MATEC Web Conf.
Volume 106, 2017International Science Conference SPbWOSCE-2016 “SMART City”
|Number of page(s)||6|
|Section||4 Applied Mechanics in Construction and Material Science|
|Published online||23 May 2017|
Parameter optimization of the program trajectory of the cellular concrete autoclaving control system
Samara State Technical University, Institute of Architecture and Civil Engineering, 194, Molodogvardeyskaya St., 443001, Samara, Russia
* Corresponding author: email@example.com
Manufacturing of cellular-concrete products that are widely used in modern construction involves high energy consumption attributable mostly to the process of autoclaving. Insufficient elaboration of issues of mathematical description of autoclaving that would be usable in engineering practice and, consequently, the lack of adequate computational models aimed for practicing technologists, make it necessary to use heuristic approaches to parameter determination for the program trajectories of autoclave automatic control systems (ACS) in manufacturing. Therefore, design and development of autoclaving computational models aimed at parameter optimization of the program trajectory is a very relevant issue. The authors have developed mathematical models of cellular concrete autoclave curing and computational algorithms enabling determination of energy consumption under the variation in dynamic parameters of the automatic system's driver unit. Using the methods of conducting computational experiments under the discrete parameter change of the program trajectory, under the conditions of limitation on the temperature derivative of semi-finished concrete and autoclaving process duration, we have established that completion of the known program trajectory as a polygonal line with two variable slope sections of the third section forming unit with a variable slope, enables reduction of energy consumption up to 8%. The research conducted is specifically focused on the use of the obtained results for optimization of cellular concrete autoclaving ACSs.
© The Authors, published by EDP Sciences, 2017
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