Multilevel Optimization Methods in Mechanics

Author(s):  
P. D. Panagiotopoulos ◽  
E. S. Mistakidis ◽  
G. E. Stavroulakis ◽  
O. K. Panagouli
2018 ◽  
Vol 40 (4) ◽  
pp. 25-33
Author(s):  
M. Fialko ◽  
A. Stepanova ◽  
S. Shevchuk ◽  
G. Sbrodova

At present, Ukraine has the necessary potential for the implementation of effective energy-saving technologies for heat recovery, and therefore the problem of their development and implementation is relevant for the country's energy sector. The solution of this problem is related to the need for systematic studies of the efficiency of optimization of heat recovery facilities from the standpoint of modern methodological approaches. The paper outlines the main stages in the development of integrated methods for assessing the efficiency and optimization of heat recovery systems based on the principles of exergic analysis, statistical methods for planning the experiment, structured variational methods, multilevel optimization methods, the theory of linear systems and the thermodynamics of irreversible processes. Examples and illustrations illustrate some of the stages in the development of complex methods. The necessary general step in the development of methodologies is the development of new performance criteria. Such criteria are highly sensitive to changes in the regime and design parameters of heat recovery systems due to the inclusion of some exergic characteristics in them. The developed criteria also serve as target optimization functions. For individual elements of heat recovery systems, efficiency and optimization methods usually include the definition of the functional dependencies of the selected efficiency criteria on the main parameters. For this, balance methods of exergic analysis and statistical methods of experiment planning are used. If such dependencies are established, optimization is carried out using known mathematical methods. For complex heat recovery systems involving a large number of elements, it is not possible to establish general analytical dependencies of the optimization objective functions on the parameters of the system when constructing mathematical models necessary for their optimization. Complex methods based on the basic principles of structural-variant methods, methods of multilevel optimization, the theory of linear systems, and the thermodynamics of irreversible processes have been developed for such cases. For this purpose, structural diagrams of plants, block diagrams of multi-level optimization have been developed, complete input matrices have been constructed, mathematical models for the processes under investigation have been developed, formulas have been derived for calculating the loss of exergy power in heat conduction processes and formulas for calculating dissipators of exergy. A well-founded choice of the methodology for evaluating efficiency and optimization raises the effectiveness of optimization, since it allows the use of parameters maximally close to optimal when developing the heat recovery system design, which in turn increases the efficiency of the system. References 14, figures 5.


2018 ◽  
Author(s):  
Gérard Cornuéjols ◽  
Javier Peña ◽  
Reha Tütüncü
Keyword(s):  

Author(s):  
Gerard Cornuejols ◽  
Reha Tutuncu
Keyword(s):  

Author(s):  
Y. Thomas Hou ◽  
Yi Shi ◽  
Hanif D. Sherali

TAPPI Journal ◽  
2013 ◽  
Vol 12 (4) ◽  
pp. 19-27
Author(s):  
PATRICK HUBER ◽  
LAURENT LYANNAZ ◽  
BRUNO CARRÉ

The fraction of deinked pulp for coated paper production is continually increasing, with some mills using 100% deinked pulp for the base paper. The brightness of the coated paper made from deinked pulp may be reached through a combination of more or less extensive deinking, compensated by appropriate coating, to optimize costs overall. The authors proposed general optimization methods combined with Kubelka-Munk multilayer calculations to find the most economical combination of deinking and coating process that would produce a coated paper made from DIP, at a given target brightness, while maintaining mechanical properties.


2018 ◽  
Author(s):  
Konstantinos Benidis ◽  
Yiyong Feng ◽  
Dajiel P. Palomar

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