scholarly journals Isogeometric Residual Minimization Method (iGRM) with direction splitting preconditioner for stationary advection-dominated diffusion problems

2021 ◽  
Vol 373 ◽  
pp. 113214
Author(s):  
V.M. Calo ◽  
M. Łoś ◽  
Q. Deng ◽  
I. Muga ◽  
M. Paszyński
2017 ◽  
Vol 42 (4) ◽  
pp. 609-617 ◽  
Author(s):  
Artur Nowoświat ◽  
Marcelina Olechowska

Abstract The objective of the residual minimization method is to determine a coefficient correcting the Sabine’s model. The Sabine’s equation is the most commonly applied formula in the designing process of room acoustics with the use of analytical methods. The correction of this model is indispensable for its application in rooms having non-diffusive acoustic field. The authors of the present paper will be using the residual minimization method to work out a suitable correction to be applied for classrooms. For this purpose, five different poorly dampened classrooms were selected, in which the measurements of reverberation time were carried out, and for which reverberation time was calculated with the use of theoretical methods. Three of the selected classrooms had the cubic volume of 258.5 m3 and the remaining two had the cubic volume of 190.8 m3. It was sufficient to estimate the correction for the Sabine’s equation. To verify the results, three other classrooms were selected, in which also the measurements of reverberation time were carried out. The results were verified by means of real measurements of reverberation time and by means of computer simulations in the program ODEON.


2012 ◽  
Vol 2012 ◽  
pp. 1-15
Author(s):  
Hui-Qiang Ma ◽  
Nan-Jing Huang

We consider the expected residual minimization method for a class of stochastic quasivariational inequality problems (SQVIP). The regularized gap function for quasivariational inequality problem (QVIP) is in general not differentiable. We first show that the regularized gap function is differentiable and convex for a class of QVIPs under some suitable conditions. Then, we reformulate SQVIP as a deterministic minimization problem that minimizes the expected residual of the regularized gap function and solve it by sample average approximation (SAA) method. Finally, we investigate the limiting behavior of the optimal solutions and stationary points.


2016 ◽  
Vol 106 ◽  
pp. 42-50 ◽  
Author(s):  
Artur Nowoświat ◽  
Marcelina Olechowska ◽  
Jan Ślusarek

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