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At least 253 records · Page 14

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.↗

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.↗

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.↗

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↗

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↗

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.↗

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↗

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↗

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↗

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↗

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↗

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↗

Clustered DNA damages induced in human hematopoietic cells by low doses of ionizing radiation

Ionizing radiation induces clusters of DNA damages--oxidized bases, abasic sites and strand breaks--on opposing strands within a few helical turns. Such damages have been postulated to be difficult to repair, as are double strand breaks (one type of cluster). We have shown that low doses of low and high linear energy transfer (LET) radiation induce such damage clusters in human cells. In human cells, DSB are about 30% of the total of complex damages, and the levels of DSBs and oxidized pyrimidine clusters are similar. The dose responses for cluster induction in cells can be described by a linear relationship, implying that even low doses of ionizing radiation can produce clustered damages. Studies are in progress to determine whether clusters can be produced by mechanisms other than ionizing radiation, as well as the levels of various cluster types formed by low and high LET radiation.

NASA Discipline Radiation Health↗

High- and low-LET induced chromosome damage in human lymphocytes: a time-course of aberrations in metaphase and interphase

PURPOSE: To investigate how cell-cycle delays in human peripheral lymphocytes affect the expression of complex chromosome damage in metaphase following high- and low-LET radiation exposure. MATERIALS AND METHODS: Whole blood was irradiated in vitro with a low and a high dose of 1 GeV u(-1) iron particles, 400MeV u(-1) neon particles or y-rays. Lymphocytes were cultured and metaphase cells were collected at different time points after 48-84h in culture. Interphase chromosomes were prematurely condensed using calyculin-A, either 48 or 72 h after exposure to iron particles or gamma-rays. Cells in first division were analysed using a combination of FISH whole-chromosome painting and DAPI/ Hoechst 33258 harlequin staining. RESULTS: There was a delay in expression of chromosome damage in metaphase that was LET- and dose-dependant. This delay was mostly related to the late emergence of complex-type damage into metaphase. Yields of damage in PCC collected 48 h after irradiation with iron particles were similar to values obtained from cells undergoing mitosis after prolonged incubation. CONCLUSION: The yield of high-LET radiation-induced complex chromosome damage could be underestimated when analysing metaphase cells collected at one time point after irradiation. Chemically induced PCC is a more accurate technique since problems with complicated cell-cycle delays are avoided.

Non-NASA Center↗

Integrating Machine Learning into a Crowdsourced Model for Earthquake-Induced Damage Assessment

On January 12th, 2010, a catastrophic 7.0M earthquake devastated the country of Haiti. In the aftermath of an earthquake, it is important to rapidly assess damaged areas in order to mobilize the appropriate resources. The Haiti damage assessment effort introduced a promising model that uses crowdsourcing to map damaged areas in freely available remotely-sensed data. This paper proposes the application of machine learning methods to improve this model. Specifically, we apply work on learning from multiple, imperfect experts to the assessment of volunteer reliability, and propose the use of image segmentation to automate the detection of damaged areas. We wrap both tasks in an active learning framework in order to shift volunteer effort from mapping a full catalog of images to the generation of high-quality training data. We hypothesize that the integration of machine learning into this model improves its reliability, maintains the speed of damage assessment, and allows the model to scale to higher data volumes.

crowdsourcing↗

Investigation of Micro-Scale Architectural Effects on Damage of Composites

This paper presents a three-dimensional, energy based, anisotropic, stiffness reduction, progressive damage model for composite materials and composite material constituents. The model has been implemented as a user-defined constitutive model within the Abaqus finite element software package and applied to simulate the nonlinear behavior of a damaging epoxy matrix within a unidirectional composite material. Three different composite microstructures were considered as finite element repeating unit cells, with appropriate periodicity conditions applied at the boundaries. Results representing predicted transverse tensile, longitudinal shear, and transverse shear stress-strain curves are presented, along with plots of the local fields indicating the damage progression within the microstructure. It is demonstrated that the damage model functions appropriately at the matrix scale, enabling localization of the damage to simulate failure of the composite material. The influence of the repeating unit cell geometry and the effect of the directionality of the applied loading are investigated and discussed.

damage↗

A Brief Overview of the Effects of Impact Damage to Rocket Motor Cases

This Technical Memorandum (TM) presents pertinent results from past experimental work concerning impact damage to composite rocket motor cases. A rocket motor case in this TM refers to filament-wound pressure vessels of a substantial size intended to be used for launch vehicles, such as the new Space Launch System (SLS) rocket. In the early 1980s, as carbon fiber composites were becoming increasingly used on aircraft, concerns about the effects of foreign object impact damage grew, since the compressive strength properties of these composites could be severely affected by impact damage. The tensile properties were not as affected by foreign object impact damage which is fortunate for rocket motor cases as they are driven by tensile loads (burst strength). While great improvements to both carbon fibers and resins have resulted in far superior toughness values compared to the early generation of carbon/epoxy systems, the stigma of composite rocket motor cases being easily damaged and the burst strength compromised persists.

impact damage↗

Best Practices, Lessons Learned, and Examples on the Application of Damage Tolerance in Space Structures

Damage tolerance is an important consideration in space structures applications. The intent of damage tolerance is to demonstrate that the structure is robust to the presence of flaws over the service life of the space vehicle. Damage tolerance requirements in documents such as those in NASA, AIAA, and ISO can be challenging to implement. The intent of this paper is three-fold: (1) Provide best practices in the application of damage tolerance requirements for space applications, (2) Provide lessons learned for each of class of hardware, (3) Provide examples of challenging situations encountered in the application of damage tolerance. Examples cover additive manufacturing, composite overwrapped pressure vessels, pressurized structures, liquid rocket engines, thermal protection systems, and other classes of hardware. The philosophy and limitations of leak before burst and proof test logic are also discussed. Finally, a discussion on elastic-plastic fracture mechanics with comparisons to test data will be presented.

Best Practices↗