Article
Mechanics
Noureddine Fahem, Idir Belaidi, Abdelmoumin Oulad Brahim, Mohammad Noori, Samir Khatir, Magd Abdel Wahab
Summary: This work presents experimental and numerical studies on the effect of porosity on the mechanical properties of Glass Fiber Reinforced Polymer (GFRP). The study found that increasing the size of air bubbles significantly reduces the load in both tensile and bending cases. Additionally, an Artificial Neural Network-Enhanced Jaya Algorithm (ANN-E JAYA) is used to predict the reduction of tensile load, and compared with other methods, showing slightly higher accuracy for ANN-E JAYA.
COMPOSITE STRUCTURES
(2023)
Article
Computer Science, Artificial Intelligence
K. Aditya Shastry, H. A. Sanjay
Summary: Crop yield prediction is crucial in agriculture, but many developing countries still rely on manual methods which are inefficient and error-prone. To address this issue, a hybrid prediction strategy is proposed, incorporating weighted principal component analysis and artificial neural network to enhance the accuracy of crop yield prediction.
APPLIED SOFT COMPUTING
(2021)
Article
Energy & Fuels
Zhe Liu, Lei Zhang, Jiajing Li, Mina Mamluki
Summary: This paper introduces a newly improved Whale Optimization Algorithm based on quantum theory to optimize the Artificial Neural Network for ground response approximation in short buildings. The study uses data from the Chi-Chi earthquake in 1999 in Taiwan and demonstrates the higher reliability of the proposed method in calculating ground response and column horizontal deflection in short buildings under earthquake loading.
Article
Computer Science, Interdisciplinary Applications
Naser Arya Azar, Nazila Kardan, Sami Ghordoyee Milan
Summary: Evaporation is a key factor in the hydrological cycle and plays a critical role in various studies. This study uses artificial neural networks and hybrid algorithms to estimate daily evaporation from the Qaleh Chay Ajab Shir dam reservoir. The results demonstrate the effectiveness of the models in estimating evaporation.
ENGINEERING WITH COMPUTERS
(2023)
Article
Agricultural Engineering
Pradeep Kumar Gandam, Madhavi Latha Chinta, Priyadarshini Gandham, Ninian Prem Prashanth Pabbathi, Aditya Velidandi, Ashish A. Prabhu, Rama Raju Baadhe
Summary: This study presents a multi-stage approach combining statistical and machine learning optimization methods to identify and optimize the chemical pre-treatment parameters of corncobs. The results showed improved performance compared to traditional statistical methods.
INDUSTRIAL CROPS AND PRODUCTS
(2024)
Article
Engineering, Mechanical
Abdelmoumin Oulad Brahim, Idir Belaidi, Noureddine Fahem, Samir Khatir, Seyedali Mirjalili, Magd Abdel Wahab
Summary: This paper presents a robust technique to predict the peak load and crack initiation energy of dynamic brittle fracture in X70 steel pipes using an improved artificial neural network. The research investigates the behavior and mechanical properties of API X70 steel pipes under brittle fracture conditions and impact at low temperatures.
THEORETICAL AND APPLIED FRACTURE MECHANICS
(2022)
Article
Computer Science, Artificial Intelligence
Trong Nghia-Nguyen, Mamoru Kikumoto, H. Nguyen-Xuan, Samir Khatir, Magd Abdel Wahab, Thanh Cuong-Le
Summary: Soil compression parameters are crucial for ensuring the safety of civil engineering structures. Currently, evaluating these parameters through laboratory tests is time-consuming and labor-intensive, leading to increased construction costs. In this paper, machine learning models are employed to establish a reliable method for obtaining these parameters, using data from five different construction projects. Various models, including artificial neural network, deep neural network, and optimized deep neural network models, are compared, with the optimized models showing superior performance. Validations using data from a road project confirm the effectiveness and potential applications of the proposed methods.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Geosciences, Multidisciplinary
Rahul Ray, Deepak Kumar, Pijush Samui, Lal Bahadur Roy, A. T. C. Goh, Wengang Zhang
Summary: This research focuses on using three soft computing techniques to analyze the shallow foundation settlement based on reliability criteria. The study found that Minimax Probability Machine Regression model outperformed Particle Swarm Optimization based Artificial Neural Network and Particle Swarm Optimization based Adaptive Network Fuzzy Inference System, making it a reliable soft computing technique for nonlinear settlement problems in soil foundations.
GEOSCIENCE FRONTIERS
(2021)
Article
Chemistry, Analytical
Mariangela Quarto, Gianluca D'Urso, Claudio Giardini, Giancarlo Maccarini, Mattia Carminati
Summary: The integrated ANN-PSO methodology is more accurate in performance predictions, while the ANN-PSO model is faster and easier to apply but requires a large amount of historical data for training. On the other hand, the FEM is more complex to set up, requiring physical and thermal characteristics of materials and a significant amount of time for a single simulation.
Article
Mathematics, Applied
Madhusmita Chand, Rajat Tripathi
Summary: This research explores the application of machine learning techniques in understanding the generation of entropy in electro-MHD Casson nanofluid flow. The study shows the impact of various parameters on velocity, nanofluid temperature, fraction of nanoparticles, entropy generation, and Bejan number through graphs. Additionally, a machine learning technique using Particle Swarm Optimization (PSO) algorithm and an Artificial Neural Network (ANN) is employed to optimize entropy generation in this specific fluidic context. The study concludes that the flow with minimum electroosmotic effect and a specific velocity slip parameter achieves optimal entropy generation.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Chemistry, Multidisciplinary
Serge Balonji, Lagouge K. K. Tartibu, Imhade P. P. Okokpujie
Summary: In this study, artificial neural network (ANN) and adaptive network-based fuzzy inference system (ANFIS) approaches were used to predict and monitor the surface roughness of aluminum Al6061 machined blocks. The results showed that factors such as population size, acceleration values, choice of membership functions, and number of neurons and layers significantly influenced the prediction performance of the models.
APPLIED SCIENCES-BASEL
(2023)
Article
Materials Science, Multidisciplinary
Inas Bouzateur, Hamza Bennacer, Mohammed Assam Ouali, Mohamed Issam Ziane, Moufdi Hadjab, Mohamed Ladjal
Summary: This paper proposes a structure based on artificial neural networks and the particle swarm optimization algorithm to predict band gap energy. The structure solves the local minima issue of artificial neural networks and improves the fitting quality. The method can quickly identify novel chalcopyrite in photovoltaic solar cells with improved resolution.
MATERIALS TODAY COMMUNICATIONS
(2023)
Article
Thermodynamics
G. Trilok, P. S. Vishweshwara, N. Gnanasekaran
Summary: In this study, the heat flux at the boundary is estimated for conjugate heat transfer under forced convection in the presence of high porosity metal foams for the first time. Experimental setup and computational fluid dynamics are used to investigate the heat transfer characteristics of the metal foams. The results show that the heat flux can be accurately estimated using methods such as neural networks and particle swarm optimization.
THERMAL SCIENCE AND ENGINEERING PROGRESS
(2022)
Article
Energy & Fuels
Abdelhalim Fetimi, Attef Daas, Slimane Merouani, Abdullah M. Alswieleh, Mourad Hamachi, Oualid Hamdaoui, Ounissa Kebiche-Senhadji, Krishna Kumar Yadav, Byong-Hun Jeon, Yacine Benguerba
Summary: The combination of Box-Behnken design, artificial neural network, particle swarm optimization, and response surface methodology was utilized to predict emulsion breakdown in the ELM process, with the hybrid ANN-PSO model outperforming the RSM in identifying optimal ANN parameters and accurately forecasting emulsion breaking percentages. This hybrid approach may serve as a valuable optimization tool for predicting critical data for ELM stability under various operating conditions.
CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION
(2022)
Article
Computer Science, Artificial Intelligence
Susmitha Vekkot, Deepa Gupta
Summary: This paper proposes an integrated speech emotion conversion framework developed using speaker-independent mixed-lingual training. The framework utilizes non-parallel training and probabilistic linear discriminant analysis (PLDA) modelling to estimate emotion-dependent latent vectors for three archetypal emotions. The results show that the proposed framework achieves perceptually relevant expressive enrichment in neutral speech with optimal training data.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Mohammadreza Koopialipoor, Bhatawdekar Ramesh Murlidhar, Ahmadreza Hedayat, Danial Jahed Armaghani, Behrouz Gordan, Edy Tonnizam Mohamad
ENGINEERING WITH COMPUTERS
(2020)
Article
Engineering, Geological
Deepanshu Shirole, Gabriel Walton, Ahmadreza Hedayat
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
(2020)
Article
Engineering, Geological
Deepanshu Shirole, Ahmadreza Hedayat, Ehsan Ghazanfari, Gabriel Walton
ROCK MECHANICS AND ROCK ENGINEERING
(2020)
Article
Chemistry, Multidisciplinary
Amir Mahdiyar, Danial Jahed Armaghani, Mohammadreza Koopialipoor, Ahmadreza Hedayat, Arham Abdullah, Khairulzan Yahya
APPLIED SCIENCES-BASEL
(2020)
Article
Geosciences, Multidisciplinary
M. A. Pirzada, H. Roshan, H. Sun, J. Oh, M. S. Andersen, A. Hedayat, M. Bahaaddini
JOURNAL OF STRUCTURAL GEOLOGY
(2020)
Article
Computer Science, Interdisciplinary Applications
Alireza Rashiddel, Mehdi Kharghani, Daniel Dias, Mohsen Hajihassani
COMPUTERS AND GEOTECHNICS
(2020)
Article
Mechanics
Nan Zhang, Ahmadreza Hedayat, Shaoyang Han, Shuqi Ma, Hector Gelber Bolanos Sosa, Roberto Pedro Huamani Bernal, Nestor Tupa, Isaac Yanqui Morales, Reynaldo Sabino Canahua Loza
Summary: This study aimed to improve the mechanical and fracture properties of mine tailings-based geopolymer by using class F fly ash (FA) as an amorphous supplements source. The results showed that the addition of FA had an influence on the fracture behavior of the geopolymer, and this influence was related to the microscopic characteristics of the material.
ENGINEERING FRACTURE MECHANICS
(2022)
Article
Polymer Science
Yibran Perera-Mercado, Ahmadreza Hedayat, Lori Tunstall, Cara Clements, Julia Hylton, Linda Figueroa, Nan Zhang, Hector Gelber Bolanos Sosa, Nestor Tupa, Isaac Yanqui Morales, Reynaldo Sabino Canahua Loza
Summary: Beneficiation of industrial wastes, such as mine tailings (MTs), through development of alternative eco-friendly geopolymer binders for construction composites offers a twofold environmental benefit, as it reduces the demand for cement and it increases the sustainability of industrial processes by creating a value-added product from an industrial byproduct. The study found that the combination of Class C Fly Ash (FAc) with low-reactive gold MTs improved the physicochemical stability of the geopolymerized samples, resulting in a significant increase in compressive strength. The presence of FAc also improved the reactivity of the MTs, increasing the geopolymer production.
Article
Construction & Building Technology
Mohammadmahdi Abedi, Omid Hassanshahi, Alireza Rashiddel, Hamidreza Ashtari, Mohammed Seddik Meddah, Daniel Dias, M. A. Arjomand, Kok Keong Choong
Summary: Eco-friendly nature, low cost, life-cycle superiority, and lightweight are the key drivers for using natural fibers in cementitious-based composites. This study focuses on developing a sustainable cementitious composite reinforced with chemically-treated kenaf and coconut fibers. Experimental and finite element analyses were conducted to investigate the mechanical, microstructural, and durability properties of the composite. The results showed that adding 1.5% wt of kenaf fiber significantly enhanced the mechanical behavior and durability performance of the composite through microstructural enhancement. This study highlights the immense potential of natural fibers in developing sustainable and affordable cementitious composites for various infrastructure applications.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Chemistry, Multidisciplinary
Asma Ramesh, Alireza Rashiddel, Mohsen Hajihassani, Daniel Dias, Majid Kiani
Summary: This study investigated the performance of straight and oblique segmented structures of Tabriz Subway Line 2 under large deformations using advanced 3D numerical finite difference code and a plastic hardening constitutive model for the soil. Centrifuge tests were conducted to validate the fault-tunnel simulations for segmental tunnels. The results showed that segmental structures outperformed continuous structures under reverse faulting, and the lining with oblique joints exhibited better behavior against faulting than the lining with straight joints.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Civil
Alireza Rashiddel, Mohsen Hajihassani, Mehdi Kharghani, Hadi Valizadeh, Reza Rahmannejad, Daniel Dias
Summary: In this paper, the effects of segmental joints on the design of segmental tunnel linings were studied using two numerical methods. It was found that the flexibility and rotational stiffness of longitudinal joints have a significant impact on the soil-segment interaction effect.
GEOMECHANICS AND ENGINEERING
(2022)
Article
Engineering, Geological
Ahmadreza Hedayat, Pierpaolo Oreste, Giovanni Spagnoli
Summary: The properties of rock mass are influenced by excavation techniques and changes in stress levels caused by rock excavation. The impact of blasting is significant near tunnel periphery due to wave energy and stress redistribution, but damage severity decreases with radial distance. It is important to consider the damaged zone when analyzing stresses and deformations around a tunnel.
GEOMECHANICS AND GEOENGINEERING-AN INTERNATIONAL JOURNAL
(2021)
Proceedings Paper
Engineering, Civil
Sana Zafar, Ahmadreza Hedayat, Omid Moradian
GEOTECHNICAL EARTHQUAKE ENGINEERING AND SPECIAL TOPICS (GEO-CONGRESS 2020)
(2020)
Proceedings Paper
Construction & Building Technology
Ketan Arora, Marte Gutierrez, Ahmadreza Hedayat
ENGINEERING, MONITORING, AND MANAGEMENT OF GEOTECHNICAL INFRASTRUCTURE (GEO-CONGRESS 2020 )
(2020)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Amin Gheibi, Lucy Davis, Ahmadreza Hedayat
MODELING, GEOMATERIALS, AND SITE CHARACTERIZATION (GEO-CONGRESS 2020)
(2020)
Article
Engineering, Multidisciplinary
Sicheng Jiao, Shixiang Wang, Minge Gao, Min Xu
Summary: This paper presents a non-contact method of thickness measurement for thin-walled rotary shell parts based on a chromatic confocal sensor. The method involves using a flip method to obtain surface profiles from both sides of the workpiece, measuring the decentration and tilt errors of the workpiece using a centering system, establishing a unified reference coordinate system, reconstructing the external and internal surface profiles, and calculating the thickness. Experimental results show that the method can accurately measure the thickness of a sapphire spherical shell workpiece and is consistent with measurements of other materials.
Article
Engineering, Multidisciplinary
Rajeev Kumar, Sajal Agarwal, Sarika Pal, Alka Verma, Yogendra Kumar Prajapati
Summary: This study evaluated the performance of a CaF2-Ag-MXene-based surface plasmon resonance (SPR) sensor at different wavelengths. The results showed that the sensor achieved the maximum sensitivity at a wavelength of 532 nm, and higher sensitivities were obtained at shorter wavelengths at the expense of detection accuracy.
Article
Engineering, Multidisciplinary
Attilio Di Nisio, Gregorio Andria, Francesco Adamo, Daniel Lotano, Filippo Attivissimo
Summary: Capacitive sensing is a widely used technique for a variety of applications, including avionics. However, current industry standard Capacitive Level Sensors (CLSs) used in helicopters perform poorly in terms of sensitivity and dynamic characteristics. In this study, novel geometries were explored and three prototypes were built and tested. Experimental validation showed that the new design featuring a helicoidal slit along the external electrode of the cylindrical probe improved sensitivity, response time, and linearity.
Article
Engineering, Multidisciplinary
Kai Yang, Huiqin Wang, Ke Wang, Fengchen Chen
Summary: This paper proposes an effective measurement method for dynamic compaction construction based on time series model, which enables real-time monitoring and measurement of anomalies and important construction parameters through simulating motion state transformation and running time estimation.
Article
Engineering, Multidisciplinary
Hui Fu, Qinghua Song, Jixiang Gong, Liping Jiang, Zhanqiang Liu, Qiang Luan, Hongsheng Wang
Summary: An automatic detection and pixel-level quantification model based on joint Mask R-CNN and TransUNet is developed to accurately evaluate microcrack damage on the grinding surfaces of engineering ceramics. The model is effectively trained on actual micrograph image dataset using a joint training strategy. The proposed model achieves reliable automatic detection and fine segmentation of microcracks, and a skeleton-based quantification model is also proposed to provide comprehensive and precise measurements of microcrack size.
Review
Engineering, Multidisciplinary
Sang Yeob Kim, Da Yun Kwon, Arum Jang, Young K. Ju, Jong-Sub Lee, Seungkwan Hong
Summary: This paper reviews the categorization and applications of UAV sensors in forensic engineering, with a focus on geotechnical, structural, and water infrastructure fields. It discusses the advantages and disadvantages of sensors with different wavelengths and addresses the challenges of current UAV technology and recommendations for further research in forensic engineering.
Article
Engineering, Multidisciplinary
Anton Nunez-Seoane, Joaquin Martinez-Sanchez, Erik Rua, Pedro Arias
Summary: This article compares the use of Mobile Laser Scanners (MLS) and Aerial Laser Scanners (ALS) for digitizing the road environment and detecting road slopes. The study found that ALS data and its corresponding algorithm achieved better detection and delimitation results compared to MLS. Measuring the road from a terrestrial perspective negatively impacted the detection process, while an aerial perspective allowed for scanning of the entire slope structure.
Article
Engineering, Multidisciplinary
Nur Luqman Saleh, Aduwati Sali, Raja Syamsul Azmir Raja Abdullah, Sharifah M. Syed Ahmad, Jiun Terng Liew, Fazirulhisyam Hashim, Fairuz Abdullah, Nur Emileen Abdul Rashid
Summary: This study introduces an enhanced signal processing scheme for detecting mouth-click signals used by blind individuals. By utilizing additional band-pass filtering and other steps, the detection accuracy is improved. Experimental results using artificial signal data showed a 100% success rate in detecting obstacles. The emerging concepts in this research are expected to benefit radar and sonar system applications.
Article
Engineering, Multidisciplinary
Jiqiang Tang, Shengjie Qiu, Lu Zhang, Jinji Sun, Xinxiu Zhou
Summary: This paper studies the magnetic noise level of a compact high-performance magnetically shielded room (MSR) under different operational conditions and establishes a quantitative model for magnetic noise calculation. Verification experiments show the effectiveness of the proposed method.
Review
Engineering, Multidisciplinary
Krzysztof Bartnik, Marcin Koba, Mateusz Smietana
Summary: The demand for miniaturized sensors in the biomedical industry is increasing, and optical fiber sensors (OFSs) are gaining popularity due to their small size, flexibility, and biocompatibility. This study reviews various OFS designs tested in vivo and identifies future perspectives and challenges for OFS technology development from a user perspective.
Article
Engineering, Multidisciplinary
Yue Wang, Lei Zhou, Zihao Li, Jun Wang, Xuangou Wu, Xiangjun Wang, Lei Hu
Summary: This paper presents a 3-D reconstruction method for dynamic stereo vision of metal surface based on line structured light, overcoming the limitation of the measurement range of static stereo vision. The proposed method uses joint calibration and global optimization to accurately reconstruct the 3-D coordinates of the line structured light fringe, improving the reconstruction accuracy.
Article
Engineering, Multidisciplinary
Jaafar Alsalaet
Summary: Order tracking analysis is an effective tool for machinery fault diagnosis and operational modal analysis. This study presents a new formulation for the data equation of the second-generation Vold-Kalman filter, using separated cosine and sine kernels to minimize error and provide smoother envelopes. The proposed method achieves high accuracy even with small weighting factors.
Article
Engineering, Multidisciplinary
Tonglei Cao, Kechen Song, Likun Xu, Hu Feng, Yunhui Yan, Jingbo Guo
Summary: This study constructs a high-resolution dataset for surface defects in ceramic tiles and addresses the scale and quantity differences in defect distribution. An improved approach is proposed by introducing a content-aware feature recombination method and a dynamic attention mechanism. Experimental results demonstrate the superior accuracy and efficiency of the proposed method.
Article
Engineering, Multidisciplinary
Qinghong Fu, Yunxi Lou, Jianghui Deng, Xin Qiu, Xianhua Chen
Summary: Measurement and quantitative characterization of aging-induced gradient properties is crucial for accurate analysis and design of asphalt pavement. This research proposes the composite specimen method to obtain asphalt binders at different depths within the mixture and uses dynamic shear rheometer tests to measure aging-induced gradient properties and reveal internal mechanisms. G* master curves are constructed to investigate gradient aging effects in a wide range. The study finds that the composite specimen method can effectively restore the boundary conditions and that it is feasible to study gradient aging characteristics within the asphalt mixture. The study also observes variations in G* and delta values and the depth range of gradient aging effects for different aging levels.
Article
Engineering, Multidisciplinary
Min Li, Kai Wei, Tianhe Xu, Yali Shi, Dixing Wang
Summary: Due to the limitations of ground monitoring stations in China for the BDS, the accuracy of BDS Medium Earth Orbit (MEO) satellite orbits can be influenced. To overcome this, low Earth orbit (LEO) satellites can be used as additional monitoring stations. In this study, data from two LEO satellites were collected to improve the precise orbit determination of the BDS. By comparing the results with GPS and BDS-2/3 solutions, it was found that including the LEO satellites significantly improved the accuracy of GPS and BDS-2/3 orbits.