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@lightsquared
Created February 10, 2018 19:00
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This [Jupyter Notebook](http://jupyter.org/) is a research notebook that I use to analyze incident pressure data from a blast. Table 1 below is the list of the data acquisition (DAC) channels, the distance from the $200\\:g$ charge and what is being measured. If you are interested in obtaining the python code please go to my [Github](https://github.com/lightsquared/Blog/blob/master/Incident%20Pressure%20Analysis/Incident%20Overpressure%20Analysis.ipynb).\n",
"\n",
"*Table 1*: DAC Channels Used in a Test Explosion Along with the Distance from the Charge to the Sensor.\n",
"\n",
"| Channel | Distance (m) | Measurement |\n",
"|---------|----------|-------------|\n",
"| **1** | **2** | **Incident** |\n",
"| 2 | 2 | Incident |\n",
"| 3 | 4 | Incident |\n",
"| 4 | 4 | Incident |\n",
"| 5 | 6 | Incident |\n",
"| 6 | 6 | Incident |\n",
"| 7 | 2 | Reflected |\n",
"| 8 | 4 | Reflected |\n",
"| 9 | 6 | Reflected |\n",
"| 10 | NA | Trigger |\n",
"\n",
"All of this can be done in [Microsoft Excel](https://products.office.com/en-US/excel?legRedir=true&CorrelationId=6189e20d-3333-4b7e-a36d-23a4c0232961) however, I have found that it is difficult to follow and more importantly reproduce what some other researcher does in Microsoft Excel. I use the Jupyter Notebook because it is reproducible python code, I can write full text in [MarkDown](https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet) to describe my thoughts, and I can write equations in [Latex](https://www.latex-project.org/) to support my analysis.\n",
"\n",
"Most Jupyter Notebooks start my loading libraries needed for the analysis. That is what I have done below, along with setting up constants in the analysis, and loading the data to be analyzed."
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
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"\n",
" .dataframe tbody tr th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>CH 1 [psi]</th>\n",
" <th>CH 2 [psi]</th>\n",
" <th>CH 3 [psi]</th>\n",
" <th>CH 4 [psi]</th>\n",
" <th>CH 5 [psi]</th>\n",
" <th>CH 6 [psi]</th>\n",
" <th>CH 7 [psi]</th>\n",
" <th>CH 8 [psi]</th>\n",
" <th>CH 9 [psi]</th>\n",
" <th>CH 10 [v]</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Time [s]</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
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" <tbody>\n",
" <tr>\n",
" <th>-0.000335</th>\n",
" <td>-0.022220</td>\n",
" <td>-0.030488</td>\n",
" <td>0.000000</td>\n",
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" <td>4.99542</td>\n",
" </tr>\n",
" <tr>\n",
" <th>-0.000334</th>\n",
" <td>-0.017459</td>\n",
" <td>0.005807</td>\n",
" <td>-0.014274</td>\n",
" <td>-0.013803</td>\n",
" <td>-0.020442</td>\n",
" <td>0.001441</td>\n",
" <td>-0.104681</td>\n",
" <td>0.068369</td>\n",
" <td>0.012390</td>\n",
" <td>4.99542</td>\n",
" </tr>\n",
" <tr>\n",
" <th>-0.000334</th>\n",
" <td>-0.019046</td>\n",
" <td>-0.001452</td>\n",
" <td>-0.012847</td>\n",
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" <td>-0.008761</td>\n",
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" <td>4.99542</td>\n",
" </tr>\n",
" <tr>\n",
" <th>-0.000333</th>\n",
" <td>-0.030156</td>\n",
" <td>-0.033392</td>\n",
" <td>-0.019983</td>\n",
" <td>-0.013803</td>\n",
" <td>-0.020442</td>\n",
" <td>0.000000</td>\n",
" <td>0.043104</td>\n",
" <td>0.043508</td>\n",
" <td>0.018586</td>\n",
" <td>4.99542</td>\n",
" </tr>\n",
" <tr>\n",
" <th>-0.000333</th>\n",
" <td>-0.026981</td>\n",
" <td>0.007259</td>\n",
" <td>0.005710</td>\n",
" <td>0.019938</td>\n",
" <td>-0.002920</td>\n",
" <td>0.000000</td>\n",
" <td>-0.030788</td>\n",
" <td>0.155385</td>\n",
" <td>0.037171</td>\n",
" <td>4.99542</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" CH 1 [psi] CH 2 [psi] CH 3 [psi] CH 4 [psi] CH 5 [psi] \\\n",
"Time [s] \n",
"-0.000335 -0.022220 -0.030488 0.000000 -0.003067 -0.005841 \n",
"-0.000334 -0.017459 0.005807 -0.014274 -0.013803 -0.020442 \n",
"-0.000334 -0.019046 -0.001452 -0.012847 0.009202 -0.008761 \n",
"-0.000333 -0.030156 -0.033392 -0.019983 -0.013803 -0.020442 \n",
"-0.000333 -0.026981 0.007259 0.005710 0.019938 -0.002920 \n",
"\n",
" CH 6 [psi] CH 7 [psi] CH 8 [psi] CH 9 [psi] CH 10 [v] \n",
"Time [s] \n",
"-0.000335 0.004323 0.000000 -0.024862 0.018586 4.99542 \n",
"-0.000334 0.001441 -0.104681 0.068369 0.012390 4.99542 \n",
"-0.000334 0.017290 0.000000 0.006215 0.018586 4.99542 \n",
"-0.000333 0.000000 0.043104 0.043508 0.018586 4.99542 \n",
"-0.000333 0.000000 -0.030788 0.155385 0.037171 4.99542 "
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Read CSV file\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from scipy.signal import argrelmax\n",
"\n",
"%matplotlib inline\n",
"import pandas as pd\n",
"from io import StringIO\n",
"\n",
"# Set plot height x width to golden ratio.\n",
"h = 8\n",
"w = h*1.61803398875\n",
"\n",
"# Set constants for analysis. This will change from shot to shot.\n",
"cH = 'CH 1 [psi]' # Set cH to the channel of interest.\n",
"dist_m = 2 #meters\n",
"weight_g = 200*1.3 #convert to TNT\n",
"sensor = \"Incident\" #pressure sensor type for analysis.\n",
"\n",
"dist_ft = dist_m*3.28084 # convert distance in meters to distance in feet.\n",
"weight_lb = weight_g*0.00220462 # convert weigth in grams to weight in pounds.\n",
"\n",
"# Set font to serif style to match Times New Roman.\n",
"font = {'family' : 'serif',\n",
" 'weight' : 'normal',\n",
" 'size' : 22}\n",
"plt.rc('font', **font)\n",
"\n",
"# Load the data for analysis into a Pandas dataframe.\n",
"shot = \"./data.CSV\"\n",
"shot_data = pd.read_csv(shot, index_col=\"Time [s]\") # read the CSV data into a dataframe and set the Time [s] as the index.\n",
"shot_data.head() # Show the first 5 rows of data loaded into the dataframe \"shot_data\"."
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(0.5732012, 2, 6.56168, '7.899')"
]
},
"execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# from numpy import sqrt # import the square root function.\n",
"sd = dist_ft/np.cbrt(weight_lb) # calcuate scaled distance.\n",
"f_sd = format(sd, '0.3f') # format output.\n",
"weight_lb, dist_m, dist_ft, f_sd"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The charge was 200 g (0.57 lb) and the transducer was 2 m (6.56 ft) for a scaled distance of: 7.90 $\\frac{ft}{^3\\sqrt{lb}}$.\n",
"\n",
"Change the dataframe index time from seconds to milliseconds. First create a new column called \"Time [msec]\" that is equal to the current index muliplied by 1000. Then set the new column \"Time [msec]\" as the dataframe's new index."
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>CH 1 [psi]</th>\n",
" <th>CH 2 [psi]</th>\n",
" <th>CH 3 [psi]</th>\n",
" <th>CH 4 [psi]</th>\n",
" <th>CH 5 [psi]</th>\n",
" <th>CH 6 [psi]</th>\n",
" <th>CH 7 [psi]</th>\n",
" <th>CH 8 [psi]</th>\n",
" <th>CH 9 [psi]</th>\n",
" <th>CH 10 [v]</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Time [msec]</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>-0.3350</th>\n",
" <td>-0.022220</td>\n",
" <td>-0.030488</td>\n",
" <td>0.000000</td>\n",
" <td>-0.003067</td>\n",
" <td>-0.005841</td>\n",
" <td>0.004323</td>\n",
" <td>0.000000</td>\n",
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" <td>4.99542</td>\n",
" </tr>\n",
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" <th>-0.3345</th>\n",
" <td>-0.017459</td>\n",
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" <th>-0.3340</th>\n",
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" <td>0.018586</td>\n",
" <td>4.99542</td>\n",
" </tr>\n",
" <tr>\n",
" <th>-0.3335</th>\n",
" <td>-0.030156</td>\n",
" <td>-0.033392</td>\n",
" <td>-0.019983</td>\n",
" <td>-0.013803</td>\n",
" <td>-0.020442</td>\n",
" <td>0.000000</td>\n",
" <td>0.043104</td>\n",
" <td>0.043508</td>\n",
" <td>0.018586</td>\n",
" <td>4.99542</td>\n",
" </tr>\n",
" <tr>\n",
" <th>-0.3330</th>\n",
" <td>-0.026981</td>\n",
" <td>0.007259</td>\n",
" <td>0.005710</td>\n",
" <td>0.019938</td>\n",
" <td>-0.002920</td>\n",
" <td>0.000000</td>\n",
" <td>-0.030788</td>\n",
" <td>0.155385</td>\n",
" <td>0.037171</td>\n",
" <td>4.99542</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" CH 1 [psi] CH 2 [psi] CH 3 [psi] CH 4 [psi] CH 5 [psi] \\\n",
"Time [msec] \n",
"-0.3350 -0.022220 -0.030488 0.000000 -0.003067 -0.005841 \n",
"-0.3345 -0.017459 0.005807 -0.014274 -0.013803 -0.020442 \n",
"-0.3340 -0.019046 -0.001452 -0.012847 0.009202 -0.008761 \n",
"-0.3335 -0.030156 -0.033392 -0.019983 -0.013803 -0.020442 \n",
"-0.3330 -0.026981 0.007259 0.005710 0.019938 -0.002920 \n",
"\n",
" CH 6 [psi] CH 7 [psi] CH 8 [psi] CH 9 [psi] CH 10 [v] \n",
"Time [msec] \n",
"-0.3350 0.004323 0.000000 -0.024862 0.018586 4.99542 \n",
"-0.3345 0.001441 -0.104681 0.068369 0.012390 4.99542 \n",
"-0.3340 0.017290 0.000000 0.006215 0.018586 4.99542 \n",
"-0.3335 0.000000 0.043104 0.043508 0.018586 4.99542 \n",
"-0.3330 0.000000 -0.030788 0.155385 0.037171 4.99542 "
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"shot_data['Time [msec]'] = shot_data.index*1000 #create a new column in the dataframe called Time [msec].\n",
"shot_data.set_index('Time [msec]', inplace=True) #set the new column as the dataframe index.\n",
"shot_data.head() #view the first 5 rows of the updated dataframe."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Just for a check, if we take 1,000 times the reciprocal of the difference between index values we should get the sample rate."
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'2,000,000'"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"shot_data[\"Diff\"] = shot_data.index # creates a new column called Diff in the dataframe and sets it equal to the index.\n",
"shot_data[\"Diff\"] = (shot_data['Diff'] - shot_data['Diff'].shift()) #subtract the current from the next row.\n",
"difference = shot_data['Diff'].iloc[1] # find difference in the second row of column Diff.\n",
"f_sample_rate = format(round(1000*(1/difference)), '0,.0f')\n",
"f_sample_rate"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The sample rate based on the time index in the data is 2,000,000 S/s.\n",
"\n",
"Now I would like to plot the data channel of interest. This was set in the first code cell as \"CH 1 [psi]\"."
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
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lSTNX7khTNQAAAHASoQSeYtpbqETSuYcxAxcAAICXEEqQcwZ27xx8vKO63sVKAAAAEA9C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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11c677048>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"start = -50 # Set plot start time.\n",
"end = 50 # Set plot end time.\n",
"\n",
"shot_data[cH][start:end].plot(figsize=(w,h));\n",
"plt.ylabel(cH);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## DC Bias Removal\n",
"All signals have DC bias. We can check and remove any DC bias by taking the mean of the data up to the trigger value."
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'0.001578'"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Take the mean of the data channel data up to time = 0 and extract the 1 first term.\n",
"cH_DC = shot_data[[cH]][:0].mean()[0]\n",
"f_cH_DC = format(cH_DC, '0.6f')\n",
"f_cH_DC"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The DC bias for this channel was 0.001578 psi. We can now remove the DC bias from the channel and replot."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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oQVbpUlwgSepWwrolAAAAuYJQAk8lu+TIm1dPkCT161rsQjUAAADwAqEEGSKxlUq6lRRJ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\nQQkRERERETmKQQkRERERETnq/wGQLI8OGJYtjwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11c2a7048>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"shot_data_dc = shot_data[cH] - cH_DC;\n",
"shot_data_dc[0:25].plot(figsize=(w,h));\n",
"plt.ylabel(cH);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Peak Pressure and Positive Phase Duration"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The local maximum value of the pressure for the channel is found along with the time at maxiumum pressure."
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"('11.012', '2.587')"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Find measuered peak overpressure and the time it occurs\n",
"peak_p = max(shot_data_dc[0:25]) #peak pressure.\n",
"peak_t = shot_data_dc[0:25].idxmax() #time at peak pressure.\n",
"f_peak_t = format(peak_t, '0.3f')\n",
"f_peak_p = format(peak_p, '0.3f')\n",
"f_peak_p, f_peak_t"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The maximum pressure occurs at the point (2.587 ms,11.012 psi). Plotting the maximum pressure value we have,"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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Stkg60VpbHrT7C2NMK0kneFIcmiSwqvuukgodrAKPqwEAAEBTNRpKjDFPOXyv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\noqhip4SIiIiIiKKKnRIiIiIiIoqq/wevk6psPpFefAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11f875cc0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"shot_data_dc[0:25].plot(figsize=(w,h));\n",
"plt.plot(peak_t, peak_p, 'ko');\n",
"plt.text(peak_t+1, peak_p, '({}, {})'.format(f_peak_t, f_peak_p));\n",
"plt.ylabel(cH);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that we have the peak value we need to find the start of the rise in pressure. I'm going to define this as the first positive pressure point that occurs if you move from the peak pressure backward in time. We can find this point by first deleting the data to the right of the peak."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Time [msec]\n",
"-0.3350 -0.023798\n",
"-0.3345 -0.019036\n",
"-0.3340 -0.020623\n",
"-0.3335 -0.031733\n",
"-0.3330 -0.028559\n",
"Name: CH 1 [psi], dtype: float64"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"left_peak = shot_data_dc[:peak_t] # new dataframe called left_peak that includes all the data in channel 1 up to the peak pressure.\n",
"left_peak.head() # first five rows of the new dataframe left_peak."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Next we need to reverse sort the data so that we start with the peak pressure."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Time [msec]\n",
"2.5865 11.011622\n",
"2.5860 10.913222\n",
"2.5855 10.818022\n",
"2.5850 10.733822\n",
"2.5845 10.649722\n",
"Name: CH 1 [psi], dtype: float64"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"left_peak_rev = left_peak.iloc[::-1]\n",
"left_peak_rev.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As you can see we're at the peak pressure now, 11.012 psi, and the time is going backwards. Now we need to find the pressure in channel 1 where it first goes negative. Then we will move one time step forward and that is where we say the positive pressure phase starts. To do that we need to first find where the pressure goes negative and record the time where that occurs."
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'2.565'"
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"neg_idx_t = left_peak_rev.index[left_peak_rev < 0][0]\n",
"f_neg_idx_t = format(neg_idx_t, '0.3f')\n",
"f_neg_idx_t"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we have the time, 2.565 ms, when the pressure first goes negative as we move left of the peak pressure. Now we need to take that time index and convert it to an integer index. Using our original shot_data dataframe we can pull out the integer index."
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"5800"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"neg_idx_int = shot_data_dc.index.get_loc(neg_idx_t)\n",
"neg_idx_int"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that we have the integer index, 5800, for the first negative pressure value we can shift one time increment in the positive direction and capture the beginning pressure of the positive phase."
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"('2.566', '0.033')"
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pos_phase_p_str = shot_data_dc.iloc[neg_idx_int+1]\n",
"pos_phase_t_str = shot_data_dc.index.values[neg_idx_int+1]\n",
"f_pos_phase_t_str = format(pos_phase_t_str, '0.3f')\n",
"f_pos_phase_p_str = format(pos_phase_p_str, '0.3f')\n",
"TOA = pos_phase_t_str\n",
"f_pos_phase_t_str, f_pos_phase_p_str"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So the beginning of the positive phase starts at 2.566 ms at a pressure of 0.033 psi."
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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X9I6krZJOstaWBe3+whjTUtKJnhSHRgms6r67uFyHqrnH1QAAAKCxGgwlxpgn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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11be9bfd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"shot_data_dc[0:25].plot(figsize=(w,h));\n",
"plt.plot(peak_t, peak_p, 'ko');\n",
"plt.plot(pos_phase_t_str, pos_phase_p_str, 'go');\n",
"plt.text(pos_phase_t_str-2.5, pos_phase_p_str-2, '({}, {})'.format(f_pos_phase_t_str,\n",
" f_pos_phase_p_str),\n",
" color='g');\n",
"plt.text(peak_t+1, peak_p, '({}, {})'.format(f_peak_t, f_peak_p), color='k');\n",
"plt.ylabel(cH);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So now we have the both the pressure 0.033 psi and time 2.566 ms where the pressure goes positive right before the abrupt shoot up to peak pressure. It would be intresting to find the number points between the start of the positive phase and the peak pressure. We can do that with the following code,"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(0.021500000000000019, 43)"
]
},
"execution_count": 60,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"num_points_rise = len(shot_data_dc[pos_phase_t_str : peak_t])\n",
"RT = num_points_rise*difference\n",
"RT, num_points_rise"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So there is $0.0215\\:ms$ (43 data points) between the start of the positive phase and the peak pressure. To have $95\\%$ confidence we captured the peak pressure we would want $10$ points. For a $99\\%$ confidence we captured the peak pressure we would want $27$ points. So the sample rates for this test were very good at 43 data points.[5]\n",
"\n",
"Now we need to find the end of the positive phase. This will be done similarly to how we found the start of the positive phase except we will not need to reverse the sort of the time index. So to start we will delete all the data to the left of the peak pressure."
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Time [msec]\n",
"2.5865 11.011622\n",
"2.5870 10.917922\n",
"2.5875 10.865622\n",
"2.5880 10.910022\n",
"2.5885 10.846522\n",
"Name: CH 1 [psi], dtype: float64"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"right_peak = shot_data_dc[peak_t:]\n",
"right_peak.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we have the the pressure-time data starting at the peak pressure. So now we can ask the question at what time does the pressure go negative."
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"'3.886'"
]
},
"execution_count": 62,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"neg_idx_t_end = right_peak.index[right_peak < 0][0]\n",
"f_neg_idx_t_end = format(neg_idx_t_end, '0.3f')\n",
"f_neg_idx_t_end"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Starting at the peak pressure and moving to the right in the data the pressure goes negative at a time of 3.886 ms which, looks about right from the plot. Now as before we need to find the integer index for this point."
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"8442"
]
},
"execution_count": 63,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"neg_idx_int_end = shot_data_dc.index.get_loc(neg_idx_t_end)\n",
"neg_idx_int_end"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that we have the integer index, 8442, for the first negative pressure value at the end of the positive pressure phase we can shift one time increment back in time and capture the ending pressure of the positive phase."
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"('3.885', '0.027')"
]
},
"execution_count": 64,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pos_phase_p_end = shot_data_dc.iloc[neg_idx_int_end-1]\n",
"pos_phase_t_end = shot_data_dc.index.values[neg_idx_int_end-1]\n",
"f_pos_phase_t_end = format(pos_phase_t_end, '0.3f')\n",
"f_pos_phase_p_end = format(pos_phase_p_end, '0.3f')\n",
"f_pos_phase_t_end, f_pos_phase_p_end"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The end of the positive phase occurs at 3.885 ms at a pressure of 0.027 psi."
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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jWkk62pPiEBPfqu7bSsq0r/I8rgYAAACxChhKjDGPunyvq621P7p8zWD+JKlA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\nRK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11c6155f8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"shot_data_dc[0:25].plot(figsize=(w,h));\n",
"plt.plot(peak_t, peak_p, 'ko');\n",
"plt.plot(pos_phase_t_str, pos_phase_p_str, 'go');\n",
"plt.plot(pos_phase_t_end, pos_phase_p_end, 'bo');\n",
"plt.text(pos_phase_t_str-2.5, pos_phase_p_str-2, '({}, {})'.format(f_pos_phase_t_str, f_pos_phase_p_str), color='g');\n",
"plt.text(pos_phase_t_end+1, pos_phase_p_end+0.75, '({}, {})'.format(f_pos_phase_t_end, f_pos_phase_p_end), color='b');\n",
"plt.text(peak_t+1, peak_p, '({}, {})'.format(f_peak_t, f_peak_p), color='k');\n",
"plt.ylabel(cH);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that we have both the start and end of the positive phase duration we can calculate the duration of the positive phase."
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'1.320'"
]
},
"execution_count": 66,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pos_phase_dur = pos_phase_t_end - pos_phase_t_str\n",
"f_pos_phase_dur = format(pos_phase_dur, '0.3f')\n",
"f_pos_phase_dur"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So the total positive phase duration is 1.320 ms. Plotting the positive phase looks like the following:"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PolyCollection at 0x11c64d668>"
]
},
"execution_count": 67,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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NcjP00jfLJUkpRsrNSNNLE5bpjF7VzdsBAAASmePwYozpJekNSQOqOT9T0jXB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\nQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11c64d198>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"shot_data_dc[2:5].plot(figsize=(w,h))\n",
"plt.ylabel(cH)\n",
"plt.fill_between(shot_data.index, 0, shot_data[cH],\n",
" where=(shot_data.index >= pos_phase_t_str) & (shot_data.index <= pos_phase_t_end),\n",
" alpha=0.3)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that we have the beginning and ending times of the positive phase we can calculate the impulse using simpson's rule."
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {},
"outputs": [],
"source": [
"def impulse(dframe, t_start, t_end):\n",
" from scipy import integrate # loads integrate functions\n",
" p = dframe[t_start:t_end].values.transpose() #slice y values from dataframe\n",
" t = dframe[t_start:t_end].index.values #slice x values from dataframe\n",
" i = integrate.simps(p,t) #integrate y values from start time to end time\n",
" return i #returns non-array value of impulse"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"'5.543'"
]
},
"execution_count": 69,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataImpulse = impulse(shot_data_dc,pos_phase_t_str,pos_phase_t_end)\n",
"f_dataImpulse = format(dataImpulse, '0.3f')\n",
"f_dataImpulse"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The impulse is 5.543 psi-ms.\n",
"\n",
"The next step is to apply the Friedlander equation from the peak to the end of the positive phase. This will allow for an improved estimation of the peak pressure as, according to the manufacturer (PCB) pressure transducers the transducers can overshoot due high frequency noise in the blast wave and excite the structural resonance of the housed quartz transduction element. At peak overpressures above about one atmosphere, the Friedlander equation is no longer able to describe accurately the pressure time-histories, and it is necessary to introduce another coefficient, α, in a modified version of the equation. [1][2][3]\n",
"\n",
"So, the modified Frielander equation is,\n",
"\n",
"$$p(t)=P_s e^{-\\alpha t} \\left(1-\\frac{t}{t^+} \\right)$$\n",
"\n",
"where $p$ is the overpressure at a fixed location, $P_s$ is the peak overpressure immediately behind the primary shock, $\\alpha$ is a new parameter used for shocks over $1\\:atm$ and, $t^+$ is the positive duration.\n",
"\n",
"We can esimate the values for $P_s$, $\\alpha$, and $t^+$ using a non-linear curve fit."
]
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[Model]]\n",
" Model(friedlander)\n",
"[[Fit Statistics]]\n",
" # function evals = 23\n",
" # data points = 2599\n",
" # variables = 3\n",
" chi-square = 85.139\n",
" reduced chi-square = 0.033\n",
" Akaike info crit = -8878.918\n",
" Bayesian info crit = -8861.330\n",
"[[Variables]]\n",
" p_s: 11.4467781 +/- 0.012894 (0.11%) (init= 11.01162)\n",
" alpha: 0.97376494 +/- 0.006606 (0.68%) (init= 0.35)\n",
" t_plus: 1.41732445 +/- 0.004910 (0.35%) (init= 1.32)\n",
"[[Correlations]] (unreported correlations are < 0.100)\n",
" C(alpha, t_plus) = 0.872 \n",
" C(p_s, alpha) = 0.687 \n",
" C(p_s, t_plus) = 0.404 \n",
"\n",
" 99.73% 95.45% 68.27% _BEST_ 68.27% 95.45% 99.73%\n",
" p_s : -0.03811 -0.02532 -0.01272 11.44678 +0.01274 +0.02536 +0.03811\n",
" alpha : -0.01908 -0.01275 -0.00640 0.97376 +0.00644 +0.01292 +0.01945\n",
" t_plus: -0.01401 -0.00943 -0.00476 1.41732 +0.00487 +0.00980 +0.01486\n"
]
},
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x11bfc7ba8>"
]
},
"execution_count": 71,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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/P9jYgJNTe2ZxjJ8oQNvjy+jO/wH6Fdt9fKBvX1i0yMLBCiFEFihvWBU2EZcn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r5F5MMPoWvXE9Od89v99/vx6CdTmBi68wG38xZ1WM4hzmA8HXmHXsymBfUbRPH995ArV/CvJdzd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\nIiKSpRSEiIiIiIhIlvp/vrtMstBPX0UAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11ff64780>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from numpy import exp\n",
"from lmfit import minimize, Parameters, Model\n",
"\n",
"# reset time to zero ms by subtracting t at start of array\n",
"t = shot_data_dc[peak_t:pos_phase_t_end].index.values - shot_data_dc[peak_t:pos_phase_t_end].index.values[0] \n",
"p = shot_data_dc[peak_t:pos_phase_t_end].values\n",
"\n",
"def friedlander(t, p_s, alpha, t_plus):\n",
" return ((1-(t/t_plus))*p_s*exp(-alpha*t))\n",
"\n",
"fmodel = Model(friedlander)\n",
"\n",
"result = fmodel.fit(p, t = t,\n",
" method='leastsq',\n",
" p_s = peak_p,\n",
" alpha = 0.35,\n",
" t_plus = pos_phase_dur)\n",
"\n",
"delp = result.eval_uncertainty(t=t, sigma=3.0) # calculates the sigma 3 (99) at each point.\n",
"ci_values = result.conf_interval() # table of ci values\n",
"best_value = result.best_values # all of the best fit values\n",
"p_CI_99_plus = list(result.ci_out.items())[0][1][6][1] #covnert ci_out to list then pick 99+\n",
"p_CI_99_minus = list(result.ci_out.items())[0][1][0][1] #covnert ci_out to list then pick 99-\n",
"p_CI_99_best = list(result.ci_out.items())[0][1][3][1] #convert ci_out to list then pick 0\n",
"n_pts = result.ndata\n",
"\n",
"f_ps = format(best_value[\"p_s\"], '0.3f')\n",
"f_a = format(best_value[\"alpha\"], '0.3f')\n",
"f_tp = format(best_value[\"t_plus\"], '0.3f')\n",
"f_p_CI_99_minus = format(p_CI_99_minus, '0.3f')\n",
"f_p_CI_99_plus = format(p_CI_99_plus, '0.3f')\n",
"f_n_pts = format(n_pts, '0,.0f')\n",
"\n",
"print(result.fit_report())\n",
"print(result.ci_report())\n",
"\n",
"fig, ax = plt.subplots(figsize=(w,h))\n",
"plt.plot(t, p,'b', label='pressure data')\n",
"plt.plot(t, result.init_fit, 'k--', label = 'initial guess')\n",
"fit = plt.plot(t, result.best_fit, 'r-',\n",
" label= r'$p(t)={} e^{{-{} t}} \\left(1-\\frac{{t}}{{{}}} \\right)$'.format(f_ps, \n",
" f_a, \n",
" f_tp))\n",
"plt.xlabel('Time (ms)')\n",
"plt.ylabel('Pressure (psi)')\n",
"plt.legend()"
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"('2,599', '11.409', '11.485')"
]
},
"execution_count": 72,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"f_n_pts, f_p_CI_99_minus, f_p_CI_99_plus"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The non-linear least-square curve fit of the pressure over the time from peak pressure to the end of the positive phase was, n = 2599, 99% CI [11.409, 11.485] (psi)."
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Clean Signal</th>\n",
" <th>Distance (ft)</th>\n",
" <th>Distance (m)</th>\n",
" <th>Impulse Data (psi-ms)</th>\n",
" <th>Peak P Data (psi)</th>\n",
" <th>Positive Phase Data (ms)</th>\n",
" <th>RT (ms)</th>\n",
" <th>SD (ft/lb^1/3)</th>\n",
" <th>Sensor</th>\n",
" <th>TOA (ms)</th>\n",
" <th>Weight (lb)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>CH 1</th>\n",
" <td>yes</td>\n",
" <td>6.56168</td>\n",
" <td>2</td>\n",
" <td>5.543122</td>\n",
" <td>11.011622</td>\n",
" <td>1.32</td>\n",
" <td>0.0215</td>\n",
" <td>7.899132</td>\n",
" <td>Incident</td>\n",
" <td>2.5655</td>\n",
" <td>0.573201</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Clean Signal Distance (ft) Distance (m) Impulse Data (psi-ms) \\\n",
"CH 1 yes 6.56168 2 5.543122 \n",
"\n",
" Peak P Data (psi) Positive Phase Data (ms) RT (ms) SD (ft/lb^1/3) \\\n",
"CH 1 11.011622 1.32 0.0215 7.899132 \n",
"\n",
" Sensor TOA (ms) Weight (lb) \n",
"CH 1 Incident 2.5655 0.573201 "
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#summary peak pressure, impulse, positive phase duration\n",
"dataSummaryTable = pd.DataFrame({'Peak P Data (psi)' : peak_p,\n",
" 'Positive Phase Data (ms)' : pos_phase_dur,\n",
" 'Impulse Data (psi-ms)' : dataImpulse,\n",
" 'SD (ft/lb^1/3)' : sd,\n",
" 'Weight (lb)' : weight_lb,\n",
" 'Distance (ft)' : dist_ft,\n",
" 'Distance (m)' : dist_m,\n",
" 'TOA (ms)' : TOA,\n",
" 'RT (ms)' : RT,\n",
" 'Sensor' : sensor,\n",
" 'Clean Signal' : 'yes'},\n",
" index=[cH[0:len(cH)-6]])\n",
"dataSummaryTable"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[1] L. Walter, Patrick, “Measuring Static Overpressures in Air Blast Environments, TN-27,” Depew, NY, 2010.\n",
"\n",
"[2] J. M. Dewey, “Measurement of the Physical Properties of Blast Waves,” in Experimental Methods of Shock Wave Research, Cham: Springer International Publishing, 2016, pp. 53–86.\n",
"\n",
"[3] G. F. Kinney, K. J. Graham, G. F. Kinney, and K. J. Graham, Explosive shocks in air, 2nd ed. New York: Springer-Verlag New York Inc., 1985.\n",
"\n",
"[4] Newville, M., Stensitzki, T., Allen, D. B., & Ingargiola, A. (2014, September 21). LMFIT: Non-Linear Least-Square Minimization and Curve-Fitting for Python. Zenodo. http://doi.org/10.5281/zenodo.11813\n",
"\n",
"\n",
"\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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",
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},
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"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": 2
}
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