scholarly journals A Problem-Oriented System of Control and Optimization of Basic Parameters of Technical Complex Systems

2021 ◽  
Vol 27 (3) ◽  
pp. 336-344
Author(s):  
E. I. Martyanov ◽  
S. V. Karpushkin ◽  
V. V. Alekseev
Keyword(s):  
Complex Systems ◽  
Empirical Equations ◽  
Traditional Methods ◽  
Design Problems ◽  
Optimization System ◽  
Basic Parameters ◽  
Blade Mixer ◽  
Technical Complex ◽  
Oriented System

: The paper proposes a methodology for the development of a control and optimization system, which is used to solve the design problems of technical complex systems. The systems developed on the basis of this methodology are easy to use and create more accurate estimates of the values of the parameters of technical complex systems than using traditional methods based on solving empirical equations. An example of the implementation of the proposed methodology is a problem-oriented system designed to optimize the parameters of a two-blade mixer of a vertical capacitive apparatus.

Handling Multiple Objectives in Decentralized Design

2005 ◽  
Author(s):  
Vincent Chanron ◽  
Kemper Lewis ◽  
Yayoi Murase ◽  
Kazuhiro Izui ◽  
Shinji Nishiwaki ◽  
...  
Keyword(s):  
Complex Systems ◽  
Design Solution ◽  
Distributed Environments ◽  
Engineering Systems ◽  
Design Problems ◽  
Design Requirements ◽  
Decentralized Design ◽  
Set Based Design ◽  
Standard Techniques ◽  
Different Parts

Most complex systems, including engineering systems such as cars, airplanes, and satellites, are the results of the interactions of many distinct entities working on different parts of the design. Decentralized systems constitute a special class of design under distributed environments. They are characterized as large and complex systems divided into several smaller entities that have autonomy in local optimization and decision-making. A primary issue in decentralized design processes is to ensure that the designers that are involved in the process converge to a single design solution that is optimal and meets the design requirements, while being acceptable to all the participants. This is made difficult by the strong interdependencies between the designers, which are usually characteristic of such systems. This paper proposes a critical review of standard techniques to modeling and solving decentralized design problems, and shows mathematically the challenges created by having multiobjective subsystems. A method based on set-based design is then proposed to alleviate some of these challenging issues. An illustration of its applicability is given in the form of the design of a space satellite.

Relationship between Fractal Dimension and Structure of Nonwovens

2013 ◽  
Vol 750-752 ◽  
pp. 1176-1179
Author(s):  
Shu Yang
Keyword(s):  
Fractal Dimension ◽  
Structural Parameters ◽  
Average Density ◽  
Traditional Methods ◽  
Pore Characteristics ◽  
Fractal Approach ◽  
Basic Parameters ◽  
The Relationship

The structures of nonwovens are so nonlinear and out-of-order that traditional methods can hardly measure it. There exist several basic parameters to characterize it, such as thickness, grammage, average density and pore characteristics etc.. It is necessary to find one integrated parameter to characterize nonwovens, and fractal approach seems to be a useful tool. In this paper, the fractal dimension is implemented to describe the structure of nonwovens. And then the relationship between the fractal dimension and several basic structural parameters are built up.

ACCOUNTING FOR UNCERTAINTY AND RANDOM RISKS OF ACTIVATION OF COMPLEX NATURAL PROCESSES USING THE BAYES TRUST NETWORK

2021 ◽  
Vol 1 (2) ◽  
pp. 38-49
Author(s):  
L. S. Zvyagin ◽  
Keyword(s):  
Complex Systems ◽  
A Priori ◽  
Bayesian Theory ◽  
Conditional Probabilities ◽  
Traditional Methods ◽  
Trust Network ◽  
Natural Processes ◽  
Stochastic Component ◽  
Modeling And Forecasting ◽  
The Impact

In the research, modeling, and forecasting of complex systems associated with various natural processes, scientists have encountered uncertainty and unpredictability. In order to eliminate or reduce the impact of uncertainty on the prediction of complex natural processes and to determine possible catastrophic consequences, traditional methods and models are not applicable and do not show reliable results, since they do not take into account the stochastic component. The article deals with the use of Bayesian theory in various spheres of life, and will also consider and highlight the factors that have a significant impact on the activation and flow of the processes and phenomena under consideration. The Bayes trust network is constructed and trained by filling in tables of conditional probabilities by experts and introducing numerical values of factors to determine the unconditional (a priori) probabilities of the factors under consideration. The constructed network can be supplemented, if necessary, with vertices and connections between them.

An optimization based algorithm for solving design problems of counter-current multistage batch solid–liquid extractors for complex systems: Application to vanilla extract

2016 ◽  
Vol 89 ◽  
pp. 53-61 ◽  
Author(s):  
K. Castillo-Santos ◽  
R.O. Aguirre-Alonso ◽  
G.C. Rodríguez-Jimenes ◽  
V.J. Robles-Olvera ◽  
M.A. Salgado-Cervantes ◽  
...  
Keyword(s):  
Complex Systems ◽  
Design Problems ◽  
Solid Liquid ◽  
Counter Current

Integrating urban analysis, generative design, and evolutionary optimization for solving urban design problems

2019 ◽  
Vol 47 (6) ◽  
pp. 997-1013
Author(s):  
Reinhard Koenig ◽  
Yufan Miao ◽  
Anna Aichinger ◽  
Katja Knecht ◽  
Kateryna Konieva
Keyword(s):  
Urban Design ◽  
Data Representation ◽  
Evolutionary Optimization ◽  
Urban Environments ◽  
Design Problems ◽  
Automated Generation ◽  
Optimization System ◽  
Master Design ◽  
Evolutionary Optimization Algorithms ◽  
Computational Representation

To better support urban designers in planning sustainable, resilient, and livable urban environments, new methods and tools are needed. A variety of computational approaches have been proposed, including different forms of spatial analysis to evaluate the performance of design proposals, or the automated generation of urban design proposals based on specific parameters. However, most of these propositions have produced separate tools and disconnected workflows. In the context of urban design optimization procedures, one of the main challenges of integrating urban analytics and generative methods is a suitable computational representation of the urban design problem. To overcome this difficulty, we present a holistic data representation for urban fabrics, including the layout of street networks, parcels, and buildings, which can be used efficiently with evolutionary optimization algorithms. We demonstrate the use of the data structure implemented for the software Grasshopper for Rhino3D as part of a flexible, modular, and extensible optimization system that can be used for a variety of urban design problems and is able to reconcile potentially contradicting design goals in a semi-automated design process. The proposed optimization system aims to assist a designer by populating the design space with options for more detailed exploration. We demonstrate the functionality of our system using the example of an urban master-design project for the city of Weimar.

Models and Concepts for Socio-Technical Complex Systems: Towards Fractal Social Organizations

2013 ◽  
Vol 30 (6) ◽  
pp. 750-772 ◽  
Author(s):  
Vincenzo De Florio ◽  
Mohamed Bakhouya ◽  
Antonio Coronato ◽  
Giovanna Di Marzo
Keyword(s):  
Complex Systems ◽  
Social Organizations ◽  
Technical Complex

scholarly journals Representing Complex Analogues Using a Function Model to Support Conceptual Design

2018 ◽  
Author(s):  
L. Siddharth ◽  
Amaresh Chakrabarti ◽  
Srinivasan Venkataraman
Keyword(s):  
Complex Systems ◽  
Engineering Design ◽  
Levels Of Abstraction ◽  
Function Model ◽  
Design Problems ◽  
Web Based ◽  
Proposed Model ◽  
Engineering Design Problems ◽  
Biological Domain ◽  
Engineered Systems

Analogical design has been a long-standing approach to solve engineering design problems. However, it is still unclear as to how analogues should be presented to engineering design in order to maximize the utility of these. The utility is minimal when analogues are complex and belong to other domain (e.g., biology). Prior work includes the use of a function model called SAPPhIRE to represent over 800 biological and engineered systems. SAPPhIRE stands for the entities: States, Actions, Parts, Phenomena, Inputs, oRgans, and Effects that together represent the functionality of a system at various levels of abstraction. In this paper, we combine instances of SAPPhIRE model for representing complex systems (also from the biological domain). We use an electric buzzer to illustrate and compare the efficacy of this model in explaining complex systems with that of a well-known model from literature. The use of multiple-instance SAPPhIRE model instances seems to provide a more comprehensive explanation of a complex system, which includes elements of description that are not present in other models, providing an indication as to which elements might have been missing from a given description. The proposed model is implemented in a web-based tool called Idea-Inspire 4.0, a brief introduction of which is also provided.

A Distributed Pool Architecture for Highly Constrained Optimization Problems in Complex Systems Design

2011 ◽  
Author(s):  
Vijitashwa Pandey ◽  
Zissimos P. Mourelatos
Keyword(s):  
Complex Systems ◽  
Optimization Problems ◽  
Mechanical Design ◽  
Systems Design ◽  
Optimization Approach ◽  
Dynamic Changes ◽  
Design Problems ◽  
Complete Knowledge ◽  
Design Variables ◽  
Design Requirements

The design of complex systems design is challenging because of the presence of numerous design variables and constraints. Dynamic changes in design requirements and lack of complete knowledge of subsystem requirements add to the complexity. A recently proposed pool architecture has been shown to aide distributed solving of optimization problems. The approach not only saves solution time but also has other benefits like resiliency against failures of some processors. We apply this approach in this paper, to highly constrained design problems, with dynamically changing constraints, where finding a feasible solution is challenging. This task is distributed between the processors in the methodology we propose. We demonstrate the efficacy of our method using an MINLP-class of mechanical design optimization problem. We demonstrate the computational savings and the resistance to partial failures in the processors. In addition, we show how the optimization approach can adapt to dynamic changes in design constraints.

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