CN3421 Process Modeling and Numerical Simulation is a 4 MC module which requires the use of MATLAB to tackle numerical methods and statistical analysis. Basically, there is content to be covered and then, we have to learn how to apply it and use it on MATLAB. For my batch, the sad part was that we didn't cover MATLAB in year 1 so Prof Zhou Kang had to have a crash course on how to use MATLAB first in the first 2 weeks. The final exam for this module is also done on a school computer and your grades is entirely based on the MATLAB files you submitted in the exam (no pen and paper hahaha).
Assessment
22.5% 3 homework assignments on numerical methods (First half of module, 7.5% each)
7.5% Homework assignment on statistics (Second half of module)
70% Finals (Open book, 4 structured questions, 2 hours, 42.5% numerical methods, 27.5% statistics)
(Basically, the numerical methods portion take up a bigger portion of the grades (65%) as compared to the statistics portion (35%); mainly because the there is much more content for the former)
7.5% Homework assignment on statistics (Second half of module)
70% Finals (Open book, 4 structured questions, 2 hours, 42.5% numerical methods, 27.5% statistics)
(Basically, the numerical methods portion take up a bigger portion of the grades (65%) as compared to the statistics portion (35%); mainly because the there is much more content for the former)
Lecturer:
Prof Zhou Kang (Weeks 1 - 9)
Prof Yap Swee Kun (Weeks 9 - 13)
Prof Zhou Kang (Weeks 1 - 9)
Prof Yap Swee Kun (Weeks 9 - 13)
Tutor:
Prof Zhou Kang (Weeks 2 - 9)
Prof Yap Swee Kun (Weeks 10 - 13)
Prof Zhou Kang (Weeks 2 - 9)
Prof Yap Swee Kun (Weeks 10 - 13)
Textbooks/Readings
- First Part of the Module on Numerical Methods:
Basic concepts of linear algebra: Strang, Gilbert, Introduction to linear algebra, 2016, Fifth edition. (Or the reference textbook used in MA1513)
Numerical methods: Ajay K. Ray and Santosh K. Gupta, Mathematical Methods in Chemical & Environmental Engineering, Second edition.
- Second Part of the Module on Statistics:
William Navidi, Statistics for Engineers and Scientists, Third Edition.
I would say there isn't a need to read the textbooks for this module. Like the lecture notes are pretty sufficient and the Profs reply their email promptly too (so if you have other queries, feel free to email them.) There are other guides like mathworks (it's a website) on MATLAB which is super helpful as well. If you are unsure of certain codes and what not for MATLAB, mathworks is a go-to place for such issues.
Lectures
As per usual Chem Eng modules, this module had a 2 hour lecture and a 1 hour lecture weekly. I wouldn't say lecture is a must go since they are webcasted. But I attended most physical lectures as I just found it useful to clear my doubts by just asking the Profs straight away after lecture. PLUS Prof Zhou Kang is super nice haha (that is, if he's still teaching this mod for your sem). Like before every lecture, he'll walk around the whole LT to ask us how we are doing (since this is our first time using MATLAB too). I guess he's also kinda worried that we aren't able to catch up hahaha but thankfully he teaches well so it wasn't that bad.
We had like basic MATLAB introduction in the beginning of the module, so we had to bring our laptops to lectures and we basically followed what Prof Zhou Kang was instructing us to do. I would say he provided a really good introduction to MATLAB which in a way built up a pretty decent foundation for us.
Eventually, as more content needed to be covered, Prof will just copy his MATLAB codes into the lecture slides and ask us to look into them by ourselves after lecture since there wasn't enough time in lectures. Some of the content have to be cut out as well for our batch since he spent the first 2 weeks covering MATLAB basics (I'm not sure about future batches but if you guys start covering MATLAB in year 1 again, then I don't think this module will be a big issue for you. It is for my batch because it is our first time (or sort of first time) having to deal with coding with MATLAB).
The content covered in numerical methods involve linear equations, non-linear equations, differentiation and integration and ordinary differential equations (Basically how to solve these things numerically). The content isn't really very easy but with sufficient practice of the lecture examples and tutorial questions, you'll soon get used to certain concepts and it won't be that bad anymore.
Now, for Prof Yap's portion, it was on statistics. The first 2 - 3 chapters are actually somewhat covered in A level statistics already (like hypothesis testing, normal distribution, t-test, z-test etc). Just that the last 2 chapters were an add on which covered 2 sample hypothesis testing and ANOVA test. I would say this portion was way more manageable and easier to understand, as compared to numerical methods. Prof Yap did a pretty decent job too to explain the concepts to us, so I feel the statistics portion isn't really a big worry for this module. She actually went through the content pretty quickly and we ended our lectures on week 12.
- First Part of the Module on Numerical Methods:
Basic concepts of linear algebra: Strang, Gilbert, Introduction to linear algebra, 2016, Fifth edition. (Or the reference textbook used in MA1513)
Numerical methods: Ajay K. Ray and Santosh K. Gupta, Mathematical Methods in Chemical & Environmental Engineering, Second edition.
- Second Part of the Module on Statistics:
William Navidi, Statistics for Engineers and Scientists, Third Edition.
I would say there isn't a need to read the textbooks for this module. Like the lecture notes are pretty sufficient and the Profs reply their email promptly too (so if you have other queries, feel free to email them.) There are other guides like mathworks (it's a website) on MATLAB which is super helpful as well. If you are unsure of certain codes and what not for MATLAB, mathworks is a go-to place for such issues.
Lectures
As per usual Chem Eng modules, this module had a 2 hour lecture and a 1 hour lecture weekly. I wouldn't say lecture is a must go since they are webcasted. But I attended most physical lectures as I just found it useful to clear my doubts by just asking the Profs straight away after lecture. PLUS Prof Zhou Kang is super nice haha (that is, if he's still teaching this mod for your sem). Like before every lecture, he'll walk around the whole LT to ask us how we are doing (since this is our first time using MATLAB too). I guess he's also kinda worried that we aren't able to catch up hahaha but thankfully he teaches well so it wasn't that bad.
We had like basic MATLAB introduction in the beginning of the module, so we had to bring our laptops to lectures and we basically followed what Prof Zhou Kang was instructing us to do. I would say he provided a really good introduction to MATLAB which in a way built up a pretty decent foundation for us.
Eventually, as more content needed to be covered, Prof will just copy his MATLAB codes into the lecture slides and ask us to look into them by ourselves after lecture since there wasn't enough time in lectures. Some of the content have to be cut out as well for our batch since he spent the first 2 weeks covering MATLAB basics (I'm not sure about future batches but if you guys start covering MATLAB in year 1 again, then I don't think this module will be a big issue for you. It is for my batch because it is our first time (or sort of first time) having to deal with coding with MATLAB).
The content covered in numerical methods involve linear equations, non-linear equations, differentiation and integration and ordinary differential equations (Basically how to solve these things numerically). The content isn't really very easy but with sufficient practice of the lecture examples and tutorial questions, you'll soon get used to certain concepts and it won't be that bad anymore.
Now, for Prof Yap's portion, it was on statistics. The first 2 - 3 chapters are actually somewhat covered in A level statistics already (like hypothesis testing, normal distribution, t-test, z-test etc). Just that the last 2 chapters were an add on which covered 2 sample hypothesis testing and ANOVA test. I would say this portion was way more manageable and easier to understand, as compared to numerical methods. Prof Yap did a pretty decent job too to explain the concepts to us, so I feel the statistics portion isn't really a big worry for this module. She actually went through the content pretty quickly and we ended our lectures on week 12.
Tutorial
Tutorials took place once a week, and they were 1 hour long (as per usual). The tutorials were in the computer lab rooms. So, we get to use the computers to do our MATLAB codes. For Prof Zhou Kang's tutorials in weeks 2 - 9, they're webcasted. (That's right, they are webcasted.) So, his tutorials were like a Q&A session instead or like a place to practice your MATLAB coding. Soooo, I didn't attend the tutorials in the first half of this module. His webcasted tutorials are also pretty sufficient; he will write the MATLAB codes for each question from scratch. So, I followed closely to his guided videos and I felt it was really helpful. Anyway, if you have any queries, you can just email him and he does reply rather quickly too.
For the second half of the module, Prof Yap doesn't webcast her tutorials. And attending her tutorials are pretty good in my opinion. She does gives tips (for MATLAB and for statistics related content) for finals so I feel you should go for her tutorials. For both Profs, each tutorial had about 2 - 3 questions and it does take a while to do each question (I mean you can just refer to the solutions once they are released but I do feel it's good to try them out first on MATLAB).
Homework Assignments
Now the homework assignments. There were 3 of them under numerical methods and 1 under statistics. Each homework had 2 - 3 questions and some were also past year finals questions. So, it serves as a good practice as well. These assignments were graded based on effort basis. Meaning so long as you submit the files with sufficient attempt in answering each question, even if you didn't obtain the correct final answer, you'll still obtain full marks.
Each homework is usually released on a certain week an then due 2 weeks later. It's a homework so you can freely discuss it with your friends. So long as you guys don't submit the exact same codes, then obviously it shouldn't be much of a problem. The table below shows the list of homework and the content tested in the homework. I would say the homework isn't really that easy, it takes like about half a day to like agar agar do the work, and then maybe another 2-3 hours discussing with your friends.
For the homework, it's all softcopy submissions. We had to place all our m files into a folder, zip it up and upload into a luminus submission folder.
For the second half of the module, Prof Yap doesn't webcast her tutorials. And attending her tutorials are pretty good in my opinion. She does gives tips (for MATLAB and for statistics related content) for finals so I feel you should go for her tutorials. For both Profs, each tutorial had about 2 - 3 questions and it does take a while to do each question (I mean you can just refer to the solutions once they are released but I do feel it's good to try them out first on MATLAB).
Homework Assignments
Now the homework assignments. There were 3 of them under numerical methods and 1 under statistics. Each homework had 2 - 3 questions and some were also past year finals questions. So, it serves as a good practice as well. These assignments were graded based on effort basis. Meaning so long as you submit the files with sufficient attempt in answering each question, even if you didn't obtain the correct final answer, you'll still obtain full marks.
Each homework is usually released on a certain week an then due 2 weeks later. It's a homework so you can freely discuss it with your friends. So long as you guys don't submit the exact same codes, then obviously it shouldn't be much of a problem. The table below shows the list of homework and the content tested in the homework. I would say the homework isn't really that easy, it takes like about half a day to like agar agar do the work, and then maybe another 2-3 hours discussing with your friends.
For the homework, it's all softcopy submissions. We had to place all our m files into a folder, zip it up and upload into a luminus submission folder.
Final Exam
The final exam was not easy in my opinion. We had to do our paper on MATLAB on a school computer. We then had to place all the submission files into one folder, zip it up and upload it onto luminus. We are given a folder in luminus to upload all our files that we wanna use for the final exam inside that folder. Then, we are only allowed to access luminus, MATLAB and our hardcopy notes for the finals itself. (No thumbdrives, no internet.) Staring at the computer screen for 2 hours was real painful for my eyes tbh.
We had 4 questions, two from numerical methods and two from statistics. The statistics portion on regression testing and hypothesis testing were pretty manageable; the real tough part is the numerical methods portion. The first question was on numerical differentiation and the second on ordinary differential questions. The questions are directly linked to chemical engineering case studies and require a little thinking out of the box haha. The paper was 2 hours long, so I would say 1 hour 15 mins can be spent on numerical methods and another 45 minutes would be spent on statistics. I advise reading the questions real carefully.
The computer keyboard also requires some getting used to to be honest, so during your free time in the semester, you can actually go to the computer labs at E1 and E2 (when there are no classes) and get used to typing on the keyboards there haha. But this is entirely optional and not doing it won't exactly slow you down or anything.
Since we are allowed to upload files into luminus, I've prepared a "homemade" list of codes for both numerical methods and statistics. They can be accessed here. There is a word document in each folder which will explain what each m file is used for. (Disclaimer: this list is prepared by me. So, use them with precaution because they might not be entirely correct, especially if I said so in the word document). Hope it'll be helpful for you.
The final exam was not easy in my opinion. We had to do our paper on MATLAB on a school computer. We then had to place all the submission files into one folder, zip it up and upload it onto luminus. We are given a folder in luminus to upload all our files that we wanna use for the final exam inside that folder. Then, we are only allowed to access luminus, MATLAB and our hardcopy notes for the finals itself. (No thumbdrives, no internet.) Staring at the computer screen for 2 hours was real painful for my eyes tbh.
We had 4 questions, two from numerical methods and two from statistics. The statistics portion on regression testing and hypothesis testing were pretty manageable; the real tough part is the numerical methods portion. The first question was on numerical differentiation and the second on ordinary differential questions. The questions are directly linked to chemical engineering case studies and require a little thinking out of the box haha. The paper was 2 hours long, so I would say 1 hour 15 mins can be spent on numerical methods and another 45 minutes would be spent on statistics. I advise reading the questions real carefully.
The computer keyboard also requires some getting used to to be honest, so during your free time in the semester, you can actually go to the computer labs at E1 and E2 (when there are no classes) and get used to typing on the keyboards there haha. But this is entirely optional and not doing it won't exactly slow you down or anything.
Since we are allowed to upload files into luminus, I've prepared a "homemade" list of codes for both numerical methods and statistics. They can be accessed here. There is a word document in each folder which will explain what each m file is used for. (Disclaimer: this list is prepared by me. So, use them with precaution because they might not be entirely correct, especially if I said so in the word document). Hope it'll be helpful for you.
Expected Grade: A-
Final Grade: A+
Final Comments
I would say that you have to get used to using MATLAB in order to do well for this module. I constantly practiced coding by redoing tutorial and assignment questions so that I get used to the way coding is done on MATLAB and of course, to reinforce my concepts as well. Also, for different topics, there are certain things/codes that will definitely be used so by practicing more often, you'll get used to what information is needed to be included for similar kind of questions and your finals should then be easier to approach.
I would say that you have to get used to using MATLAB in order to do well for this module. I constantly practiced coding by redoing tutorial and assignment questions so that I get used to the way coding is done on MATLAB and of course, to reinforce my concepts as well. Also, for different topics, there are certain things/codes that will definitely be used so by practicing more often, you'll get used to what information is needed to be included for similar kind of questions and your finals should then be easier to approach.
Stay tuned for more updates.
- Alan
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