In particular, this paper focuses on the estimation of the partition coefficient of the AI in the polymer through activity coefficients, that are estimated with a group-contribution model for polymers (GC-Flory EoS).
Therefore, the estimation of the DME-partitioning coefficient (KDME) is crucial to evaluate and understand the performance of DME-enhanced waterflooding (DEW) at reservoir or lab/pilot-scale.
Some authors, using Bayesian methodology, have avoided the visualisation problem by considering only point estimation of the sample partition (Corander et al., 2003; Huelsenbeck et al., 2007; Coulon et al., 2008).
The resulting algorithm allows for the efficient estimation of the random-cluster partition function encoding the information of all Potts models, even with a non-integer number of states, for all temperatures in a single simulation run per system size.
Furthermore, the k-means algorithm itself is somewhat stochastic in nature, and so it is likely that repeated analyses of the same dataset might lead to the estimation of partitioning schemes with very minor differences.
The standard varieties used to connect the different blocks enabled estimation of the inter-block variance and partitioning of the variance into block and error components.
The major objective of hydrocyclone modelling is estimation of the separation in form of the partition curve.
The SPME technique can be used to determine the partitioning of HOCs in a three-phase water system consisting of a solution, dissolved organic matter, and particulate organic matter and allows for the estimation of specific partition coefficients such as KOC and KDOC[16, 21, 22].
The irreversible binding characteristics and the stability of regional [123I]FP-CIT and of [123I]IBZM uptake have been shown to allow estimation of the specific-to-nondisplaceable equilibrium partition coefficient (V3″), which is proportional to free transporter or receptor density (Bmax) [48], [49].
