Ac 2011-682: Balancing Theory, Simulation and Physical Experiments In

Some big problems for students studying heat transfer are (1) difficulty in visualizing both basic and complex theoretical concepts, (2) unsure how to design changes effect heat flow or temperature distributions, (3) unclear how to apply theoretical concepts in the development of components / systems and (4) confusion with how to extend single point experiments to generic applications. It is impossible for students to solve complex heat transfer problems through theoretical hand calculations or execute real experiments when the boundary conditions are complicated because of time and laboratory equipment cost constraints. During the laboratory experience, students are guided in the use of SolidWorks/Simulation for conducting virtual experiments and comparing them to theoretical concepts presented in lecture along with simple physical measurements in the laboratory. Thru the use of virtual experiments in the SolidWorks environment, students have full control of the experiment by having the ability to change virtual boundary conditions and running the virtual experiments as many times as needed until they understand the concepts. The applications of virtual experiments which include geometric sensitivity studies help students to visualize the application of concepts in simulated design applications. From our direct observations in several classes, students gain a better understanding of both the theoretical concepts and application to design refinement by creating virtual components in addition to gaining hands-on experience directly applicable to industrial applications. With the introduction of true 3D CAD and associated simulation software such as SolidWorks/SolidWorks Simulation, the concept of balancing virtual simulations for comparison to theory and physical experiments are presented in this paper for effectively teaching heat transfer in a mechanical curriculum. Introduction: Developing student understanding, visualization and theoretical concept application to design are key components to successful education of future engineers. Application to design is not satisfied simply by conducting physical experiments without imparting a deeper understanding of the underlying phenomenon relative to design decisions. Developing experiments that address design change sensitivity on system performance can be both exceedingly costly and time consuming. Experiments alone can actually be detrimental if the students are not able to visualize the broader impact of complex boundary conditions encountered in real life on design decisions. A potential solution to impart better understanding is to combine concept validation type physical experiments with virtual experiments that extend the basic phenomenon covered in lectures using available analysis software packages in wide spread industrial use such as SolidWorks [1]. The concept of developing virtual parts, assemblies and the analysis of virtual parts using SolidWorks and Simulation [1, 2, 3 and 4] can be extended to enhancing student theoretical visualization and laboratory experiences. This paper presents two examples of a balanced approach for using virtual experiments with physical experimentation in teaching basic concepts of heat transfer; one dimensional conduction and conduction in extended surfaces. The internal temperature distributions in these two examples are compared to theory and available laboratory hardware. One Dimensional Heat Transfer: References [5 and 6] provide a traditional development of the general heat conduction equation in both rectangular and cylindrical coordinate systems based on sound thermodynamic principles. The concept of thermal conductivity as a material property is presented along with illustrations of the experimental set up used to quantify the value for various substances. The simplified Fourier equation for conduction expressed in both differential and algebraic forms in rectangular and cylindrical coordinates is provided below as equations 1 thru 5 with the associated temperature distributions as equations 6 and 7.