Numerical optimization of partial pressures of working mixture excimer HgBr/Hgl lamp

2000 ◽  
Vol 7 (0) ◽  
pp. 127-130
Author(s):  
А. В. Поляк ◽  
М. М. Гуйван ◽  
О. М. Малінін
Keyword(s):  
Numerical Optimization ◽  
Partial Pressures

Numerical optimization of a Francis turbine’s guide vane axis location including inflow uncertainties

2013 ◽  
pp. 36-41
Author(s):  
Olivier Brugière ◽  
Guillaume Balarac ◽  
Christophe Corre ◽  
Olivier Métais ◽  
Emmanuel Flores ◽  
...  
Keyword(s):  
Numerical Optimization ◽  
Guide Vane

Numerical Optimization of a Centrifugal Pump Impeller with Splitter Blades Running in Reverse Mode

2016 ◽  
Vol 10 (4) ◽  
pp. 215 ◽  
Author(s):  
Ioannis Kassanos ◽  
Marios Chrysovergis ◽  
John Anagnostopoulos ◽  
George Charalampopoulos ◽  
Stamelos Rokas ◽  
...  
Keyword(s):  
Centrifugal Pump ◽  
Numerical Optimization ◽  
Pump Impeller ◽  
Reverse Mode ◽  
Centrifugal Pump Impeller

Numerical Optimization Algorithm for Unsteady Flows of Rotor based on Web Service

2019 ◽  
pp. -1--1
Author(s):  
Jilin Zhang ◽  
Xuechao Liu ◽  
Jian Wan ◽  
Yongjian Ren ◽  
Binglin Xu ◽  
...  
Keyword(s):  
Web Service ◽  
Optimization Algorithm ◽  
Numerical Optimization ◽  
Unsteady Flows

Corrosion behavior of pipeline steel welds in simulated produced water with different CO2 partial pressures under high temperature

2017 ◽  
Vol 59 (4) ◽  
pp. 348-354 ◽  
Author(s):  
Yongxin Lu ◽  
Hongyang Jing ◽  
Yongdian Han ◽  
Lianyong Xu
Keyword(s):  
High Temperature ◽  
Corrosion Behavior ◽  
Produced Water ◽  
Pipeline Steel ◽  
Partial Pressures ◽  
Steel Welds

M-Elite Coevolutionary Algorithm for Numerical Optimization

2009 ◽  
Vol 20 (11) ◽  
pp. 2925-2938 ◽  
Author(s):  
Cai-Hong MU ◽  
Li-Cheng JIAO ◽  
Yi LIU
Keyword(s):  
Numerical Optimization ◽  
Coevolutionary Algorithm

NDBEPR PROCESS OPTIMIZATION IN SBRs: REDUCTION OF EXTERNAL CARBON-SOURCE AND OXYGEN SUPPLY

1994 ◽  
Vol 30 (4) ◽  
pp. 169-179 ◽  
Author(s):  
Carl Demuynck ◽  
Peter Vanrolleghem ◽  
Carine Mingneau ◽  
Jan Liessens ◽  
Willy Verstraete
Keyword(s):  
Process Optimization ◽  
Phosphorus Removal ◽  
Numerical Optimization ◽  
Cost Savings ◽  
Operating Costs ◽  
Nitrification Rate ◽  
Aeration Time ◽  
Time Scheduling ◽  
Better Than ◽  
The Ideal

In SBR plants for nutrient removal it is often necessary to add supplementary rbCOD during the anoxic phase to obtain complete nitrogen removal. In addition to the aeration, this supply of high-quality BOD is a non-negligible part in the operating costs. Because of the complexity of the bighly interconnected biological processes a heuristic approach for process optimization is hardly possible. Therefore the Nitrification Denitrification Biological Excess Phosphorus Removal (NDBEPR) model of Wentzel et al. and a numerical optimization a1goritbm were used to optimize SBR time scheduling, i.e. minimize both effluent concentrations and operating costs. It was found that a sequence of short aerobic/anoxic phases appears to be better than the usual sequence (one aerobic phase followed by one anoxic phase). This result was validated on a 500 I scale SBR. The optimized process saves up to 50% on extra BOD supply and up to 30% on aeration time. Moreover, it was shown that these cost savings were not at the expense of the phosphorus removal efficiency or the nitrification rate. From an additional numerical optimization it was seen that the ideal SBR time scheduling may depend on the loading. Therefore. a control strategy hased on OUR and ORP measurements is proposed.

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