. The Bauschinger effect (BE) is an important concept, vital in the accurate prediction of cyclic stress-strain response of ductile materials such as metals. The ISV model has been successfully used to capture the behavior and damage, and the BE of different aluminum alloys and steels. The ISV model uses kinematic and isotropic hardening to help capture deformations of the material at the macro scale. To understand this hardening relationship, calculating the kinematic and isotropic hardening relationship in the material is warranted for a high-fidelity model. Electron Backscattered Diffraction (EBSD) was used to characterize the as-fabricated microstructure, where a fully-dense equiaxed grain morphology with average grain size of 2.5 μm was observed. Microhardness mapping of the as-built structures, monotonic tension and compression experiments at both quasi-static (0.001/s) strain rates, tension-followed-by-compression and compression-followed-by-tension experiments were performed to obtain the set of plasticity and damage constants necessary to capture strain rate and stress state behavior of this additive material. To calibrate the plasticity-damage model, a single set of constants were determined to capture the different stress states the MELD AA2219. One set of the constants was determined from experimental true stress-strain curves for the tension and compression data. Additionally, microstructural information and data from the open literature were used as the other model constants. This research is a first of its kind for AFS AA2219, includes correlating the ISV model to the monotonic experimental results that capture the isotropic and kinematic plasticity mechanical response.

Rivera, O. G.↗
NASA NTRS2018

Real Time Detection of Damage During Quasi-Static Loading of a Single Stringer Panel Using Passive Thermography

Real time nondestructive evaluation is required for composites load testing. The early detection and measurement of damage progression is important to understand failure modes. A single stringer panel was subjected to quasi-static loading to induce deformation which can result in the formation of delamination damage between the stiffener flange and skin. Passive thermography was used to detect damage in real time as a function of the applied load. The loading was stopped when damage growth was detected. Of particular interest was the early detection of damage formation which can be challenging, as compared to cyclic fatigue loading. Passive thermography data were acquired and processed in real time and revealed damaged areas due to heating from fiber breakage and delamination formation. The processed thermal imagery was also compared to acoustic emission and ultrasound data.

Zalameda, Joseph N.↗
NASA NTRS2018

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↗
NASA NTRS2018

A Nonlocal Progressive Damage Model for Composite Materials

Fiber reinforced composite materials are widely used in aerospace structures due to their high specific stiffness and strength. These materials exhibit complex deformation, damage and failure mechanisms under high strain rate loading conditions. Many different failure criteria have been proposed in literature to describe the damage initiation and evolution of fiber reinforced composite materials. Most of these damage models are based on a local framework. In a local framework, the material behavior is based on a point-wise constitutive relation which is independent of the effect of the surrounding points. These models include stiffness degradation when damage initiates in the material, which within a local framework leads to a highly mesh dependent result. This could be overcome using a nonlocal finite element approach. In the current work, a nonlocal formulation based on the work by Andrade et al [1] is adapted to describe composite material behavior. The LS-DYNA rate dependent progressive damage model, MAT162 is employed to detect the initiation and evolution of damage in orthotropic composite materials. This model is developed as a FORTRAN user material subroutine in the LS-DYNA environment. The results of MAT162 with and without the nonlocal formulation are compared at different mesh densities to validate the model. The numerical analysis exhibits the advantages of the nonlocal formulation.

Kodagali, Karan↗
NASA NTRS2020

Repair of Sandwich Structure in Support of the Payload Adapter Fitting (PAF) Part II: Severe Damage Repair

As part of a program examining a Payload Adaptor Fitting (PAF) for NASA’s Space Launch System (SLS), a repair study of impact damage and misdrilled holes in composite sandwich structure was undertaken.1 In that study, it was shown that small holes and barely visible impact damage (BVID) could be repaired and all the measured undamaged in-plane compression strength recovered without removing the damaged material using a simple patch repair. It was noted that for more severe damage, either larger patches or removal of damage (or both) may be necessary to regain all of the measured undamaged compression strength. This Technical Memorandum (TM) presents the results of an experimental investigation into repair of more severely damaged sandwich structure than what was studied in reference 1.

Nettles, A. T.↗
NASA NTRSDate not supplied

A SATELLITE AGNOSTIC APPROACH TO QUANTIFYING HAIL DAMAGE SWATHS ACROSS THE CENTRAL UNITED STATES AND OTHER AGRICULTURAL REGIONS

Intense thunderstorms can bring damaging winds and large hail to agricultural regions during the prime growing season. In certain cases, large swaths of damage from the wind and hail are left behind and visible to satellite remote sensing instruments. Often times, Earth observing optical remote sensing from low to high spatial resolutions are able to view these damaged swaths. With the large number of moderate to high-resolution instruments in orbit, these damaged areas have potential to be viewed daily. However, during the prime growing season, clouds frequently block the viewing of the land surface by these optical instruments. Space-borne synthetic aperture radar (SAR) instruments allow for the viewing of the land surface in most weather conditions, but instead measure backscatter as opposed to optical sensors measuring reflected or emitted radiation. Additionally, the number of SAR instruments with free and open data lags behind the number of optical sensors. This paper describes the development of a methodology that attempts to characterize hail damaged swaths, through independent use of multiple optical and SAR platforms. This satellite-agnostic approach will focus statistical analysis by comparing undamaged areas to suspected damaged areas by using commonly derived indices from optical instruments and SAR backscatter from multiple polarizations.

Jordan R Bell↗
NASA NTRS2020

Widespread Mangrove Damage Resulting from the 2017 Atlantic Mega Hurricane Season

Comprised of 17 named tropical storms, 6 of which were major hurricanes, the 2017 Atlantic hurricane season ranked as one of the most damaging and costly hurricane seasons on record. In addition to socio-economic impacts, many previous studies have shown that important coastal ecosystems like mangroves are shaped by severe storms. However, little is known about how the cumulative effects of storms over entire hurricane seasons affect mangroves across large regions. We used satellite imagery from the entire Caribbean and Gulf of Mexico region to show that 2017 resulted in disproportionate mangrove damage compared to baseline responses over the previous 8 years. Specifically, we observed 30 times more mangrove damage, via a reduction in the normalized difference vegetation index (NDVI), during 2017 compared to any of the eight previous hurricane seasons, and most (72%) of this damage persisted throughout the 7 month post-hurricane season period as indicated by no NDVI recovery. Furthermore, wind speed, rainfall, and canopy height data showed that mangrove damage primarily resulted from high maximum wind speeds, but flooding (cumulative rainfall), previous storm history, and mangrove structure (canopy height) were also important predictors of damage. While mangroves are known to be resilient to hurricane impacts, our results suggest that increasingly frequent mega-hurricane seasons in the Caribbean region will dramatically alter mangrove disturbance dynamics.

Temilola Elisabeth Fatoyinbo Agueh↗
NASA NTRS2022

A Damage Resistance Comparison of Wet-Wound IM7 and T1100 Carbon Fiber/Epoxy Cylinders

This technical report presents the results of a damage tolerance comparison of two wet-wound cylinders; one made with IM7 carbon fiber and the other with T1100 carbon fiber. Damage was inflicted on the cylinders in the form of impact and the resulting damage was assessed mainly by cross-sectional examination of the damage zone after impact. Due to financial restraints, no residual strength testing was performed in this study. The amount of fiber breakage was the response variable of interest since fiber breakage, rather than delaminations or other matrix damage, governs the burst strength of rocket motor cases. The results showed that the T1100 fiber may be slightly more damage resistant than the IM7 fiber.

A T Nettles↗
NASA NTRS2023

Damage Detection of a Pressure Vessel with Smart Sensing and Deep Learning

Structural Health Monitoring plays a crucial role in ensuring the safety and reliability of critical infrastructure, including pressure vessels involved in various applications. This research reports the damage detection of a pressure box employed in space habitat that operates in harsh environment where both structural failure and bolt joint loosening may occur. These failure modes are extremely hard to model based on first principles. We explore proper sensing mechanism and the associated inverse analysis algorithm that can elucidate the health condition of the pressure box. It is identified that piezoelectric impedance based active interrogation can provide necessary information for damage detection in such a system. Concurrently, deep learning technique leveraging spatial convolutional neural network is synthesized to analyze the raw data acquired and identify different types of damage. By training the deep learning model on a dataset of healthy and various damage scenarios, we can achieve high accuracy in identifying the presence of damage and its type. This research provides a data-driven methodology for structural damage detection using deep learning and has the potential to be extended to various systems with different failure modes.

Yang Zhang↗
NASA NTRSDate not supplied

Open-Hole Testing of Resin Infused Carbon Composite Laminates to Facilitate Damage Growth and Failure Analysis Tools for Structural Design

In manufacturing of carbon-fiber reinforced composite aircraft structures, resin infusion offers a highly repeatable process for manufacturing structural components with resin content control, low labor requirements, and complex curvatures. To further understand the structural capabilities of res-in infused composites (RIC), this study – as part of the NASA-led Hi-Rate Composite Aircraft Manufacturing project efforts – performed open hole tension (OHT) and open hole compression (OHC) testing on RIC laminates. This testing provides information on the damage morphology and growth characteristics of RICs, which fuels the development and evaluation of analysis tools for progressive damage growth and failure responses. X-ray computed tomography (XCT) was implemented on each OHC and OHT specimen prior to mechanical testing to identify preexisting damage and/or defects. Two OHT and OHC specimens were loaded monotonically to failure and an additional OHT and OHC specimen were loaded intermittently at defined conditions and XCT scanned after each run. From the data obtained in this study, damage mechanisms leading to failure were identified, damage morphology and size were assessed, and damage initiation and failure loads were measured.

HiCAM↗
NASA NTRS2024

Harnessing Collaborative Learning Automata to Guide Multi-objective Optimization based Inverse Analysis for Structural Damage Identification

Structural damage identification based on physical models is often transformed into an optimization problem that minimizes the difference between measurement information of structure being monitored and the model prediction in the parametric space. However, the objective function in this context often exhibits multimodality, involving high-dimensional variables due to the reliance on finite element models for damage identification. These features pose challenges to optimization algorithms, where entrapment in local solutions can lead to false positives and false negatives in damage identification. In this research, we propose a reinforcement learning based multi-swarm optimizer to tackle such challenges in pursuit of a small yet diverse solution set that can capture the true damage scenario as one of the solutions. The proposed method leverages the flexibility of the particle swarm optimizer and incorporates novel strategies of metaheuristics to realize targeted improvement. To enable the particle swarm to adaptively select the appropriate search strategy based on the current environment, we adopt the learning automata technique, which sidesteps the need for reward strategy selection that is usually ad hoc at each step of the search. The integration harnesses the automatic learning and self-adaptation capabilities of learning automata, enabling the particles to navigate based on environmental signals. This leads to accumulated probabilities tied to advantageous movements, fostering an adaptive exploration of particles in the search space. The proposed approach is first validated through implementing into benchmark test cases with comparisons. It is then applied to structural damage identification with piezoelectric admittance experimental signals. `The results highlight the capability of the algorithm to identify a small solution set with high accuracy to match the actual damage scenario.

Yang Zhang↗
DOE OSTI2024

Repair strategy for fused silica wedged focus lens with high-density filamentary damage

The National Ignition Facility (NIF) is intentionally operated with the final fused silica glass (SiO2) optics exposed to fluences and intensities with the potential to induce damage that will grow with additional laser exposure. Therefore, the NIF operates a recycle loop to refurbish final optics by mitigating any initiated surface damage to arrest its growth. However, the morphology of filamentary damage, caused by local self-focusing in the bulk of a silica optic, adds complexity to optics mitigation and provides a limitation to optic reusability. Here, we evaluate techniques for mitigating isolated and clustered filamentary damage. Optical microscopy before and after installation on NIF was used to determine the efficacy of filamentary mitigation after a series of high fluence and intensity laser exposures. The challenges and success rate of the methods are compared for various filamentary damage mitigation strategies.

National Ignition Facility↗
DOE OSTI2025

Impact of amorphous pockets on displacement damage evolution in silicon

Silicon has long been known to exhibit amorphization in response to heavy particle bombardment. For doses below the total amorphization threshold, partial amorphization is observed in the form of scattered amorphous pockets. While extensive research has gone into modeling the formation and evolution of amorphous pockets in response to irradiation, no studies yet investigate their impact on the evolution of other damage such as interstitial supersaturation and clustering. In this study, we survey the impact of amorphous pockets on defect evolution in silicon when treated as static sinks. MD is first used to show that amorphous pockets provide energetically favorable sites for point defects relative to the crystalline bulk, supporting the hypothesis that they act as sinks. A 0-D cluster dynamics model is then constructed, taking an interstitial clustering model from the literature and including amorphous pockets as a sink species. We conduct our survey for temperatures between 30 and 400 °C and sink strengths between 1 to 6 x 10 10 cm −2 . Both implantation- and radiation-induced damage states are investigated using interstitial and vacancy concentrations as initial condition variables. We find that, due to the differing migration rates of the interstitial and the vacancy, amorphous pockets have a non-monotonic impact on the final damage state depending on the effective sink strength of the amorphous pockets, resulting in increased damage formation in regimes of intermediate amorphization. In conclusion, this result emphasizes the important role of amorphous pockets in governing the evolution of damage in partially amorphized crystalline materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Characterization of proton-induced damage in thick, p-channel skipper-CCDs

Here, in this work, we characterize the radiation-induced damage in two thick, p-channel skipper-CCDs irradiated unbiased and at room temperature with 217-MeV protons. We evaluate the overall performance of the sensors and demonstrate their single-electron/single-photon sensitivity after receiving a fluence on the order of 10 10 protons/cm 2 . Using the pocket-pumping technique, we quantify and characterize the proton-induced defects from displacement damage. We report an overall trap density of 0.134 traps/pixel for a displacement damage dose of 2.3 × 10 7 MeV/g. Three main proton-induced trap species were identified, V 2 , C i O i and V n O m , and their characteristic trap energies and cross sections were extracted. We found that while divacancies are the most common proton-induced defects, C i O i defects have a greater impact on charge integrity at typical operating temperatures because their emission-time constants are comparable or larger than typical readout times. To estimate ionization damage, we measure the characteristic output transistor curves. We found no threshold voltage shifts after irradiation. Our results highlight the potential of skipper-CCDs for applications requiring high-radiation tolerance and can be used to find the operating conditions in which effects of radiation-induced damage are mitigated.

47 OTHER INSTRUMENTATION↗