ENGI 1151 Level 1 Computational Tools for Engineers and Scientists: Computational Tools - Portfolio Submission
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ENGI 1151
Level 1 Computational Tools for Engineers and Scientists: Computational Tools - Portfolio Submission
2022/2023
Coursework specification
The coursework assignment is to put together a portfolio based on the following sessions:
1. Session 7: MatPower Monte Carlo simulation
2. Session 12: Advanced Simulink
3. Session 15: Python Optimisation.
Each of these sessions should be written up as a ‘mini lab report’ (see below) and be preceded by a reflective introduction.
Computational Tools: Portfolio guidelines
You are asked to produce a portfolio of work to demonstrate how well you have achieved the module learning outcomes. The portfolio consists of the reports from three sessions and a reflective introduction. The reflective introduction should be no more than one page, and (1) signpost how you demonstrate your achievement of the learning outcomes and (2) critically review your work (what went well, what challenges were there?). Each of the three reports should be no more than 2 pages. Therefore, the total report content should not be more than 7 pages.
Assessment Criteria (see marking matrix for details)
Reflective introduction (10%):
• Signposting of the portfolio [50%]
• Critical demonstration of appropriateness of tools [50%]
Report (3x30%):
• Written report quality [50%]
• Presentation of results (tabular and/or graphical) [25%]
• Curiosity driven learning [25%]
Learning Outcomes
Subject-specific Knowledge:
• An understanding of how Engineering analysis is carried out using a variety of tools
• An appreciation of the role of Engineering and computational tools in the modern world
• An understanding of several approaches to analysing Engineering data
• An appreciation of the practical limitations of computational tools in Engineering Subject-specific Skills:
• On completion of the module, students will be able to write software programs to analyse Engineering data
• On completion of the module, students will be able to use off-the-shelf programs to analyse Engineering data
• On completion of the module, students will be able to select the appropriate computational tool for the problem at hand and be able to discuss the merits of their chosen approach
• On completion of the module, students will be able apply off-the-shelf or bespoke programs to carry out Engineering analysis
Key Skills:
• Structured presentation of information in written form
Submission structure
The recommended structure for the report is that of a mini-lab report. One suggestion is to use the following sections:
1. Introduction and background: what is the problem, why is it interesting, what (if any) other background work are you basing your solution on?
2. Methodology: how are you going to solve this problem and why is this an appropriate approach?
3. Results: present the key results of your approach, explaining what these are (i.e. guide the reader through how to read the results!)
4. Discussion: what do these results mean? What can you infer or learn?
5. Conclusion: at this point you should revisit the problem statement in the introduction and critically review how well you think this approach has addressed the problem. What went well, and what problems/shortcomings still remain (or you think there might be a better way of solving next time!)?
Avoid a linear narrative of how the session developed, focus on the scientific exploration you undertake. You do not need to include code in your reports. If you do, aim to only show the key aspect that is needed (this should rarely be more than 2 lines!). No other code should be submitted, the assessment is purely based on the reporting and analysis of your results.
2023-03-27