طرق عددية

MODULE DESCRIPTION FORM

نموذج وصف المادة الدراسية

Module Information معلومات المادة الدراسية
Module Title	Numerical Methods in Chemical Engineering				Module Delivery
Module Type	Core				☒ Theory ☒ Lecture ☒ Lab ☒ Tutorial ☐ Practical ☐ Seminar
Module Code	CHPR309
ECTS Credits	6
SWL (hr/sem)	150
Module Leve		UGx11 UGIII	Semester of Delivery				6
Administering Department		CHPR	College	COGE
Module Leader	Nuhad AbdulWahed		e-mail	E-mail
Module Leader’s Acad. Title		Lecturer	Module Leader’s Qualification				Ph.D.
Module Tutor	Name (if available)		e-mail	E-mail
Peer Reviewer Name		Name	e-mail	E-mail
Scientific Committee Approval Date		01/06/2023	Version Number			1.0

Relation with other Modules

العلاقة مع المواد الدراسية الأخرى

Prerequisite module

None

Semester

Co-requisites module

None

Semester

Module Aims, Learning Outcomes and Indicative Contents

أهداف المادة الدراسية ونتائج التعلم والمحتويات الإرشادية

Module Objectives

أهداف المادة الدراسية

Introduce approximation techniques for functions.
Familiarize students with numerical integration methods.
Provide an understanding of solving nonlinear equations.
Develop skills in solving ordinary differential equations.
Introduce linear programming and its applications.

Module Learning Outcomes

مخرجات التعلم للمادة الدراسية

Apply interpolation and extrapolation techniques to approximate functions.
Utilize numerical integration methods to calculate definite integrals.
Solve nonlinear equations using various iterative methods.
Solve ordinary differential equations using numerical techniques.
Formulate and solve linear programming problems.

Indicative Contents

المحتويات الإرشادية

Indicative content includes the following.

Approximation of functions interpolation and extrapolation of techniques; forward, backward and central difference, error approximation; Numerical integration – Newton Cotes Integration technique, Simpson’s 1/3rd and 3/8th rule, trapezoidal rule, Gaussian quadrature; Multiple Integral solution of Non-linear equation, bisection methods, regular-falsi method, Newton-Raphson methods, Euler’s method, Euler’s modified iteration technique, Picard's method, Runge-Kutta 4th order technique, Taylor series method; Solutions of ordinary differential equation (initial and boundary value problem) Linear programming.

Learning and Teaching Strategies

استراتيجيات التعلم والتعليم

Strategies

The main strategy that will be adopted in delivering this module is to encourage students’ participation in the exercises, while at the same time refining and expanding their critical thinking skills. This will be achieved through classes, interactive tutorials and by considering types of simple experiments involving some sampling activities that are interesting to the students.

Student Workload (SWL)

الحمل الدراسي للطالب محسوب لـ ١٥ اسبوعا

Structured SWL (h/sem)

الحمل الدراسي المنتظم للطالب خلال الفصل

100

Structured SWL (h/w)

الحمل الدراسي المنتظم للطالب أسبوعيا

Unstructured SWL (h/sem)

الحمل الدراسي غير المنتظم للطالب خلال الفصل

Unstructured SWL (h/w)

الحمل الدراسي غير المنتظم للطالب أسبوعيا

Total SWL (h/sem)

الحمل الدراسي الكلي للطالب خلال الفصل

150

Module Evaluation تقييم المادة الدراسية
As		Time/Number	Weight (Marks)	Week Due	Relevant Learning Outcome
Formative assessment	Quizzes	2	10% (10)	5 and 10	LO #1, #2 and #3
	Assignments	2	20% (20)	2 and 12	LO #3, #4 and #5
	Projects / Lab.	8	10% (10)	Continuous	All
	Report	1	10% (10)	13	LO #4,and #5
Summative assessment	Midterm Exam	1.5hr	10% (10)	7	LO #1 - #4
Summative assessment	Final Exam	2hr	50% (50)	16	All
Total assessment			100% (100 Marks)

Delivery Plan (Weekly Syllabus) المنهاج الاسبوعي النظري
Week	Material Covered
Week 1	Function Approximation Techniques
Week 2	Numerical Integration: Newton-Cotes Integration Techniques
Week 3	Numerical Integration: Simpson's Rule and Trapezoidal Rule
Week 4	Numerical Integration: Gaussian Quadrature
Week 5	Nonlinear Equation Solving: Bisection and Regula-Falsi Methods
Week 6	Nonlinear Equation Solving: Newton-Raphson Method
Week 7	Nonlinear Equation Solving: Euler's Method and Modified Euler's Method
Week 8	Nonlinear Equation Solving: Picard's Method
Week 9	Nonlinear Equation Solving: Runge-Kutta 4th Order Method
Week 10	Taylor Series Method for Ordinary Differential Equations
Week 11	Initial Value Problems: Euler's Method and Runge-Kutta Methods
Week 12	Boundary Value Problems: Shooting Method and Finite Difference Method
Week 13	Boundary Value Problems: Finite Element Method
Week 14	Introduction to Linear Programming
Week 15	Linear Programming Applications
Week 16	Preparatory week before the final Exam

Delivery Plan (Weekly Lab. Syllabus) المنهاج الاسبوعي للمختبر
Week	Material Covered
Week 1	Introduction to MATLAB: Familiarization with MATLAB environment and basic programming concepts.
Week 2	Function Approximation: Implementing interpolation techniques (e.g., polynomial interpolation) in MATLAB.
Week 3	Numerical Integration: Writing MATLAB code to perform numerical integration using various methods.
Week 4	Nonlinear Equation Solving: Implementing iterative methods (e.g., bisection, Newton-Raphson) to solve nonlinear equations in MATLAB.
Week 5	Ordinary Differential Equations: Solving initial value problems using MATLAB's numerical ODE solvers.
Week 6	Boundary Value Problems: Solving boundary value problems using MATLAB's finite difference method.
Week 7	Linear Programming: Formulating and solving linear programming problems using MATLAB's optimization toolbox.

Learning and Teaching Resources مصادر التعلم والتدريس
	Text	Available in the Library?
Required Texts	"Numerical Methods for Engineers" by Steven C. Chapra and Raymond P. Canale	No
Recommended Texts	"Numerical Analysis" by Richard L. Burden and J. Douglas Faires	No
Websites	https://books.google.iq/books/about/Numerical_Analysis.html?id=zXnSxY9G2JgC&redir_esc=y

Grading Scheme مخطط الدرجات
Group	Grade	التقدير	Marks %	Definition
Success Group (50 - 100)	A - Excellent	امتياز	90 - 100	Outstanding Performance
	B - Very Good	جيد جدا	80 - 89	Above average with some errors
	C - Good	جيد	70 - 79	Sound work with notable errors
	D - Satisfactory	متوسط	60 - 69	Fair but with major shortcomings
	E - Sufficient	مقبول	50 - 59	Work meets minimum criteria
Fail Group (0 – 49)	FX – Fail	راسب (قيد المعالجة)	(45-49)	More work required but credit awarded
Fail Group (0 – 49)	F – Fail	راسب	(0-44)	Considerable amount of work required

Note: Marks Decimal places above or below 0.5 will be rounded to the higher or lower full mark (for example a mark of 54.5 will be rounded to 55, whereas a mark of 54.4 will be rounded to 54. The University has a policy NOT to condone "near-pass fails" so the only adjustment to marks awarded by the original marker(s) will be the automatic rounding outlined above.

طرق عددية

Numerical Methods in Chemical Engineering

Core

CHPR309

6

150