000089249 001__ 89249
000089249 005__ 20181203020530.0
000089249 0247_ $$2doi$$a10.1016/0045-7825(95)00793-Z
000089249 022__ $$a0045-7825
000089249 02470 $$2ISI$$aA1995RM28900002
000089249 037__ $$aARTICLE
000089249 245__ $$aAn Adaptive Finite-Element Algorithm for a 2-Dimensional Stationary Stefan-Like Problem
000089249 260__ $$c1995
000089249 269__ $$a1995
000089249 336__ $$aJournal Articles
000089249 500__ $$aPicasso, m, ecole polytech fed lausanne,dept math,ch-1015 lausanne,switzerland.
000089249 500__ $$aISI Document Delivery No.: RM289
000089249 500__ $$aTimes Cited: 5
000089249 500__ $$aCited Reference Count: 48
000089249 520__ $$aAn efficient adaptive algorithm is presented for a stationary regularized Stefan problem in 2D. The adaptive criteria relies upon a posteriori estimates based on the residual equation. Since the problem we are studying is a non-linear diffusion-convection problem, these error estimates are relatively crude in the sense that the constant relating the true error to the error indicator is unknown. Thus, instead of trying to build a mesh such that the true error is below a given tolerance, the local error indicator is equidistributed in a way such that the final number of triangles is close to a desired value. At each iteration of the adaptive algorithm, the new triangulation is obtained from the previous one by adding or deleting vertices according to the error indicator and a global mesh regeneration is performed using a Delaunay mesh generator. Numerical experiments for two practical situations show the efficiency and the robustness of our approach.
000089249 6531_ $$aPOSTERIORI ERROR ESTIMATORS
000089249 6531_ $$aPARABOLIC PROBLEMS
000089249 6531_ $$aLINEAR SCHEME
000089249 6531_ $$aSOLIDIFICATION
000089249 6531_ $$aIMPLEMENTATION
000089249 6531_ $$aTRIANGULATIONS
000089249 6531_ $$aSIMULATION
000089249 6531_ $$aEQUATIONS
000089249 700__ $$g106096$$aPicasso, M.$$0241282
000089249 773__ $$j124$$tComputer Methods in Applied Mechanics and Engineering$$k3$$q213-230
000089249 909C0 $$xU10795$$0252201$$pASN
000089249 909CO $$pSB$$particle$$ooai:infoscience.tind.io:89249
000089249 937__ $$aASN-ARTICLE-1995-002
000089249 970__ $$a95/ASN
000089249 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000089249 980__ $$aARTICLE