Vision-based multi-level synthetical evaluation of seismic damage for RC structural components: a multi-task learning approach

Recent studies for computer vision and deep learning-based,post-earthquake inspections on RC structures mainly perform well for specific tasks,while the trained models must be fine-tuned and re-trained when facing new tasks and datasets,which is inevitably time-consuming.This study proposes a multi-task learning approach that simultaneously accomplishes the semantic segmentation of seven-type structural components,three-type seismic damage,and four-type deterioration states.The proposed method contains a CNN-based encoder-decoder backbone subnetwork with skip-connection modules and a multi-head,task-specific recognition subnetwork.The backbone subnetwork is designed to extract multi-level features of post-earthquake RC structures.The multi-head,task-specific recognition subnetwork consists of three individual self-attention pipelines,each of which utilizes extracted multi-level features from the backbone network as a mutual guidance for the individual segmentation task.A synthetical loss function is designed with real-time adaptive coefficients to balance multi-task losses and focus on the most unstably fluctuating one.Ablation experiments and comparative studies are further conducted to demonstrate their effectiveness and necessity.The results show that the proposed method can simultaneously recognize different structural components,seismic damage,and deterioration states,and that the overall performance of the three-task learning models gains general improvement when compared to all single-task and dual-task models.

Bridging finite element and deep learning: High-resolution stress distribution prediction in structural components

Finite-element analysis(FEA)for structures has been broadly used to conduct stress analysis of various civil and mechanical engineering structures.Conventional methods,such as FEA,provide high fidelity results but require the solution of large linear systems that can be computationally intensive.Instead,Deep Learning(DL)techniques can generate results significantly faster than conventional run-time analysis.This can prove extremely valuable in real-time structural assessment applications.Our proposed method uses deep neural networks in the form of convolutional neural networks(CNN)to bypass the FEA and predict high-resolution stress distributions on loaded steel plates with variable loading and boundary conditions.The CNN was designed and trained to use the geometry,boundary conditions,and load as input to predict the stress contours.The proposed technique’s performance was compared to finite-element simulations using a partial differential equation(PDE)solver.The trained DL model can predict the stress distributions with a mean absolute error of 0.9%and an absolute peak error of 0.46%for the von Mises stress distribution.This study shows the feasibility and potential of using DL techniques to bypass FEA for stress analysis applications.

Structural Analysis of Platforms with the Effect of Joint Flexibility

A modified space beam element is presented in this paper to consider the local joint flexibility of T, Y tubular joints subjected to axial forces and in-plane bending moments for analysis of platforms. Two numerical examples are shown to verify the efficiency and validity of the method presented here.

THEORY OF ELASTICITY OF AN ANISOTROPIC BODY FOR THE BENDING OF BEAMS

A theory of elasticity for the bending of orthogonal anisotropic beams was developed in this paper by analogy with the special case, which can be obtained by applying the theory of elasticity for bending of transversely isotropic plates to the problems of two dimensions. The authors also presented a method to solve the problems of bending of orthogonal anisotropic beams and a new theory of the deep-beam whose ratio of depth to length is larger. It is pointed out that Reissner's theory which takes into account the effect of transverse shear deformation is not suitable for the components of stress in our case.

Seawater Corrosion Fatigue of Welded Joints Under Random Variable Amplitude Loading

Offshore platforms are always subjected to wave action which is random variable amplitude cyclic loading. In order to simulate the stressing condition at the 'hot spot' of the tubular joints and the marine environment, random variable amplitude fatigue tests have been carried out on welded plate joints in sea water. The tests have been conducted under the conditions of loading frequency of 0.2 Hz/, stress ratio of -1, seawater temperature of about 20°C and cathodic protection with the potential about -850 mV, SCE. The test results have been compared with the seawater corrosion fatigue life under constant amplitude loading. Miner's linear cumulative damage summation rule has been used to predict the corrosion fatigue life under variable amplitude loading. The predicted life is in good agreement with the test data.

Regression Formulations for the Stress at Hot Spot of Multiplanar Tubular DT Joints

Stress concentration analysis of multiplanar tubular DT joints plays an important role in the fatigue design of offshore platforms. A semi-analytic method for stress analysis under the condition of any loads is briefly introduced in the paper. Nineteen multiplanar tubular DT joints with one of two braces of the same dimension subjected to axial loads and out- of- plane bending moments are computed for parametric stress analysis by using the present method. The influence of geometrical parameters on the stresses of multiplanar tubular DT joints is discussed and compared with corresponding uniplanar T joints. The regression formulae for the stress at hot spot of multiplanar DT joints are found by modification of SCF of corresponding uniplanar T joints. The parametric formulae for the maximum stress by superposition. Finally, the influences of stiffening effect and load-interaction effect on the maximum stress of DT joints are discussed.

PERTURBATION SOLUTION FOR THERMAL EXPANSION BUCKLING OF NO EXPANSION JOINT SLOPE PAVEMENT PLATE

The mechanical mechanism of thermal expansion buckling of no expansion joint slope pavement undergoing the action of a temperature field was analyzed. By using the regular perturbation method, the formula of perturbation solution for this problem was derived, the relationship between critical laying temperature difference of slope pavement and of level straight pavement was studied, and the unified solution as well as its numerical results was also obtained. In terms of this research, the reasonable laying temperature of no expansion joint slope pavement was given.

P-FEMOL ANALYSIS OF PLATE BENDING PROBLEMS

In this paper, the p- version of the finite element method of lines (FEMOL) for the analysis of the Mindlin-Reissner plate bending problems is presented and a class of p-FEMOL elements with polynomial degrees as high as nine is developed. Numerical examples given in this paper show tremendous performance of the present method: namely, rapid convergence rate, high accuracy for both displacements and stress resultants, removal of shear-locking trouble, capability of dealing with difficult problems such as the boundary layer behavior near a free edge and stress concentration around a hole.

The effects of torsional ground motion on thin cylindric shell structures

The effects of torsional component of earthquake ground motion on thin cylindric shell structures were investigated qualitatively and quantitatively.The results show that the contributions of torsional component to structural response are related to the height,the radius-to-height ratio,and the stiffness of the structure.The structural response caused by torsional component can not be neglected for the containment structure of nuclear power plant and the industrial oil tank.

gscaLCA in R: Fitting Fuzzy Clustering Analysis Incorporated with Generalized Structured Component Analysis

Clustering analysis identifying unknown heterogenous subgroups of a population(or a sample)has become increasingly popular along with the popularity of machine learning techniques.Although there are many software packages running clustering analysis,there is a lack of packages conducting clustering analysis within a structural equation modeling framework.The package,gscaLCA which is implemented in the R statistical computing environment,was developed for conducting clustering analysis and has been extended to a latent variable modeling.More specifically,by applying both fuzzy clustering(FC)algorithm and generalized structured component analysis(GSCA),the package gscaLCA computes membership prevalence and item response probabilities as posterior probabilities,which is applicable in mixture modeling such as latent class analysis in statistics.As a hybrid model between data clustering in classifications and model-based mixture modeling approach,fuzzy clusterwise GSCA,denoted as gscaLCA,encompasses many advantages from both methods:(1)soft partitioning from FC and(2)efficiency in estimating model parameters with bootstrap method via resolution of global optimization problem from GSCA.The main function,gscaLCA,works for both binary and ordered categorical variables.In addition,gscaLCA can be used for latent class regression as well.Visualization of profiles of latent classes based on the posterior probabilities is also available in the package gscaLCA.This paper contributes to providing a methodological tool,gscaLCA that applied researchers such as social scientists and medical researchers can apply clustering analysis in their research.

Structural elucidation of sex pheromone components of the Geometridae Semiothisa cinerearia(Bremer et Grey)in China

An extract from the female sex gland of Semiothisa cinerearia attracted conspecific males in field tests.A major active component was isolated from the extract and identified by GC-MS,GC-IR and microchemical reactions as cis-3,4-cpoxy-(Z,Z)-6,9-heptadecadiene,which showed strong EAG response.Another minor yet important component was identified as (Z,Z,Z)-3,6,9-heptadecatriene.

SIMULATION OF THE INTERFACED STRUCTURAL COMPONENT BASED ON A MULTIPLE-TIME-SCALE ALGORITHM

A multiple-time-scale algorithm is developed to numerically simulate certain structural components in civil structures where local defects inevitably exist. Spatially, the size of local defects is relatively small compared to the structural scale. Different length scales should be adopted considering the efficiency and computational cost. In the principle of physics, different length scales are stipulated to correspond to different time scales. This concept lays the foundation of the framework for this multiple-time-scale algorithm. A multiple-time-scale algorithm, which involves different time steps for different regions, while enforcing the compatibility of displacement, force and stress fields across the interface, is proposed. Furthermore, a defected beam component is studied as a numerical sample. The structural component is divided into two regions： a coarse one and a fine one; a micro-defect exists in the fine region and the finite element sizes of the two regions are diametrically different. Correspondingly, two different time steps are adopted. With dynamic load applied to the beam, stress and displacement distribution of the defected beam is investigated from the global and local perspectives. The numerical sample reflects that the proposed algorithm is physically rational and computationally efficient in the potential damage simulation of civil structures.

A plating method for metal coating of fiber Bragg grating

We present a method for metal coating optical fiber and in-fiber Bragg grating. The technology process which is based on electroless plating and electroplating method is described in detail. The fiber is firstly coated with a thin copper or nickel plate with electroless plating method. Then, a thicker nickel plate is coated on the surface of the conductive layer. Under the optimum conditions, the surfaces of chemical plating and electroplating coatings are all smooth and compact. There is no visible defect found in the cross-section. Using this two-step metallization method, the in-fiber Bragg grating can be well protected and its thermal sensitivity can be enhanced. After the metallization process, the fiber sensor is successfully embedded in the 42CrMo steel by brazing method. Thus a smart metal structure is achieved. The embedding results show that the plating method for metallization protection of in-fiber Bragg grating is effective.

Continuous-wave and Q-switched performance of an Yb:YAG/YAG composite thin disk ceramic laser pumped with 970-nm laser diode

Using front face-pumped compact active mirror laser （CAMIL） structure, we have demonstrated an Yb：YAG/YAG composite ceramic disk laser with pumping wavelength at 970 nm. The laser has been operated in both continuous-wave （CW） and Q-switching modes. Under CW operation, laser output power of 1.05 W with 2% transmission output coupler was achieved at the wavelength of 1031 nm. Q- switched laser output was gotten by using an acousto-optic Q-switch. The repetition rate ranged from 1 to 30 kHz and the pulse width varied from 166 to 700 ns.

X-ray photon-counting detector based on a micro-channel plate for pulsar navigation

The pulse time of arrival （TOA） is a determining parameter for accurate timing and positioning in X-ray pulsar navigation. The pulse TOA can be calculated by comparing the measured arrival time with the predicted arrival time of the X-ray pulse for pulsar. In this study, in order to research the measurement of pulse arrival time, an experimental system is set up. The experimental system comprises a simulator of the X-ray pulsar, an X-ray detector, a time-measurement system, and a data-processing system. An X-ray detector base is proposed on the basis of the micro-channel plate （MCP）, which is sensitive to soft X-ray in the 1–10 keV band. The MCP-based detector, the structure and principle of the experimental system, and results of the pulse profile are described in detail. In addition, a discussion of the effects of different X-ray pulse periods and the quantum efficiency of the detector on pulse-profile signal-to-noise ratio （SNR） is presented. Experimental results reveal that the SNR of the measured pulse profile becomes enhanced as the quantum efficiency of the detector increases. The SNR of the pulse profile is higher when the period of the pulse is smaller at the same integral.

Polarization conversions of diffractive wave plates based on orthogonal circular-polarization holography

A polarization holographic grating, which integrates the functions of a grating and a wave plate and is called a diffractive wave plate, is recorded by two beams （left and right circularly polarized） of a 532 nm laser in an azo polymer with a liquid-crystal structure. The polarization conversion characteristics of the diffractive wave plates are investigated with a detecting light of 650 nm by metering the polarization state of first-order diffracted light. It is confirmed that the diffractive wave plates convert the incident linear polarization into circular polarization for a linearly polarized probe laser and reverse the sense of rotation of the circular polarization when the detecting light is circularly polarized light.

Synthesis and optical properties of PbMoO_4 nanoplates

Nanometer sized lead molybdate （PbMoO4） plates are prepared through conventional hydrothermal together with sonochemical methods. The plates are then characterized using field-emission scanning electron microscopy, X-ray diffractometry, Fourier transform infrared （FTIR） spectrometry, photoluminescence spectrometry, and ultraviolet-visible （UV-VIS） spectrometry. The results indicate that the nanoplates have a characteristically narrow particle size distribution and their tetragonal scheelite-type structure is confirmed by both X-ray diffractometry and FTIR spectrometry. When the nanoplates are compared with the corresponding bulk crystals, blue shifts in their photoluminescence peaks, wider optical band gaps, and the broadening of the X-ray diffractometer peaks are observed. These can be ascribed to the decrease in crystal size.

Experimental Investigation on Heat Transfer Enhancement in Composite Porous Media

The method of composite porous media with mini-longitudinal channels at the surface and with heads packing between plates was put forward to improve the integrated performance of flow and heat transfer in porous media. The experimental results in the corresponding porous media were reported and analyzed. The experiments indicate that with proper matching of the particle diameter dp, the mini-channel width ω, the channel depth d and the distance between plates δr the heat transfer in the composite porous media is enhanced and flow resistance reduced compared with those of no mini-longitudinal channels at the surface. So this is an effective method to improve the integrated performance of flow and heat transfer in porous media.

Highly efficient mid-infrared metasurface based on metallic rods and plate

Metasurface is a new kind of 2D metamaterial that is able to manage a variety of light beam modulations through steering the phase of the scattering waves. In this work, we utilize the metasurface to manipulate the light beam in the mid-infrared regime. By using the metallic rod and the plate structure, the metasurface presents a high polarization conversion efficiency and a wide working bandwidth. With specially rotated metallic rods, the meta- surface can realize various light beam manipulations, such as negative reflection, beam collimation, and focusing. All of these results show that such a metasurface will have potential applications in future mid-infrared optics.