Non-Destructive Testing of Structures Using Optical and Other Methods: A Review

Non-destructive testing (NDT) of structures is one of the most important tasksof the proper maintenance and diagnosis of machines and constructions structuralcondition. NDT methods contribute to the damage tolerance philosophy used in theaircraft design methodology as well as many other operation and maintenance programsof machinery and constructions. The following study is focusing on overviewing animportant group of NDT methods: the optical and other ones, which found broadapplicability in scientific and industrial studies nowadays. The paper discusses theselected most widely applicable methods, namely, visual testing, ultrasonic testing,radiographic testing, infrared thermography as well as electronic speckle patterninterferometry and shearographic testing. Besides the basic principles of testing usingthese methods, their potential applications in various industrial and technologicalbranches are broadly discussed. The analysis as categorization of the NDT methodsprovided in this paper may help in selection of such methods in diagnosis of varioustypes of structures and defects and damage occurring in these structures.

Effectiveness Assessment of the Search-Based Statistical Structural Testing

Search-based statistical structural testing(SBSST)is a promising technique that uses automated search to construct input distributions for statistical structural testing.It has been proved that a simple search algorithm,for example,the hill-climber is able to optimize an input distribution.However,due to the noisy fitness estimation of the minimum triggering probability among all cover elements(Tri-Low-Bound),the existing approach does not show a satisfactory efficiency.Constructing input distributions to satisfy the Tri-Low-Bound criterion requires an extensive computation time.Tri-Low-Bound is considered a strong criterion,and it is demonstrated to sustain a high fault-detecting ability.This article tries to answer the following question:if we use a relaxed constraint that significantly reduces the time consumption on search,can the optimized input distribution still be effective in faultdetecting ability?In this article,we propose a type of criterion called fairnessenhanced-sum-of-triggering-probability(p-L1-Max).The criterion utilizes the sum of triggering probabilities as the fitness value and leverages a parameter p to adjust the uniformness of test data generation.We conducted extensive experiments to compare the computation time and the fault-detecting ability between the two criteria.The result shows that the 1.0-L1-Max criterion has the highest efficiency,and it is more practical to use than the Tri-Low-Bound criterion.To measure a criterion’s fault-detecting ability,we introduce a definition of expected faults found in the effective test set size region.To measure the effective test set size region,we present a theoretical analysis of the expected faults found with respect to various test set sizes and use the uniform distribution as a baseline to derive the effective test set size region’s definition.

Setup and application of a structural seismic hybrid simulation system on local area network

To implement structural hybrid simulation independent of the control system of any testing equipment in civil engineering, an external command control approach is put forward. Several setup technologies and the corresponding API approaches are investigated to simultaneously combine numerical simulation with physical testing. Hybrid program technology is put forward and described in detail, using Visual C++ program to effectively and accurately control testing equipment and MATLAB program to implement numerical simulation with easy extension. The control program of testing equipment and numerical simulation program are integrated by calling MATLAB engine in Visual C++. A hybrid simulation about a full-scale six-story masonry structure is carried out. The testing results manifest that the external command control approach has the versatility because of simple hardware connection and control program independent on control software of testing equipment; powerful program function of Visual C++ and flexible program of MATLAB are integrated by hybrid program technology; hybrid simulation system provides a realistic and cost-effective testing platform that enables earthquake engineer researchers to accurately and efficiently capture the seismic performance of large or complex structures without having to carry out physical testing of the entire structure.

An Improved Parasitic Parameter Extraction Method for InP HEMT

An improved parasitic parameter extraction method for InP high electron mobil-ity transistor(HEMT)is presented.Parasitic parameter extraction is the first step of model parameter extraction and its accuracy has a great impact on the subsequent internal pa-rameter extraction.It is necessary to accurately determine and effectively eliminate the parasitic effect,so as to avoid the error propagation to the internal circuit parameters.In this paper,in order to obtain higher accuracy of parasitic parameters,parasitic parameters are extracted based on traditional analytical method and optimization algorithm to obtain the best parasitic parameters.The validity of the proposed parasitic parameter extraction method is verified with excellent agreement between the measured and modeled S-param-eters up to 40 GHz for InP HEMT.In 0.1-40 GHz InP HEMT,the average relative error of the optimization algorithm is about 9%higher than that of the analysis method,which verifies the validity of the parasitic parameter extraction method.The extraction of parasit-ic parameters not only provides a foundation for the high-precision extraction of small sig-nal intrinsic parameters of HEMT devices,but also lays a foundation for the high-preci-sion extraction of equivalent circuit model parameters of large signal and noise signals of HEMT devices.

Knowledge-embedded spatio-temporal analysis for euploidy embryos identification in couples with chromosomal rearrangements

Background:The goal of the assisted reproductive treatment is to transfer one euploid blastocyst and to help infertile women giving birth one healthy neonate.Some algorithms have been used to assess the ploidy status of embryos derived from couples with normal chromosome,who subjected to preimplantation genetic testing for aneuploidy(PGT-A)treatment.However,it is currently unknown whether artificial intelligence model can be used to assess the euploidy status of blastocyst derived from populations with chromosomal rearrangement.Methods:From February 2020 to May 2021,we collected the whole raw time-lapse videos at multiple focal planes from in vitro cultured embryos,the clinical information of couples,and the comprehensive chromosome screening results of those blastocysts that had received PGT treatment.Initially,we developed a novel deep learning model called the Attentive Multi-Focus Selection Network(AMSNet)to analyze time-lapse videos in real time and predict blastocyst formation.Building upon AMSNet,we integrated additional clinically predictive variables and created a second deep learning model,the Attentive Multi-Focus Video and Clinical Information Fusion Network(AMCFNet),to assess the euploidy status of embryos.The efficacy of the AMCFNet was further tested in embryos with parental chromosomal rearrangements.The receiver operating characteristic curve(ROC)was used to evaluate the superiority of the model.Results:A total of 4112 embryos with complete time-lapse videos were enrolled for the blastocyst formation prediction task,and 1422 qualified blastocysts received PGT-A(n=589)or PGT for chromosomal structural rearrangement(PGT-SR,n=833)were enrolled for the euploidy assessment task in this study.The AMSNet model using seven focal raw time-lapse videos has the best real-time accuracy.The real-time accuracy for AMSNet to predict blastocyst formation reached above 70%on the day 2 of embryo culture,and then increased to 80%on the day 4 of embryo culture.Combing with 4 clinical features of couples,the AUC of AMCFNet with 7 focal points increased to 0.729 in blastocysts derived from couples with chromosomal rearrangement.Conclusion:Integrating seven focal raw time-lapse images of embryos and parental clinical information,AMCFNet model have the capability of assessing euploidy status in blastocysts derived from couples with chromosomal rearrangement.

Novel serpentine structure design method considering confidence level and estimation precision

Due to the importance of metal layers in the product yield,serpentine test structures are usually fabricated on test chips to extract parameters for yield prediction.In this paper,the confidence level and estimation precision of the average defect density on metal layers are investigated to minimize the randomness of experimental results and make the measured parameters more convincing.On the basis of the Poisson yield model,the method to determine the total area of all serpentine test structures is obtained using the law of large numbers and the Lindeberg-Levy theorem.Furthermore,the method to determine an adequate area of each serpentine test structure is proposed under a specific requirement of confidence level and estimation precision.The results of Monte Carlo simulation show that the proposed method is consistent with theoretical analyses.It is also revealed by wafer experimental results that the method of designing serpentine test structure proposed in this paper has better performance.

High-Strain Fiber Bragg Gratings for Structural Fatigue Testing of Military Aircraft

This paper reports on an experimental program of work which investigates the reliability, durability, and packaging of fiber Bragg gratings （FBGs） for application as distributed strain sensors during structural fatigue testing of military platforms. The influence of the FBG fabrication process on sensor reliability is investigated. In addition, methodologies for broad-area packaging and surface-mounting of FBG sensing arrays to defense platforms are developed and tested.

Fiducial generalized p-values for testing zero-variance components in linear mixed-effects models

Linear mixed-effects models are widely used in analysis of longitudinal data. However, testing for zero-variance components of random effects has not been well-resolved in statistical literature, although some likelihood-based procedures have been proposed and studied. In this article, we propose a generalized p-value based method in coupling with fiducial inference to tackle this problem. The proposed method is also applied to test linearity of the nonparametric functions in additive models. We provide theoretical justifications and develop an implementation algorithm for the proposed method. We evaluate its finite-sample performance and compare it with that of the restricted likelihood ratio test via simulation experiments. We illustrate the proposed approach using an application from a nutritional study.

Corrosion Behavior of S450EW Low-alloy Weathering Steel in Cyclically Alternate Corrosion Environments

Weathering steel is widely used in various fields due to its excellent mechanical properties and high corrosion resistance. The effect of chromium content on the S450 EW weathering steel in cyclic immersion test was studied. The results indicated that the corrosion resistance of S450 EW weathering steel is closely related to chromium content. The addition of chromium significantly inhibited the weathering steel corrosion. The corrosion rate of experimental steel after 96 h immersion was 1.101 g·m-2·h-1. The rust of S450 EW weathering steel was mainly constituted of Fe OOH and Fe3O4 phase, and the elevation of chromium content promoted the formation of α-Fe OOH. The fine precipitates of the two phases contributed to the formation of dense dust layer of test steel. Furthermore, the increase of chromium is beneficial for the cure of original defects and cracks of the rust layer via the enrichment of chromium. The corrosion potential and the resistance of corrosion process were thus increased, protecting the experimental steel from further corrosion. A S450 EW steel with corrosion resistance more than 1.5 times of Q450NQR1 steel was prepared.

Towards Fast and Efficient Algorithm for Learning Bayesian Network

Learning Bayesian network structure is one of the most exciting challenges in machine learning. Discovering a correct skeleton of a directed acyclic graph（DAG） is the foundation for dependency analysis algorithms for this problem. Considering the unreliability of high order condition independence（CI） tests, and to improve the efficiency of a dependency analysis algorithm, the key steps are to use few numbers of CI tests and reduce the sizes of conditioning sets as much as possible. Based on these reasons and inspired by the algorithm PC, we present an algorithm, named fast and efficient PC（FEPC）, for learning the adjacent neighbourhood of every variable. FEPC implements the CI tests by three kinds of orders, which reduces the high order CI tests significantly. Compared with current algorithm proposals, the experiment results show that FEPC has better accuracy with fewer numbers of condition independence tests and smaller size of conditioning sets. The highest reduction percentage of CI test is 83.3% by EFPC compared with PC algorithm.

Biomimicking and evaluation of dragonfly wing morphology with polypropylene nanocomposites

Dragonfly hindwing inspired two different flapping wing morphologies are investigated for flexible flapping wing micro air vehicles(FWMAV)applications.The wing skin is developed using 1%functionalized carbon nanotubes reinforced polypropylene nanocomposites with carbon fiber epoxy composite strands as venation pattern.The resonance frequencies are the fundamental information for biomimicking and were calculated theoretically from stiffness data.Bending dominated first natural frequency was obtained from flexural stiffness data and found close to the flapping frequency of natural dragonfly hindwing.Twisting dominated second natural frequency was obtained from torsional stiffness,which revealed that the artificial wings can be fabricated thinner.The flapping frequency of artificial wings is unaffected by the twisting deformation.The bending and twisting dominated mode shapes are also studied using the digital image correlation(DIC)system.To verify the static and dynamic results,finite element simulations are performed that agree with experimental findings.It was found that the proposed flexible nanocomposite wing skin can control the bending and twisting dominated frequencies by tailoring the wing morphology without affecting the mode shapes of deformation.