Plan your solution: Draw a picture, in this case, list all of your data and equations (see the first post of this series) Remember the fundamentals (steady state material balance) and apply Draw your material or energy balance envelope (continuous distillation at wikipedia) Remember [Accumulation = In – Out + Source/Sink] Think about what you […]

# Posts from ‘July, 2009’

## Steady-State Material Balances on a Separation Train – Problem Description

Reference: This is problem 1.5 in "Problem Solving in Chemical Engineering with Numerical Methods" by Michael Cutlip and Mordecai Shacham, Prentice-Hall ISBN 0-13-862566-2. This problem is about solving the material balance for a set of three distillation columns with a feed containing four components. Since you’re at steady state with no recycle, you have a […]

## Solving Differential Algebraic Equations – Solution

Solve the problem: So, let’s execute the program we developed in the last post and see how the concentration changes with time and if we believe what the computer is telling us. If you need a refresher for how to execute a program script in IPython, go to IPython documentation webpage. It has a tremendous […]

## Solving Differential Algebraic Equations – Programming Approach

Plan your solution: Draw a picture, in this case, list all of your data and equations (see the first post of this series) Remember the fundamentals (unsteady state material balance) and apply Draw your material or energy balance envelope (batch distillation at wikipedia) Remember [Accumulation = In – Out + Source/Sink] Think about what you […]

## Solving Differential Algebraic Equations – Problem Description

Reference: This is problem 3.8 in "Problem Solving in Chemical Engineering with Numerical Methods" by Michael Cutlip and Mordecai Shacham, Prentice-Hall ISBN 0-13-862566-2. This problem is a batch distillation problem with two ideal components. You have an unsteady state mass balance (ODE) to solve along with algebraic equations describing parts of the problem. Concepts: Solve […]

## Install Pylab (Python/Scipy/Matplotlib/IPython) on a Mac OS

How do you install Pylab on a Mac? As you all know, earlier in the blog, I posted instructions on installing Pylab (Python/Scipy/Matplotlib/IPython) on Windows and Linux systems. I use both in the course of my job and teaching. I used a Mac many years ago, but I had to use specialized software that wasn’t […]

## Terminal Velocity of Falling Particles – Solution

Solve the problem: Execute the problem and then examine the output. Remember, you’re solving for 1 g and 30 g accelerations. Look at the solutions and see if they make physical sense. Remember, non-linear equations can be very ‘entertaining’. Terminal particle velocities (finally….the answer): For 1 g, the terminal velocity = 0.015 m/s, and at […]

## Terminal Velocity of Falling Particles – Programming Approach

Plan your solution: Draw a picture, in this case, list all of your data and equations (see the first post of this series) Remember the fundamentals (force balance = terminal velocity equations) and apply Draw your material or energy balance envelope (see force balance for terminal velocity) Remember [Accumulation = In – Out + Source/Sink] […]

## Terminal Velocity of Falling Particles – Problem Description

Reference: This is problem 5.6 in "Problem Solving in Chemical Engineering with Numerical Methods" by Michael Cutlip and Mordecai Shacham, Prentice-Hall ISBN 0-13-862566-2. This problem is about solving a single nonlinear equation, but with a changing drag coefficient as a result of the velocity. Concepts: Set up the equation to solve for a root Use […]

## Python Video Tutorials – A Break from Solving Problems

What have we done so far? In the first few posts, we discussed ‘why’ a blog about practical engineering problem solving and then worked through some examples. After all, many blogs are about ‘productivity’ such as David Allen’s GTD or using Gmail more effectively or about popular music or current events. For sure, blogs […]