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Omotayo Farai, Nicole Metje, Carl Anthony and David Chapman
Wireless sensor networks (WSN) have emerged as a robust and cost-effective solution for buried pipeline monitoring due to the low cost (a maximum of a few tens of UK pounds (GBP)), low power supply capacity (in the order of 1 watt/hour) and small size (c...
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Weixing Han, Guang Yang, Chunsheng Hao, Zhengqi Wang, Dejing Kong and Yu Dong
The insulation condition of cables has been the focus of research in power systems. To address the problem that the electric field is not easily measured under the operating condition of 10 kV transmission cables with insulation defects, this paper propo...
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Zijie Shen, Bai Liu and Guangchun Zhou
This paper reveals the failure characteristic points of the spiral reinforced column during the damage process by modeling and analyzing the stressing state of the column with the test and finite element output data. At the same time, the structural stre...
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Lucian Daniel Dobreci, Valentin Zichil, Elena Nechita, Cosmin Constantin Grigora? and Vlad Andrei Ciubotariu
Shockwave therapy is a noninvasive treatment technique used in multidisciplinary fields, such as sports medicine, physical therapy, and orthopedics. This method of treatment is recommended for medical conditions, such as muscle contractions, intramuscula...
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Shifa Xia, Xiulin Li, Fuye Xu, Lufei Chen and Yong Zhang
Finite element data form an important basis for engineers to undertake analysis and research. In most cases, it is difficult to generate the internal sections of finite element data and professional operations are required. To display the internal data o...
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Matthias Heinrich, Ute Rabe and Bernd Valeske
The results of this study can be used in nondestructive quality inspection of serial parts by analyzing their eigenfrequencies via acoustic resonance testing. Representative and valid training data are mandatory to identify suitable acoustic test charact...
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Abouzar Choubineh, Jie Chen, David A. Wood, Frans Coenen and Fei Ma
Machine Learning (ML) and/or Deep Learning (DL) methods can be used to predict fluid flow in porous media, as a suitable replacement for classical numerical approaches. Such data-driven approaches attempt to learn mappings between finite-dimensional Eucl...
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Qiang Fang, Clemente Ibarra-Castanedo and Xavier Maldague
In quality evaluation (QE) of the industrial production field, infrared thermography (IRT) is one of the most crucial techniques used for evaluating composite materials due to the properties of low cost, fast inspection of large surfaces, and safety. The...
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William Finnegan, Yadong Jiang, Nicolas Dumergue, Peter Davies and Jamie Goggins
As the world shifts to using renewable sources of energy, wind energy has been established as one of the leading forms of renewable energy. As the requirement for wind energy increases, so too does the size of the turbines themselves, where the latest tu...
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Lorena Salazar-Llano and Camilo Bayona-Roa
One challenging problem is the representation of three-dimensional datasets that vary with time. These datasets can be thought of as a cloud of points that gradually deforms. However, point-wise variations lack information about the overall deformation p...
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Petr S. Martyshko, Igor V. Ladovskii, Denis D. Byzov and Alexander G. Tsidaev
We present a new method for gravity data inversion for the linear problem (reconstruction of density distribution by given gravity field). This is an iteration algorithm based on the ideas of local minimization (also known as local corrections method). U...
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Xiaocui Yang, Xinmin Shen, Haiqin Duan, Fei Yang, Xiaonan Zhang, Ming Pan and Qin Yin
Sound absorption performance of polyurethane foam could be improved by adding a prepositive microperforated polymethyl methacrylate panel to form a composite sound-absorbing structure. A theoretical sound absorption model of polyurethane foam and that of...
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Shuai Teng, Gongfa Chen, Gen Liu, Jianbin Lv and Fangsen Cui
In this paper, a convolutional neural network (CNN) was used to extract the damage features of a steel frame structure. As structural damage could induce changes of the modal parameters of the structure, the convolution operation was used to extract the ...
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Lixiu Zhang, Chaoqun Li, Yuhou Wu, Ke Zhang and Huaitao Shi
The thermal characteristics of a motorized spindle are the main determinants of its performance, and influence the machining accuracy of computer numerical control machine tools. It is important to accurately predict the thermal field of a motorized spin...
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Evaggelos Kaselouris, Stella Paschalidou, Chrisoula Alexandraki and Vasilis Dimitriou
The transient acoustic dynamics of a splash cymbal are investigated via the Finite Element Method-Boundary Element Method. Real three-dimensional motion data recorded from the interaction of drummer?drumstick?cymbal provide the initial and the loading co...
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Michael Lo, Saravanan Karuppanan and Mark Ovinis
Machine learning tools are increasingly adopted in various industries because of their excellent predictive capability, with high precision and high accuracy. In this work, analytical equations to predict the failure pressure of a corroded pipeline with ...
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Gunther Steenackers, Jeroen Peeters, Simon Verspeek and Bart Ribbens
Carbon fiber bicycle frames are complex-shaped structures and are prone to delaminations and difficult to inspect. The use of finite element model updating is common in structural dynamics but not so common in active thermography inspection. However, the...
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Benjamin Lumantarna
Pág. pp. 77 - 82
This paper presents visual application of a finite element program for plane stress and plane strain problems. The elements used in this program are isoparametric triangular (three nodes) and rectangular (four nodes) and subparametric triangular (six nod...
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Guang Ma, Ling Cheng, Yu Han and Chengxu He
The magnetic properties of a 0.10 mm ultra-thin, grain-oriented (UTGO) silicon steel and an Fe-based amorphous (FBA) alloy under sinusoidal excitation were experimentally researched, and the magnetic field strength and iron loss of the two materials unde...
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Alexey Liogky and Victoria Salamatova
Data-driven simulations are gaining popularity in mechanics of biomaterials since they do not require explicit form of constitutive relations. Data-driven modeling based on neural networks lacks interpretability. In this study, we propose an interpretabl...
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