Numerical Methods for Differential Algebraic Equations in Chemical Engineering — PickAClass
⏱ 2h 42m 📚 27 lessons 🎧 Audio version

Numerical Methods for Differential Algebraic Equations in Chemical Engineering

Learn to model and solve complex chemical engineering systems governed by combined differential and algebraic equations using modern numerical techniques.

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About this course

Chemical engineering systems often involve complex physical processes, such as mass transfer, chemical reactions, and thermodynamic equilibria, which are modeled using combined differential and algebraic equations (DAEs). Understanding how to set up and solve these mathematical models is essential for designing and optimizing chemical reactors, separation columns, and process piping networks. This text-based course guides you through the fundamental theory and practical numerical methods needed to resolve these coupled systems. By working through this course, you will transition from a basic understanding of calculus and algebra to confidently setting up, analyzing, and solving structured DAE systems. You will learn how to identify index problems, apply robust numerical solvers, and interpret your simulation results to make informed engineering decisions. What you'll learn: - Understand the fundamental differences between ordinary differential equations (ODEs) and differential algebraic equations (DAEs) in chemical processes. - Classify DAE systems by their index and apply index reduction techniques to make them solvable. - Implement numerical integration methods, such as backward differentiation formulas (BDF) and implicit Runge-Kutta methods, to solve stiff systems. - Model multi-component flash distillation and chemical reaction kinetics using structured mathematical formulations. - Apply modern numerical software workflows and scripting practices to automate process simulation and ensure convergence. The course begins with foundational definitions of DAEs, index classification, and core mathematical concepts. You will then progress step-by-step through numerical solvers, error control, and realistic chemical engineering case studies that you can work through on your own. This course is designed for undergraduate students, graduate researchers, and practicing chemical engineers who have a basic background in calculus and linear algebra but are new to numerical DAE modeling. No advanced programming experience is required. Start reading today to master the mathematical modeling of complex chemical systems.

What you'll get

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  • Short & focused
    2h 42m of practical content

Certificate of completion

Every course you complete on PickAClass issues a credential like this — original, with its own code, verifiable by URL, and detailed about what was actually demonstrated.

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Certificate of Mastery
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Name Surname
has successfully demonstrated mastery of
Numerical Methods for Differential Algebraic Equations in Chemical Engineering
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1.2 hrs
Decision-architecture frameworks
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1.4 hrs
A/B test design
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1.7 hrs
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Numerical Methods for Differential Algebraic Equations in Chemical Engineering
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Performance detail
Coursework summary
Lessons completed 14 / 14
Practice questions 26 / 28
Assignments submitted 4 (avg 4.5 / 5)
Capstone project Reviewed — 4.6 / 5
Total practice 6.2 hrs
Performance benchmark
Cohort rank Top 12% of 1,625
Time to completion 11 days (median: 22)
Mastery score 91 / 100
Practice-question score 94%
Skill verification Verified Skill Path
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Issued under the academic standards of PickAClass. Skill levels reflect assessed performance against the course's competency rubric. This is an original credential of this platform.

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Yes — full refund within 14 days, no questions asked.

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