. . "RIV/68407700:21110/12:00203304!RIV13-GA0-21110___" . "21110" . "Processor Farming in Homogenization of Coupled Heat and Moisture Transfer" . "Coupled heat and moisture transport in extremely heterogeneous materials like a ma- sonry still cannot be solved for large strucutres. Multi-scale methods with the macro and meso-scale levels are usually used. The biggest disadvantage of such methods stems from their enormous computational demands. Small coupled problem on the meso-scale level has to be solved for every integration point of the macro-scale prob- lem. The number of the integration points is in thousands or tens of thousands. The multi-scale method can be efficiently implemented in parallel because the particular computations connected with the integration points are totally independent. The strat- egy denoted the processor farming can be used."@en . "Krej\u010D\u00ED, Tom\u00E1\u0161" . "Proceedings of the Eighth International Conference on Engineering Computational Technology" . . . "Edinburgh" . . "RIV/68407700:21110/12:00203304" . "P(GAP105/10/1682)" . "Processor Farming in Homogenization of Coupled Heat and Moisture Transfer"@en . . "Civil-Comp Press" . . . "S\u00FDkora, Jan" . "13"^^ . . "Kruis, Jaroslav" . . "\u0160ejnoha, Michal" . "Dubrovnik, Croatia" . "1759-3433" . . "Processor Farming in Homogenization of Coupled Heat and Moisture Transfer" . . . "2012-09-04+02:00"^^ . . . . "coupled heat and moisture transport; Kunzel model; parallel computing"@en . "4"^^ . "978-1-905088-55-3" . "Processor Farming in Homogenization of Coupled Heat and Moisture Transfer"@en . "162421" . "4"^^ . . . . "Coupled heat and moisture transport in extremely heterogeneous materials like a ma- sonry still cannot be solved for large strucutres. Multi-scale methods with the macro and meso-scale levels are usually used. The biggest disadvantage of such methods stems from their enormous computational demands. Small coupled problem on the meso-scale level has to be solved for every integration point of the macro-scale prob- lem. The number of the integration points is in thousands or tens of thousands. The multi-scale method can be efficiently implemented in parallel because the particular computations connected with the integration points are totally independent. The strat- egy denoted the processor farming can be used." . "[8B064CB1E324]" . .