{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "ChEn-3170: Computational Methods in Chemical Engineering Spring 2024 UMass Lowell; Prof. V. F. de Almeida **17Jan24**\n", "\n", "# Laboratory Work 01 (17Jan24)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Name: `your name`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Rubric for each assignment: \n", "\n", "| Context | Points |\n", "| ----------------------- | ------- |\n", "| Precision of the answer | 80% |\n", "| Answer Markdown readability | 10% |\n", "| Code readability | 10% |\n", " " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Guidance:\n", "\n", "+ \n", " Save your work frequently to a file locally to your computer.\n", " \n", "+ \n", " During your work and before submitting the final version do: Kernel -> Restart & Run All, to verify your notebook runs correctly.\n", " \n", "+ \n", " Save your file again.\n", " \n", "+ \n", " Upload the notebook file in the Blackboard submission portal as: \n", " \n", " \n", " **lastname-firstname-labwork-xx.ipynb**\n", " \n", " NB: Please note lowercase." ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2022-01-19T02:51:21.616703Z", "start_time": "2022-01-19T02:51:21.612171Z" } }, "source": [ "---\n", "### Table of Assignments\n", "* [Assignment 1 (5 pts)](#a1) Jupyter notebooks\n", "* [Assignment 2 (5 pts)](#a2) Workflow\n", "* [Assignment 3 (5 pts)](#a3) Code block\n", "* [Assignment 4 (5 pts)](#a4) Plot\n", "* [Assignment 5 (5 pts)](#a5) Boolean\n", "* [Assignment 6 (10 pts)](#a6) String\n", " - [6.1)](#a61)(5 pts) Example\n", " - [6.2)](#a62)(5 pts) Size\n", "* [Assignment 7 (20 pts)](#a7) Geometry\n", " - [7.1)](#a71)(10 pts) Triangle\n", " - [7.2)](#a72)(10 pts) Cylinder\n", "* [Assignment 8 (20 pts)](#a8) Heat transfer\n", " - [8.1)](#a81)(10 pts) Power\n", " - [8.2)](#a82)(5 pts) Cost\n", " - [8.3)](#a83)(5 pts) Comment\n", "* [Assignment 9 (20 pts)](#a9) String\n", "* [Assignment 10 (5 pts)](#a10) Unclear points.\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## [Assignment 1 (5 pts)](#toa)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Describe with your own words what a Jupyter Notebook is and how you would learn more about it." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Answer:**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## [Assignment 2 (5 pts)](#toa)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Describe the typical workflow of a Jupyter Notebook." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Answer:**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## [Assignment 3 (5 pts)](#toa)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Copy a Python code block from [here](https://matplotlib.org/stable/gallery/index.html), insert below as Markdown, and describe the steps you have taken to create the Markdown block." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Code block:**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Description:**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## [Assignment 4 (5 pts)](#toa)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Create a code cell with the code in Assignment 3 and produce a plot." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-01-19T02:47:37.090042Z", "start_time": "2022-01-19T02:47:36.462670Z" } }, "outputs": [], "source": [ "'''Code'''" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## [Assignment 5 (5 pts)](#toa)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Create a Python code cell with a boolean variable and print its type." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-01-19T02:47:37.103170Z", "start_time": "2022-01-19T02:47:37.091616Z" } }, "outputs": [], "source": [ "'''Code'''" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## [Assignment 6 (10 pts)](#toa)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### [6.1](#toa)(5pts) Create a Python code cell with a string variable and print its type." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-01-19T02:47:37.107588Z", "start_time": "2022-01-19T02:47:37.104398Z" } }, "outputs": [], "source": [ "'''Code'''" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### [6.2](#toa)(5pts) Create a Python code cell with a string variable 10-characters long or more and print its type and its length." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-01-19T02:47:37.114014Z", "start_time": "2022-01-19T02:47:37.110190Z" }, "scrolled": true }, "outputs": [], "source": [ "'''Code'''" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## [Assignment 7 (20 pts)](#toa)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### [7.1](#toa)(10 pts) Create a Python code to compute the area of a right triangle with sides $a = 1.23$ and $b = 2.45$, and its hypotenuse; print the results. On a Markdown cell, explain your results mathematically." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-01-19T02:47:37.119996Z", "start_time": "2022-01-19T02:47:37.115264Z" } }, "outputs": [], "source": [ "'''Code'''" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Explanation:**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### [7.2](#toa)(10 pts) Create a Python code to compute the volume of a right cylinder with radius $r = 2.45$ and height $h = 5.13$; print the results. On a Markdown cell, explain your results mathematically." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-01-19T02:47:37.125922Z", "start_time": "2022-01-19T02:47:37.122044Z" } }, "outputs": [], "source": [ "'''Code'''" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Explanation:**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## [Assignment 8 (20 pts)](#toa)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### [8.1](#toa)(10 pts) Calculate the heating power in a homogeneous, open flow system at steady state with the following data and explain your calculation: \n", " \n", "| Property | Variable | Value | Unit |\n", "| ----------------------- | ------------------ |----------------------|-------------------|\n", "|system volume | $V$ | 0.25 | $\\text{m}^3$ | \n", "|mass density | $\\rho$ | 1010 | kg/$\\text{m}^3$ |\n", "|heat capacity | $C$ | 4184 | J/(kg K) |\n", "|temperature difference | $\\Delta T$ | 78.5 | K |\n", "|flow residence time | $\\tau$ | 25 | s |\n", " \n", "### " ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2022-01-19T03:49:07.342234Z", "start_time": "2022-01-19T03:49:07.338292Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Heat generation density = 331.72844 [MJ/m^3]\n", "Volumetric flow rate = 10.0 [L/s]\n", "Heating power = 3.3172843999999997 [MW]\n" ] } ], "source": [ "'''Code'''\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Explanation:**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### [8.2](#toa)(5 pts) What is the cost per hour to run this system in Massachusetts if the cost per energy is $0.23/kWh?" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-01-19T03:49:11.283813Z", "start_time": "2022-01-19T03:49:11.280807Z" } }, "outputs": [], "source": [ "'''Code'''" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### [8.3](#toa)(5 pts) Explain qualitatively the cost obtained, *i.e.*, why is it low or high or an acceptable value? In other words, as an engineer, explain why this cost is reasonable or not." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Explanation:**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## [Assignment 9 (20 pts)](#toa)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Compute the area under the line of the plot below; show the plot." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2022-01-19T02:47:37.372601Z", "start_time": "2022-01-19T02:47:37.140795Z" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "plt.plot(range(5,13), range(1,9))\n", "plt.ylabel('y')\n", "plt.xlabel('x')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2022-01-19T02:47:37.379974Z", "start_time": "2022-01-19T02:47:37.375598Z" } }, "outputs": [], "source": [ "'''Code'''" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## [Assignment 10 (5 pts)](#toa)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Describe the most unclear point in the course content presented so far. Then, make an effort to clarify the point on your own." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Description and troubleshooting:**" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.8" }, "latex_envs": { "LaTeX_envs_menu_present": true, "autoclose": false, "autocomplete": true, "bibliofile": "biblio.bib", "cite_by": "apalike", "current_citInitial": 1, "eqLabelWithNumbers": true, "eqNumInitial": 1, "hotkeys": { "equation": "Ctrl-E", "itemize": "Ctrl-I" }, "labels_anchors": false, "latex_user_defs": false, "report_style_numbering": false, "user_envs_cfg": false } }, "nbformat": 4, "nbformat_minor": 4 }