iosr-JMCE   Volume-20 ~ Issue-6 ~ Nov – Dec. 2023

Abstract: Machining processes play a crucial role in shaping, drilling, and contouring composite laminates for various product applications. Among these processes, drilling stands out as a fundamental method for attaching fasteners and assembling composite laminates. The inherent material anisotropy, arising from the fiber reinforcement, significantly impacts the machinability of these materials. Even though most....

Keywords: Glass fiber reinforced epoxy(GFRP); Thrust; Delamination; Design of experiments; ANOVA

[1]. ]P. Jagadeesh, M. Puttegowda, Y.G.T. Girijappa, S.M. Rangappa, M.K. Gupta, S. Siengchin, Mechanical, Electrical And Thermal Behaviour Of Additively Manufactured Thermoplastic Composites For High-Performance Applications, 2021, Https://Doi.Org/10.1007/978-981-16-3184-9_7.
[2]. Tatar, S. Milev, Durability Of Externally Bonded Fiber-Reinforced Polymer Composites In Concrete Structures: A Critical Review, Polymers (Basel) 13 (2021) 1–26, Https://Doi.Org/10.3390/Polym13050765.
[3]. [7]J. Praveenkumara, P. Madhu, T.G. Yashas Gowda, M.R. Sanjay, S. Siengchin, A Comprehensive Review On The Effect Of Synthetic Filler Materials On Fibre-Reinforced Hybrid Polymer Composites, J. Text. Inst. (2021) 1–9,
Https://Doi.Org/10.1080/00405000.2021.1920151.
[4]. M.Mehdikhani, L. Gorbatikh, I. Verpoest, S.V. Lomov, Voids In Fiber-Reinforced Polymer Composites: A Review On Their Formation, Characteristics, And Effects On Mechanical Performance, J. Compos. Mater. 53 (2019) 1579–1669,
Https://Doi.Org/10.1177/0021998318772152.
[5]. [9]P. Jagadeesh, Y.G. Thyavihalli Girijappa, M. Puttegowda, S.M. Rangappa, S. Siengchin, Effect Of Natural Filler Materials On Fiber Reinforced Hybrid Polymer Composites: An Overview, J. Nat. Fibers (2020) 1–16,
Https://Doi.Org/10.1080/15440478.2020.1854145.

Abstract: In recent times, soft clay has become a commonly encountered soil type, known for its limited strength and pronounced compressibility, presenting significant challenges in the construction of geotechnical structures. Therefore, enhancing its properties before construction is imperative to prevent issues like settlement, instability, or structural damage. This experimental study aims to explore the impact of eggshell powder (ESP) content and curing times on the compression behaviour of fly ash (FA) stabilized soft clay, as there is limited research on the synergy of these two......

Keywords: Compressibility, Curing Time, Eggshell Powder, Fly Ash, Soft Clays, Soil Stabilization, Yielding Stress

[1]. Ahmaruzzaman, M. (2010). A Review On The Utilization Of Fly Ash. Progress In Energy And Combustion Science, 36(3), 327–363. Https://Doi.Org/10.1016/J.Pecs.2009.11.003
[2]. Akhtar, M. N., & Akhtar, J. N. (2018). Suitability Of Class F Flyash For Construction Industry: An Indian Scenario. International Journal Of Structural And Construction Engineering, 12(9), 892–897.
[3]. Anoop, S. P., Hizana, B., Jwoleena, P. J., Midhula, J., Tharis Muhammed, T. N., & Prasanth, S. (2017). Potential Of Egg Shell Powder As Replacement Of Lime In Soil Stabilization. International Journal Of Advanced Engineering Research And Science, 4(8), 86–88. Https://Doi.Org/10.22161/Ijaers.4.8.15
[4]. Asokan, P., Saxena, M., & Asolekar, S. R. (2005). Coal Combustion Residues - Environmental Implications And Recycling Potentials. Resources, Conservation And Recycling, 43(3), 239–262. Https://Doi.Org/10.1016/J.Resconrec.2004.06.003
[5]. Benny, J. R., Jolly, J., Sebastian, M., & Students, M. T. (2017). IJERT-Effect Of Glass Powder On Engineering Properties Of Clayey Soil Effect Of Glass Powder On Engineering Properties Of Clayey Soil. IJERT Journal International Journal Of Engineering Research And Technology, 6(05), 228–231. Www.Ijert.Org.

Abstract: This study presents the comparative performance of hydrate pressure and temperature prediction model along crude oil transmission pipeline in Usan Oil Field, Rivers State, Nigeria.Computational fluid dynamic model was utilized to simulate the fluid parameter (pressure, temperature and flow-rate) along the pipeline in MATLAB domain. PIPESIM software was then utilized to compare the simulated results obtained. 9,875.52m, 0.228m/s, 289.51K and 68.95 bar were the input parameters for the pipeline length, fluid velocity, inlet temperature and inlet pressure, respectively, while the flow rate and fluid density were kept constant at 1000 STB/d and 828.5 kg/m³, respectively......

Keywords: PIPESIM, Model, Hydrate, Pressure, Temperature, Crude Oil Pipeline

[1] Bergman, T.L., Lavine, A.S., Incropera, F.P., & Dewitt, D.P. (2011).Fundamentals Of Heat And Mass Transfer (7th Edition), USA: John Wiley & Sons.
[2] Cao, J., Zhu, S., Li, C., & Han, B. (2020). Integrating Support Vector Regression With Genetic Algorithm For Hydrate Formation Condition Prediction. Processes, 8, 519-529.
[3] Davitashvili, T. (2021).On Liquid Phase Hydrates Formation In Pipelines In The Course Of Gas Non-Stationary Flow.E3S Web Of Conferences On Gas Hydrate Technologies: Global Trends, Challenges And Horizons, 230, 01006.
[4] Guimin, Y., Hao, J., &Qingwen, K. (2022). Study On Hydrate Risk In The Water Drainage Pipeline For Offshore Natural Gas Hydrate Pilot Production. Frontier In Earth Science, 9, 816873.
[5] Hashim, F.M., &Abbasi, A. (2016).Empirical Modelling Of Hydrate Formation Prediction In Deepwater Pipelines. ARPN Journal Of Engineering And Applied Sciences, 11(20), 12212-12216

Abstract: Background: The protection of the environment is the matter of utmost concern to achieve the sustainable development goals, if not dealt scientifically and logically would impact ecosystems within the boundary of urban area as well as outside it, with implications for the quality of life of people. The construction is one of the main source of environmental pollution. The construction activities affect the environment negatively throughout the life cycle of the constructed building, starting from period of construction period, period of its use to its demolition at the end of its service life. Although the period of construction of building is too less in comparison to its useful life, but the activities in short time impose significant impact on environment. There are no explicit comprehensive references by the law enforcing agencies at local, state and national level to the building planners, designers and contractors. It create huge challenges for urban local bodies for maintaining the environmental quality......

Key Word: Environmental Impact Assessment (EIA), Environmental Risk Assessment (ERA), Environmental Risk (ER), Severity of Impact, Weighted Score (WS).

[1] Akintoye, A.S. And Macleod, M.J. (1997) Risk Analysis And Management In Construction. International Journal Of Project Management, 15 (1997); 31-38. Https://Doi.Org/10.1016/S0263-7863(96)00035-X
[2] Alberto, D. M. And Muhammad, J. T. (2013), Risk Analysis In Construction Projects: A Practical Selection Methodology. American Journal Of Applied Sciences. 11(1); 74-84.
[3] Christini Gwen, Michael Fetsko & Chris Hendrickson (2004), Environmental Management Systems And ISO 14001 Certification For Construction Firms, Journal Of Construction Engineering And Management 130(3); 330-320. DOI:10.1061/(ASCE)0733-9364(2004)130:3(330)
[4] Dalya Ismael & Tripp Shealy (2018), Sustainable Construction Risk Perceptions In The Kuwaiti Construction Industry, Sustainability, 10(2018); 1 -17.
[5] Deulkar Ranjit M., Gajare Kunal T. & Misal S. A. (2017), Environmental Impact Assessment Study And Mitigation Measures For Building Construction Activities, International Journal Of Engineering Sciences & Research Technology, 6(10); 258 – 270.

Abstract: Deep excavation is one of the more critical issues, various procedures or processes are utilized to reduce the impact of deep excavation on neighbouring structures related with the choose of the retaining system. The main purpose of this research is to assess the diaphragm wall behaviour for deep excavation of the Heliopolis Cairo metro tunnelling station and choose the more acceptable numerical modelling for simulation the case study depends on the field inclinometer data. The performance of deep excavations is influenced by both stability and deformation. Two-dimensional (2D) and three-dimensional (3D) analysis in the PLAXIS geotechnical program is used to simulate the case study problem. In this study, the sand clay soil layers are simulated by u......

Key Word: : Deep excavation system, Simulation of diaphragm wall, Lateral deformation, Two-dimensional and three-dimensional numerical modeling, Hardening soil model, Mohr coulomb model, Plane strain ratio.

[1] Gue SS, Tan YC. Design and construction considerations for deep excavation. Lecture. IEM Northern Branch. 1998 Sep 26;26.
[2] Masuda T, Einstein HH, Mitachi T. Prediction of lateral deflection of diaphragm wall in deep excavations. Doboku Gakkai Ronbunshu. 1994 Dec 21;1994(505):19-29.
[3] Hsieh PG, Ou CY, Shih C. A simplified plane strain analysis of lateral wall deflection for excavations with cross walls. Canadian Geotechnical Journal. 2012 Oct;49(10):1134-46.
[4] Lim A, Ou CY, Hsieh PG. Investigation of the integrated retaining system to limit deformations induced by deep excavation. Acta Geotechnica. 2018 Aug;13(4):973-95.
[5] Zhao HJ, Liu W, Shi PX, Du JT, Chen XM. Spatiotemporal deep learning approach on estimation of diaphragm wall deformation induced by excavation. Acta Geotechnica. 2021 Nov;16(11):3631-45.

Abstract: This study explores how cutting parameters impact the quality of drilled holes in glass fibre-reinforced thermoset polymers. Using Taguchi's L27 orthogonal array, the experiments were designed to optimise drilling parameters. Specifically, 6 mm twist drill bits were employed to drill holes at different feeds and spindle speeds. The analysis involved measuring maximum diameters on both the entry and exit sides of the drilled holes using an optical microscope to understand the influence of drilling parameters on machining damage. Among the parameters tested,......

Key Word: : Drilling, Composite, Hole Quality, Glass Fiber, Delamination

[1]. Koklu, U., Morkavuk, S., Featherston, C., Haddad, M., Sanders, D., Aamir, M., Pimenov D. Y., & Giasin,
[2]. K. (2021). The Effect Of Cryogenic Machining Of S2 Glass Fibre Composite On The Hole Form And Dimen- Sional Tolerances. The International Journal Of Ad- Vanced Manufacturing Technology, 115(1), 125–140.
[3]. [Crossref]
[4]. Khashaba, U. A. (2004). Delamination In Drilling Gfr-Thermoset Composites. Composite Structures, 63(3), 313–327. [Crossref]
[5]. Singh, I., Bhatnagar, N., & Viswanath, P. (2008). Drilling Of Uni-Directional Glass Fiber Reinforced Plastics: Experimental And Finite Element Study. Ma- Terials And Design, 29(2), 546–553. [Crossref]

Abstract: Corrosion is a prevalent issue in the mechanical industries. Corrosion gets developed because of environmental variables such as temperature, humidity and acidic nature of the liquids. There are different techniques for detecting and monitoring corrosion development, both destructive and non-destructive. Visual inspection is a common technique of surface corrosion analysis, but manual inspection is extremely dependent on the inspecting person's abilities and expertise. The findings of the manual inspection are qualitative and may be biased, may result into the accidents because of incorrect analysis. Corrosion must be accurately detected in early phases to prevent unwanted accidents

[1]. Image Processing-Based Pitting Corrosion Detection Using Metaheuristic Optimized Multilevel Image Thresholding And Machine-Learning Approaches, Nhat-Duc Hoang,
Mathematical Problems In Engineering Volume 2020, Article Id 6765274, 19 Pages
[2]. Surface Corrosion Grade Classification Using Convolution Neural Network, Sanjay Kumar Ahuja, Manoj Kumar Shukla, Kiran Kumar Ravulakollu International Journal Of Recent Technology And Engineering (Ijrte) Issn: 2277-3878, Volume-8 Issue-3,
September 2019
[3]. Corrosion Detection Using A.I. : A Comparison Of Standard Computer Vision Techniques And Deep Learning Model, Luca Petricca, Tomas Moss , Gonzalo Figueroa And Stian Broen
[4]. Image Classification Via Support Vector Machine Xiaowu Sun , Lizhen Liu , Hanshi Wang , Wei Song , Jingli Lu, 2015 4th International Conference On Computer Science And Network Technology
[5]. Image Classification Using Support Vector Machine And Artificial Neural Network Article In International, International Journal Of Information Technology And Computer Science · May 2012