Article
Construction & Building Technology
Hui Wei, Hu Zhang, Jue Li, Jianlong Zheng, Juanjuan Ren
Summary: Uniaxial compression tests were conducted on asphalt mixtures with six loading rates to investigate their failure characteristics and modes. Acoustic emission (AE) technology was used to monitor the entire failure process, and typical AE characteristic parameters were analyzed. The results showed that the failure load and compressive strength of the asphalt mixtures increased significantly with the loading rate. Correlation analysis revealed favorable correlation and regularity in the amplitude-hits and amplitude-energy for loading rates of 0.2-5 mm/min, but no regularity for a loading rate of 0.05 mm/min. The dominant frequency of the AE signals ranged from 50-350 kHz, and the failure mode could be identified based on the difference in AE parameters and dominant frequency distribution.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Automation & Control Systems
Wuzhen Huang, Yuan Li, Xian Wu, Jianyun Shen
Summary: This paper focuses on the detection of electroplated diamond mill-grinding tools by using the acoustic emission sensor. The wear stages of the tools are divided into three parts and the methods of characteristic parameter and waveform analysis are used for analysis. The wear characteristics of the tool and workpiece in different wear stages are observed and analyzed.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Engineering, Multidisciplinary
Pawel Twardowski, Maciej Tabaszewski, Martyna Wiciak-Pikula, Agata Felusiak-Czyryca
Summary: The study focuses on monitoring tool wear based on acoustic emission signals, using machine learning methods to accurately predict tool condition class with an error value below 6% through the decision tree approach. It also compares the results with other machine learning methods.
PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY
(2021)
Article
Chemistry, Analytical
Khadijat A. Olorunlambe, Zhe Hua, Duncan E. T. Shepherd, Karl D. Dearn
Summary: Acoustic emission (AE) testing is effective in detecting mechanical flaws and assessing human joints and orthopaedic implants. This study uses supervised learning to classify AE signals, with the back propagation (BP) neural network achieving the highest classification accuracy of 98%. This represents an exciting development for using AE signals as a bio-tribological diagnostic tool.
Article
Polymer Science
Michal Sofer, Pavel Sofer, Marek Pagac, Anastasia Volodarskaja, Marek Babiuch, Filip Grun
Summary: The characterisation of failure mechanisms in CFRP materials using the AE technique has been the focus of many studies. However, obtaining comprehensive and reliable information about individual failure mechanisms is challenging. In this study, tensile and compact tension tests were performed on specimens with different stacking sequences to induce specific failure modes and mechanisms. AE activity was monitored using two different wideband AE sensors and analysed using a hybrid hit detection process. The clustering analysis of the datasets revealed distinct failure mechanisms, which were confirmed by SEM analysis. Evaluation: 8 points.
Article
Chemistry, Analytical
Juan Luis Ferrando Chacon, Telmo Fernandez de Barrena, Ander Garcia, Mikel Saez de Buruaga, Xabier Badiola, Javier Vicente
Summary: There is an increasing trend in the industry towards real-time monitoring of critical aspects like tool wear to reduce costs and scrap in machining processes. Machine learning models based on tool wear data are becoming popular as they simplify the development of physical models. While acoustic emission (AE) technique is widely used for real-time monitoring of industrial assets like cutting tools, the interpretation and processing of AE signals is complex.
Article
Automation & Control Systems
Samuel Soares Ferreira, Fred Lacerda Amorim, Janes Landre Junior, Luis Henrique Andrade Maia, Alisson Rocha Machado, Wisley Falco Sales
Summary: This study proposed a new technique for identifying electrode wear during electrical discharge machining (EDM) using acoustic emission (AE) signals. It demonstrated the differences in wear rate of electrolytic copper electrodes under different parameters and their correlation with AE signals. The results indicated that the new technique's signals effectively responded to electrode wear and were sensitive to the wear rate.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Construction & Building Technology
Soufyane Benaboud, Mokhfi Takarli, Bertrand Pouteau, Fatima Allou, Frederic Dubois, Pierre Hornych, Mai Lan Nguyen
Summary: This paper presents an experimental study on the damage behavior of asphalt concrete under bending fatigue loading, using acoustic emission measurements to investigate the damage and failure processes. The results show variations in acoustic emission activity at different fatigue stages.
ROAD MATERIALS AND PAVEMENT DESIGN
(2021)
Article
Engineering, Mechanical
P. R. Sreeraj, Jiju Elias, R. Manu, Jose Mathew
Summary: This study aims to predict tool wear by analyzing acoustic emission signals using FFT. Through spectral analysis, a correlation between acoustic signal amplitude and flank wear is established, enabling accurate prediction of flank wear progression in machining processes.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
(2021)
Article
Engineering, Electrical & Electronic
Zhiwen Huang, Jiajie Shao, Weicheng Guo, Weidong Li, Jianmin Zhu, Qichao He, Dianjun Fang
Summary: Tool wear condition monitoring is crucial in intelligent manufacturing systems. This study proposes a tool wear prediction method based on multi-information fusion and genetic algorithm optimized Gaussian process regression. Experimental results show that the proposed method can effectively lower prediction error and uncertainty of flank wear width in milling.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Materials Science, Multidisciplinary
Ziqi Zhang, Zhanqiang Liu, Xiaoping Ren, Jinfu Zhao
Summary: A new prediction method was proposed based on the positive feedback relationship between tool geometry and tool wear rate. Dry orthogonal cutting of Inconel 718 was used as a case study. The tool wear rate models and a tool wear prediction flowchart were established first. The evolution of tool geometry during tool wear was analyzed, considering the combined effect of tool crater wear and tool flank wear. The evolution of cutting temperature, normal stress, and tool-chip relative sliding velocity on the tool wear surface was studied, revealing the evolution of the tool wear rate during tool wear. Finally, the evolution of tool geometry and tool wear rate were applied to accurately predict the tool wear, with a prediction error of KT less than 15% compared to the experimental results. The tool wear prediction method in this paper is helpful to improve the prediction accuracy of tool crater wear.
Article
Engineering, Mechanical
P. Revill, A. Clarke, R. Pullin, G. Dennis
Summary: Self-lubricating composite bearing liners used in aerospace systems require periodic replacement, and research is focusing on developing smart bearings that can identify critical damage to improve asset availability and reduce maintenance costs. This study demonstrates the feasibility of monitoring wear processes using Acoustic Emission (AE) in a laboratory setting, and introduces a new method of analyzing AE signals for integration into a Structural Health Monitoring (SHM) system for asset management.
Article
Materials Science, Multidisciplinary
Andrey Filippov, Andrey Vorontsov, Nickolay Shamarin, Evgeny Moskvichev, Olga Novitskaya, Evgeny Knyazhev, Yuliya Denisova, Andrei Leonov, Vladimir Denisov, Sergei Tarasov
Summary: In this study, single-layer ZrN and CrN coatings, as well as multi-layer ZrN/CrN coatings were investigated under different operating conditions. Vibration accelerations and AE energy were found to be effective monitoring methods for coating wear, while median AE frequency was less informative. Multi-layer ZrN/CrN coatings exhibited higher wear resistance compared to single-layer ZrN and CrN coatings.
Article
Engineering, Mechanical
Mengyu Chai, Pan Liu, Yuhang He, Zelin Han, Quan Duan, Yan Song, Zaoxiao Zhang
Summary: This study proposes a general machine learning-based approach for fatigue crack growth rate (FCGR) prediction using multivariate acoustic emission (AE) online monitoring data. A backpropagation neural network optimized by genetic algorithm (GA-BPNN) is developed to improve the prediction accuracy. The GA-BPNN model exhibits higher accuracy and superior adaptability in predicting FCGR from unseen data compared to other methods.
FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES
(2023)
Article
Mechanics
Mengyang Zhai, Lei Xue, Hongran Chen, Chao Xu, Yuan Cui
Summary: The study found that the shear rate significantly affects the failure process and AE characteristics of layered rocks. Increasing shear rate leads to higher average released AE energy, while decreasing total AE number and b-values, indicating faster crack propagation and more high-energy AE events.
ENGINEERING FRACTURE MECHANICS
(2021)
Article
Chemistry, Applied
R. K. Sundaram, Senthil S. Kumaran, Edwin P. Samson
Summary: The purpose of this study is to reduce interfacial tension and evaluate the mechanical, thermal, and thermo-mechanical behavior of immiscible polymer blends by increasing adhesion between different phases. The study prepared polymer blend composites using a twin-screw extruder followed by injection molding and examined their behavior under various test conditions. The findings indicate that the inclusion of a compatibilizer and glass fiber reinforcement improved the mechanical properties and thermo-mechanical behavior of the polymer blends.
PIGMENT & RESIN TECHNOLOGY
(2023)
Review
Nanoscience & Nanotechnology
Utkarsh Chadha, Preetam Bhardwaj, Senthil Kumaran Selvaraj, Kaviya Arasu, S. Praveena, A. Pavan, Mayank Khanna, Prabhpreet Singh, Shalu Singh, Arghya Chakravorty, Badrish Badoni, Murali Banavoth, Prashant Sonar, Velmurugan Paramasivam
Summary: Nanotechnology can enhance the barrier and antimicrobial properties of food packaging, keeping food fresh. Silver nanoparticles and nanoclay are commonly used in the market, while zinc oxide and titanium dioxide have limited applications. These nanomaterials improve nutritional values, appearance, and shelf life of food products. However, the potential migration of nanomaterials, especially in acidic conditions, raises concerns for their harmful effects.
JOURNAL OF NANOMATERIALS
(2022)
Article
Chemistry, Physical
M. Natesh, Senthil Kumaran Selvaraj, N. Arivazhagan, M. Manikandan, Szymon Tofil, Norbert Radek, Yash Mistry, Muthu Sm
Summary: This study investigates the micro-segregation of elements in Incoloy 20 and explores the possibility of reducing it through argon arc welding with Ni and Mo-rich filler wire. Crack-free welds with different structures are achieved using continuous current argon arc welding (CCAAW) and pulsed current argon arc welding (PCAAW). Results show that PCAAW effectively suppresses elemental segregation, enhances toughness and hardness, and leads to higher tensile strength and smaller grain sizes compared to CCAAW.
Review
Engineering, Manufacturing
Aditya Raj, Utkarsh Chadha, Arisha Chadha, R. Rishikesh Mahadevan, Buddhi Rohan Sai, Devanshi Chaudhary, Senthil Kumaran Selvaraj, R. Lokeshkumar, Sreethul Das, B. Karthikeyan, R. Nagalakshmi, Vishjit Chandramohan, Haitham Hadidi
Summary: Welding Engineering is a crucial part of manufacturing engineering that involves joining different materials through various processes. Machine learning implementation is the most suitable solution for weld quality assessment due to the complexities in welding engineering. The use of image processing concepts and sensors, along with real-time monitoring supported by ML models, helps in detecting issues within the weld, such as internal fatigues, cracks, or flaws. This review comprehensively presents the ML models and sensors used for weld quality monitoring and assessment.
INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM
(2023)
Review
Engineering, Manufacturing
Hardik Sachin Totla, Aman Gupta, Swapnil Mishra, Sarthak Sharma, Senthil Kumaran Selvaraj
Summary: This paper provides a comprehensive overview of resistance welding in the aerospace industry for joining composite structures. Thermoplastic composites have become a crucial material in this industry due to its advantages over thermoset composites. Resistance welding of thermoplastics is a fast and precise process that offers an advantageous alternative to mechanical fasteners and adhesive joints. The ability to control multiple welding parameters optimizes the process, and various welding geometries can be achieved. Defects and challenges in the resistance welding process are discussed, and surface treatments and additives are used for weld strengthening. Further research is needed for detailed analysis in different aspects, such as fatigue analysis of the weld joint for critical aircraft structures.
INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM
(2023)
Review
Mathematics, Interdisciplinary Applications
Utkarsh Chadha, Senthil Kumaran Selvaraj, Abel Saji Abraham, Mayank Khanna, Anirudh Mishra, Isha Sachdeva, Swati Kashyap, S. Jithin Dev, R. Srii Swatish, Ayushma Joshi, Simar Kaur Anand, Addisalem Adefris, R. Lokesh Kumar, Jayakumar Kaliappan, S. Dhanalakshmi
Summary: Powder bed fusion (PBF) is a metal printing process that can be used to build complex parts using various metallic materials. Machine learning algorithms are used to optimize cost-effectiveness. The review discusses the applications of neural networks and special-purpose algorithms, as well as the challenges and prospects of PBF technology.
Article
Engineering, Environmental
Sivakumar Subpiramaniyam, Sung-Chul Hong, Pyong-In Yi, Seong-Ho Jang, Jeong-Min Suh, Eun-Sang Jung, Je-Sung Park, Velmurugan Palanivel, Young-Chae Song, Lae-Hyeon Cho, Young-Hoon Park, Ji-Suk Kim
Summary: Phytoremediation of metals from water and nutrient media exposed to waste metal cutting fluid was tested using Azolla imbricata. Results showed that biomass was higher in nutrient media than in water media without waste metal cutting fluid. However, growth failed when exposed to high concentrations of waste metal cutting fluid. Correlation analysis revealed that biomass was positively affected by temperature and negatively affected by humidity and metal accumulation. The average accumulations of Al, Cd, Cr, Fe, Pb, and Zn were observed and the bioconcentration factor indicated Azolla imbricata acts as a hyperaccumulator of Zn and as an accumulator or excluder of other metals. Overall, the phytoremediation performance of Azolla imbricata in multi-metal-contaminated waste metal cutting fluid was high in water media under all environmental conditions. The use of water media was determined to be an economically feasible approach for the removal of metals from waste metal cutting fluid.
JOURNAL OF HAZARDOUS MATERIALS
(2023)
Review
Engineering, Manufacturing
Preet Ashok Shah, M. K. Srinath, R. Gayathri, P. Puvandran, Senthil Kumaran Selvaraj
Summary: The world is currently undergoing a shift in manufacturing processes, with Industry 4.0 playing a significant role in bridging the gap between technology and manufacturing. Digital manufacturing, using advanced techniques such as machine learning, the Internet of Things, and artificial intelligence, has the potential to enhance productivity and overcome limitations of conventional welding techniques.
INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM
(2023)
Article
Engineering, Manufacturing
P. Sujitha Magdalene, Philip Raj, Gohula Priya, B. Karthikeyan, Senthil Kumaran Selvaraj, Marc Azab
Summary: This paper discusses the experimental investigations of ultra-high-strength mortar mixtures made with different combinations of fine aggregates, metallic and non-metallic fibers, and cured at different temperatures. Various materials were used as partial replacements for river sand, and the compressive strength of the mixtures was tested under different curing regimes. The results showed that certain mixtures achieved high strengths, and a predictive model was developed to validate the experimental results.
INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM
(2023)
Review
Engineering, Manufacturing
S. Ram Kishore, A. P. Sridharan, Utkarsh Chadha, Deva Narayanan, Mayank Mishra, Senthil Kumaran Selvaraj, Albert E. Patterson
Summary: Due to their renewable and sustainable nature, natural fibres are being increasingly used as reinforcement in polymer matrix composites. This study reviews and lists the existing studies conducted in 3D and 4D printing, their techniques, and materials. The proposal suggests the use of 4D printed bio mulch films with customized shape memory properties as a sustainable alternative to conventional mulching practices. The study also discusses suitable bio-composites for 4D printing, as well as their mechanical and microstructural properties, shape-memory behavior, and printing techniques.
PROGRESS IN ADDITIVE MANUFACTURING
(2023)
Review
Nanoscience & Nanotechnology
Ayan Roy, Dikshita Kabra, Garima Pareek, Kanak Kumari, Pandali Pratyush Kashyap, Samriddhi Naik, Utkarsh Chadha, Senthil Kumaran Selvaraj
Summary: The rapidly growing global economies drive the increasing demand for oil and gas, making the oil and gas sector one of the most important industries. While renewable energy technologies are a more sustainable option, their accessibility needs to be improved through technological advancements. Therefore, due to the limitations of renewable energy technologies, oil and gas remain a more viable alternative. Extensive research is being conducted on the applications of nanotechnology to enhance efficiency and environmental friendliness in the oil and gas sector, particularly in areas such as exploration, separation techniques, refining, and transportation. This review highlights the need for nanomaterials in the oil and gas industry and summarizes novel nanomaterials developed for various activities, along with a brief description of their synthesis mechanisms. Current challenges and future prospects in this field are also emphasized.
Article
Materials Science, Multidisciplinary
Nevan Nicholas Johnson, Vaishnav Madhavadas, Brajesh Asati, Anoj Giri, Shinde Ajit Hanumant, Nikhil Shajan, Kanwer Singh Arora, Senthil Kumaran Selvaraj
Summary: This study focuses on the effects of three critical welding parameters, welding current, welding time, and electrode force, on the weld quality of 1.40-mm-thick DP780 steel sheets. The research findings indicate that welding current has the most significant impact on the weld quality, followed by electrode force and welding time.
JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE
(2023)
Article
Acoustics
Moorthy Muruganandham, Kanagasabapathy Sivasubramanian, Palanivel Velmurugan, Subbaiah Suresh Kumar, Natarajan Arumugam, Abdulrahman I. Almansour, Raju Suresh Kumar, Sivakumar Manickam, Cheng Heng Pang, Subpiramaniyam Sivakumar
Summary: This study focuses on the extraction and optimization of yellow dye from Cassia alata flower petals, as well as its application in dyeing cotton, silk, and leather without a mordant. Additionally, the antibacterial activity of the extracted dye was evaluated.
ULTRASONICS SONOCHEMISTRY
(2023)
Article
Materials Science, Multidisciplinary
Moorthy Muruganandham, Fatimah Oleyan Al-Otibi, Raedah Ibrahim Alharbi, Kanagasabapathy Sivasubramanian, Anon Chaulagain, Palanivel Velmurugan, Nagaraj Basavegowda
Summary: The present study involved the green synthesis of silver nanoparticles (AgNPs) using Tabebuia rosea seeds as a reducing agent. The synthesized AgNPs exhibited potential antibacterial, antioxidant, and cytotoxicity effects. The findings suggest that utilizing T. rosea seeds to produce AgNPs holds promise for their potential application as nano drugs.
MATERIALS RESEARCH EXPRESS
(2023)
Article
Construction & Building Technology
P. Sujitha Magdalene, B. Karthikeyan, Senthil Kumaran Selvaraj, S. Deepika, Yousef Alqaryouti, Hany M. Seif ElDin, Marc Azab
Summary: This research discusses the behavior of ultra-high-performance concrete specimens made with dumped waste iron ore tailing as a fine aggregate in the mix. The experimental investigations confirmed that the mix with 1% steel fiber, 1.5% glass fiber, and 30% IOT exhibited improved tensile and impact strength compared to standard conventional concrete.
CASE STUDIES IN CONSTRUCTION MATERIALS
(2023)
