scholarly journals DEVELOPMENT OF A METHODOLOGYFOR DETERMINING THE BEST OPTION FOR THE ROUTE OF THE HEAT NETWORK AT THE INITIAL DESIGN STAGE

2021 ◽  
pp. 36-43
Author(s):  
A. A. Chuikina ◽  
M. Ya. Panov ◽  
S. N. Kuznetsov
Keyword(s):  
Mathematical Model ◽  
Vector Optimization ◽  
Optimization Problem ◽  
Pairwise Comparison ◽  
Design Stage ◽  
Heat Network ◽  
Thermal Network ◽  
Initial Design ◽  
Matrix Generalization ◽  
Joint Application

Statement of the problem. Choosing the best option for the route of the thermal network at the initial stage of design is a complex multifactorial task, in addition, due to the lack of a number of necessary design calculations, its solution is accompanied by a limited set of initial data. Thus, it becomes relevant to develop a new methodology for designing the optimal route of the heat supply system considering the qualitative and quantitative characteristics of the discussed object.Results. A mathematical model of a generalized additive vector optimality criterion has been developed, taking into account the material consumption of the heat network, its reliability, construction time, annual thermal losses, heat turnover and temperature dispersion at the consumer. A method is proposed for determining the best option for the route of a thermal network at the initial design stage by jointly solving the optimization problem using vector optimization and matrix generalization methods. The expediency of the joint application of the methods of pairwise comparison and vector optimization in solving the problem under consideration is noted.Conclusions. An important characteristic of the developed mathematical model of the generalized criterion is the possibility of obtaining a more accurate solution to the optimization problem under consideration with an uneven distribution of the heat load by means of a biased estimate of the temperature variance among consumers. A combination of the methods of matrix generalization, pairwise comparison and vector optimization can improve the accuracy of the calculation while solving the optimization problem of choosing the best route of the thermal network.

Development of a Methodology for Determining the Best Option for the Route of the Heat Network at the Initial Design Stage

2021 ◽  
pp. 57-64
Author(s):  
А. А. Чуйкина
Keyword(s):  
Mathematical Model ◽  
Vector Optimization ◽  
Optimization Problem ◽  
Pairwise Comparison ◽  
Design Stage ◽  
Heat Network ◽  
Thermal Network ◽  
Initial Design ◽  
Matrix Generalization ◽  
Joint Application

Постановка задачи. Выбор наилучшего варианта трассы тепловой сети на начальном этапе проектирования является сложной многофакторной задачей, кроме того, ввиду отсутствия ряда необходимых конструктивных расчетов ее решение сопровождается ограниченностью набора исходных данных. Таким образом, становится актуальной разработка новой методики проектирования оптимальной трассы системы теплоснабжения, учитывающей качественные и количественные характеристики рассматриваемого объекта. Результаты. Разработана математическая модель обобщенного аддитивного векторного критерия оптимальности, учитывающая материалоемкость тепловой сети, ее надежность, время строительства, годовые тепловые потери, оборот теплоты и дисперсию температуры у потребителя. Предложен способ определения наилучшего варианта трассы тепловой сети на начальном этапе проектирования путем совместного решения задачи оптимизации методами векторной оптимизации и матричного обобщения. Отмечена целесообразность совместного применения методов попарного сравнения и векторной оптимизации при решении рассматриваемой задачи. Выводы. Важной характеристикой разработанной математической модели обобщенного критерия является возможность получения более точного решения рассматриваемой оптимизационной задачи при неравномерным распределении тепловой нагрузки посредством смещенной оценки дисперсии температуры у потребителей. Совместное применение методов матричного обобщения, попарного сравнения и векторной оптимизации позволяет повысить точность расчета при решении оптимизационной задачи выбора наилучшей трассы тепловой сети. Statement of the problem. Choosing the best option for the route of the thermal network at the initial stage of design is a complex multifactorial task, in addition, due to the lack of a number of necessary design calculations, its solution is accompanied by a limited set of initial data. Thus, it becomes relevant to develop a new methodology for designing the optimal route of the heat supply system, taking into account the qualitative and quantitative characteristics of the object under consideration. Results. A mathematical model of a generalized additive vector optimality criterion has been developed, taking into account the material consumption of the heat network, its reliability, construction time, annual thermal losses, heat turnover and temperature dispersion at the consumer. A method is proposed for determining the best option for the route of a thermal network at the initial design stage by jointly solving the optimization problem using vector optimization and matrix generalization methods. The expediency of the joint application of the methods of pairwise comparison and vector optimization in solving the problem under consideration is noted. Conclusions. An important characteristic of the developed mathematical model of the generalized criterion is the possibility of obtaining a more accurate solution to the optimization problem under consideration with an uneven distribution of the heat load by means of a biased estimate of the temperature variance among consumers. The combined application of the methods of matrix generalization, pairwise comparison and vector optimization can improve the accuracy of the calculation when solving the optimization problem of choosing the best route of the thermal network.

FEATURES OF APPLICATION OF SMALL RECONNAISSANCE ROBOT

2019 ◽  
pp. 29-38 ◽  
Author(s):  
R. Zinko ◽  
P. Kazan ◽  
D. Khaustov ◽  
O. Bilyk
Keyword(s):  
Mathematical Model ◽  
Armed Forces ◽  
Climatic Conditions ◽  
Design Stage ◽  
Experimental Sample ◽  
Single Trial ◽  
Test Cycle ◽  
Military Equipment ◽  
The Mathematical Model ◽  
Human Losses

A small intelligence robot (SSR) is a special military intelligence means. It is used to obtain information about the enemy - the collection of intelligence, the search for targets and target indication, observation of the situation, etc. The use of a small intelligence robot is assumed in various natural and climatic conditions: in temperate terrain, on soils with low bearing capacity, at low temperatures, in the desert, on sandy and marshy soils, on rocky soils, in elevated temperature and dustiness of air, and also in conditions highlands In the article an overview of modern developments of remotely controlled robotic military complexes, principles of their construction and perspective directions of development in the armed forces are reviewed. The issues of robotization of existing weapons and military equipment are considered. Every sample of a SSR used in combat action must possess all combat characteristics at once in an optimal ratio between them, ensuring its maximum effectiveness. Ignoring any of the properties or enhancing one property at the expense of others will not enable the full realization of the small surveillance robot. It is reasonable to select the relevant properties at the design stage, using the possibilities of mathematical modeling. The set of tactical and technical characteristics of the SSR allowed forming this. Its characteristics determine the scope and possibilities of application. The mathematical model of the SSR motion is written in the Matlab Simulink environment. Recorded mathematical model of SSR motion, formed single test cycle and input data allowed to conduct computer simulation of motion in possible conditions of operation of small surveillance robot.The single trial cycle presented contains a set of individual sites and reproduces the testing test cycle of a real polygon. On the basis of the developed tactical and technical characteristics of the SSR, the experimental sample was made. An example of the use of SSR for the intelligence of the settlement and at keeping the node of barriers has been provided. The efficiency of performing intelligence units’ tasks and reducing the risk of human losses are shown.

Pipe Routing using Reinforcement Learning on Initial Design Stage

2020 ◽  
Vol 57 (4) ◽  
pp. 191-197
Author(s):  
Dong-seon Shin ◽  
Byeong-cheol Park ◽  
Chae-og Lim ◽  
Sang-jin Oh ◽  
Gi-yong Kim ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Design Stage ◽  
Initial Design ◽  
Pipe Routing

scholarly journals Vector variational inequalities and their relations with vector optimization

2013 ◽  
Vol 4 (1) ◽  
pp. 35-44 ◽  
Author(s):  
Surjeet Kaur Suneja ◽  
Bhawna Kohli
Keyword(s):  
Variational Inequalities ◽  
Vector Optimization ◽  
Optimization Problem ◽  
Vector Optimization Problem ◽  
Clarke Subdifferential ◽  
Vector Variational Inequalities ◽  
Regularity Assumption ◽  
Weak Minimum ◽  
Minimum Solution ◽  
Clarke Subdifferentials

In this paper, K- quasiconvex, K- pseudoconvex and other related functions have been introduced in terms of their Clarke subdifferentials, where   is an arbitrary closed convex, pointed cone with nonempty interior. The (strict, weakly) -pseudomonotonicity, (strict) K- naturally quasimonotonicity and K- quasimonotonicity of Clarke subdifferential maps have also been defined. Further, we introduce Minty weak (MVVIP) and Stampacchia weak (SVVIP) vector variational inequalities over arbitrary cones. Under regularity assumption, we have proved that a weak minimum solution of vector optimization problem (VOP) is a solution of (SVVIP) and under the condition of K- pseudoconvexity we have obtained the converse for MVVIP (SVVIP). In the end we study the interrelations between these with the help of strict K-naturally quasimonotonicity of Clarke subdifferential map.

Derivatives of Hadamard type in vector optimization

2018 ◽  
Vol 68 (2) ◽  
pp. 421-430
Author(s):  
Karel Pastor
Keyword(s):  
Nonlinear Analysis ◽  
Optimality Conditions ◽  
Vector Optimization ◽  
Optimality Condition ◽  
Optimization Problem ◽  
Vector Optimization Problem ◽  
Dini Derivatives ◽  
Scalar Optimality ◽  
Derivatives Of

Abstract In our paper we will continue the comparison which was started by Vsevolod I. Ivanov [Nonlinear Analysis 125 (2015), 270–289], where he compared scalar optimality conditions stated in terms of Hadamard derivatives for arbitrary functions and those which was stated for ℓ-stable functions in terms of Dini derivatives. We will study the vector optimization problem and we show that also in this case the optimality condition stated in terms of Hadamard derivatives is more advantageous.

Mathematical Model for the Influence of Machine Tool Parts Deformation on Machining Accuracy

2014 ◽  
Vol 556-562 ◽  
pp. 1354-1357
Author(s):  
Li Gong Cui ◽  
Gui Qiang Liang ◽  
Fang Shao
Keyword(s):  
Mathematical Model ◽  
Mathematical Method ◽  
Machine Tool ◽  
Cutting Tool ◽  
Lower Surface ◽  
Design Stage ◽  
Machining Accuracy ◽  
Cutting Point ◽  
The Mathematical Model

This paper presents a mathematical method to analyze the influence of each machine tool part deformation on the machining accuracy. Taking a 3-axis machine tool as an example, this paper divides the machine tool into the cutting tool sub-system and workpiece sub-system. Taking the deformation of lower surface of the machine bed as the research target, the mathematical model of the deformation on the displacement of the cutting point was established. In order to distribute the stiffness of each part, the contribution degree of each part on the machining accuracy was analyzed. Using this mathematical model, the stiffness of each part can be distributed at the design stage of the machine tool, and the machining accuracy of the machine tool can be improved economically.

scholarly journals Development of Design Process Simulator for the Ship Initial Design Stage

2009 ◽  
Vol 9 (0) ◽  
pp. 211-222
Author(s):  
Kunihiro Hamada ◽  
Mitsuru Kitamura ◽  
Souichi Yasui ◽  
Hiroshi Kawasaki
Keyword(s):  
Design Process ◽  
Design Stage ◽  
Initial Design ◽  
Process Simulator
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