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Three-scale stochastic homogenization of elastic recycled aggregate concrete based on nano-indentationdigital images

Chen WANG, Yuching WU, Jianzhuang XIAO

《结构与土木工程前沿（英文）》 2018年 第12卷 第4期   页码 461-473 doi: 10.1007/s11709-017-0441-7

摘要： In this paper, three-scale stochastic elastic finite element analyses are made for recycled aggregate concrete (RAC) based on nano-indentation digital images. The elastic property of RAC contains uncertainties across scales. It has both theoretical and practical values to model and predict its mechanical performance. Based on homogenization theory, effective stochastic elastic moduli of RAC at three different scales are obtained using moving window technique, nano-indentation digital images, and Monte-Carlo method. It involves the generation of a large number of random realizations of microstructure geometry based on different volume fraction of the inclusions and other parameters. The mean value, coefficient of variation and probability distribution of the effective elastic moduli are computed considering the material multiscale structure. The microscopic randomness is taken into account, and correlations of RAC among five phases are investigated. The effective elastic properties are used to obtain the global behavior of a composite structure. It is indicated that the response variability can be considerably affected by replacement percentage of recycled aggregates.

关键词： RAC     nano-indentation digital image     multiscale     microscopic randomness     homogenization    

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Digital image correlation-based structural state detection through deep learning

《结构与土木工程前沿（英文）》 2022年 第16卷 第1期   页码 45-56 doi: 10.1007/s11709-021-0777-x

摘要： This paper presents a new approach for automatical classification of structural state through deep learning. In this work, a Convolutional Neural Network (CNN) was designed to fuse both the feature extraction and classification blocks into an intelligent and compact learning system and detect the structural state of a steel frame; the input was a series of vibration signals, and the output was a structural state. The digital image correlation (DIC) technology was utilized to collect vibration information of an actual steel frame, and subsequently, the raw signals, without further pre-processing, were directly utilized as the CNN samples. The results show that CNN can achieve 99% classification accuracy for the research model. Besides, compared with the backpropagation neural network (BPNN), the CNN had an accuracy similar to that of the BPNN, but it only consumes 19% of the training time. The outputs of the convolution and pooling layers were visually displayed and discussed as well. It is demonstrated that: 1) the CNN can extract the structural state information from the vibration signals and classify them; 2) the detection and computational performance of the CNN for the incomplete data are better than that of the BPNN; 3) the CNN has better anti-noise ability.

关键词： structural state detection     deep learning     digital image correlation     vibration signal     steel frame    

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Deformation field and crack analyses of concrete using digital image correlation method

Yijie HUANG, Xujia HE, Qing WANG, Jianzhuang XIAO

《结构与土木工程前沿（英文）》 2019年 第13卷 第5期   页码 1183-1199 doi: 10.1007/s11709-019-0545-3

摘要： The study on the deformation distribution and crack propagation of concrete under axial compression was conducted by the digital image correlation (DIC) method. The main parameter in this test is the water-cement ( / ) ratio. The novel analysis process and numerical program for DIC method were established. The displacements and strains of coarse aggregate, and cement mortar and interface transition zone (ITZ) were obtained and verified by experimental results. It was found that the axial displacement distributed non-uniformly during the loading stage, and the axial displacements of ITZs and cement mortar were larger than that of coarse aggregates before the occurrence of macro-cracks. The effect of / on the horizontal displacement was not obvious. Test results also showed that the transverse and shear deformation concentration areas (DCAs) were formed when stress reached 30%–40% of the peak stress. The transverse and shear DCAs crossed the cement mortar, and ITZs and coarse aggregates. However, the axial DCA mainly surrounded the coarse aggregate. Generally, the higher / was, the more size and number of DCAs were. The crack propagations of specimens varied with the variation of / . The micro-crack of concrete mainly initiated in the ITZs, irrespective of the / . The number and distribution range of cracks in concrete with high / were larger than those of cracks in specimen adopting low / . However, the value and width of cracks in high / specimen were relatively small. The / had an obvious effect on the characteristics of concrete deterioration. Finally, the characteristics of crack was also evaluated by comparing the calculated results.

关键词： deformation filed distribution     crack development     digital image correlation method     mechanical properties     water-cement ratio     characteristics of deformation and crack    

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fracture process in forta and polypropylene fiber-reinforced concrete using experimental analysis and digitalimage correlation

Seyed Hamid KALALI; Hamid ESKANDARI-NADDAF; Seyed Ali EMAMIAN

《结构与土木工程前沿（英文）》 2022年 第16卷 第12期   页码 1633-1652 doi: 10.1007/s11709-022-0876-3

摘要： This paper aims to characterize the evolution of the fracture process and the cracking behavior in Forta-Ferro (FF) and Polypropylene (PP) fiber-reinforced concrete under the uniaxial compressive loading using experimental analysis and digital image correlation (DIC) on the surface displacement. For this purpose, 6 mix designs, including two FF volume fractions of 0.10, and 0.20% and three PP volume fractions of 0.20, 0.30, and 0.40%, in addition to a control mix were evaluated according to compressive strength, modulus of elasticity, toughness index, and stress-strain curves. The influence of fibers on the microstructural texture of specimens was analyzed by scanning electron microscope (SEM) imaging. Results show that FF fiber-reinforced concrete specimens demonstrated increased ductility and strength compared to PP fiber. DIC results revealed that the major crack and fracture appeared at the peak load of the control specimen due to brittleness and sudden gain of large lateral strain, while a gradual increase in micro-crack quantity at 75% of peak load was observed in the fiber specimens, which thenbegan to connect with each other up to the final fracture. The accuracy of the results supports DIC as a reliable alternative for the characterization of the fracture process in fiber-reinforced concrete.

关键词： fiber-reinforced concrete     forta-ferro and polypropylene fiber     fracture process     cracking behavior     digital image correlation    

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Deep learning in digital pathology image analysis: a survey

Shujian Deng, Xin Zhang, Wen Yan, Eric I-Chao Chang, Yubo Fan, Maode Lai, Yan Xu

《医学前沿（英文）》 2020年 第14卷 第4期   页码 470-487 doi: 10.1007/s11684-020-0782-9

摘要： deep learning (DL) has achieved state-of-the-art performance in many digital pathology analysis tasks. Traditional methods usually require hand-crafted domain-specific features, and DL methods can learn representations without manually designed features. In terms of feature extraction, DL approaches are less labor intensive compared with conventional machine learning methods. In this paper, we comprehensively summarize recent DL-based image analysis studies in histopathology, including different tasks (e.g., classification, semantic segmentation, detection, and instance segmentation) and various applications (e.g., stain normalization, cell/gland/region structure analysis). DL methods can provide consistent and accurate outcomes. DL is a promising tool to assist pathologists in clinical diagnosis.

关键词： pathology     deep learning     segmentation     detection     classification    

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polypropylene-reinforced ultra-high-performance concrete through numerical analyses and experimental multi-target digitalimage correlation

《结构与土木工程前沿（英文）》   页码 1228-1248 doi: 10.1007/s11709-023-0931-8

摘要： This study presents experimental and numerical investigations on the mechanical properties of ultra-high-performance concrete (UHPC) reinforced with single and hybrid micro- and macro-steel and polypropylene fibers. For this purpose, a series of cubic, cylindrical, dog-bone, and prismatic beam specimens (total fiber by volume = 1%, and 2%) were tested under compressive, tensile, and flexural loadings. A method, namely multi-target digital image correlation (MT-DIC) was used to monitor the displacement and deflection values. The obtained experimental data were subsequently used to discuss influential parameters, i.e., flexural strength, tensile strength, size effect, etc. Numerical analyses were also carried out using finite element software to account for the sensitivity of different parameters. Furthermore, nonlinear regression analyses were conducted to obtain the flexural load-deflection curves. The results showed that the MT-DIC method was capable of estimating the tensile and flexural responses as well as the location of the crack with high accuracy. In addition, the regression analyses showed excellent consistency with the experimental results, with correlation coefficients close to unity. Furthermore, size-effect modeling revealed that modified Bazant theory yielded the best estimation of the size-effect phenomenon compared to other models.

关键词： UHPC     MT-DIC     flexural behavior     tensile behavior     steel fiber     polypropylene fiber    

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简述图像被动取证技术 Review

林祥, 李建华, 王士林, 刘伟聪, 程峰, 黄潇洒

《工程（英文）》 2018年 第4卷 第1期   页码 29-39 doi: 10.1016/j.eng.2018.02.008

摘要：

随着图像编辑和篡改技术越发成熟，数字图像的真实性通常难以从视觉上直接分辨。为了检测数字图像篡改，在过去十年内，已经出现多种数字图像取证技术。其中，主动取证方法需要嵌入额外信息。相比之下，被动取证方法因为其适用场景更广而更加流行，也吸引了学术界和工业界越来越多的研究兴趣。一般而言，被动取证基于以下依据来检测图像伪造：图像采集或存储过程中会在原始图像中遗留某些固有的模式特征，或者在图像存储或编辑过程中会留下某些特定的模式特征。通过分析上述模式特征，可以验证图像的真实性。被动数字取证方法正处于快速发展之中，本文简要回顾其发展，并全面介绍该研究领域的最新进展。根据所追踪痕迹的不同，这些取证方法被分为3 类，即采集痕迹法、存储痕迹法和编辑痕迹法。我们将逐一详解这些方法的取证场景、基本原理和研究现状。此外，我们讨论了当前图像取证方法的主要局限，并指出了该领域一些可能的研究方向和关键问题。

关键词： 数字图像取证     图像篡改检测     多媒体安全    

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Assessing compressive strengths of mortar and concrete from digital images by machine learning techniques

Amit SHIULY; Debabrata DUTTA; Achintya MONDAL

《结构与土木工程前沿（英文）》 2022年 第16卷 第3期   页码 347-358 doi: 10.1007/s11709-022-0819-z

摘要： Compressive strength is the most important metric of concrete quality. Various nondestructive and semi-destructive tests can be used to evaluate the compressive strength of concrete. In the present study, a new image-based machine learning method is used to predict concrete compressive strength, including evaluation of six different models. These include support-vector machine model and various deep convolutional neural network models, namely AlexNet, GoogleNet, VGG19, ResNet, and Inception-ResNet-V2. In the present investigation, cement mortar samples were prepared using each of the cement:sand ratios of 1:3, 1:4, and 1:5, and using the water:cement ratios of 0.35 and 0.55. Cement concrete was prepared using the cement:sand:coarse aggregate ratios of 1:5:10, 1:3:6, 1:2:4, 1:1.5:3 and 1:1:2, using the water:cement ratio of 0.5 for all samples. The samples were cut, and several images of the cut surfaces were captured at various zoom levels using a digital microscope. All samples were then tested destructively for compressive strength. The images and corresponding compressive strength were then used to train machine learning models to allow them to predict compressive strength based upon the image data. The Inception-ResNet-V2 models exhibited the best predictions of compressive strength among the models tested. Overall, the present findings validated the use of machine learning models as an efficient means of estimating cement mortar and concrete compressive strengths based on digital microscopic images, as an alternative nondestructive/semi-destructive test method that could be applied at relatively less expense.

关键词： support vector machine     deep convolutional neural network     microscope     digital image     curing period    

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Quantification of coarse aggregate shape in concrete

Xianglin GU,Yvonne TRAN,Li HONG

《结构与土木工程前沿（英文）》 2014年 第8卷 第3期   页码 308-321 doi: 10.1007/s11709-014-0266-6

摘要： The objective of this study is to choose indices for the characterization of aggregate form and angularity for large scale application. For this purpose, several parameters for aggregate form and angularity featured in previous research are presented. Then, based on these established parameters, 200 coarse quartzite aggregates are analyzed herein by using image processing technology. This paper also analyzes the statistical distributions of parameters for aggregate form and angularity as well as the correlation between form and angularity parameters. It was determined that the parameters for form or angularity of coarse aggregates could be fitted by either normal distribution or log-normal distribution at a 95% confidence level. Some of the form parameters were influenced by changes in angularity characteristics, while aspect ratio and angularity using outline slope, area ratio and radius angularity index, and aspect ratio and angularity index were independent of each other, respectively; and consequently, the independent parameters could be used to quantify the aggregate form and angularity for the purpose to study the influence of aggregate shape on the mechanical behavior of concrete. Furthermore, results from this study’s in-depth investigations showed that the aspect ratio and the angularity index can further understanding of the effects of coarse aggregates form and angularity on concrete mechanical properties, respectively. Finally, coarse aggregates with the same content, type and surfaces texture, but different aspect ratios and angularity indices were used to study the influence of coarse aggregate form and angularity on the behavior of concrete. It was revealed that the splitting tensile strength of concrete increased with increases in the aspect ratio or angularity index of coarse aggregates.

关键词： coarse aggregate     form     angularity     digital image analysis     statistical distribution     splitting tensile strength    

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Strengthening of the concrete face slabs of dams using sprayable strain-hardening fiber-reinforced cementitious composites

《结构与土木工程前沿（英文）》 2022年 第16卷 第2期   页码 145-160 doi: 10.1007/s11709-022-0806-4

摘要： In this study, sprayable strain-hardening fiber-reinforced cementitious composites (FRCC) were applied to strengthen the concrete slabs in a concrete-face rockfill dam (CFRD) for the first time. Experimental, numerical, and analytical investigations were carried out to understand the flexural properties of FRCC-layered concrete slabs. It was found that the FRCC layer improved the flexural performance of concrete slabs significantly. The cracking and ultimate loads of a concrete slab with an 80 mm FRCC layer were 132% and 69% higher than those of the unstrengthened concrete slab, respectively. At the maximum crack width of 0.2 mm, the deflection of the 80-mm FRCC strengthened concrete slab was 144% higher than that of the unstrengthened concrete slab. In addition, a FE model and a simplified analytical method were developed for the design and analysis of FRCC-layered concrete slabs. Finally, the test result of FRCC leaching solution indicated that the quality of the water surrounding FRCC satisfied the standard for drinking water. The findings of this study indicate that the sprayable strain-hardening FRCC has a good potential for strengthening hydraulic structures such as CFRDs.

关键词： strain-hardening cementitious composites     engineered cementitious composites     sprayable     shotcrete     strengthening     concrete-face rockfill dam     digital image correlation    

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Crack evolution of soft–hard composite layered rock-like specimens with two fissures under uniaxial compression

《结构与土木工程前沿（英文）》 2021年 第15卷 第6期   页码 1372-1389 doi: 10.1007/s11709-021-0772-2

摘要： Acoustic emission and digital image correlation were used to study the spatiotemporal evolution characteristics of crack extension of soft and hard composite laminated rock masses (SHCLRM) containing double fissures under uniaxial compression. The effects of different rock combination methods and prefabricated fissures with different orientations on mechanical properties and crack coalescence patterns were analyzed. The characteristics of the acoustic emission source location distribution, and frequency changes of the crack evolution process were also investigated. The test results show that the damage mode of SHCLRM is related to the combination mode of rock layers and the orientation of fractures. Hard layers predominantly produce tensile cracks; soft layers produce shear cracks. The first crack always sprouts at the tip or middle of prefabricated fractures in hard layers. The acoustic emission signal of SHCLRM with double fractures has clear stage characteristics, and the state of crack development can be inferred from this signal to provide early warning for rock fracture instability. This study can provide a reference for the assessment of the fracture development status between adjacent roadways in SHCLRM in underground mines, as well as in roadway layout and support.

关键词： soft−hard composite layered rock mass     double cracks     crack evolution     acoustic emission     digital image correlation    

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A study on fatigue damage of asphalt mixture under different compaction using 3D-microstructural characteristics

Jing HU, Pengfei LIU, Bernhard STEINAUER

《结构与土木工程前沿（英文）》 2017年 第11卷 第3期   页码 329-337 doi: 10.1007/s11709-017-0407-9

摘要： The aim of this paper is investigating the microstructural characteristics of asphalt mixture under different compaction powers. In order to achieve this aim, a test track was built to provide asphalt mixture specimens and X-ray computed tomography (XCT) device was used to scan the internal structure. The aggregate particles and air-voids were extracted using Digital Image Processing (DIP), so the relationship between compaction and air-voids was determined at first, and then, the effect of aggregate particles on the morphology of air-voids can be evaluated, finally, fatigue properties of asphalt mixture with different air-void ratio were measured by indirect tensile fatigue test as well. The research results release the distribution of microstructures in asphalt pavement. 3D fractal dimension is an effective indicator to quantize the complexity of aggregate particles and air-voids; suffering the same compaction power, aggregates cause different constitutions of air-voids in asphalt mixture; investigation in this paper can present the essential relationship between microstructures and fatigue properties.

关键词： asphalt mixture     microstructure     morphology     digital image processing     fatigue damage    

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Effect of TGO on the tensile failure behavior of thermal barrier coatings

Le WANG, Yuelan DI, Ying LIU, Haidou WANG, Haoxing YOU, Tao LIU

《机械工程前沿（英文）》 2019年 第14卷 第4期   页码 452-460 doi: 10.1007/s11465-019-0541-2

摘要： Thermally grown oxide (TGO) may be generated in thermal barrier coatings (TBCs) after high-temperature oxidation. TGO increases the internal stress of the coatings, leading to the spalling of the coatings. Scanning electron microscopy and energy-dispersive spectroscopy were used to investigate the growth characteristics, microstructure, and composition of TGO after high-temperature oxidation for 0, 10, 30, and 50 h, and the results were systematically compared. Acoustic emission (AE) signals and the strain on the coating surface under static load were measured with AE technology and digital image correlation. Results showed that TGO gradually grew and thickened with the increase in oxidation time. The thickened TGO had preferential multi-cracks at the interface of TGO and the bond layer and delayed the strain on the surface of the coating under tensile load. TGO growth resulted in the generation of pores at the interface between the TGO and bond layer. The pores produced by TGO under tensile load delayed the generation of surface cracks and thus prolonged the failure time of TBCs.

关键词： thermally grown oxides     thermal barrier coatings     acoustic emission technology     digital image correlation     pores    

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Long term performance of recycled concrete beams with different water–cement ratio and recycled aggregate replacement rate

Jingwei YING; Feiming SU; Shuangren CHEN

《结构与土木工程前沿（英文）》 2022年 第16卷 第3期   页码 302-315 doi: 10.1007/s11709-022-0803-7

摘要： The purpose of this study is to reveal the service performance of recycled aggregate concrete (RAC) components for different values of water−cement ratio and replacement rate of recycled coarse aggregate (RCA). Generally, the concrete strength decreases with the increase of the replacement rate of RCA, in order to meet the strength requirements when changing the replacement rate of RCA, it is necessary to change the water−cement ratio at the same time. Therefore, the axial compressive strengths of prism with 25 mix proportions, the short-term mechanical properties and long-term deformation properties of reinforced concrete beams were tested respectively by changing water−cement ratio and RCA replacement rate. The bearing capacity and the strain nephogram of samples under different loads were obtained using the Digital Image Correlation (DIC) method, and a self-made gravity loading experimental device was used for long-term deformation investigation. Results showed that the damage pattern of RAC was the same as that of natural aggregate concrete (NAC), but the brittleness was more pronounced. The brittleness of concrete before failure can be reduced more effectively by adjusting the replacement rate of RCA than by adjusting the water−cement ratio. The water−cement ratio has an evident influence on the axial compressive strength and early creep of concrete, while the replacement rate of RCA has a remarkable effect on the long-term deformation of the concrete beams.

关键词： recycled concrete     beam     the replacement rate of recycled coarse aggregate     water–cement ratio     digital image correlation    

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Turbidity-adaptive underwater image enhancement method using image fusion

《机械工程前沿（英文）》 2022年 第17卷 第3期 doi: 10.1007/s11465-021-0669-8

摘要： Clear, correct imaging is a prerequisite for underwater operations. In real freshwater environment including rivers and lakes, the water bodies are usually turbid and dynamic, which brings extra troubles to quality of imaging due to color deviation and suspended particulate. Most of the existing underwater imaging methods focus on relatively clear underwater environment, it is uncertain that if those methods can work well in turbid and dynamic underwater environments. In this paper, we propose a turbidity-adaptive underwater image enhancement method. To deal with attenuation and scattering of varying degree, the turbidity is detected by the histogram of images. Based on the detection result, different image enhancement strategies are designed to deal with the problem of color deviation and blurring. The proposed method is verified by an underwater image dataset captured in real underwater environment. The result is evaluated by image metrics including structure similarity index measure, underwater color image quality evaluation metric, and speeded-up robust features. Test results exhibit that the method can correct the color deviation and improve the quality of underwater images.

关键词： turbidity     underwater image enhancement     image fusion     underwater robots     visibility    

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标题 作者 时间 类型 操作

Three-scale stochastic homogenization of elastic recycled aggregate concrete based on nano-indentationdigital images

Chen WANG, Yuching WU, Jianzhuang XIAO

期刊论文

Digital image correlation-based structural state detection through deep learning

期刊论文

Deformation field and crack analyses of concrete using digital image correlation method

Yijie HUANG, Xujia HE, Qing WANG, Jianzhuang XIAO

期刊论文

fracture process in forta and polypropylene fiber-reinforced concrete using experimental analysis and digitalimage correlation

Seyed Hamid KALALI; Hamid ESKANDARI-NADDAF; Seyed Ali EMAMIAN

期刊论文

Deep learning in digital pathology image analysis: a survey

Shujian Deng, Xin Zhang, Wen Yan, Eric I-Chao Chang, Yubo Fan, Maode Lai, Yan Xu

期刊论文

polypropylene-reinforced ultra-high-performance concrete through numerical analyses and experimental multi-target digitalimage correlation

期刊论文

简述图像被动取证技术

林祥, 李建华, 王士林, 刘伟聪, 程峰, 黄潇洒

期刊论文

Assessing compressive strengths of mortar and concrete from digital images by machine learning techniques

Amit SHIULY; Debabrata DUTTA; Achintya MONDAL

期刊论文

Quantification of coarse aggregate shape in concrete

Xianglin GU,Yvonne TRAN,Li HONG

期刊论文

Strengthening of the concrete face slabs of dams using sprayable strain-hardening fiber-reinforced cementitious composites

期刊论文

Crack evolution of soft–hard composite layered rock-like specimens with two fissures under uniaxial compression

期刊论文

A study on fatigue damage of asphalt mixture under different compaction using 3D-microstructural characteristics

Jing HU, Pengfei LIU, Bernhard STEINAUER

期刊论文

Effect of TGO on the tensile failure behavior of thermal barrier coatings

Le WANG, Yuelan DI, Ying LIU, Haidou WANG, Haoxing YOU, Tao LIU

期刊论文

Long term performance of recycled concrete beams with different water–cement ratio and recycled aggregate replacement rate

Jingwei YING; Feiming SU; Shuangren CHEN

期刊论文

Turbidity-adaptive underwater image enhancement method using image fusion

期刊论文