Computer Science » Matlab

Project – Data Analysis and User Interface

Data Entry

• Open all of your CSV files in Excel 2016 and save them as worksheets in the Cool It Excel Workbook

template file provided. Give the worksheets meaningful names and add the sheet names to the

Data Summary sheet which already exists.

• Using MATLAB, read the Data Summary sheet from the Excel file. Then using loops and the sheet

names listed in the Data Summary sheet, read in the data from each of the sheets without

hardcoding any sheet names, etc. Store each matrix in a cell of a cell array of size N x 2 (where N

is the number of cylinders and spheres tested). The first column will contain the room

temperature data matrix and the second column will contain the cooling data matrix.

• Read data provided as an Excel file containing the Table 1: Material Properties worksheet to your

MATLAB program.

• Do not re‐arrange data or do any calculations in Excel.

• You will submit your Excel file along with your MATLAB files.

Analysis ‐ introduction

All plots created in this project will include at least one logarithmic‐scale axis. Axis limits (minimum and

maximum axis values) on logarithmic axes must be even powers of ten and which contain the full range

of data being plotted. For example, axis limits of 0.1 to 10 are acceptable, while axis limits of 0.3 to 3 are

not.

Analysis – create two temperature‐decline plots

We will assume temperature difference declines following an exponential decay curve (see Equation 2 on

the first page). Although the exponent is expected to be negative, we will work with positive values for

the cooling factor, r, by defining the exponent in the cooling equation to be –r.

Create and use a user‐defined function, named as described in the Submission section below, to plot

multiple data series on a proper plot of temperature change (ΔT) [°C] as a function of time (t) [min]. Avoid

the mistake of plotting temperature vs. time! All proper‐plot rules (Chapter 11.2) apply. Make one or

both axes logarithmic as needed to linearize the data (make it appear linear). Add an appropriate trendline

(TL) to each data series. Review Chapters 12 and 13 for guidance on which TL type to select for your data.

You only need to add one TL equation to each of your temperature change plots. The TL equation should

not overlap any data markers of trendlines on your plot.

Call this function twice to prepare two proper plots. Call the plotting function once to plot cooling data

for all the uniform area spheres; and a second time to plot cooling data for all uniform mass & specific

heat cylinders. Your code should identify which objects belong in each plot.

Analysis – create two parameter plots

complete detail will share after fix deal

Engenharia Elétrica Matlab and Mathematica Python Research Writing Estatísticas

ID do Projeto: #19118939

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