CHEM ENG 2013 - Advanced Process Modelling

North Terrace Campus - Semester 2 - 2014

This course will extend the modelling skills introduced in the course CHEM ENG 1011. Extension will primarily come through consideration of chemical, biochemical and pharmaceutical processes of increasing complexity, including real-life processes. Skills will be developed in developing models for the processes using fundamental principles and solving these efficiently using numerical methods. An integrated problem-based approach will ensure various process modelling techniques, including data regression and model validation, will be developed in the process engineering context.

  • General Course Information
    Course Details
    Course Code CHEM ENG 2013
    Course Advanced Process Modelling
    Coordinating Unit School of Chemical Engineering
    Term Semester 2
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 4 hours per week
    Incompatible CHEM ENG 2006
    Assumed Knowledge CHEM ENG 1011, MATHS 2201, CHEM ENG 1007
    Course Description This course will extend the modelling skills introduced in the course CHEM ENG 1011. Extension will primarily come through consideration of chemical, biochemical and pharmaceutical processes of increasing complexity, including real-life processes. Skills will be developed in developing models for the processes using fundamental principles and solving these efficiently using numerical methods. An integrated problem-based approach will ensure various process modelling techniques, including data regression and model validation, will be developed in the process engineering context.
    Course Staff

    Course Coordinator: Dr Philip Kwong

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    By the end of this course, students should be able to describe,
    1 How to formulate numerical problems using

    a.    Consecutive calculations

    b.    System of linear algebraic equations

    c.    Single nonlinear algebraic equations

    d.    Multiple linear and polynomial regressions

    e.    System of first-order ordinary differential equations

    f.     System of nonlinear algebraic equations

    with the aid of mathematical software packages; and
    2 How to apply the methods in (1) for real-life engineering problems; and

    3 How to choose/ build an appropriate model for the regression and correlation of experimental data and subsequently evaluate the accuracy of the model.

    University Graduate Attributes

    No information currently available.

  • Learning Resources
    Recommended Resources
    Reference Book

    Cutlip, M. B. and M. Shacham (2008). Problem Solving in Chemical and Biochemical Engineering with POLYMATH, EXCEL, and MATLAB. Upper Saddle River, NJ, Prentice Hall.

    Online Learning
    A range of online resources will be provided via MyUni.

  • Learning & Teaching Activities
    Learning & Teaching Modes
    The course will be delivered as a series of weekly lectures. Lectures are designed to deliver new materials and tutorials are designed as guided-workshops with practical sessions to help you to achieve the indented learning outcomes.
    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    Activity Contact hours Workload hours
    Lectures 22 44
    Computer Labs 20 50
    Assignments 0 48
    Examination 0 12
    TOTAL 42 154
    Learning Activities Summary
    Topic 1: Introduction/ Basic Principles and Calculations
    Problem solving using single nonlinear algebraic equation, solution of a system of linear equations, regression of polynomials, single nonlinear algebraic equation and simultaneous ordinary differential equations.

    Topic 2: Regression and Correlation of Data
    Data correlations using linear and non-linear regression models, linearization and transformation of functions, model comparison using confidence intervals, residual plots and sum of squares techniques.

    Topic 3: Numerical Problems in Thermodynamics
    Modelling of compressibility factor, isothermal compression of gas, thermodynamic properties of pure substances using various equation of state.

    Topic 4: Numerical Problems in Chemical Reaction Engineering
    Modelling of batch, continuous flow, tubular and packed bed reactors using mass balance
    equations and the determination of kinetic parameters from different
    experimental data.

  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary

    No information currently available.

    Assessment Detail

    No information currently available.

    Submission

    No information currently available.

    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

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