precede 发表于 2025-3-25 03:45:26
Stochastic Differential Equations and Related Inverse Problems,hich is a measure of the distance a solute tracer would travel when the mean velocity is normalized to be one. One would expect such a measure to be a mechanical property of the porous medium under consideration, but the evidence are there to show that dispersivity is dependent on the scale of the eGRAIN 发表于 2025-3-25 10:42:22
http://reply.papertrans.cn/67/6672/667107/667107_22.pngDigest 发表于 2025-3-25 14:25:39
http://reply.papertrans.cn/67/6672/667107/667107_23.pngGNAW 发表于 2025-3-25 16:19:07
http://reply.papertrans.cn/67/6672/667107/667107_24.png有毒 发表于 2025-3-25 21:50:00
http://reply.papertrans.cn/67/6672/667107/667107_25.pngfinale 发表于 2025-3-26 01:14:33
The Stochastic Solute Transport Model in 2-Dimensions, porous media for the flow lengths ranging from 1 to 10000 m. For computational efficiency, we have employed one of the fastest converging kernels tested in Chapter 6 for illustrative purposes, but, in principle, the SSTM should provide scale independent behaviour for any other velocity covariance kapropos 发表于 2025-3-26 04:24:52
Multiscale Dispersion in Two Dimensions, directions using the stochastic inverse method (SIM), which is based on the maximum likelihood method. We have seen that transverse dispersion coefficient relative to longitudinal dispersion coefficient increases as .. increases when the flow length is confined to 1.0. In this chapter, we extend thLipohypertrophy 发表于 2025-3-26 11:38:32
Stochastic Differential Equations and Related Inverse Problems,l mathematical setting. In this chapter we review some essential concepts in stochastic processes and stochastic differential equations in order to understand the stochastic calculus in a more applied context.行为 发表于 2025-3-26 14:56:41
http://reply.papertrans.cn/67/6672/667107/667107_29.pngGLADE 发表于 2025-3-26 18:52:39
Don Kulasirin, this representation appears to be useful for a number of other execution methods, including interpretation, compilation into conventional Lisp with “promises”, and mapping into “supercombinators” for parallel architectures.