volume-1 MAE issue 2
RUNGTA INTERNATIONAL OF JOURNAL OF MECHANICAL AND AUTOMOBILE ENGINEERING
RUNGTA INTERNATIONAL OF JOURNAL OF MECHANICAL AND AUTOMOBILE ENGINEERING
• Volume 1 (Jan 2024- Dec 2024)
Issue 2
1. Study on the effectiveness of Non-Newtonian fluid-based Speed Braker
Nivesh Agrawal1,# , Manoj Kumar Soni1 , Ishwar Prasad Sahu1, Anand Kumbhare1, Y. Venkat Ramana1Author Affiliations
Department of Mechanical Engineering, Rungta College of Engineering and Technology, Bhilai, India- 490024
ABSTRACT:
The study investigates the effectiveness of non-Newtonian fluid (NNF) based speed breakers as an innovative solution to enhance road safety and traffic control. Traditional speed breakers, while effective in reducing vehicle speed, often cause discomfort to drivers and can lead to vehicle damage over time. Non-Newtonian fluids, with their unique property of viscosity change under stress, offer a promising alternative. This research focuses on the development, testing, and analysis of a speed breaker prototype utilizing NNF technology. The study explores the fluid’s behaviour under varying vehicle loads and speeds, the mechanical design of the speed breaker, and its potential benefits compared to conventional rigid speed bumps. The results show that the NNF- based speed breaker provides a smoother driving experience while still effectively reducing vehicle speed. Furthermore, the adaptive nature of the non-Newtonian fluid allows for variable resistance, potentially enhancing the comfort and safety of road users. This study also highlights the environmental sustainability of the proposed system, as NNF-based speed breakers can be designed with eco-friendly materials and components. The findings suggest that NNF-based speed breakers could offer a viable solution to modernizing traffic control systems, balancing efficiency, safety, and user experience. Further research is recommended to refine the system and evaluate its performance under diverse environmental conditions.
Keywords: Non-Newtonian fluid, speed breaker, road safety, traffic control, vehicle speed, adaptive resistance, sustainable design.
2. Artificial Intelligence in SOLIDWORKS: Applications and Impacts
Sanjay G Sakharwade1,# , Kush Kumar Dewangan1 , Suraj Bandhekar1 , Rahul Mishra1 , Sameer Singh1 , Anant Kumar1Author Affiliations
Department of Mechanical Engineering, Rungta College of Engineeing and Technology, Bhilai, India- 490024
ABSTRACT:
The integration of Artificial Intelligence (AI) and Machine Learning (ML) into SOLIDWORKS has revolutionized mechanical engineering workflows, enabling unprecedented efficiency, creativity, and precision in product design. This paper explores SOLIDWORKS’ AI-driven tools, their applications, and their transformative impact on the field. SOLIDWORKS 2025 introduces Aura AI, a context-aware assistant embedded directly into the CAD environment. Aura automates repetitive tasks, generates design alternatives, and provides real-time regulatory compliance insights, allowing engineers to focus on innovation. AI reduces repetitive tasks, allowing engineers to dedicate 40% more time to creative problem-solving. However, human oversight remains critical. SOLIDWORKS aims to expand industry-specific AI customization, particularly for aerospace and medical devices, while improving predictive maintenance algorithms using IoT sensor data. This synergy positions SOLIDWORKS as a leader in smart manufacturing, driving innovation while maintaining the critical role of engineering expertise.
Keywords: Solidworks; digital manufacturing; artificial intelligence; industry 4.0
3. AI-Driven Supplier Selection Using AHP and TOPSIS Approaches for Optimized Supply Chain Management
Chandra Shekhar Nagendra1, # , Roshan Dutt Kashyap2 , Lakhwinder Kaur3, T M Swathy4, Megha Kataria5, B Laxman Rao6Author Affiliations
1 ,2,5,6Department of Mechanical Engineering, 3Department of Electronics and Telecommunication Engineering, 4Department of Electrical Engineering, Rungta College of Engineering & Technology, Bhilai 490024
ABSTRACT:
In the modern globalized and digitally connected marketplace, the selection of suitable contractors is a critical strategic decision with far-reaching implications across the supply chain. Conventional supplier evaluation methods, though beneficial, often prove inadequate when dealing with ambiguity, scarce information, and subjective inputs. Incorporating artificial intelligence into these processes can significantly improve the efficiency, accuracy, and responsiveness of decision- making. This research explores the integration of AI with established supplier selection models namely AHP and TOPSIS, to offer supply chain managers a robust framework for comparative assessment and enhanced strategic choices. Application of AI to AHP and TOPSIS results in more adaptive, data-driven evaluations that strengthen strategic sourcing decisions in dynamic supply chain environments; and the ability to process complex datasets and generate optimized supplier rankings with greater reliability and speed.
Keywords: Supplier Selection, AHP, TOPSIS
4. HEAT EXCHANGER MODIFICATION
Rajkumar Rai1# , Pranjal Kumar Pandey2, Shreyash Suman3, Suraj Bandhekar4, Taha Qamer5 Author Affiliations1 Department of Mechanical Engineering, Rungta College of Engineering and Technology, Bhilai, India-490023
2 Department of Mechanical Engineering, Rungta College of Engineering and Technology, Bhilai, India-490023
3 Department of Mechanical Engineering, Rungta College of Engineering and Technology, Bhilai, India-490023
4Department of Mechanical Engineering, Rungta College of Engineering and Technology, Bhilai, India-490023
5 Department of Mechanical Engineering, Rungta College of Engineering and Technology, Bhilai, India-490023
ABSTRACT:
Heat exchangers are integral to industrial processes involving thermal energy exchange. Traditional designs such as the shell-and-tube configuration often suffer from suboptimal thermal performance, fouling, and pressure drops. This paper investigates cost-effective passive modification techniques including helical baffles, vortex generators, and nanofluids for enhancing heat exchanger performance. The objective is to optimize heat transfer without significant penalties in pressure drop or system complexity. Computational Fluid Dynamics (CFD) simulations coupled with experimental validation are used to analyse the effects of these modifications. Results show up to 40% improvement in heat transfer coefficient and over 35% increase in Nusselt number with limited increase in pressure drop. The study concludes that retrofitting existing exchangers with such enhancements is a practical approach to improving thermal systems. These findings suggest that integrating nanotechnology and geometric modifications can lead to significant energy savings and improved process reliability in various industrial applications. Keywords: Heat exchangers, passive enhancement, helical baffles, vortex generators, nanofluids, Computational Fluid Dynamics (CFD), Nusselt number, heat transfer coefficient, retrofitting, thermal performance.
5. Compilation of Mechanical Properties of Kenaf- Reinforced Polymer Composites with Varying Fibre Content and Matrices
Aditya Rajput1,#, Shourya Chandrakar2,, Ansh Mishra2, Md Muzaffar Ansari2, Agnivesh Kumar Sinha3, Ram Krishna Rathore3 Author Affiliations1 Department of Civil Engineering, Rungta College of Engineering and Technology, Bhilai, India-490024
2 Department of Data Science, Rungta College of Engineering and Technology, Bhilai, India-490024
3 Department of Mechanical Engineering, Rungta College of Engineering and Technology, Bhilai, India- 490024 ABSTRACT:
Kenaf fibre has emerged as a promising natural reinforcement in polymer composites due to its sustainability, cost-effectiveness, and favorable mechanical properties. This review compiles and analyzes experimental data on a wide variety of kenaf-reinforced polymer composites to evaluate their mechanical performance. The composites studied include single and hybrid reinforcements combined with matrices such as epoxy, polyester, polyurethane, polylactic acid, and polypropylene. Mechanical properties such as tensile strength, flexural strength, impact strength, Young’s modulus, and elongation at break were compared across different fibre loadings and composite formulations. The results indicate that the incorporation of kenaf fibres significantly enhances mechanical performance, particularly when combined with other reinforcements like glass fibre, banana fibre, or basalt. For example, hybrid kenaf-basalt epoxy composites demonstrated tensile strengths up to 150 MPa and impact strengths exceeding 29 kJ/m². Additionally, fibre loading was found to strongly influence mechanical behavior, with optimal ranges varying by matrix type. Notably, polylactic acid and epoxy-based systems generally showed superior strength and stiffness. This comprehensive dataset highlights the potential of kenaf fibre composites for structural and semi-structural applications in automotive, construction, and consumer product sectors.
Keywords: Polymer matrix composites; Structural applications; Mechanical properties; Sustainable materials; Reinforcement hybridization; Fibre-matrix compatibility