Combining Mathematical Programming and SysML for Automated Component Sizing of Hydraulic Systems

Author(s):  
Aditya A. Shah ◽  
Christiaan J. J. Paredis ◽  
Roger Burkhart ◽  
Dirk Schaefer

In this paper, we present a framework for automated component sizing to extend a designer's ability to evaluate a particular configuration during the architecture exploration phase of a design process. Component sizing is a hard problem to solve, both from a computational and modeling aspect. This is because of competing objectives, requirements from multiple disciplines, and the need to find a good solution quickly for the architecture being considered. In current approaches, designers rely on heuristics and iterate over the multiple objectives and requirements until a satisfactory solution is found. To improve on this state of practice, we introduce advances in the following two areas: (a) solving the problem efficiently so that all of the imposed requirements are satisfied simultaneously and the solution obtained is mathematically optimal and (b) modeling a component sizing problem in a manner that is convenient to designers. An acausal, algebraic, equation-based, declarative modeling approach using mathematical programming (GAMS) is taken to solve these problems more efficiently. The object management group systems modeling language (OMG SysML™) is used to model component sizing problems in order to facilitate problem formulation, model reuse and automatic generation of low-level code that can be solved using GAMS and its solvers. This framework is demonstrated by applying it to an example of a hydraulic log splitter. Based on this initial example, we discuss two advantages of this framework—total time taken in solving multiple scenarios for a given configuration and the graphical representation of a problem in SysML.

Author(s):  
Aditya A. Shah ◽  
Christiaan J. J. Paredis ◽  
Roger Burkhart ◽  
Dirk Schaefer

In this paper, we present a framework that improves a designer’s capability to determine near-optimal sizes of components for a given system architecture. Component sizing is a hard problem to solve because of competing objectives, requirements from multiple disciplines, and the need for finding a solution quickly for the architecture being considered. In current approaches, designers rely on heuristics and iterate over the multiple objectives and requirements until a satisfactory solution is found. To improve on this state of practice, we introduce advances in the following two areas: a) Formulating a component sizing problem in a manner that is convenient to designers and b) Solving the problem efficiently so that all of the imposed requirements are satisfied simultaneously and the solution obtained is mathematically optimal. An acausal, algebraic, equation-based, declarative modeling approach using mathematical programming (GAMS) is taken to solve these problems more efficiently. In addition the Systems Modeling Language (OMG SysML™) is used to formulate component sizing problems to facilitate problem formulation, model reuse and the automatic generation of low-level code that can be solved using GAMS and its solvers (BARON). This framework is demonstrated by applying it to an example of a hydraulic log splitter.


Author(s):  
Aleksandr A. Kerzhner ◽  
Christiaan J. J. Paredis

Modern systems are difficult to design because there are a significant number of potential alternatives to consider. The specification of an alternative includes an architecture (which describes the components and connections of the system) and component sizings (the sizing parameter for each component). In current practice, designers rely mainly on their experience and intuition to select a desired architecture without much computational support and then spend most of their effort on optimizing component sizings. In this paper, an approach for representing an architecture selection as a mixed-integer linear programming optimization is presented; existing solvers are then used to identify promising candidate architectures at early stages of the design process. Mathematical programming is a common optimization technique, but it is rarely used for architecture selection because of the difficulty of manually formulating an architecture selection as a mathematical program. In this paper, the formulation is presented in a modular fashion so that model transformations can be applied to transform a problem formulation that is convenient for designers into the mathematical programming optimization. A modular superstructure representation is used to model the design space; in a superstructure a union of all potential architectures is represented as a set of discrete and continuous variables. Algebraic constraints are added to describe both acceptable variable combinations and system behavior to allow the solver to eliminate clearly poor alternatives and identify promising alternatives. The framework is demonstrated on the selection of an actuation subsystem for a hydraulic excavator, although the solution approach would be similar for most mechanical systems.


2016 ◽  
Vol 9 (1) ◽  
pp. 48-51
Author(s):  
Сазонова ◽  
Svetlana Sazonova

Problem definition of parametrical optimization of hydraulic systems is considered. The general problem of parametrical optimization for systems of water supply and gas supply is presented in the form of a problem of mathematical programming. As a result of the solution of the considered task optimum parameters of the studied systems have to be determined, the required levels of reliability and safety when functioning are ensured.


Author(s):  
Luisa Lugli ◽  
Stefania D’Ascenzo ◽  
Roberto Nicoletti ◽  
Carlo Umiltà

Abstract. The Simon effect lies on the automatic generation of a stimulus spatial code, which, however, is not relevant for performing the task. Results typically show faster performance when stimulus and response locations correspond, rather than when they do not. Considering reaction time distributions, two types of Simon effect have been individuated, which are thought to depend on different mechanisms: visuomotor activation versus cognitive translation of spatial codes. The present study aimed to investigate whether the presence of a distractor, which affects the allocation of attentional resources and, thus, the time needed to generate the spatial code, changes the nature of the Simon effect. In four experiments, we manipulated the presence and the characteristics of the distractor. Findings extend previous evidence regarding the distinction between visuomotor activation and cognitive translation of spatial stimulus codes in a Simon task. They are discussed with reference to the attentional model of the Simon effect.


2012 ◽  
Author(s):  
Kelci Conti ◽  
Laura S. Guy ◽  
Rebecca Nelson ◽  
Samantha L. Fusco

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