Created
February 17, 2015 18:38
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| import numpy as np | |
| from scipy.interpolate import interp1d | |
| from pylab import plt | |
| def process_rpt(fname): | |
| with open(fname, 'rb') as f: | |
| lines = f.readlines() | |
| lines_cleaned = [] | |
| for line in lines: | |
| # Strip leading and trailing whitespace | |
| line_cleaned = line.lstrip().rstrip() | |
| # Ignore blank lines | |
| if len(line_cleaned): | |
| # Check if first element is a float | |
| line_cleaned = line_cleaned.split() | |
| try: | |
| float(line_cleaned[0]) | |
| lines_cleaned.append(line_cleaned) | |
| except: | |
| pass | |
| tmp = np.zeros((len(lines_cleaned),len(lines_cleaned[0]))) | |
| for i,line in enumerate(lines_cleaned): | |
| tmp[i,:] = np.array(map(float, line)) | |
| return tmp | |
| class hot_spot_stress(object): | |
| def __init__(self, abaqus_xy_report_file, t, order=2): | |
| fname = abaqus_xy_report_file | |
| self.s_max_path = process_rpt(fname) | |
| self.t = t | |
| self.order = order | |
| self.x = self.s_max_path[:,0] | |
| self.s_max_range = self.s_max_path[:,1] | |
| def calculate(self): | |
| self.trialX = np.linspace(self.x[0], self.x[-1], 100) | |
| self.fitted_interp_2nd = np.polyfit(self.x, self.s_max_range, self.order)[::-1] | |
| self.second_order_y = np.zeros(len(self.trialX)) | |
| for i in range(len(self.fitted_interp_2nd)): | |
| self.second_order_y += self.fitted_interp_2nd[i]*self.trialX**i | |
| f = interp1d(self.trialX, self.second_order_y) | |
| if self.x[-1] < 1.5*self.t: | |
| end = self.x[-1] | |
| else: | |
| end = 1.5*self.t | |
| interp_x = np.array([0.5*self.t,end]) | |
| interp_y = f(interp_x) | |
| self.fitted_interp = np.polyfit(interp_x, interp_y, 1)[::-1] | |
| self.straight_y = np.zeros(len(self.trialX)) | |
| for i in range(len(self.fitted_interp)): | |
| self.straight_y += self.fitted_interp[i]*self.trialX**i | |
| def plot(self): | |
| plt.figure() | |
| plt.plot(self.x, | |
| self.s_max_range, | |
| label='Data', | |
| marker='o') | |
| plt.plot(self.trialX, | |
| self.straight_y, | |
| label = 'Linear extrapolation') | |
| plt.plot(self.trialX, | |
| self.second_order_y, | |
| label = 'Polynomial order {} fit'.format(self.order)) | |
| plt.legend() | |
| plt.ymin=0.0 | |
| def plot_raw(self): | |
| plt.figure() | |
| plt.plot(self.x, | |
| self.s_max_range, | |
| label='Data', | |
| marker='o') | |
| plt.legend() | |
| plt.ymin=0.0 | |
| def hot_spot(self, z): | |
| root_interp_stress = 0.0 | |
| for i in range(len(self.fitted_interp)): | |
| root_interp_stress += self.fitted_interp[i]*z**i | |
| return root_interp_stress |
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