
DDC
| 003.3 |
Tác giả CN
| Kuneš, Josef |
Nhan đề
| Similarity and modeling in science and engineering / Josef Kuneš |
Thông tin xuất bản
| Cambridge :Springer,2012 |
Mô tả vật lý
| 440 p. :ill. ;25 cm. |
Tóm tắt
| The fundamental point of view, enabling one to sort all models, is that of information flux between a model and an original expressed by the similarity and abstraction Each chapter includes original examples and applications. In this respect, the models can be divided into several groups. The following models are dealt with separately by chapter; mathematical and physical models, physical analogues, deterministic, stochastic, and cybernetic computer models. The mathematical models are divided into asymptotic and phenomenological models. The phenomenological models, which can also be called experimental, are usually the result of an experiment on an complex object or process. The variable dimensionless quantities contain information about the real state of boundary conditions, parameter (non-linearity) changes, and other factors. |
Từ khóa tự do
| Simulation methods. |
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245 | |aSimilarity and modeling in science and engineering /|cJosef Kuneš |
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260 | |aCambridge :|bSpringer,|c2012 |
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300 | |a440 p. :|bill. ;|c25 cm. |
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520 | |aThe fundamental point of view, enabling one to sort all models, is that of information flux between a model and an original expressed by the similarity and abstraction Each chapter includes original examples and applications. In this respect, the models can be divided into several groups. The following models are dealt with separately by chapter; mathematical and physical models, physical analogues, deterministic, stochastic, and cybernetic computer models. The mathematical models are divided into asymptotic and phenomenological models. The phenomenological models, which can also be called experimental, are usually the result of an experiment on an complex object or process. The variable dimensionless quantities contain information about the real state of boundary conditions, parameter (non-linearity) changes, and other factors. |
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653 | |aSimulation methods. |
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