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Development of a technology type factor for jacket structures for offshore wind turbines in Rhode Island

JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY 2012年第6期4卷 063120-063120-11页

作者： Hensel, Jonas Sharma, M. S. Ravi Baxter, Christopher D. P. Hu, Sau-Lon James Tech Univ Carolo Wilhelmina Braunschweig Inst Welding Technol D-38106 Braunschweig Germany Ocean & Coastal Consultants Inc Trumbull CT 06611 USA Univ Rhode Isl Dept Ocean Engn Kingston RI 02881 USA

A marine spatial planning approach was used to locate possible sites for offshore wind development in Rhode Island. In connection with the Rhode Island ocean special area management plan, a technology development index was developed by Spaulding et al. (2010) to quantify the technical challenges of a particular site relative to its potential power production. A component of this index is the technology type (TT) factor, which quantifies the relative cost of a structure/foundation system as a function of environmental loading, water depth, and soil conditions. This paper presents the development of TT factors for jacket type support structures that is proposed for supporting the offshore wind turbines in Rhode Island Sound. TT factors were calculated by the total weight of the jacket and piles for a given water depth and soil conditions normalized by the weight of a reference structure. Jacket structure weights were determined by a frequency driven finite element analysis using the program ANSYS. The structure was subjected to hydrodynamic and quasi-static turbine loads from 50-year extreme wind and the 100-year extreme wave loading in Rhode Island Sound to determine the ultimate stresses in the structural members. Pile foundation weights were determined from an analysis of the axial capacity and the lateral capacity using commercially available pile design software. Jacket and foundation weights were calculated for water depth ranging from 30 m to 60 m and for three representative soil types. These analyses resulted in a Technology Type factor that varies with water depth according to a 2nd order polynomial, and also with soil type. The results were compared to the weights of two existing jacket structures in Europe and found to be in agreement with the upper bound estimate derived from this study. The Technology Type factor derived in this study was also in good agreement with the published actual cost (normalized) of jacket type foundations used in the United King

关键词： CAD environmental factors facilities planning foundations geotechnical engineering hydrodynamics offshore installations polynomials soil stress analysis structural engineering computing supports wind turbines

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Two-dimensional synthetic aperture imaging of targets behind reinforced concrete walls

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IET RADAR SONAR AND NAVIGATION 2022年第11期16卷 1851-1860页

作者： Ghobadi-Rad, Alireza Tayarani, Majid Dehmollaian, Mojtaba Iran Univ Sci & Technol Sch Elect Engn Tehran *** Iran Ecole Polytech Montreal Montreal PQ Canada

Synthetic aperture imaging of targets closely behind a reinforced concrete wall, modelled by a periodic structure by using the proper Green's function (GF) of the structure, is studied. To compute the GF accurately, using the rigorous coupled-wave analysis (RCWA) is proposed. The radiation of a line source in the spectral domain as a summation of plane waves is represented. Illuminating the periodic structure by each plane wave, Bragg modes by RCWA are computed. Then, the GF is estimated as the superposition of all the Bragg modes' contributions. The numerical Finite Element Method results of COMSOL validate the results of our semi-analytical approach. Having COMSOL numerically calculated backscattered fields of a target behind the wall and the simple free-space GF, the synthetic aperture image of a target is not focussed. Employing the phase of the proper GF instead of the simple free-space GF, the target image is successfully refocussed. The effect of the number of Bragg modes on the estimation of the GF and also uncertainties in the distances between reinforced metallic bars on the target image is investigated.

关键词： finite element analysis reinforced concrete COMSOL periodic structure reinforced metallic bars bars walls Bragg modes rigorous coupled-wave analysis numerical finite element method Green's function methods Green function two-dimensional synthetic aperture imaging reinforced concrete wall structural engineering computing RCWA periodic structures semianalytical approach spectral domain image processing

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Measurement of dynamic vibration in cycling using portable terminal measurement system

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IET INTELLIGENT TRANSPORT SYSTEMS 2019年第3期13卷 469-474页

作者： Xie, Ning Li, Hui Zhao, Wenzhong Ni, Ying Liu, Chenwen Zhang, Yi Xu, Zhigang Tongji Univ Minist Educ Key Lab Rd & Traff Engn Shanghai 201804 Peoples R China Univ Calif Davis Dept Civil & Environm Engn Pavement Res Ctr Davis CA 95616 USA Hebei Qugang Expressway Dev Co Shijiazhuang 073000 Hebei Peoples R China Rhein Westfal TH Aachen Fac Civil Engn D-52074 Aachen Nordrhein Westf Germany Changan Univ Minist Educ & China Mobile Joint Lab Internet Vehicles Sch Informat Engn Xian 710064 Shaanxi Peoples R China

Bicycling is a potential way to improve sustainable urban transportation system. However, the evaluation methods and metrics for bicycle ride quality and slow traffic pavement condition are still in the preliminary stages. The traditional bicycling vibration measurement used instrumented probe bicycle (IPB), which contains several independent devices and obtains scattering data. This method cannot show the detailed pavement condition. A technical challenge for monitoring real-time bicycling comfort and obtain the pavement condition in detail is to combine the intelligent transportation system (ITS) with bicycles. In this study, two schemes have been proposed to acquire the vibration data based on portable terminal measurement systems. Scheme (1) was based on the IPB using GPS, accelerometers, and sport cameras. The microcontroller was used to integrate several modules to develop scheme (2). Wavelet analysis was introduced to analyse random signal data. Then the pavement condition can be reflected in detail by vibration response. Data derived from the proposed system can be successfully applied to promote the use of bicycles as a reflecting tool for the pavement surface conditions. This method can provide a reference database for pavements' surface maintenance and for cyclists to choose cycling routes.

关键词： Global Positioning System microcontrollers vibrations bicycles maintenance engineering roads accelerometers vibration measurement wavelet transforms intelligent transportation systems structural engineering computing vibrational signal processing condition monitoring real-time bicycling comfort intelligent transportation system portable terminal measurement systems IPB vibration response pavement surface conditions sustainable urban transportation system instrumented probe bicycle bicycling vibration measurement ITS GPS accelerometers sport cameras microcontroller wavelet analysis random signal data analysis

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Algorithm to decompose three-dimensional complex structures at the necks: tested on snow structures

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IET IMAGE PROCESSING 2011年第2期5卷 132-140页

作者： Theile, T. Schneebeli, M. WSL Inst Snow & Avalanche Res SLF CH-7260 Davos Switzerland

The separation of overlapping particles in three-dimensional images is an image processing task with many fields of application. However, commonly used image processing algorithms have difficulties to identify the single particles and their connections in certain structures. Here the authors present an alternative algorithm for part decomposition, which performs better on some structures than common algorithms. This algorithm is a special case of part decomposition, as it decomposes a structure at the necks into single particles. The necks are detected based on their characteristic negative Gaussian curvature. The algorithm itself consists of three steps: cutting at negative Gaussian curvature, region growing and intersecting plane minimisation. The authors tested the performance of the algorithm by comparison with two state-of-the-art algorithms for part decomposition, the watershed and a skeleton-based algorithm on strongly differing geometries, taken from natural snow samples. The two test algorithms are known for having difficulties to decompose certain structures. As the new algorithm uses a different characteristic to decompose the structure, the new algorithm is a good alternative to the existing algorithms. The new algorithm decomposes 72% of the reference structure correctly. This is a better performance than by the two other algorithms.

关键词： snow structures structural engineering computing Mechanical engineering applications of IT three-dimensional images image processing snow negative Gaussian curvature Computer vision and image processing techniques decompose three-dimensional complex structures Mechanical structures skeleton-based algorithm Optical, image and video signal processing Civil and mechanical engineering computing overlapping particles

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3-D finite element modeling of the welding process using element birth and element movement techniques

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JOURNAL OF PRESSURE VESSEL TECHNOLOGY-TRANSACTIONS OF THE ASME 2003年第2期125卷 144-150页

作者： Fanous, IFZ Younan, MYA Wifi, AS Amer Univ Cairo Dept Mech Engn Cairo Egypt Cairo Univ Mech Design & Prod Dept Cairo Egypt

The modeling and simulation of the welding process has been of main concern for different fields of applications. Most of the modeling of such a problem has been mainly in 2-D forms that may also include many sorts of approximation and assumptions. This is due to limitations in the computational facilities as the analysis of 3-D problems consumes a lot of time. With the evolution of new finite element tools and fast computer systems, the analysis of such problems is becoming in hand. In this research, a simulation of the welding process with and without metal deposition is developed. A new technique for metal deposition using element movement is introduced. It helps in performing full 3-D analysis in a shorter time than other previously developed techniques such as the element birth.

关键词： Metals Heat finite element analysis Modeling Stress welding structural engineering computing Welding Temperature Finite element analysis

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A Probabilistic assessment of the design S-N curves f or 1Cr18Ni9Ti pipe-welded joint

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JOURNAL OF PRESSURE VESSEL TECHNOLOGY-TRANSACTIONS OF THE ASME 2003年第2期125卷 195-200页

作者： Zhao, YX SW Jiaotong Univ Inst Engn Mech Chengdu 610031 Peoples R China

A probabilistic assessment is made of the design S-N curves for 1Cr18Ni9Ti pipe-welded joint. The material exhibits a character of random cyclic stress-strain and fatigue life responses. Then, both the S and N in the virtual stress amplitude-fatigue crack initiation life (S-N) data are random variables. A general maximum likelihood method, which considers the randomness of the test S-N data, is developed to model the probabilistic S-N relations of material. The design S-N curves with reduction factors of 20 oil cycles, 2 on stress and 2.5 on stress applied to the best-fit S-N curve of test data as used in the ASME code and general practice, are assessed in a probabilistic sense. The results reveal that in the lower S regime the 20 and 2.5 reduction factor curves may be appropriate, while the reduction factor of 2 is slightly nonconservative. But in the higher S regime these curves are all much more conservative. The intrinsic cause is that the standard deviation of logN exhibits an increase with the S decreasing, while the constant reduction factors do not consider this increase. It is shown that from the general statistical scatter of S-N data the design S-N curves should be appropriately determined by a probabilistic approach.

关键词： stress-strain relations probability structural engineering computing Fatigue Temperature Fatigue life nickel alloys boilers fatigue cracks maximum likelihood estimation chromium alloys Pipes Fatigue testing titanium alloys Probability Stress random processes pressure vessels Cycles Design Chaos

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Pavement crack detection using non-local theory and iterative sampling

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IET IMAGE PROCESSING 2022年第3期16卷 869-877页

作者： Wei, Zixian Sun, Tao Wu, Yuhao Zhou, Liqing Ruan, Xiaoli Wuhan Univ Elect Informat Sch Wuhan 430072 Peoples R China China Railway Bridge Sci Res Inst Ltd Wuhan Peoples R China State Key Lab Hlth & Safety Bridge Struct Wuhan Peoples R China

Crack is a common form of road distress and a key study of an intelligent transportation system. However, automatic pavement crack detection is a very challenging task due to noisy texture background, intensity inhomogeneity, and topology complexity. In this paper, a new pavement crack detection algorithm to address these issues is proposed. First, non-local block matching strategy and local statistical mean are put together to generate the probability map of cracks, which has advantages on automatic threshold choosing and strong resistance to intensity inhomogeneity. Second, an iterative seed points sampling algorithm is proposed, which makes full use of the area and shape of connected regions where the seeds lie in, thus exploiting high reliable crack seeds for following curves extraction. Finally, a minimum spanning tree (MST) is adopted to connect points into crack curves and employ a crack growth method to find out the cracks, which is specified to deal with complex topology of cracks. For parameters, a robust and optimal parameters selection rule is obtained by data driven method. The algorithm is compared with other state-of-the-art algorithms on two datasets. The experiment result shows that the proposed method has a better detection performance on F1-measure score over other methods.

关键词： minimum spanning tree road building probability crack seeds intelligent transportation system probability map condition monitoring intelligent transportation systems noisy texture background image matching intensity inhomogeneity trees (mathematics) feature extraction curve extraction MST parameter selection rule sampling methods crack growth method topology complexity nonlocal block matching strategy pavement crack detection local statistical mean iterative seed point sampling iterative methods crack curves nonlocal theory crack detection automatic threshold choosing structural engineering computing road distress feature selection

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A new image processing strategy for surface crack identification in building structures under non-uniform illumination

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IET IMAGE PROCESSING 2022年第2期16卷 407-415页

作者： Parrany, Ahmad Mahdian Mirzaei, Mohsen Vali E Asr Univ Rafsanjan Dept Mech Engn Imam Khomeini Sq Rafsanjan *** Iran

Crack detection in building structures is an important approach to evaluating the safety of these structures. However, in some cases under special circumstances, it is very difficult to identify all features of cracks by visual inspection. To tackle this problem and offer a higher potential for practical implementations, developing an automatic crack detection method seems essential. This paper establishes a novel algorithm for surface crack detection in building walls based on image processing techniques to enhance crack visibility. One of the most prevalent issues in surface crack detection from digital crack images is non-uniform illumination of background which makes narrow and tiny cracks indistinguishable. In this regard, an integrated approach, combining adaptive image threshold using local first-order statistics, contrast-limited adaptive histogram equalization, and noise filtering using non-linear diffusion filtering, is proposed to extract the whole skeleton of the crack from digital crack images with non-uniform illumination. Several realistic crack images, suffering from noise and uneven lighting of background, are processed through the proposed algorithm to demonstrate the robustness and high accuracy of the method.

关键词： nonlinear filters adaptive image threshold digital crack images safety building structures realistic crack images local first-order statistics automatic optical inspection statistical analysis nonlinear diffusion filtering tiny cracks nonuniform illumination visual inspection crack visibility narrow cracks feature extraction image filtering image segmentation image enhancement automatic crack detection buildings (structures) realistic images image processing surface crack detection surface cracks building walls contrast-limited adaptive histogram equalization image denoising crack detection structural engineering computing walls structural safety surface crack identification noise filtering

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A PERSPECTIVE ON COMPUTATIONAL STRUCTURES TECHNOLOGY

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COMPUTER 1993年第10期26卷 38-46页

作者： NOOR, AK VENNERI, SL UNIV VIRGINIA CHARLOTTESVILLEVA 22903 NASA HEADQUARTERS DIV SPACE RESWASHINGTONDC

Computational structures technology (CST), which blends structural modeling with computational methods and is an outgrowth of matrix methods used to analyze the dynamic and static responses of structures, is reviewed. The authors summarize CST's history and status, emphasizing software development, goals, and promising research areas. Example applications of CST from the aerospace field are presented

关键词： aerospace computational methods computational structures technology goals matrix methods research areas software development structural engineering computing structural modeling

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A deep learning-based method for pixel-level crack detection on concrete bridges

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IET IMAGE PROCESSING 2022年第10期16卷 2609-2622页

作者： Ji Kun Zhang Zhenhai Yu Jiale Dang Jianwu Lanzhou Jiaotong Univ Sch Automat & Elect Engn Lanzhou Gansu Peoples R China Gansu Artificial Intelligence & Graph Image Proc Lanzhou Gansu Peoples R China

Crack detection of the concrete bridge is an essential index for the safety assessment of bridge structure. It is more important to check the whole structure than to check the accuracy in the damage assessment. However, the traditional deep learning model method cannot completely detect the crack structure, which challenges image-based crack detection. For this reason, we propose deep bridge crack classification (DBCC)-Net as a classification-based deep learning network. By pruning the Yolox, the regression problem of the target detection is converted to the binary classification problem to avoid the network performance degradation caused by the translation invariance of the convolutional neural network (CNN). In addition, the network post-processing and a two-stage crack detection strategy are proposed to enable the network to detect cracks and extract crack morphology in high-resolution images quickly. In the first stage, DBCC-Net realizes the coarse extraction of crack position based on image slice classification. In the second stage, the complete crack morphology is extracted from the location suggested by the semantic segmentation network. Experimental results show that the proposed two-stage method has 19 frames per second (FPS) and 0.79 Miou (mean intersection over union) at the actual bridge images with 2560x2560 pixels. Although FPS is reduced, the Miou value is 7.8% higher than other methods, proving this paper's practical value.

关键词： high-resolution images convolutional neural network semantic segmentation network traditional deep learning model method regression analysis crack position network post-processing actual bridge images two-stage crack detection strategy deep learning-based method two-stage method convolutional neural nets image slice classification target detection bridges (structures) classification-based deep learning network regression problem damage assessment complete crack morphology essential index DBCC-Net feature extraction crack structure deep learning (artificial intelligence) image segmentation safety assessment image-based crack detection bridge structure binary classification problem cracks pixel-level crack detection deep bridge crack classification-Net concrete bridge object detection inference mechanisms network performance degradation crack detection image classification structural engineering computing image resolution

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