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Relevant bibliographies by topics / Artificial crack

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Academic literature on the topic 'Artificial crack'

Author: Grafiati

Published: 2 November 2024

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Journal articles on the topic "Artificial crack"

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Raihan, Prodhan Md Safiq, Anik Md Shahjahan, Shamima Akter Shimky, Toki Thamid Zim, Summa Parven, Abdul Ali Khan, and Mir Fazle Rabbi. "Pavement Crack Detection and Solution with Artificial Intelligence." European Journal of Theoretical and Applied Sciences 2, no. 4 (July 1, 2024): 277–314. http://dx.doi.org/10.59324/ejtas.2024.2(4).25.

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Detecting and repairing pavement cracks is essential to ensure road safety and longevity. Traditional inspection and maintenance methods are time-consuming, expensive and often inaccurate. In recent years, there has been a growing trend to use artificial intelligence (AI) to automate the process of pavement crack detection and repair. The article focuses on using AI techniques to detect pavement cracks and provide solutions to repair them. The proposed solution is based on using deep learning algorithms to analyze high-resolution images of the road surface. Photos are taken with a vehicle camera or a drone. The deep learning algorithm is trained using a large data set of tagged sidewalk crack images. Once trained, the algorithm can accurately detect and classify the type of cracks on the pavement surface, including longitudinal, transverse, block and crocodile cracks. The algorithm can also determine the severity of each crack and help prioritize repairs. When cracks are detected, the AI system can make recommendations for repair solutions. This includes identifying the appropriate caulk or filler material to use depending on the type and severity of the crack. The AI system can also recommend the most efficient and cost-effective repair method, such as B. Crack sealing, crack filling or deep repair. Overall, using AI to detect and repair cracks in sidewalks offers a more accurate, efficient, and cost-effective solution to keep roads safe and sustainable. By automating the inspection and repair process, this technology can help prevent accidents, reduce maintenance costs, and improve overall road safety.

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Kuttimarks, Dr M. S. "Crack Detection of Structures using Artificial Intelligence System." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (May 31, 2024): 1894–901. http://dx.doi.org/10.22214/ijraset.2024.61958.

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Abstract: Structural Health Monitoring (SHM) having wider scope of operations such as structural audit, rehabilitation of structures and along with it a major scope of crack detection is also included. Effective crack detection is vital for ensuring the safety and longevity of civil engineering structures. Crack Detection in existing methods is tedious process, it requires costly equipment’s as well as time consuming, and inaccuracy in mechanical equipment’s. The technological advancements especially in the field of Artificial Intelligence (AI) maybe an acceptable solution for crack identification through mobile app using Image processing techniques. The mobile app can be used to accurately identify crack pattern and measure the size of cracks in structures (concrete and steel). The app needed to capture and process data from diverse sources, such as images, in real time. It allows for real-time monitoring of structures and ensures safety and integrity of it. The image processing algorithm is used for to accurately identifying various types of cracks in different lighting, environmental conditions, effective and optimized solution. This project explained about real-time data processing for crack detection and its challenges. This demanded robust backend infrastructure and efficient data processing techniques to deliver prompt and accurate results. User Interface and Experience developing an intuitive and user-friendly interface for the app while maintaining high performance.

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Wang, Zi Zhen, Ri He Wang, Yu Huan Bu, and Xun Shan. "A New Method of Preparing Artificial Cores with Certain Cracks for Experiment Study of Elastic Wave Propagation." Advanced Materials Research 356-360 (October 2011): 2954–57. http://dx.doi.org/10.4028/www.scientific.net/amr.356-360.2954.

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Crack universally existing underground is an important kind of pores. In order to study the elastic wave propagation in fractured medium through experiment, a new method to make artificial core with certain cracks using oil well cement and camphor sheet or thin steel sheet is put forward. Geometric parameters of the crack, such as shape, size and aspect ratio, are approximately equal to that of camphor sheet or thin steel sheet. Using the thin steel sheet to make crack can be more easy and accurate to control the crack angle than using camphor sheet. The crack opening scales at millimeters. The aspect ratio of cracks formed by camphor sheet ranges from 1.4 to 8, and aspect ratio of cracks formed by thin steel sheet ranges from 2.5 to 70. This method is proved simple and feasible by experiment practice, which can provide artificial cores with certain crack for acoustic wave propagation study.

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Wu, Zhenkai, Xizhe Li, Hanmin Xiao, Xuewei Liu, Wei Lin, Yuan Rao, Yang Li, and Jie Zhang. "The Establishment and Evaluation Method of Artificial Microcracks in Rocks." Energies 14, no. 10 (May 12, 2021): 2780. http://dx.doi.org/10.3390/en14102780.

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It is necessary to carry out experiments on cores with different degrees of crack development when studying the seepage law of cracked reservoirs and evaluating cracks. The seepage experiment in the laboratory requires cores with different degrees of microcrack development; cores obtained via conventional drilling cannot meet the requirements, and the efficacies and evaluation methods of geological parameters used for artificial cracks are not perfect. In this study, cores are loaded using a triaxial gripper, and cracks are produced by changing the difference of stress; the relationship between the increased rate of permeability and the change in stress concentration is used to evaluate the degree of development of the crack in real time. The angle between the cracks and the maximum principal stress direction, calculated using the Mohr–Coulomb failure criterion, is 20–27.5°, which provides theoretical support for the process of crack creation. The experimental results show that the permeability variation curve shows two obvious turning points, which divide the whole zone into a reduction zone, a slow increase zone, and a rapid increase zone. Through the obtained experimental and evaluation results, a complete system for crack creation and evaluation is established, which can provide strong support for the study of cracked reservoirs.

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Sakamoto, Junji, Yoshimasa Takahashi, and Hiroshi Noguchi. "Small Fatigue Crack Growth Behavior from Artificial Notch with Focused Ion Beam in Annealed 0.45% Carbon Steel." Key Engineering Materials 488-489 (September 2011): 319–22. http://dx.doi.org/10.4028/www.scientific.net/kem.488-489.319.

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The aim of this study is firstly to investigate the applicability of a sharp notch with Focused Ion Beam (FIB) as a crack for fatigue limit evaluation. Secondly we investigate a condition in which artificial defects (drilled hole, FIB notch) can be used as a crack for fatigue limit evaluation. To achieve the aim, the growth behaviors and the non-propagating crack sizes of small fatigue cracks initiated from a FIB notch and a drilled hole are carefully compared with those of an annealed fatigue crack which imitates an ideally sharp crack. The results show that a FIB notch can be used as a crack for fatigue limit evaluation under some conditions. The results also show that the condition which controls the applicability of an artificial defect as an ideal crack for fatigue limit evaluation is strongly dependent on the relation between (i) the length of a non-propagating fatigue crack and (ii) the crack length when the small fatigue crack growth behaviors from an artificial defect and an ideal pre-crack become almost the same. It is found that the length of (ii) can be obtained by the analyses using the number of cycles from a certain crack length to failure.

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Fathalla, Eissa, Yasushi Tanaka, Koichi Maekawa, and Akito Sakurai. "Quantitative Deterioration Assessment of Road Bridge Decks Based on Site Inspected Cracks." Applied Sciences 8, no. 7 (July 21, 2018): 1197. http://dx.doi.org/10.3390/app8071197.

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By integrating a multi-scale simulation with the pseudo-cracking method, the remaining fatigue life of in-service reinforced concrete (RC) bridge decks can be estimated based upon their site-inspected crack patterns. But, it still takes time for computation. In order to achieve a quick deterioration-magnitude assessment of RC decks based upon their crack patterns, two evaluation methods are proposed. A predictive correlation between the remaining fatigue life and the cracks density (both cracks length and width) is presented as a fast judgment. For fair-detailed judgment, an artificial neural network (ANN) model is also introduced which is the basis of the machine learning. Both assessment methods are built commonly by thousands of artificial random crack patterns to cover all possible ranges since the variety of the real crack patterns on site is more or less limited. The built ANN performances are examined by k-fold cross-validation besides checking the prediction accuracy of real crack patterns of bridge RC decks. Finally, the hazard map of the deck’s bottom surface is introduced to indicate the location of higher risk cracking, which derives from the estimated weight of individual neuron in the built artificial neural network.

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Hendroprasetyo, Wing, and Henry Haidar Jati Andrian. "Analysis of Eddy Current Testing Detection Ability to the Varied Longitudinal Cracks on Coated Weld Metal Tee Joint of 5083 Aluminum Ship Structure." IOP Conference Series: Earth and Environmental Science 972, no. 1 (January 1, 2022): 012041. http://dx.doi.org/10.1088/1755-1315/972/1/012041.

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Abstract Due to its service, crack sometimes occur on the coated 5083 aluminum weld metal. One method for finding crack under protective coating is by using eddy current testing (ECT). This method of nondestructive testing relies on a circular electrical path generated by the coils positioned just above the surface being examined. The purpose of this research is to analyze the sensitivity of ECT by using variety of crack dimensions on 5083 aluminum welded plate tee joint. Five test pieces, each 200 mm × 50 mm × 10 mm were used and each sample contain four cracks. Artificial cracks are fabricated using electrical discharge machining (EDM) with length and depth variations. Variations in crack length are 5.0 mm, 7.0 mm, 9.0 mm, and 15.0 mm, and variation in depth are 0.5 mm, 1.0 mm, 1.5 mm, 2.0 mm and 2.5 mm. Results obtained by the analysing height and average length of the crack signal indication are as follows: for 0.5 mm crack depth, the height of the crack signal is 5 mm; 1.0 mm depth is 11.75 mm; 1.5 mm depth is 19.75 mm; 2.0 mm depth is 26.5 mm and 2.5 mm depth is 31.25 mm. The degree of accuracy obtained for the detection of crack depth is 93.57%. For the detection of crack length, it is found that the measured average length of artificial cracks is 5 mm actual crack length has measured crack length of 6.32 mm; 7 mm actual crack length has measured crack length value of 7.18 mm; 9 mm actual crack length has a measured crack length value of 8.8 mm and 15 mm actual crack length has measured crack length of 14.48 mm. The degree of accuracy obtained for crack length detection is 91.31%.

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Kim, Jung Jin, Ah-Ram Kim, and Seong-Won Lee. "Artificial Neural Network-Based Automated Crack Detection and Analysis for the Inspection of Concrete Structures." Applied Sciences 10, no. 22 (November 16, 2020): 8105. http://dx.doi.org/10.3390/app10228105.

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The damage investigation and inspection methods for infrastructures performed in small-scale (type III) facilities usually involve a visual examination by an inspector using surveying tools (e.g., cracking, crack microscope, etc.) in the field. These methods can interfere with the subjectivity of the inspector, which may reduce the objectivity and reliability of the record. Therefore, a new image analysis technique is needed to automatically detect cracks and analyze the characteristics of the cracks objectively. In this study, an image analysis technique using deep learning is developed to detect cracks and analyze characteristics (e.g., length, and width) in images for small-scale facilities. Three stages of image processing pipeline are proposed to obtain crack detection and its characteristics. In the first and second stages, two-dimensional convolutional neural networks are used for crack image detection (e.g., classification and segmentation). Based on convolution neural network for the detection, hierarchical feature learning architecture is applied into our deep learning network. After deep learning-based detection, in the third stage, thinning and tracking algorithms are applied to analyze length and width of crack in the image. The performance of the proposed method was tested using various crack images with label and the results showed good performance of crack detection and its measurement.

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M N, Sumaiya, Prajwal K, Rao Shravan Vasudev, Shreya K A, Thrishul R, and R. Manjunath Prasad. "Comparative Analysis of Concrete Crack Detection using Image Processing and Artificial Intelligence." Journal of Image Processing and Artificial Intelligence 9, no. 1 (January 11, 2023): 8–15. http://dx.doi.org/10.46610/joipai.2023.v09i01.002.

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Cracks in concrete structures can be formed due to many reasons such as physical damage, hydraulic shrinkage, thermal shrinkage, swelling, and corrosion of steel reinforcements. These vulnerable entities present in structures are responsible for reducing the performance and strength of the concrete. Inspecting these entities and deciding the nature of these cracks is an essential element for the maintenance of the structure. Concrete crack detection based on Image Processing and Artificial Intelligence involves using computer vision techniques to automatically identify and classify cracks in concrete structures. Detection and classification of these cracks can be done using a combination of various machine learning algorithms and image processing techniques. Our project aims to detect the location of the cracks on the structures using various processing techniques such as resizing, gray scaling, binarization, segmentation, enhancement, and filtering out the noise. Detection of the cracks can be performed using thresholding techniques. Later classification of these detected cracks can be done using Deep Learning techniques concerning various deciding parameters such as length, width, and area of cross-section of the detected crack. The cracks can be classified based on their size they can be thin, medium, or wide cracks. They can also be classified based on the appearance of the crack, which may be longitudinal, vertical or transversal.

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Sun, Xichen, Jie Chen, Siyi Lu, Miaomiao Liu, Siyu Chen, Yifei Nan, Yang Wang, and Jun Feng. "Ureolytic MICP-Based Self-Healing Mortar under Artificial Seawater Incubation." Sustainability 13, no. 9 (April 25, 2021): 4834. http://dx.doi.org/10.3390/su13094834.

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Ureolytic microbial-induced calcium carbonate precipitation (MICP) is a promising green technique for addressing sustainable building concerns by promoting self-healing mortar development. This paper deals with bacteria-based self-healing mortar under artificial seawater incubation for the sake of fast crack sealing with sufficient calcium resource supply. The ureolytic MICP mechanism was explored by morphology characterization and compositional analysis. With polyvinyl alcohol fiber reinforcement, self-healing mortar beams were produced and bent to generate 0.4 mm width cracks at the bottom. The crack-sealing capacity was evaluated at an age of 7 days, 14 days, and 28 days, suggesting a 1-week and 2-week healing time for 7-day- and 14-day-old samples. However, the 28-day-old ones failed to heal the cracks completely. The precipitation crystals filling the crack gap were identified as mainly vaterite with cell imprints. Moreover, fiber surface was found to be adhered by bacterial precipitates indicating fiber–matrix interfacial bond repair.

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Dissertations / Theses on the topic "Artificial crack"

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Rehman, Atiq-Ur. "An investigation of methods of reducing fatigue crack growth by artificial crack-closure effects." Thesis, University of Salford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.315379.

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Yang, Jidong. "Road crack condition performance modeling using recurrent Markov chains and artificial neural networks." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000567.

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Bezerra, Agnes. "The Use of Artificial Intelligence for Assessing Damage in Concrete Affected by Alkali-Silica Reaction (ASR)." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42730.

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Over the last decades, numerous techniques have been proposed worldwide to assess the actual damage of critical concrete infrastructure. A method that has progressively been used in North America is a novel microscopic tool, the Damage Rating Index (DRI). This semi-quantitative petrographic tool was developed to reliably appraise both the nature and degree of damage in concrete affected by alkali-silica reaction (ASR), which may threaten the serviceability and the durability of concrete infrastructure around the world. Performing the DRI consists of counting numerous distress features (i.e. closed and open cracks in the aggregate and cement paste) encountered on the surface of polished concrete sections (lab-made specimens or cores extracted from field structures) using a stereomicroscope at 16x magnification; once recognized and counted, the distinct distress features are multiplied by weighting factors whose purpose is to balance their relative importance towards the distress mechanism under consideration (e.g., ASR). Although reliable and efficient, performing the DRI is exceptionally time-consuming, and its results are highly operator sensitive, requiring an experienced petrographer. Therefore, this study proposes using artificial intelligence (AI) through machine learning (ML) techniques to automate the DRI test protocol estimating the damage degree of concrete affected by ASR. The ML subfield known as Deep Learning (DL) was implemented to create human-like intelligence connections using a Convolutional Neural Network (CNN) algorithm, which can predict the DRI results (machine assessment) that are close to those expected (human assessment. This research is divided into two phases: 1) performing cracks recognition using sliding windows and 2) an advanced pixel recognition. In the first phase, the results displayed some inconsistencies in cracks classification; yet, for cracks identification in the cement paste, in particular, this method presented promising results. However, the advanced pixel recognition improved the drawbacks of the first phase, providing a more accurate cracks recognition and classification. The DRI number estimation was subsequently implemented into the CNN model achieving a 74.4% accuracy. Hence, the DRI automation is a revolutionary step towards a more ubiquitous use of the method since less time is required to perform the task, besides avoiding variability among petrographers and enabling non/less experienced professionals to take advantage of this powerful microscopic tool. With a more widely accessible diagnostic tool, ASR-affected critical concrete infrastructure could be more efficiently assessed, which would ultimately increase their safety.

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田中, 啓介, Keisuke TANAKA, 義明秋庭, Yoshiaki AKINIWA, 博央來海, Hirohisa KIMACHI, 和之伊藤, and Kazuyuki ITOH. "防振ゴム材料における疲労き裂進展挙動へのJ 積分の適用." 日本機械学会, 2003. http://hdl.handle.net/2237/9154.

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Furfari, Domenico. "Short track growth from artificial defects in Ti-10V-2Fe-3Al : a study using optical techniques for crack measurements and detection." Thesis, Cranfield University, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.427204.

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Hou, Chuanchuan. "Vibration-based damage identification with enhanced frequency dataset and a cracked beam element model." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/20434.

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Damage identification is an important topic in structural assessment and structural health monitoring (SHM). Vibration-based identification techniques use modal data to identify the existence, location and severity of possible damages in structures, often via a numerical model updating procedure. Among other factors influencing the practicality and reliability of a damage identification approach, two are of primary interest to this study. The first one concerns the amount and quality of modal data that can be used as ‘response’ data for the model updating. It is generally recognised that natural frequencies can be measured with relatively high accuracy; however, their number is limited. Mode shapes, on the other hand, are susceptible to larger measurement errors. Seeking additional modal frequency data is therefore of significant value. The second one concerns the errors at the numerical (finite element) model level, particularly in the representation of the effect of damage on the dynamic properties of the structure. An inadequate damage model can lead to inaccurate and even false damage identification. The first part of the thesis is devoted to enhancing the modal dataset by extracting the so called ‘artificial boundary condition’ (ABC) frequencies in a real measurement environment. The ABC frequencies correspond to the natural frequencies of the structure with a perturbed boundary condition, but can be generated without the need of actually altering the physical support condition. A comprehensive experimental study on the extraction of such frequencies has been conducted. The test specimens included steel beams of relatively flexible nature, as well as thick and stiffer beams made from metal material and reinforced concrete, to cover the typical variation of the dynamic characteristics of real-life structures in a laboratory condition. The extracted ABC frequencies are subsequently applied in the damage identification in beams. Results demonstrate that it is possible to extract the first few ABC frequencies from the modal testing in different beam settings for a variety of ABC incorporating one or two virtual pin supports. The inclusion of ABC frequencies enables the identification of structural damages satisfactorily without the necessity to involve the mode shape information. The second part of the thesis is devoted to developing a robust model updating and damage identification approach for beam cracks, with a special focus on thick beams which present a more challenging problem in terms of the effect of a crack than slender beams. The priority task has been to establish a crack model which comprehensively describes the effect of a crack to reduce the modelling errors. A cracked Timoshenko beam element model is introduced for explicit beam crack identification. The cracked beam element model is formulated by incorporating an additional flexibility due to a crack using the fracture mechanics principles. Complex effects in cracked thick beams, including shear deformation and coupling between transverse and longitudinal vibrations, are represented in the model. The accuracy of the cracked beam element model for predicting modal data of cracked thick beams is first verified against numerically simulated examples. The consistency of predictions across different modes is examined in comparison with the conventional stiffness reduction approach. Upon satisfactory verification, a tailored model updating procedure incorporating an adaptive discretisation approach is developed for the implementation of the cracked beam element model for crack identification. The updating procedure is robust in that it has no restriction on the location, severity and number of cracks to be identified. Example updating results demonstrate that satisfactory identification can be achieved for practically any configurations of cracks in a beam. Experimental study with five solid beam specimens is then carried out to further verify the developed cracked beam element model. Both forward verification and crack damage identification with the tested beams show similar level of accuracy to that with the numerically simulated examples. The cracked beam element model can be extended to crack identification of beams with complex cross sections. To do so the additional flexibility matrix for a specific cross-section type needs to be re-formulated. In the present study this is done for box sections. The stress intensity factors (SIF) for a box section as required for the establishment of the additional flexibility matrix are formulated with an empirical approach combining FE simulation, parametric analysis and regression analysis. The extended cracked beam element model is verified against both FE simulated and experimentally measured modal data. The model is subsequently incorporated in the crack identification for box beams. The successful extension of the cracked beam element model to the box beams paves the way for similar extension to the crack identification of other types of sections in real-life engineering applications.

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Ingabire, Annick, and Robin Olsson. "Standardization of Eddy Current Testing Calibration for Valve Spring Wire." Thesis, KTH, Industriell produktion, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-232712.

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Elektromagnetisk provning (ECT) har blivit en av de mest använda metoderna för attkvalitetssäkra produkter där icke-destruktiv testning av material krävs. Vid provning av ståltrådinteragerar utrustningen med det testade materialet och upptäcker ytdefekter och, i vissomfattning, om strukturen skiljer sig från det kalibrerade provet. Om produkten befinner sigutanför specifikationen, skrotas den eller ombearbetas. Denna Mastersuppsats undersökerkalibreringsförfarandet för elektromagnetisk provning som utförs av Suzuki Garphyttan, som är enav de största tillverkarna i världen av ventil- och transmissionsfjädrar för bilindustrin. Genom deslutsatser som framgår av denna rapport, som baseras på undersökningar gjorda i vetenskapligaartiklar och genom att analysera den data som inhämtats från produktionen, presenteras enstandardisering av kalibreringsförfarandet. Detta är nödvändigt för att säkerställa såväl testernastillförlitlighet, såväl som minimering av risken för att skrota ut material på grund av felaktigainställningar, till exempel på grund av otillräckligt signal-brus (S/N)-förhållande. Fokus ligger påsond-baserad, roterande testning, i denna avhandling kallad circografen, eftersom den är manuelltkalibrerad.Några av de konstaterade resultaten i rapporten är:● Standard Operating Procedures (SOP)-baserade instruktioner implementeras i företagetskvalitetssystem. Detta för att minska variationer i kvalitet mellan olika operatörer ochmaskiner.● Ett förslag på intervaller för värden (fasvinkel, förstärkning, korrigering av filter och såvidare) presenteras. Detta är baserat på insamlad unik produktionsdata från operatöreroch utförda test.● Fasvinklarna som används varierar inom specifika intervaller och bestäms av materialval iallmänhet och frekvensval i synnerhet.● Konduktivitets- och permeabilitetsvärdena för oljehärdad tråd, liksom penetrationsdjupetför tre olika frekvenser presenteras.● Härdningsfel kan inte detekteras i roterande provning● Ökat kolinnehåll minskar den elektriska ledningsförmågan och ger ökad resistivitet, vilketgör att fasen flyttar sig och resulterar i ett minskande gap mellan brussignal ochspricksignal.
Eddy current testing (ECT) has become one of the most extensively used methods to secure theproducts and constructions when non-destructive testing is required. In typical cases of steel wiretesting, the equipment interacts with the tested material and discovers surface defects and, to alimited extent, if the inner structure is differing from the calibration sample. If the product isfound to be outside specification, it is either scrapped or reworked. This master thesis investigatesthe Eddy current testing calibration procedures performed by steel wire manufacturer SuzukiGarphyttan, which is one of the largest producers in the world of valve and transmission springwire for the automotive industry. By the research shown in this thesis, based on the investigationmade in scientific papers and by analyzing data extracted from production, a standardization ofthe calibration procedure is being presented. This is to secure both the testing reliability, andminimizing the risk of scrapping material due to inaccurate settings, for example due toinsufficient signal to noise (S/N) ratio. The focus is on probe-based, rotating testing, in this thesiscalled the circograph, since it is manually calibrated.Some of the findings established in the report: Standard Operating Procedures (SOP) based instructions is being implemented in thecompany's Quality system. This is to decrease the process variations between differentoperators and machines. Suggestions of intervals for values (Phase angle, gain, filter correction and so forth) arepresented. These values are based on collected unique production data from operators andmachines, as well as performed tests. The phase angles used are ranging between specific value intervals, and set by materialchoice in general and choice of frequency in particular. The conductivity and permeability values for oil-tempered wire, as well as penetrationdepth for three different frequencies, are presented. Hardening error cannot be detected in the circograph. Increased carbon content is decreasing conductivity and increasing resistivity, causing thephase to move slightly and decreasing the gap between noise signal and crack signal.

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Nguyen, Thi Thu Trang. "Influence de l'effet de l'interface acier/béton (top-bar effect) sur la corrosion de structures en béton armé exposées en environnement de chlorures ou de carbonatation." Electronic Thesis or Diss., Université de Toulouse (2023-....), 2024. http://www.theses.fr/2024TLSEI009.

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Le béton armé est connu l’un des matériaux les plus utilisés dans la construction. Néanmoins, après une période de mise en exploitation, il peut se corroder. Les chlorures et la carbonatation sont les principaux facteurs provoquant la corrosion des structures en béton armé. La thèse a pour objectif d’étudier le comportement à la corrosion du béton armé sous l’environnement de carbonatation ou des chlorures, correspondant à l'influence de l’effet de la qualité de l’interface acier/mortier (top-bar effet), du type de ciment ainsi que de la fissure transversale artificielle ou des fissures transversales induites par la charge mécanique.En général, la corrosion induite par la carbonatation est étudiée du point de vue de la corrosion uniforme. Le premier objectif de la thèse est de confirmer l’opinion de la corrosion par macro-cellule ou non uniforme dans la corrosion induite par la carbonatation. Selon les résultats expérimentaux, le taux de corrosion dans les armatures de béton carbonaté est susceptible d'être considéré du point de vue de la corrosion uniforme et macro-cellule, qui est fortement influencée par le rapport cathode/anode. De plus, l'application de CEM III utilisant des laitiers comme addition minérale a montré une réduction efficace de la corrosion non uniforme.La deuxième partie se concentre sur l'influence de l’effet de la qualité de l’interface acier/mortier (top-bar effet) sur le comportement de la corrosion dans le cas d'une corrosion induite par la carbonatation et de la présence d'une fissure induite par la charge mécanique. Le suivi du courant de corrosion par macro-cellule a été utilisée dans les essais expérimentaux. Puis la perte de masse ainsi que la cinétique de corrosion ont été calculée. La corrosion s'est développée principalement au niveau du pré-fissures. En raison de l’effet de la qualité de l’interface acier/mortier, les barres supérieures étaient plus corrodées que les barres inférieures. La valeur du courant de la corrosion mesurée sur les barres supérieures a été observée plus élevée que sur les barres inférieures. La perte de masse de l'acier calculée à partir de la mesure du suivi de courant ne correspond qu'à une petite partie de la perte de masse totale déterminée par la mesure gravimétrique. La corrosion uniforme semble être le phénomène principal.La dernière partie étudie l’effet de la qualité de l’interface acier/mortier (top-bar effet) dans des échantillons de béton fibré avec ou sans fissure artificielle sur la corrosion induite par les chlorures. Les barres supérieures sont plus corrodées que les barres inférieures et la partie supérieure de la barre supérieure présente une corrosion plus élevée que la partie inférieure. En présence de fissures artificielles, le ‘’top-bar effet’’ entraîne la propagation de la corrosion le long de la surface des barres d'acier. La corrosion se développe également le long de la barre supérieure lorsqu'il n'y a pas de fissure artificielle, dans un temps pas si différent du cas d'une fissure artificielle. Cela confirme que l'exposition de la surface supérieure et l’effet de la qualité de l’interface acier/mortier sont très préjudiciables à la corrosion. En comparant le comportement avec un béton sans fibres, il apparaît que l'ajout de fibres dans le béton armé entraîne une augmentation de la résistance à la fissuration induite par la corrosion.Dans chaque partie, les observations expérimentales sont couplées à des simulations numériques pour comparer et démontrer les résultats expérimentaux
Reinforced concrete is known one of the most popular materials applied in construction. Nevertheless after a period of time it can be corroded. Chloride and carbonation are the main factors causing to corrosion in reinforced concrete structure. The thesis aimed to study the corrosion behavior of reinforcement concrete under carbonation or chloride environment, corresponding to the influence of top-bar effect, the cement type as well as artificial transverse crack or load-induced cracks.In general carbonation induced corrosion is usually researched from the point of view that it generates uniform corrosion. The first objective of the thesis is to confirm the opinion of macro cell or non-uniform corrosion in carbonated induced corrosion. According to the results of experiments in this part, corrosion rate in carbonated concrete reinforcement is likely to consider from the point of view of both uniform and macro cell corrosion, which is highly influenced by the ratio cathode/anode. In addition the application of CEM III using slag as addictive exhibited reduction of non-uniform corrosion effectively.The second part focuses on the influence of top-bar effect on corrosion behavior in the case carbonation induced corrosion and presence of load induced crack. Macro cell corrosion current monitoring was utilized in the experiment following the loss of mass as well as corrosion kinetic was calculated. Corrosions mainly developed at the position of the pre-cracks. Due to the top-bar effect upper bars were more corroded than bottom bars. Current corrosion value of top bars was observed higher than bottom bars. Loss of steel mass calculated from macro cell current measurement corresponds to only to a small part of the total loss of mass determined by gravimetric measurement. Uniform corrosion appears to be the main phenomena.The last part investigates the effect of top-bar effect in fibers concrete samples with or without artificial crack on chloride induced corrosion. The top steel bars are more corroded than the bottom bars and the upper part of the top bar is recorded higher corrosion than the lower part. In presence of artificial crack the top casting effect results that corrosions spread along the surface of the steel bars. Corrosion also spread along the top bar when there is no artificial crack, in a time not so different from the case of artificial crack. It confirms that top surface exposure and top bar effect are highly prejudicial for corrosion. By comparing the behavior with concrete without fibers, it appears that the addition of fibers in reinforced concrete leads to an increase of resistance to corrosion induced cracking.For each part, experimental observations are coupled with numerical simulations to compare as well as demonstrate the experimental results

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Mirjana, Filipovic. "Evolution of artificial defects during shape rolling." Licentiate thesis, Högskolan Dalarna, Materialvetenskap, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:du-5215.

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Very often defects are present in rolled products. For wire rods, defects are very deleterious since the wire rods are generally used directly in various applications. For this reason, the market nowadays requires wire rods to be completely defect-free. Any wire with defects must be rejected as scrap which is very costly for the production mill. Thus, it is very important to study the formation and evolution of defects during wire rod rolling in order to better understand and minimize the problem, at the same time improving quality of the wire rods and reducing production costs. The present work is focused on the evolution of artificial defects during rolling. Longitudinal surface defects are studied during shape rolling of an AISI M2 high speed steel and a longitudinal central inner defect is studied in an AISI 304L austenitic stainless steel during ultra-high-speed wire rod rolling. Experimental studies are carried out by rolling short rods prepared with arteficial defects. The evolution of the defects is characterised and compared to numerical analyses. The comparison shows that surface defects generally reduce quicker in the experiments than predicted by the simulations whereas a good agreement is generally obtained for the central defect.

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Datsiou, Kyriaki Corinna. "Design and performance of cold bent glass." Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/269408.

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The demand for flat glass is high and increasing significantly in the building industry as a direct result of architectural requirements for lightness, transparency and natural light. Current architectural trends require glass in curvilinear forms for smooth free-form façades. Two principal challenges arise from this: to cost-effectively produce the desired curvature and; to ensure its safe performance after exposure to ageing. The recent availability of high strength glass provides an opportunity to address the first challenge by developing cold bent glass. Cold bending involves the straining of relatively thin glass components, at ambient temperatures, and is a low energy and cost effective manner of creating curvilinear forms. However, cold bending is not yet widely established as a reliable method. The aim of this thesis is to develop the understanding of cold bent glass during the bending process and to evaluate its post-ageing performance. This thesis, firstly, investigates the mechanical response of monolithic glass plates during the cold bending process. The stability of cold bent glass is investigated experimentally by bending it in double curved anticlastic shapes. A parametric numerical analysis involves different boundary conditions, geometrical plate characteristics and bending parameters. The principal outcome is that a local instability, now termed cold bending distortion, occurs when certain displacement limits are exceeded and could degrade the optical quality of the glass. An evaluation procedure is also formulated to set limits and aid designers/manufacturers to predict the mechanical response and the optical quality of the glass. Cold bent glass is subjected to permanent bending stresses throughout its service life and therefore, its strength degradation after ageing needs to be quantified. Analytical, experimental and numerical investigations are undertaken in this thesis to identify the most effective method for estimating glass strength (evaluation of destructive tests, required number of specimens, statistical analysis methods and sub-critical crack growth). The limited availability of naturally aged toughened glass and the absence of a reliable ageing standard impede the evaluation of its aged performance. Therefore, a parametric experimental investigation of artificial ageing methods on glass is undertaken in this thesis. A procedure for the evaluation of the strength of aged glass is finally, formulated to allow the selection of artificial ageing parameters that correspond to a target level of erosion. The knowledge on artificial ageing and strength prediction acquired above is finally implemented on different types of glass to determine their strength after ageing and assess their safe use in cold bending / load bearing applications. The investigation showed that fully toughened glass has a superior performance to chemically toughened or annealed glass. Overall, the research presented in this thesis demonstrates that high quality cold bent toughened glass can be created when certain applied displacement limits are respected. These can be used as a safe, cost-effective and energy efficient replacement to the more conventional hot bent glass. However, cold bending / load bearing applications in which the stressed glass surface is exposed to ageing, require glass with a relatively high case depth such as fully toughened or bi-tempered glass.

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Books on the topic "Artificial crack"

1

Rehman, Atiq-Ur. An investigation of methods of reducing fatigue crack growth by artificial crack-closure effects. Salford: University of Salford, 1992.

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Rosenberg, Tom, Brian Taylor, and Mark Neveldine. Crank 2: High voltage. Santa Monica, Calif: Lionsgate, 2009.

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Book chapters on the topic "Artificial crack"

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Li, Wei, Xin’an Yuan, Jianming Zhao, Xiaokang Yin, and Xiao Li. "Research on Real-time and High-Precision Cracks Inversion Algorithm for ACFM Based on GA-BP Neural Network." In Alternating Current Field Measurement Technique for Detection and Measurement of Cracks in Structures, 1–13. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-7255-1_1.

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AbstractAlternating current field measurement (ACFM) technology is an emerging nondestructive testing method, which has been used widely in oil industry for detecting and evaluating of surface cracks on structures. It is hard to achieve real-time and high-precision cracks inversion for ACFM based on traditional characteristic signals. In this paper, based on the finite element method (FEM) model of electromagnetic coupling ACFM probe, the energy spectrum and phase threshold determination method is present to obtain the crack characteristic signals in real time. The real-time and high- precision cracks inversion system for ACFM is set up and verified by artificial cracks. The length and depth of cracks are calculated using the characteristic signals obtained from experiments based the Genetic Algorithm (GA) and Back Propagation (BP) neural network real-time and high- precision cracks inversion algorithm. The results show that the FEM model of electromagnetic coupling ACFM probe can simulate the characteristic signals perfectively. The energy spectrum and phase threshold determination method can obtain the crack characteristic signals in real time. The GA-BP neural network can invert the length and depth of crack perfectly and the relative error of inversion accuracy is less than 10%.

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Aravindkumar, S., P. Varalakshmi, and Chindhu Alagappan. "Automatic Road Surface Crack Detection Using Deep Learning Techniques." In Artificial Intelligence and Technologies, 37–44. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-6448-9_4.

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Mahmud, Mat Nizam, Nur Nadhirah Naqilah Ahmad Sabri, Muhammad Khusairi Osman, Ahmad Puad Ismail, Fadzil Ahmad Mohamad, Mohaiyedin Idris, Siti Noraini Sulaiman, Zuraidi Saad, Anas Ibrahim, and Azmir Hasnur Rabiain. "Pavement Crack Detection from UAV Images Using YOLOv4." In Artificial Intelligence and Industrial Applications, 73–85. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43520-1_7.

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Roul, Rajendra Kumar, Navpreet, and Jajati Keshari Sahoo. "Ensemble-Based Road Surface Crack Detection: A Comprehensive Approach." In Big Data and Artificial Intelligence, 166–84. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-49601-1_12.

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Nabizadeh, Elham, and Anant Parghi. "Deep Learning-Based Concrete Crack Detection Using YOLO Architecture." In Artificial Intelligence and Smart Vehicles, 182–93. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43763-2_11.

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Palanisamy, T., Rajat Shakya, Sudeepthi Nalla, and Sai Shruti Prakhya. "Crack Detection in Concrete Using Artificial Neural Networks." In Lecture Notes in Civil Engineering, 877–85. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12011-4_74.

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Seguini, Meriem, Tawfiq Khatir, Samir Khatir, Djilali Boutchicha, Nedjar Djamel, and Magd Abdel Wahab. "Crack Identification in Pipe Using Improved Artificial Neural Network." In Lecture Notes in Mechanical Engineering, 15–25. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4835-0_2.

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Li, Yaoyao, Pengyu Liu, Shanji Chen, Kebin Jia, and Tianyu Liu. "The Identification of Slope Crack Based on Convolutional Neural Network." In Advances in Artificial Intelligence and Security, 16–26. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78618-2_2.

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Dunis, Christian L., Peter W. Middleton, Konstantinos Theofilatos, and Andreas Karathanasopoulos. "Modelling, Forecasting and Trading the Crack: A Sliding Window Approach to Training Neural Networks." In Artificial Intelligence in Financial Markets, 69–106. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-137-48880-0_3.

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Zhang, XiaoGang, Shao Cui, Sen Zhang, JingFang Su, CaiXing Wang, and Derek Perakis. "Research on Crack Detection Technology of Buildings After Earthquake Based on Structured Light." In Advances in Artificial Intelligence and Security, 26–39. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06761-7_3.

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Conference papers on the topic "Artificial crack"

1

Bostancioglu, Onur, and Levent Karacan. "Crack Detection with Conditional Diffusion Model." In 2024 8th International Artificial Intelligence and Data Processing Symposium (IDAP), 1–4. IEEE, 2024. http://dx.doi.org/10.1109/idap64064.2024.10711097.

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Wang, Zikang, and Shanjun Zhang. "Development of a roadway crack detection system tailored for specific environments." In Sixth International Conference on Image, Video Processing and Artificial Intelligence (IVPAI 2024), edited by Ruidan Su, 14. SPIE, 2024. http://dx.doi.org/10.1117/12.3046210.

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Dai, Lu, Di Wang, Fengquan Song, and Han Yang. "Concrete Bridge Crack Detection Method Based on an Improved RT-DETR Model." In 2024 3rd International Conference on Robotics, Artificial Intelligence and Intelligent Control (RAIIC), 172–75. IEEE, 2024. http://dx.doi.org/10.1109/raiic61787.2024.10670904.

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Hata, Seiji, Akira Mizobuchi, and Tadashi Inai. "Development of evaluation method for concrete crack." In Quality Control by Artificial Vision, edited by Kenneth W. Tobin, Jr. and Fabrice Meriaudeau. SPIE, 2003. http://dx.doi.org/10.1117/12.514941.

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Selek, M., O. S. Sahin, and S. Kahramanli. "Thermographical Investigation of Crack Initiation Using Artificial Neural Networks." In EUROCON 2007 - The International Conference on "Computer as a Tool". IEEE, 2007. http://dx.doi.org/10.1109/eurcon.2007.4400354.

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Lin, Heng-Xiang, Wei-Jie Chen, Yu-Tong Lin, Ye Song, Zi-Yi He, Lu-Peng Jian, Xin-Yi Chen, Lin Wei, Zne-Jung Lee, and Zhong-Yuan Chen. "House Inspection System Using Artificial Intelligence for Crack Identification." In 2023 IEEE 5th Eurasia Conference on IOT, Communication and Engineering (ECICE). IEEE, 2023. http://dx.doi.org/10.1109/ecice59523.2023.10382996.

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Kim, Tae-il. "Development in nanoscale crack based sensors for advanced wearable electronics." In Neural Interfaces and Artificial Senses. València: Fundació Scito, 2021. http://dx.doi.org/10.29363/nanoge.nias.2021.014.

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Vaheesan, Kanapathippillai, Chanjief Chandrakumar, Senthan Mathavan, Khurram Kamal, Mujib Rahman, and Amin Al-Habaibeh. "Tiled fuzzy Hough transform for crack detection." In The International Conference on Quality Control by Artificial Vision 2015, edited by Fabrice Meriaudeau and Olivier Aubreton. SPIE, 2015. http://dx.doi.org/10.1117/12.2182913.

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Aldea, Emanuel, and Sylvie Le Hégarat. "Robust crack detection strategies for aerial inspection." In The International Conference on Quality Control by Artificial Vision 2015, edited by Fabrice Meriaudeau and Olivier Aubreton. SPIE, 2015. http://dx.doi.org/10.1117/12.2182920.

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Huang, Lei, Vignesh Mohanraj, and Hossein Asghari,. "Improved automatic road crack detection and classification." In 2018 International Conference on Image, Video Processing and Artificial Intelligence, edited by Ruidan Su. SPIE, 2018. http://dx.doi.org/10.1117/12.2504606.

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Reports on the topic "Artificial crack"

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Nestleroth, Dr J. Bruce. PR-3-823-R01 Remote Field Eddy Current Detection of Stress-Corrosion Cracks. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), February 1990. http://dx.doi.org/10.55274/r0011870.

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The feasibility of detecting stress-corrosion cracks (SCC) using the Remote Field Eddy Current (RFEC) technique was demonstrated. The RFEC technique interrogates the entire thickness of the pipe and is applicable for in-line inspection. If it can be shown that the RFEC technique is effective in detecting SCC, then the technique is an ideal method for detecting the defects of interest. A defect detection model is proposed for explaining the mechanism for crack detection. For axially orientated, closed cracks, such as SCC, the conventional defect detection model proved to be too simplistic and not applicable. Therefore, a new detection model that examines the flow of circumferential eddy currents was developed based on experimental results. This model, though not rigorous, provides a general understanding of the applicability of the RFEC technique for finding SCC. The data from the cracks and various artificial defects are presented in three formats: isometric projections, pseudocolor images, and line-of-sight data. Though only two cracks were found, the experimental results correlate well with the circumferential eddy current theory. A theoretical analysis of the effects of motion on the output signal of the receiver is presented. This analysis indicates that the inspection speed of simple implementations may be limited to a few miles per hour.

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Kanakamedala, Deven, Jungil Seo, Amit H. Varma, Robert J. Connor, and Anna Tarasova. Shear and Bearing Capacity of Corroded Steel Beam Bridges and the Effects on Load Rating. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317634.

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Corrosion in the girders of steel girder bridges often occurs due to the deicing salts, water, and other debris that leak through the deck joints into the web and bottom flange at the girder ends. Corrosion causes loss of cross-sectional area leading to a reduction in section properties of the member, which eventually results in a reduction in structural resistance against shear and bearing. In this study, seven full-scale tests were performed on decommissioned steel girders acquired from bridges scheduled for demolition in Indiana. Two of the four girders had severe corrosion with cracks and holes in the bottom of the web induced by corrosion, while four girders had moderate section loss induced artificially. All seven girders were subjected to shear loading to determine the residual shear and bearing capacity. Test results revealed a reduction in strength due to section loss compared to nominal sections. Failure modes observed during these four large-scale experiments were shear buckling, shear rupture, and web local crippling. Finite element models were developed and benchmarked to the experimental results. Parametric studies were performed for unstiffened and stiffened girders and included different corrosion scenarios by varying parameters such as corrosion height, length, and thickness loss. Results were analyzed to investigate the effect of each parameter and a modification factor was developed to estimate the residual shear and bearing capacity of corroded girders.

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