Search the articles

SI: Steels and Composites for Engineering Structures Views: 2,112 Downloads: 1,142 Vol. 16, No. 59 (2022) December 22, 2021 pp. 461-470

Damage Detection in Structural Health Monitoring using Hybrid Convolution Neural Network and Recurrent Neural Network

Thanh Bui-Tien, Dung Bui-Ngoc, Hieu Nguyen-Tran, Lan Nguyen-Ngoc, Hoa Tran-Ngoc, Hung Tran-Viet

The process of damage identification in Structural Health Monitoring (SHM) gives us a lot of practical information about the current status of the inspected structure. The target of the process is to detect damage status by processing data…

10.3221/IGF-ESIS.59.30Copy the DOI link

Details: Damage Detection in Structural Health Monitoring using Hybrid Convolution Neural Network and Recurrent Neural Network PDF Visual Abstract

PDF Visual Abstract

Fracture Views: 1,523 Downloads: 1,015 Vol. 17, No. 63 (2023) December 21, 2022 pp. 234-245

Computer Vision Algorithm for the detection of fracture cracks in Oil Hardening Non-Shrinking (OHNS) die steel after machining process

Akshansh Mishra, Vijaykumar S Jatti, Nitin K Khedkar, Rahul B. Dhabale, Ashwini V Jatti

A variant of neural network for processing with images is a convolutional neural network (CNN). This type of neural network receives input from an image and extracts features from the image while also providing learnable parameters to…

10.3221/IGF-ESIS.63.18Copy the DOI link

Details: Computer Vision Algorithm for the detection of fracture cracks in Oil Hardening Non-Shrinking (OHNS) die steel after machining process PDF Visual Abstract

PDF Visual Abstract

SI: Steels and Composites for Engineering Structures Views: 734 Downloads: 500 Vol. 15, No. 58 (2021) September 25, 2021 pp. 442-452

Sensitivity analysis of the GTN damage parameters at different temperature for dynamic fracture propagation in X70 pipeline steel using neural network

Abdelmoumin Ouladbrahim, Idir Belaidi, Samir Khatir, Erica Magagnini, Roberto Capozucca, Magd Abdel Wahab

In this paper, the initial and maximum load was studied using the Finite Element Modeling (FEM) analysis during impact testing (CVN) of pipeline X70 steel. The Gurson-Tvergaard-Needleman (GTN) constitutive model has been used to simulate…

10.3221/IGF-ESIS.58.32Copy the DOI link

Details: Sensitivity analysis of the GTN damage parameters at different temperature for dynamic fracture propagation in X70 pipeline steel using neural network PDF Visual Abstract

PDF Visual Abstract

Structural Integrity and Safety: Experimental and Numerical Perspectives Views: 1,881 Downloads: 1,043 Vol. 17, No. 63 (2023) December 21, 2022 pp. 37-45

Artificial neural network based delamination prediction in composite plates using vibration signals

T. G. Sreekanth, M. Senthilkumar, S. Manikanta Reddy

Dynamic loading on composite components may induce damages such as cracks, delaminations, etc. and development of an early damage detection technique for delaminations is one of the most important aspects in ensuring the integrity and…

10.3221/IGF-ESIS.63.04Copy the DOI link

Details: Artificial neural network based delamination prediction in composite plates using vibration signals PDF Visual Abstract

PDF Visual Abstract

Failure Analysis and Forensic Engineering Views: 563 Downloads: 289 Vol. 20, No. 76 (2026) January 6, 2026 pp. 49-66

Hybrid feedforward neural network for pressure vessel internal corrosion prediction: integrating chemical models with inspection data for structural integrity assessment

Mina Pascal

This study presents a hybrid framework integrating a physics-based corrosion model with a feedforward neural network (FNN) to predict corrosion rates and estimate the remaining useful life (RUL) of industrial pressure vessels for…

10.3221/IGF-ESIS.76.04Copy the DOI link

Details: Hybrid feedforward neural network for pressure vessel internal corrosion prediction: integrating chemical models with inspection data for structural integrity assessment Graphical Abstract PDF HTML

+2Other formats

Visual Abstract Podcast

Graphical Abstract PDF HTML Visual Abstract Podcast

Miscellanea Views: 971 Downloads: 519 Vol. 9, No. 34 (2015) September 29, 2015

Defect detection of wire rope for oil well based on adaptive angle

Zhang Jijun, Meng Xiangqing

This paper uses a digital image processing method which is based on texture feature of steel cable to detect the fracture of steel wire. At first, it uses a modified homomorphic filtering method to eliminate environment heterogeneous…

10.3221/IGF-ESIS.34.65Copy the DOI link

Details: Defect detection of wire rope for oil well based on adaptive angle PDF

PDF

Analytical, computational and physical models Views: 732 Downloads: 575 Vol. 18, No. 70 (2024) August 2, 2024 pp. 71-90

Modeling turning performance of Inconel 718 with hybrid nanofluid under MQL using ANN and ANFIS

Paresh Kulkarni, Satish Chinchanikar

Soft computing techniques, with their self-learning capabilities, fuzzy principles, and evolutionary computational philosophy, are being increasingly utilized in modeling complex machining processes. This study develops artificial neural…

10.3221/IGF-ESIS.70.04Copy the DOI link

Details: Modeling turning performance of Inconel 718 with hybrid nanofluid under MQL using ANN and ANFIS PDF Visual Abstract

PDF Visual Abstract

Analytical, Numerical and Physical Models Views: 959 Downloads: 740 Vol. 17, No. 66 (2023) September 27, 2023 pp. 191-206

Prediction of Mechanical Behavior of Epoxy Polymer Using Artificial Neural Networks (ANN) And response Surface Methodology (RSM)

Khalissa Saada, Salah Amroune, Moussa Zaoui

The aim of this study is to analyze the effect of different geometries and sections on the mechanical properties of epoxy specimens. Five tensile tests were carried out on three types of series. The experimental results obtained were…

10.3221/IGF-ESIS.66.12Copy the DOI link

Details: Prediction of Mechanical Behavior of Epoxy Polymer Using Artificial Neural Networks (ANN) And response Surface Methodology (RSM) PDF Visual Abstract

PDF Visual Abstract

SI: Fracture Mechanics versus Environment Views: 884 Downloads: 456 Vol. 13, No. 49 (2019) June 9, 2019 pp. 291-301

Detection and diagnosis of fault bearing using wavelet packet transform and neural network

Said DJABALLAH, Kamel Meftah, Khaled Khelil, Mohsein Tedjini, Lakhdar Sedira

Bearings, considered crucial components in rotating machinery, are widely used in the industry. Bearing status monitoring has become an essential step in the deployment of preventive maintenance policy. This work is part of the diagnosis…

10.3221/IGF-ESIS.49.29Copy the DOI link

Details: Detection and diagnosis of fault bearing using wavelet packet transform and neural network PDF Visual Abstract

PDF Visual Abstract

SI: Modeling in Structural Integrity Views: 664 Downloads: 378 Vol. 19, No. 73 (2025) May 7, 2025 pp. 74-87

Predictive modeling of PMMA-based polymer composites reinforced with hydroxyapatite: a machine learning and FEM approach

Rohit Kumar Singh, Khyati Verma, G. C. Mohan Kumar

This research examines the mechanical characteristics of polymer composites (PMMA) that are reinforced with Hydroxyapatite (HAp), with a particular emphasis on the Elastic Modulus and Compressive Strength. The investigation employs a…

10.3221/IGF-ESIS.73.06Copy the DOI link

Details: Predictive modeling of PMMA-based polymer composites reinforced with hydroxyapatite: a machine learning and FEM approach PDF HTML Visual Abstract

+1Other formats

Podcast

PDF HTML Visual Abstract Podcast

SI: Russian mechanics contributions for Structural Integrity Views: 1,315 Downloads: 900 Vol. 17, No. 63 (2023) December 21, 2022 pp. 110-121

A method and apparatus for inspecting large flat composite parts by using the Infrared LST technique

Vladimir Vavilov, Arsenii Chulkov, Denis Nesteruk, Douglas Burleigh, Alexey Moskovchenko

The principle of Line Scan Thermography (LST) was used to develop a self-propelled infrared thermographic nondestructive testing device for the inspection of large, relatively flat composite aerospace parts, such as aircraft wings. The…

10.3221/IGF-ESIS.63.11Copy the DOI link

Details: A method and apparatus for inspecting large flat composite parts by using the Infrared LST technique PDF Visual Abstract

PDF Visual Abstract

SI: Steels and Composites for Engineering Structures Views: 874 Downloads: 571 Vol. 15, No. 58 (2021) September 25, 2021 pp. 308-318

Evaluating structural safety of trusses using Machine Learning

Tran-Hieu Nguyen, Anh-Tuan Vu

In this paper, a machine learning-based framework is developed to quickly evaluate the structural safety of trusses. Three numerical examples of a 10-bar truss, a 25-bar truss, and a 47-bar truss are used to illustrate the proposed…

10.3221/IGF-ESIS.58.23Copy the DOI link

Details: Evaluating structural safety of trusses using Machine Learning PDF Visual Abstract

PDF Visual Abstract

Miscellanea Views: 969 Downloads: 877 Vol. 17, No. 65 (2023) June 22, 2023 pp. 300-319

Damage assessment in beam-like structures by correlation of spectrum using machine learning

Toan Pham Bao, Vien Le-Ngoc, Luan Vuong Cong, Nhi Ngo Kieu

Damage assessment in the actual operating process of the structure is a modern and exciting problem of construction engineering due to several practical knowledge about the current condition of the inspected structures. However, the…

10.3221/IGF-ESIS.65.20Copy the DOI link

Details: Damage assessment in beam-like structures by correlation of spectrum using machine learning PDF Visual Abstract

PDF Visual Abstract

Miscellanea Views: 1,002 Downloads: 632 Vol. 12, No. 45 (2018) June 21, 2018 pp. 147-155

Eddy current modelling using multi-layer perceptron neural networks for detecting surface cracks

Salaheddine Harzallah, R. Rebhi, M. Chabaat, A. Rabehi

A new method for computing fracture mechanics parameters using computational Eddy Current Modelling by Multi-layer Perceptron Neural Networks for detecting surface cracks. The method is based upon an inverse problem using an Artificial…

10.3221/IGF-ESIS.45.12Copy the DOI link

Details: Eddy current modelling using multi-layer perceptron neural networks for detecting surface cracks PDF Visual Abstract

PDF Visual Abstract

Integrity of materials and structures Views: 565 Downloads: 362 Vol. 19, No. 72 (2025) February 8, 2025 pp. 121-136

A digital twin framework with MobileNetV2 for damage detection in slab structures

Huong Duong Nguyen, Huan Nguyen, Xiaohong Gao

In this study, a digital twin framework is proposed for damage detection in a civil structure, which consists of a finite element model, neural networks, model updating methods, and signal processing. To verify the proposed framework, we…

10.3221/IGF-ESIS.72.09Copy the DOI link

Details: A digital twin framework with MobileNetV2 for damage detection in slab structures PDF HTML Visual Abstract

PDF HTML Visual Abstract

Failure Analysis and Forensic Engineering Views: 500 Downloads: 387 Vol. 18, No. 70 (2024) September 5, 2024 pp. 242-256

Tool wear evaluation of self-propelled rotary tool and conventional round tool during turning Inconel 718

Satish Chinchanikar, Nitin Motgi

Enhancing the machinability of difficult-to-cut materials is imperative, and a non-conventional rotary tool has shown high potential when machining these materials. This work comparatively evaluates the tool wear of conventional round…

10.3221/IGF-ESIS.70.14Copy the DOI link

Details: Tool wear evaluation of self-propelled rotary tool and conventional round tool during turning Inconel 718 PDF Visual Abstract

PDF Visual Abstract

Structural Integrity and Durability of Structures Views: 1,836 Downloads: 722 Vol. 17, No. 65 (2023) June 22, 2023 pp. 112-134

Crack simulation for the cover of the landfill – A seismic design

Abdoullah Namdar, Mehran Karimpour-Fard, Omer Mughieda, Filippo Berto, Nurmunira Muhammad

The stability of the landfill is an environmental issue. The collapse of the landfill causes environmental pollution and influences human life. In the present study, the crack on the cover of the landfill was simulated. Rankine’s theory…

10.3221/IGF-ESIS.65.09Copy the DOI link

Details: Crack simulation for the cover of the landfill – A seismic design PDF Visual Abstract

PDF Visual Abstract

Structural Integrity and Durability of Structures Views: 880 Downloads: 717 Vol. 17, No. 65 (2023) June 22, 2023 pp. 160-177

Structural Health Evaluation of Arch Bridge by Field Test and Optimized BPNN Algorithm

Zhihua Xiong, Jiachen She, Zhuoxi Liang, Xulin Mou, Yu Zhang

Arch bridges play an important role in rural roads in China. Due to insufficient funds and a lack of management techniques, many rural arch bridges are in a state of disrepair, unable to meet the increasing transportation needs. Thus, it…

10.3221/IGF-ESIS.65.11Copy the DOI link

Details: Structural Health Evaluation of Arch Bridge by Field Test and Optimized BPNN Algorithm PDF Visual Abstract

PDF Visual Abstract

Structural Integrity and Durability of Structures Views: 996 Downloads: 0 Vol. 13, No. 50 (2019) August 30, 2019 pp. 149-162

Experimental and numerical investigation of the properties of the Hot Mix Asphalt Concrete with basalt and glass fiber

Mahmoud Ameri, Mehdi Nemati, Hamid Shaker, Faezeh jafari

Abstract. In the recent decades, different kinds of fiber materials are used for improving the asphalt mixture performance. Meanwhile, different kinds of fiber are used excessively due to their desirable physical and chemical properties…

10.3221/IGF-ESIS.50.14Copy the DOI link

Details: Experimental and numerical investigation of the properties of the Hot Mix Asphalt Concrete with basalt and glass fiber PDF Visual Abstract

PDF Visual Abstract

Fatigue and Fracture of metallic alloys Views: 955 Downloads: 751 Vol. 18, No. 68 (2024) March 10, 2024 pp. 340-356

Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process

Mohsen Sarparast, Majid Shafaie, Mohammad Davoodi, Ahmad Memaran Babakan, Hongyan Zhang

This study focuses on ductile fracture behavior prediction for Ti6Al4V alloys fabricated via Selective Laser Melting (SLM). A modified Gurson-Tvergaard-Needleman (GTN) model characterizes void growth and shear mechanisms under uniaxial…

10.3221/IGF-ESIS.68.23Copy the DOI link

Details: Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process PDF Visual Abstract

PDF Visual Abstract

Integrity of materials and structures Views: 453 Downloads: 609 Vol. 18, No. 70 (2024) July 16, 2024 pp. 55-70

Correlation coefficients of vibration signals and machine learning algorithm for structural damage assessment in beams under moving load

Toan Pham Bao, Vien Le-Ngoc

This paper presents a novel method of assessing structural damage in beams exposed to moving loads via acceleration signals through experimental studies. In this study, beams are supported on both ends, and their dynamic response to moving…

10.3221/IGF-ESIS.70.03Copy the DOI link

Details: Correlation coefficients of vibration signals and machine learning algorithm for structural damage assessment in beams under moving load PDF Visual Abstract

PDF Visual Abstract

Advanced Manufacturing and Processing Views: 758 Downloads: 779 Vol. 18, No. 67 (2024) December 17, 2023 pp. 176-191

Investigations on tool wear behavior in turning AISI 304 stainless steel: An empirical and neural network modeling approach

Satish Chinchanikar, Mahendra Gadge

Machining with a cutting edge with extensive damage or a fractured cutting edge significantly influences the machining performance. Therefore, investigations on tool wear behavior, their forms, and wear mechanisms will be very helpful in…

10.3221/IGF-ESIS.67.13Copy the DOI link

Details: Investigations on tool wear behavior in turning AISI 304 stainless steel: An empirical and neural network modeling approach PDF Visual Abstract

PDF Visual Abstract

SI: Russian mechanics contributions for Structural Integrity Views: 833 Downloads: 527 Vol. 18, No. 70 (2024) August 14, 2024 pp. 121-132

Application of deep learning for technological parameter optimization of laser shock peening of Ti-6Al-4V alloy

Mikhail Verezhak, Aleksei Vshivkov, Elena Gachegova, Maria Bartolomei, Alexander Mayer, Sathya Swaroop

The paper is devoted to the development of the method of laser shock peening (LSP) of metals. To optimize the mode of LSP for Ti-6Al-4V specimens a deep learning model for predicting residual stresses by laser shock peening was developed.…

10.3221/IGF-ESIS.70.07Copy the DOI link

Details: Application of deep learning for technological parameter optimization of laser shock peening of Ti-6Al-4V alloy PDF Visual Abstract

PDF Visual Abstract

Fatigue Views: 777 Downloads: 603 Vol. 16, No. 62 (2022) September 22, 2022 pp. 505-515

Deep Learning algorithm for the assessment of the first damage initiation monitoring the energy release of materials

Dario Milone, Dario Santonocito

Monitoring the energy release during fatigue tests of common engineering materials has been shown to give relevant information on fatigue properties, reducing the testing time and material consumption. During a static tensile test, it is…

10.3221/IGF-ESIS.62.34Copy the DOI link

Details: Deep Learning algorithm for the assessment of the first damage initiation monitoring the energy release of materials PDF Visual Abstract

PDF Visual Abstract

Reliability and Life Extension of Components Views: 1,168 Downloads: 642 Vol. 15, No. 57 (2021) June 22, 2021 pp. 138-159

Reliability and Reliability-based Sensitivity Analyses of Steel Moment-Resisting Frame Structure subjected to Extreme Actions

Abbasali Sadeghi, Hamid Kazemi, Maysam Samadi

The ground external columns of buildings are vulnerable to the extreme actions such as a vehicle collision. This event is a common scenario of buildings' damages. In this study, a nonlinear model of 2-story steel moment-resisting frame (…

10.3221/IGF-ESIS.57.12Copy the DOI link

Details: Reliability and Reliability-based Sensitivity Analyses of Steel Moment-Resisting Frame Structure subjected to Extreme Actions PDF Visual Abstract

PDF Visual Abstract

Structural Integrity and Safety: Experimental and Numerical Perspectives Views: 852 Downloads: 715 Vol. 16, No. 61 (2022) June 19, 2022 pp. 487-495

Natural Frequency based delamination estimation in GFRP beams using RSM and ANN

T. G. Sreekanth

The importance of delamination detection can be understood from aircraft components like Vertical Stabilizer, which is subjected to heavy vibration during the flight movement and it may lead to delamination and finally even flight crash…

10.3221/IGF-ESIS.61.32Copy the DOI link

Details: Natural Frequency based delamination estimation in GFRP beams using RSM and ANN PDF Visual Abstract

PDF Visual Abstract

SI: Russian mechanics contributions for Structural Integrity Views: 628 Downloads: 508 Vol. 19, No. 72 (2025) January 7, 2025 pp. 26-33

Numerical study of residual stress fields after double-sided symmetric laser shock peening of blade edge

Mariia L. Bartolomei, Igor S. Kudryashev, Rustam R. Sabirov, Alexander M. Korsunsky

This paper deals with numerical modelling of the residual stress field formed after laser shock peening of a thin blade edge from TC4. It is shown that the application of double-sided symmetric laser shock peening is an effective way of…

10.3221/IGF-ESIS.72.03Copy the DOI link

Details: Numerical study of residual stress fields after double-sided symmetric laser shock peening of blade edge PDF HTML Visual Abstract

PDF HTML Visual Abstract

Advanced Manufacturing and Processing Views: 518 Downloads: 456 Vol. 14, No. 53 (2020) July 19, 2020 pp. 325-336

A new approach of CMT seam welding deformation forecasting based on GA-BPNN

Yao Lu, Yanfeng Xing, Xuexing Li, Sha Xu

Welding deformation affects the quality of the welded parts. In this paper, by introducing improved back propagation neural network (BPNN), a cold metal transfer (CMT) welding deformation prediction model for aluminum-steel hybrid sheets…

10.3221/IGF-ESIS.53.25Copy the DOI link

Details: A new approach of CMT seam welding deformation forecasting based on GA-BPNN PDF Visual Abstract

PDF Visual Abstract