Inverse Theory and Applications for Engineers |
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Page 183
... sensor place- ment in the following way . We have already examined the inverse problem with a row of nine sensors placed along the line j = 10 . When the row of nine sensors were placed along j = 9 or j = 10 the surface condition ...
... sensor place- ment in the following way . We have already examined the inverse problem with a row of nine sensors placed along the line j = 10 . When the row of nine sensors were placed along j = 9 or j = 10 the surface condition ...
Page 185
... nine sensors along the row j 10 is presented . The sums of the magnitudes of the nodal response for each of the nine sensors has been added together and plotted as a function of position . = = This plot shows that when all nine sensors ...
... nine sensors along the row j 10 is presented . The sums of the magnitudes of the nodal response for each of the nine sensors has been added together and plotted as a function of position . = = This plot shows that when all nine sensors ...
Page 217
... 9 Figure 5.24 : Tpeak vs. Ne for various sensor depths . Each curve is obtained from nine sensors along a row of constant j . interesting phenomona . As we expect , the peak T is most accurate for the nine sensors located along the line ...
... 9 Figure 5.24 : Tpeak vs. Ne for various sensor depths . Each curve is obtained from nine sensors along a row of constant j . interesting phenomona . As we expect , the peak T is most accurate for the nine sensors located along the line ...
Common terms and phrases
ability accuracy Actual adjoint algorithm analysis application approach approximation assume boundary condition Chapter coefficients compared computed Conduction contains curve determine developed device discrete discussed distribution effects employ engineering Equation errors estimates evaluate example expect expression filter finite difference Fourier frequency function specification method given governing guess heat flux high frequency illustrated indicates initial interior internal inverse problem known least squares linear locations look low pass filter marching matrix measurement method nodes nonlinear objective observation obtained parabolic parameters periodic physical plot position presented procedure properties region regularizer require residuals resolution resolving response sampled sensitivity sensors shown in Figure signal smoothing solid solution solve spatial step surface condition surface heat flux surface temperature techniques thermal tion transform unknown vector әт
References to this book
Inverse Problems in Engineering Mechanics Masataka Tanaka,G.S. Dulikravich No preview available - 1998 |