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At least 415 records · Page 23

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NASA NTRS2007

Recovery of Electron/Proton Radiation-Induced Defects in n+p AlInGaP Solar Cell by Minority-Carrier Injection Annealing

A high efficient In0.48Ga0.52P/In0.01Ga0.99As/Ge triple junction solar cell has been developed for application in space and terrestrial concentrator PV system [1-3]. Recently, a high conversion efficiency of 31.5% (AM1.5G) has been obtained in InGaP/(In)GaAs/Ge triple junction solar cell, and as a new top cell material of triple junction cells, (Al)InGaP [1] has been proposed to improve the open-circuit voltage (Voc) because it shows a higher Voc of 1.5V while maintaining the same short-circuit current (ISC) as a conventional InGaP top cell under AM1.5G conditions as seen in figure 1 (a). Moreover, the spectral response of 1.96eV AlInGaP cell with a thickness of 2.5..m shows a higher response in the long wavelength region, compared with that of 1.87eV InGaP cell with 0.6..m thickness, as shown in figure 1 (b). Its development will realize next generation multijunction (MJ) solar cells such as a lattice mismatched AlInGaP/InGaAs/Ge 3-junction and lattice matched AlInGaP/GaAs/InGaAsN/Ge 4-junction solar cells. Figure 2 shows the super high-efficiency MJ solar cell structures and wide band spectral response by MJ solar cells under AM1.5G conditions. For realizing high efficient MJ space solar cells, the higher radiation-resistance under the electron or proton irradiation is required. The irradiation studies for a conventional top cell InGaP have been widely done [4-6], but little irradiation work has been performed on AlInGaP solar cells. Recently, we made the first reports of 1 MeV electron or 30 keV proton irradiation effects on AlInGaP solar cells, and evaluated the defects generated by the irradiation [7,8]. The present study describes the recovery of 1 MeV electron / 30 keV proton irradiation-induced defects in n+p- AlInGaP solar cells by minority-carrier injection enhanced annealing or isochronal annealing. The origins of irradiation-induced defects observed by deep level transient spectroscopy (DLTS) measurements are discussed.

Lee, H. S.↗

NASA NTRS2004

Atomic Force Microscope Observation of Growth and Defects on As-Grown (111) 3C-SiC Mesa Surfaces

This paper presents experimental atomic force microscope (AFM) observations of the surface morphology of as-grown (111) silicon-face 3C-SiC mesa heterofilms. Wide variations in 3C surface step structure are observed as a function of film growth conditions and film defect content. The vast majority of as-grown 3C-SiC surfaces consisted of trains of single bilayer height (0.25 nm) steps. Macrostep formation (i.e., step-bunching) was rarely observed, and then only on mesa heterofilms with extended crystal defects. As supersaturation is lowered by decreasing precursor concentration, terrace nucleation on the top (111) surface becomes suppressed, sometimes enabling the formation of thin 3C-SiC film surfaces completely free of steps. For thicker films, propagation of steps inward from mesa edges is sometimes observed, suggesting that enlarging 3C mesa sidewall facets begin to play an increasingly important role in film growth. The AFM observation of stacking faults (SF's) and 0.25 nm Burgers vector screw component growth spirals on the as-grown surface of defective 3C films is reported.

Neudeck, Philip G.↗

NASA NTRS2016

Stacking Defects in Synthetic and Meteoritic Hibonites: Implications for High-Temperature Processes in the Solar Nebula

Hibonite (CaAl12O19) is a primary, highly refractory phase occurring in many Ca-Al-rich inclusions (CAIs) from different chondrite groups, except CI chondrites. Hibonite is predicted to be one of the earliest minerals to condense during cooling of the solar nebula at higher temperatures than any other major CAI mineral. Therefore, hibonite has great potential to reveal the processes and conditions of the very early, high-temperature stages of the solar nebular evolution. Previous microstructural studies of hibonite in CAIs and their Wark-Lovering (WL) rims showed the presence of numerous stacking defects in hibonite. These defects are interpreted as the modification of the stacking sequences of spinel and Ca-containing blocks within the ideal hexagonal hibonite structure, as shown by experimental studies of reaction-sintered ceramic CaO-Al2O3 compounds. We performed preliminary experiments in the CaO-Al2O3-MgO system to understand the formation processes and conditions of defect-structured hibonite found in meteorites.

Han, J.↗

NASA NTRS2016

Experimental Insights into the Origin of Defect-Structured Hibonites Found in Meteorites

Hibonite (CaAl12O19) is a primary, highly refractory phase occurring in many Ca-Al-rich inclusions (CAIs). Previous microstructural studies of hibonite in CAIs and their Wark-Lovering (WL) rims showed the presence of numerous stacking defects in hibonites. These defects are interpreted as the modification of the stacking sequences of spinel and Ca-containing blocks within the ideal hexagonal hibonite structure due to the presence of wider spinel blocks [3], as shown by experimental studies of reaction-sintered compounds in the CaO-Al2O3 system. We performed a series of experiments in the CaO-Al2O3-MgO system in order to provide additional in-sights into the formation processes and conditions of defect-structured hibonites found in meteorites.

Han. J.↗

NASA NTRS2014

Empirical and Face Validity of Software Maintenance Defect Models Used at the Jet Propulsion Laboratory

At the Mission Design and Navigation Software Group at the Jet Propulsion Laboratory we make use of finite exponential based defect models to aid in maintenance planning and management for our widely used critical systems. However a number of pragmatic issues arise when applying defect models for a post-release system in continuous use. These include: how to utilize information from problem reports rather than testing to drive defect discovery and removal effort, practical model calibration, and alignment of model assumptions with our environment.

software reliability↗

NASA NTRS2017

A Thermal Runaway Failure Model for Low-Voltage BME Ceramic Capacitors with Defects

Reliability of base metal electrode (BME) multilayer ceramic capacitors (MLCCs) that until recently were used mostly in commercial applications, have been improved substantially by using new materials and processes. Currently, the inception of intrinsic wear-out failures in high quality capacitors became much greater than the mission duration in most high-reliability applications. However, in capacitors with defects degradation processes might accelerate substantially and cause infant mortality failures. In this work, a physical model that relates the presence of defects to reduction of breakdown voltages and decreasing times to failure has been suggested. The effect of the defect size has been analyzed using a thermal runaway model of failures. Adequacy of highly accelerated life testing (HALT) to predict reliability at normal operating conditions and limitations of voltage acceleration are considered. The applicability of the model to BME capacitors with cracks is discussed and validated experimentally.

reliability↗

NASA NTRS2018

A Risk Analysis Tool for Estimating the Risk of Electrical Failures Due to Human Induced Defects

Aerospace electrical systems are required to withstand and adequately operate in extremely harsh environments that include, for example, high radiation exposure, temperature extremes, intense vibrational stress and drastic temperature cycling. The nature of aerospace electronics also demands high reliability since, with very few exceptions, there is no chance for hardware servicing or repairs. Common risk mitigation techniques for this type of situation are to perform a Reliability Analysis of the system throughout the development cycle, and to use electrical components that are regarded as “high reliability” because of additional controls and requirements applied in their design, manufacturing and testing. Unfortunately, studies have shown that even though these techniques are used, many systems fail to meet mission requirements well before the predicted lifetimes. This paper presents the analysis of failures of electrical parts, experienced during various stages of system development, at NASA Goddard Space Flight Center, Greenbelt MD, between the years 2001 and 2013. These components were subjected to qualification, screening and testing in which the goal was to ensure that the components would survive the stresses of the mission. The analysis categorizes failures by part type and failure mechanisms. One of the results of the analysis was the realization that a surprising proportion of failures experienced during system integration and testing were caused by human error (i.e. human induced defect). Further analysis included the determination of root failure mechanisms and any influencing factors contributing to these failures. The major causes of these defects were attributed to electrostatic damage (ESD), electrical overstress (EOS), mechanical overstress (MOS), and thermal overstress (TOS). Finally, the study proposes a risk analysis tool which incorporates these major causes for the failures, termed error-producing conditions (EPCs), and a proportionality factor representing the number of each type of failure that has occurred at the facility under study. These factors are quantified and used to communicate the risk of human induced defects for the assembly, integration and testing of space hardware based on the system’s electrical parts list. The new risk identification can trigger risk-mitigating actions more effectively, based on the presence of component categories or other hazardous conditions that have a history of failure due to human error.

Majewicz, Peter J.↗

NASA NTRS2020

Ultrasonic Lamb Wave Inspection of Composite Defects

Composites have been extensively used in aerospace engineering due to their advantages of light weight, high strength, and engineering design flexibility. Manufacturing defects such as wrinkle and porosity can affect the performance of the composites and may lead to failure in the end, while damage such as delamination, fiber fraction, and matrix cracking can directly cause failure of the composites. In this paper, a Lamb wave based nonintrusive nondestructive evaluation system, which employs piezoelectric transducer for actuation and scanning laser Doppler vibrometer for wavefield sensing, is presented for typical composite defect and damage inspection and evaluation. Two composite panels with different geometry (flat or curved) and with various embedded defects (wrinkle and delamination) are inspected using the nonintrusive Lamb wave system. Both the wrinkles and delamination are detected from the wavefield and approximately quantified through wavefield imaging methods.

Wrinkles↗

NASA NTRSDate not supplied

3D Localization of Defects in Facility Inspection

Wind tunnels are crucial facilities that support the aerospace industry. However, these facilities are large, complex, and pose unique maintenance and inspection requirements. Manual inspections to identify defects such as cracks, missing fasteners, leaks, and foreign objects are important but labor and schedule intensive. Our goal is to utilize small Unmanned Aircraft Systems (sUAS) and computer vision-based analysis to automate the inspection of the interior and exterior of NASA’s critical wind tunnel facilities. We detect missing fasteners as our defect class, and detect existing fasteners to provide potential future missing fastener sites for preventative maintenance. These detections are done on both 2D raw images and in 3D space to provide a visual reference and real world location to facilitate repairs. A dataset was created consisting of images taken along a grid-like pattern of an interior tunnel section in the AEDC National Full-Scale Aerodynamics Complex (NFAC) at NASA Ames Research Center. Our method uses object detection to create image level bounding boxes of the fasteners and missing fasteners, then uses photogrammetry to create a mapping from 2D image locations to 3D real world locations. The image level bounding boxes and the 2D to 3D mapping are then combined to determine the 3D location of the defects. We describe the data collection, photogrammetry, and computer vision techniques used for object detection as well as a quantitative analysis of the method.

Small Unmanned Aircraft Systems (sUAS)↗

NASA NTRS2020

Fatigue Failures at Defective Grains in a Single Crystal Nickel-Base Superalloy

Single crystal nickel-base superalloys used as turbine engine blades can have much higher creep and fatigue resistance than many polycrystalline superalloys due to the absence of weak grain boundaries as well as the ability to orient the blades in the primary loading direction on to the low elastic modulus [001] orientation, which significantly lowers the stresses imposed on the blades. However, grain defects can occur in these crystals, impairing these advantages. In the present study, fatigue tests of a single crystal superalloy uncovered unexpected defective grains in the test specimens, which initiated premature fatigue failures. The characteristics of these defective grains and the associated failures were evaluated and related to the observed fatigue lives.

superalloy↗

NASA NTRSDate not supplied

Towards Integrated Computational Materials Engineering for Quantifying Performance Impacts of Microstructure and Defect Interactions in Powder Bed Fusion Parts

Powder bed fusion (PBF) additive manufacturing (AM) enables the creation of parts with complexity and functionality levels that were previously impossible with traditional manufacturing methods. By modifying the laser power, hatch spacing, or the numerous other processing parameters, the PBF process supports the production of a wide set of materials and geometries. However, that same process parameter design flexibility causes the process-design space of PBF to be massive and expensive to explore experimentally. Another challenge is quality variation across a build. As a part is being built, geometric variance between locations, such as at a thin-wall section vs. the bulk material, may cause the specified processing parameters to no longer be acceptable for producing defect-free printing. Furthermore, if the processing parameters deviate during the print process, it is difficult to assess if the part will still perform satisfactorily. Integrated Computational Materials Engineering (ICME) provides a way to understand and address these various challenges. This talk will present advancements in process-structure simulations of PBF at NASA Langley Research Center. The ability to simulate grain-scale PBF microstructures using the Physically Based Monte Carlo method will be demonstrated and compared to experimental measurements. Techniques for simulating three-dimensional lack-of-fusion and keyhole porosity defects based on the specific processing conditions and approaches for integrating the two porosity prediction techniques alongside the computational microstructure evolution models will be shown. Finally, the integration of simulated PBF microstructures, embedded process defects, and crystal plasticity finite element models to elucidate the interaction of porosity and microstructure on micromechanical fields will be demonstrated. These integrated techniques demonstrate an example of using ICME to relate processing to performance for PBF AM materials. With continued maturity, it is hoped that such ICME approaches will lead to next-generation computational-materials supported qualification and certification of AM parts.

Additive manufacturing↗

NASA NTRSDate not supplied

Discerning Cell Surface Defects with 3D Optical Profilometry

This investigation seeks to establish better criteria that can be used for qualitative visual screening of cylindrical battery cells through exploration of various defects across multiple cylindrical Lithium-Ion battery cells. This investigation focuses on INR18650s and INR21700s cells from Molicel, LG, and Samsung. The principal instrument used is a high-definition 3D optical profilometer with measurement accuracy less than 0.5 microns. Through this effort, a catalog was built discerning minor surface imperfections from significant flaws. The catalog generated covers a comparison of axial and radial scratches, less than 5 microns, greater than 5 microns and greater than 15 microns, as well as the difference between surface discoloration, early-stage pitting, and late stages of corrosion. An exploration is made into cell button defects and crimp shoulder defects. When ultra-high-power optical magnification and three-dimension topological tools are not immediately available, this catalog will help determine if an individual cell is usable, worth further investigation, or failing. The purpose of this catalog is to be a field guide used for quick reference of a potential issue, with the goal of increasing screening throughput while reducing the need for costly examination. Trade names and trademarks are used in this abstract for identification only. Their usage does not constitute an official endorsement, either expressed or implied, by the National Aeronautics and Space Administration.

battery↗

NASA NTRSDate not supplied

Discerning Cell Surface Defects with 3D Optical Profilometry

battery↗

NASA NTRSDate not supplied

Defect Detection in ISC Cylinder Using Spoof Plasmon Polaritons

NASA is exploring the use of microwave spoof plasmon polaritons to detect defects in integrally stiffened cylinders. This work investigates the detection of simulated defects in the form of aluminum wires as small as 10 mm long and 3.1 mm diameter that are placed in between stiffeners of an ISC. The wires simulate manufacturing inclusions defects, and the sum of the delta impedance is shown to increase with increasing volume of added metal.

spoof↗

DOE OSTI2025

Fusion of Experiments and Simulations for Real-Time Identification of Pipeline Defects

In this study, we explored fusion of experiments and simulations for real time identification of pipeline defects across physical and non-physical domains. The challenges associated to data processing were addressed and a combined classification models was presented via CNN models. In addition, regression model based on XGBOOST is built to determine the defect location and defect dimension from data-driven features of guided wave signals captured by SMS fiber optic sensor.

deep learning↗

DOE OSTI2025

Effective Defect Detection Using Instance Segmentation for NDI

Ultrasonic testing is a common Non-Destructive Inspection (NDI) method used in aerospace manufacturing. However, the complexity and size of the ultrasonic scans make it challenging to identify defects through visual inspection or machine learning models. Using computer vision techniques to identify defects from ultrasonic scans is an evolving research area. In this study, we used instance segmentation to identify the presence of defects in the ultrasonic scan images of composite panels that are representative of real components manufactured in aerospace. We used two models based on Mask- RCNN (Detectron 2) and YOLO 11 respectively. Additionally, we implemented a simple statistical pre-processing technique that reduces the burden of requiring custom-tailored pre-processing techniques. Our study demonstrates the feasibility and effectiveness of using instance segmentation in the NDI pipeline by significantly reducing data pre-processing time, inspection time, and overall costs.

computer vision techniques↗

DOE OSTI2024

A Finite Difference informed Random Walk solver for simulating radiation defect evolution in polycrystalline structures with strongly inhomogeneous diffusivity

Diffusivity of species and defects on grain boundaries is usually several orders of magnitude larger than that inside grains. Such strongly inhomogeneous diffusivity requires prohibitively high computational demands for modeling microstructural evolution. Here, this paper presents a highly-efficient numerical solver, combining the Finite Difference method and Random Walk model, designed for accurately modeling strongly inhomogeneous diffusion within polycrystalline structures. The proposed solver, termed Finite Difference informed Random Walk (FDiRW), integrates a customized Finite Difference (cFD) scheme tailored for fast diffusion along thin grain boundaries represented by a single-layer of nodes. Numerical experiments demonstrate that the FDiRW solver achieves an impressive efficiency gain of 1560x compared to traditional Finite Difference methods while maintaining accuracy, making it feasible for personal computer machines to handle diffusional systems with strongly inhomogeneous diffusivity across static polycrystalline microstructures. The model has been successfully applied to simulate radiation defect evolution, showcasing its scalability to engineering scales in both length and time dimensions.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Mechanochemical topological defects in an active nematic

We propose a reaction-diffusion system that converts topological information of an active nematic into chemical signals. We show that a curvature-activated reaction dipole is sufficient for creating a system that dynamically senses topology by producing a concentration field possessing local extrema coinciding with ±$\frac{1}{2}$ defects. The enabling term is analogous to polarization charge density seen in dielectric materials. We demonstrate the ability of this system to identify defects in both passive and active nematics. Our results illustrate that a relatively simple feedback scheme, expressed as a system of partial differential equations, is capable of producing chemical signals in response to inherently nonlocal structures in anisotropic media. Here, we posit that such coarse-grained systems can help generate testable hypotheses for regulated processes in biological systems, such as morphogenesis, and motivate the creation of bio-inspired materials that utilize dynamic coupling between nematic structure and biochemistry.

42 ENGINEERING↗