TY  - CHAP
A1  - König, Reinhard
A1  - Varoudis, Tasos
T1  - Spatial Optimizations: Merging depthmapX , spatial graph networks and evolutionary design in Grasshopper
T2  - Proceedings of ecaade 34: Complexity & Simplicity
N2  - In the Space Syntax community, the standard tool for computing all kinds of spatial graph network measures is depthmapX (Turner, 2004; Varoudis, 2012). The process of evaluating many design variants of networks is relatively complicated, since they need to be drawn in a separated CAD system, exported and imported in depthmapX via dxf file format. This procedure disables a continuous integration into a design process. Furthermore, the standalone character of depthmapX makes it impossible to use its network centrality calculation for optimization processes. To overcome this limitations, we present in this paper the first steps of experimenting with a Grasshopper component (reference omitted until final version) that can access the functions of depthmapX and integrate them into Grasshopper/Rhino3D. Here the component is implemented in a way that it can be used directly for an evolutionary algorithm (EA) implemented in a Python scripting component in Grasshopper
KW  - depthmapx
KW  - python
KW  - optimization
KW  - space syntax
KW  - grasshopper
Y1  - 2016
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20160622-26040
SP  - 1
EP  - 6
CY  - Oulu, Finland
ER  - 
TY  - INPR
A1  - Rezakazemi, Mashallah
A1  - Mosavi, Amir
A1  - Shirazian, Saeed
T1  - ANFIS pattern for molecular membranes separation optimization
N2  - In this work, molecular separation of aqueous-organic was simulated by using combined soft computing-mechanistic approaches. The considered separation system was a microporous membrane contactor for separation of benzoic acid from water by contacting with an organic phase containing extractor molecules. Indeed, extractive separation is carried out using membrane technology where complex of solute-organic is formed at the interface. The main focus was to develop a simulation methodology for prediction of concentration distribution of solute (benzoic acid) in the feed side of the membrane system, as the removal efficiency of the system is determined by concentration distribution of the solute in the feed channel. The pattern of Adaptive Neuro-Fuzzy Inference System (ANFIS) was optimized by finding the optimum membership function, learning percentage, and a number of rules. The ANFIS was trained using the extracted data from the CFD simulation of the membrane system. The comparisons between the predicted concentration distribution by ANFIS and CFD data revealed that the optimized ANFIS pattern can be used as a predictive tool for simulation of the process. The R2 of higher than 0.99 was obtained for the optimized ANFIS model. The main privilege of the developed methodology is its very low computational time for simulation of the system and can be used as a rigorous simulation tool for understanding and design of membrane-based systems.
Highlights are, Molecular separation using microporous membranes. Developing hybrid model based on ANFIS-CFD for the separation process, Optimization of ANFIS structure for prediction of separation process
KW  - Fluid
KW  - Simulation
KW  - Molecular Liquids
KW  - optimization
KW  - machine learning
KW  - Membrane contactors
KW  - CFD
Y1  - 2018
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20181122-38212
N1  - This is the pre-peer reviewed version of the following article:
https://www.sciencedirect.com/science/article/pii/S0167732218345008, which has been published in final form at https://doi.org/10.1016/j.molliq.2018.11.017.
VL  - 2018
SP  - 1
EP  - 20
ER  -