Reference no: EM132872475
KB7043 Multidisciplinary Design & Engineering Optimisation - Northumbria University
Learning Outcome 1: A systematic understanding of knowledge which is at the forefront of modern engineering design and optimisation
Learning Outcome 2: Knowledge of conducting essential calculations for reliability driven design and design under uncertainties
Learning Outcome 3: Ability to plan design optimisation processes for complex engineering problems and to formulate their corresponding optimisation problem and identifying the best applicable search method
Learning Outcome 4: Skill of using optimisation methods to find the optimum solution for a given optimisation problem and develop critiques of the methods and the optimality of the solution
Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
Learning Outcome 5: Increase proficiency in applying new design and optimisation techniques towards designing products and processes with improved performance and less environmental impact.
Coursework Overview
The waste heat from an organic rankine cycle is used as activation energy in a biodigestor as shown in the figure below.
Design an optimised heat exchanger to facilitate heat transfer between the organic rankine cycle and the biodigester. Make use of ANSYS Workbench, ANSYS Fluent and ANSYS DesignXplorer to conduct the study. Investigate the effect of uncertainty in the design parameters on the performance of the heat exchanger using the Six Sigma Analysis from the ANSYS DesignXplorer toolbox.
The working fluid (fluid 2) entering the biodigester is water and must not exceed 38 °C.
Each student will have a unique set of data provided to them by the module tutor. This unique data set includes:
• the atmospheric temperature
• working fluid 1 specification
• working fuild 1 inlet temperature
Coursework Tasks to be Completed by Students
The following tasks are to be completed on the chosen design problem:
• Provide a description of the design. Include a drawing/sketch/model of the heat exchanger clearly showing the parameters.
• Discuss the model setup in ANSYS Workbench indicating the diffirent steps required to perform the analysis. Explain how the response surface is created focusing on the theory of generating reduced order meta-models.
• Present and interpret the results obtained from the response surface.
• Present and interpret the results obtained from the response surface optimisation. Clearly indicate the implications for the design and the optimal values of the selected parameters
• Investigate the range of performance as the design and operating parameters vary by performing a Six Sigma Analysis in ANSYS Workbench.
• Conclude the report with the major findings.
Referencing Style
You are to write your coursework using the Cite Them Right version of the IEEE referencing system.
Attachment:- Multidisciplinary Design.rar
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