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Comprehensive Course Listing Across 8 Semesters

Detailed Course Descriptions for Departmental Electives

The department offers a wide array of advanced elective courses designed to provide students with specialized knowledge and skills in emerging fields. These courses are taught by faculty members who are experts in their respective domains and have extensive industry experience.

Advanced Thermodynamics

This course delves into the principles of thermodynamic cycles, entropy production, and non-equilibrium thermodynamics. Students will study advanced topics such as exergy analysis, thermodynamic optimization, and applications in energy conversion systems. The course includes laboratory experiments that simulate real-world scenarios in power plants, refrigeration systems, and gas turbine operations.

Computational Fluid Dynamics

Students learn to model fluid behavior using numerical methods and computational tools. Topics include Navier-Stokes equations, turbulence modeling, CFD software usage (ANSYS Fluent, STAR-CCM+), and applications in aerodynamics, heat transfer, and chemical processes. The course emphasizes practical implementation through case studies from automotive and aerospace industries.

Machine Learning for Engineers

This elective introduces students to machine learning algorithms specifically tailored for engineering applications. It covers supervised and unsupervised learning techniques, neural networks, data preprocessing, and model validation. Students will apply these methods to solve problems in predictive maintenance, process optimization, and quality control.

Advanced Materials Science

The course explores the structure-property relationships of advanced materials including composites, ceramics, polymers, and nanomaterials. Students study synthesis methods, characterization techniques, mechanical properties, and applications in aerospace, biomedical, and electronics industries. Laboratory sessions involve hands-on experience with scanning electron microscopy, X-ray diffraction, and material testing equipment.

Biomechanics

This course combines principles of mechanics with biological systems to understand motion and forces in living organisms. Topics include human body mechanics, joint modeling, biomaterials design, and medical device development. Students engage in research projects involving musculoskeletal modeling, prosthetic design, and rehabilitation technologies.

Renewable Energy Systems

This course examines various renewable energy technologies including solar, wind, hydroelectric, and geothermal systems. Students study energy conversion processes, grid integration strategies, environmental impact assessments, and policy frameworks. The curriculum includes practical work on designing and testing small-scale renewable energy prototypes.

Smart Manufacturing Technologies

The course explores Industry 4.0 concepts such as IoT integration, digital twins, automation systems, and data analytics in manufacturing environments. Students learn to design smart production lines, implement predictive maintenance strategies, and optimize manufacturing processes using real-time data insights.

Advanced Robotics and Automation

This elective covers advanced robotics concepts including sensor integration, control systems, artificial intelligence in robotics, and human-robot interaction. Students work on projects involving mobile robots, manipulators, and collaborative automation systems. The course includes hands-on programming using ROS (Robot Operating System) and simulation environments.

Finite Element Analysis

This course teaches students how to use finite element methods for solving complex engineering problems. Topics include mesh generation, boundary conditions, material modeling, and solution techniques. Students apply FEM to structural analysis, heat transfer, fluid flow, and electromagnetics through practical assignments and research projects.

Energy Storage Systems

The course explores various energy storage technologies including batteries, supercapacitors, compressed air systems, and pumped hydro storage. Students study system design, performance evaluation, integration with renewable sources, and economic analysis. Laboratory sessions involve testing different storage technologies and analyzing their efficiency under various conditions.

Human Factors in Engineering

This course focuses on ergonomics, human-centered design, and safety considerations in engineering systems. Students learn about cognitive psychology, user interface design, risk assessment, and workplace safety protocols. Projects involve designing products or systems that optimize human performance while minimizing risks.

Design Optimization

The course introduces optimization techniques for engineering design including linear programming, nonlinear optimization, genetic algorithms, and multi-objective optimization. Students learn to formulate design problems mathematically and solve them using appropriate computational tools and methods.

Advanced Manufacturing Techniques

This elective covers modern manufacturing processes such as additive manufacturing (3D printing), laser processing, electron beam welding, and precision machining. Students study process parameters, material compatibility, quality control, and cost analysis of advanced manufacturing technologies.

Nanotechnology in Engineering

The course explores the application of nanoscale science and technology in engineering systems. Topics include nanomaterial synthesis, characterization techniques, quantum effects, and applications in sensors, electronics, medicine, and energy systems. Students engage in research projects involving nanofabrication and nanodevice development.

Engineering Innovation and Entrepreneurship

This course encourages students to think creatively about engineering solutions while developing entrepreneurial skills. Topics include innovation frameworks, business model development, intellectual property, funding strategies, and startup launch processes. Students work on real-world challenges and develop business plans for potential ventures.

Project-Based Learning Philosophy

Our department strongly believes in experiential learning through project-based assignments that simulate real-world engineering challenges. The philosophy behind this approach is to develop critical thinking, problem-solving abilities, and teamwork skills essential for professional success.

The mini-projects begin in the third semester and continue through the sixth semester, with increasing complexity and scope. Each project has defined learning objectives, milestones, and evaluation criteria. Students work in teams of 3-5 members, guided by faculty mentors who provide technical support, feedback, and industry insights.

Project selection involves a competitive process where students propose ideas based on their interests and career goals. Faculty review these proposals for feasibility, relevance, and alignment with departmental expertise. Selected projects are then assigned to teams with appropriate supervision and resources.

The final-year thesis/capstone project is a comprehensive undertaking that requires students to apply all their learned knowledge to solve an industry-relevant problem. This project typically spans the entire seventh and eighth semesters, involving extensive research, experimentation, and documentation. The evaluation includes peer reviews, faculty assessment, and presentation defense before a panel of experts.

The structure emphasizes iterative development, where students receive continuous feedback throughout the project lifecycle. This approach ensures that students not only develop technical competencies but also gain experience in managing timelines, budgets, and stakeholder expectations—a crucial aspect of professional engineering practice.