Development of modular and accessible teaching labs, incorporating modelling and practical experimentation

Practical laboratory experimentation has always been a crucial part of engineering education and its effectiveness in facilitating learning is universally acknowledged. Huge advances in computer science, coupled with significant increases in the cost of ever more complex and sophisticated laboratory set-ups, have led to engineering schools’ adopting computer models and simulation software. Although simulation-based laboratory work does enhance the learning experience, it plays a more effective role alongside practical experimentation rather than as a replacement. This case study presents the results and experience gained from an enquiry-based learning of power-converter development laboratory work to support a power electronic converter module at the University of Greenwich. The approach taken allows students to learn the basics of the module through a combination of modelling, simulation and practical experimentation. The modular and portable nature of the laboratory set-ups afforded the students more time and opportunity to explore the subject matter and integrate the laboratory experience with the concepts covered in the lectures. The feedback from students, which was gathered from the students through the university’s EVASYS system, strongly indicated that the approach led to a sustained improvement in students’ learning experience and satisfaction with the module

Engineering simulations for cancer systems biology

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

Integrated Educational Project of Theoretical, Experimental, and Computational Analyses

This research demonstrates how to design an integrated capstone project by including theoretical, experimental and computational analyses of a truss bridge. The project mainly focused on leading students to approach engineering problems with various methods and to understand the advantages and disadvantages of each method. The students applied three methods to acquire the values of stresses and deflections of members in the given truss bridge. First, they calculated the stresses and deformations theoretically. Second, they actually conducted an experiment of the truss bridge with electronic measuring equipment. Lastly, they built two simulation models with Autodesk Inventor and Dassault Systèmes SolidWorks. From the comparisons of above three methods, students were guided to the validation of assumptions of theories.Cockrell School of Engineerin

A comprehensive fractal approach in determination of the effective thermal conductivity of gas diffusion layers in polymer electrolyte membrane fuel cells

The challenges in the fuel cell industry is to produce the efficient thermal and water management for accurate determination of the effectiveness thermal conductivity of gas diffusion layers (GDL) used in polymer electrolyte membrane fuel cells (PEMFC‟s). This is one of the factors affecting the durability of a fuel cell and need to get a solution to minimize costs and optimize the use of electrodes and cells. The main objectives of this research focus on the capability of the fractal approach for estimation the effectiveness of thermal conductivity of gas diffusion layer. Moreover, on this research also to propose modified fractal equations in determination of the effective thermal conductivity of GDL in PEMFCs based on previous study. Other objectives in this study are demonstrated the thermal conductivity of GDL treated with PTFE contents by using through-plane thermal conductivity experiment method. The through-plane measurement (experiment method) has been used in estimating through-plane thermal conductivity of the GDL. Thermal resistance for GDL also has been investigated under compression pressure 0.1 MPa until 1.0 MPa. In fractal equation, the determination of tortuous and pore fractal dimension can be done by using Scanning Electron Microscopy (SEM) method. Determination of effectiveness thermal conductivity using of fractal equation with slightly modified. In findings, it was found that fractal equation have been modified and measured on the GDL parameter characteristics. It was shown that the value of the effectiveness thermal conductivity of the sample using fractal approach is in good agreement with the experimental value. Finally, all the effective thermal conductivity measured by experimental and fractal approach have been determined with the variant temperature and compression pressure to show the validation result between of this two methods

Constructing a Virtual Training Laboratory Using Intelligent Agents

This paper reports on the results and experiences of the Trilogy project; a collaborative project concerned with the development of a virtual research laboratory using intelligence agents. This laboratory is designed to support the training of research students in telecommunications traffic engineering. Training research students involves a number of basic activities. They may seek guidance from, or exchange ideas with, more experienced colleagues. High quality academic papers, books and research reports provide a sound basis for developing and maintaining a good understanding of an area of research. Experimental tools enable new ideas to be evaluated, and hypotheses tested. These three components-collaboration, information and experimentation- are central to any research activity, and a good training environment for research should integrate them in a seamless fashion. To this end, we describe the design and implementation of an agent-based virtual laboratory