Quadratic Finite Element Methods for Unilateral Contact Problems
... inequality formulation is given. Section 4 is concerned with the convergence study of the methods for which we prove identical convergence rates under various regularity hypotheses. Finally, in section 5, we carry out numerical experiments where quadratic finite elements and linear finite elements a ...
... inequality formulation is given. Section 4 is concerned with the convergence study of the methods for which we prove identical convergence rates under various regularity hypotheses. Finally, in section 5, we carry out numerical experiments where quadratic finite elements and linear finite elements a ...
Gauss`s Hypergeometric Equation
... Theorem A also tells us that there is second independent solution of GHE (0.1) near x = 0 with exponent m = 1 − c. This solution can be found directly, by substituting y = x 1−c (a0 + a1 x + a2 x 2 + · · · ) into GHE (0.1) and calculating the coefficients. The other way of finding the solution is to ...
... Theorem A also tells us that there is second independent solution of GHE (0.1) near x = 0 with exponent m = 1 − c. This solution can be found directly, by substituting y = x 1−c (a0 + a1 x + a2 x 2 + · · · ) into GHE (0.1) and calculating the coefficients. The other way of finding the solution is to ...
Solutions for the exercises - Delft Center for Systems and Control
... Figure 3: Feasible set and contour plot for Exercise 2.1 Solution: Figure 3 shows the contour plot and the feasible region of the optimization problem. The solution is in a vertex of the feasible set, which is obtained with the graphical method (we shift one of the contour lines in a parallel way in ...
... Figure 3: Feasible set and contour plot for Exercise 2.1 Solution: Figure 3 shows the contour plot and the feasible region of the optimization problem. The solution is in a vertex of the feasible set, which is obtained with the graphical method (we shift one of the contour lines in a parallel way in ...
Undecidability of the unification and admissibility problems for
... However, nearly nothing has been known about the decidability status of the unification and admissibility problems for other important modal logics such as the (‘non-transitive’) basic logic K, various multi-modal, hybrid and description logics. In fact, only one—rather artificial—example of a decid ...
... However, nearly nothing has been known about the decidability status of the unification and admissibility problems for other important modal logics such as the (‘non-transitive’) basic logic K, various multi-modal, hybrid and description logics. In fact, only one—rather artificial—example of a decid ...
Positive and Negative Results for Higher
... The long -normal form of a closed term of type 1 : : : n ! is xn :s where the free variables of s are included in xn . The fact that some xi occurs or does not occur in s has a great importance for solving equations or disequations between terms. Given an equation 9X1 ; X2 : xyz:X1 (x; ...
... The long -normal form of a closed term of type 1 : : : n ! is xn :s where the free variables of s are included in xn . The fact that some xi occurs or does not occur in s has a great importance for solving equations or disequations between terms. Given an equation 9X1 ; X2 : xyz:X1 (x; ...
Sensitivity Analysis of Optimal Control Problems with Bang–Bang
... which precludes the application to bang–bang or singular controls. Here, we focus attention on optimal control problems with bang–bang controls. Recently, Agrachev et al. [1] have developed second–order sufficient conditions (SSC) for bang–bang controls which are stated in terms of an associated fin ...
... which precludes the application to bang–bang or singular controls. Here, we focus attention on optimal control problems with bang–bang controls. Recently, Agrachev et al. [1] have developed second–order sufficient conditions (SSC) for bang–bang controls which are stated in terms of an associated fin ...
Predictability and Correlation in Human Metrology
... we involve only the measurements that share some edge with X in the correlation graph, i.e., the members in the subset XCG = {Y |τ < |ρXY |}, where τ is the threshold. The second approach would be to use those measurements that minimize the error when used to predict the unknown measurement. For eac ...
... we involve only the measurements that share some edge with X in the correlation graph, i.e., the members in the subset XCG = {Y |τ < |ρXY |}, where τ is the threshold. The second approach would be to use those measurements that minimize the error when used to predict the unknown measurement. For eac ...
