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Optimization Engr Design

by: Chloe Reilly

Optimization Engr Design ME 6103

Chloe Reilly

GPA 3.62

Berdinus Bras

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Berdinus Bras
Class Notes
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This 0 page Class Notes was uploaded by Chloe Reilly on Monday November 2, 2015. The Class Notes belongs to ME 6103 at Georgia Institute of Technology - Main Campus taught by Berdinus Bras in Fall. Since its upload, it has received 11 views. For similar materials see /class/234235/me-6103-georgia-institute-of-technology-main-campus in Mechanical Engineering at Georgia Institute of Technology - Main Campus.

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Date Created: 11/02/15
ME 6103 Optimization in Engineering Design Bras TERMS COMMONLY USED IN OPTIMIZATION LITERATURE Variables A variable is a factor subject to change within the problem that is its value may change within certain limits Continuous variables Variables that may take on anyvalues between an upper and lower limit are said to be continuous Discrete variables Variables that may take on only certain prescribed values are said to be discrete For instance if x1 can take on only the values 0 1 52 and 1032 then x1 is discrete Integer variables Variables that can take on only integer such as 5 0 2 3 values Integer variables are a special subclass of discrete variables Boolean variables Variables that can take on only the value 0 or 1 false or true Boolean variables are a special subclass of integer variables Decision variable Variable that is under the control of the decision maker and could have an impact on the solution of the problem of interest is termed a decision or control variable System variables These are quantities that specify different states of a system by assuming different values possibly within acceptable ranges Examples are the air ow rate of a compressor the size of an engine System parameters These are quantities that are given one specific value in any particular model statement They are xed by the application of the mode rather than by the underlying phenomenon Examples are atmospheric pressure and required power System constants These are quantities xed by the underlying phenomenon rather than by the particular model statement Typically they are natural constants for example a gas constant and the designer has no in uence upon them Design parameter See de nition of system variable However the term 125ng parameters strengthens the notion that it is a variable being controlled by a designer Mathematical relations These are equalities and inequalities that relate system variables parameters and constants The relations include some type of functional representation Stating these relations is the most difficult part of modeling Linear Functions A linear function contains terms each of which is composed of only a single continuous variable raised to and only to the power of 1 No functions such as cosx logx or expx may be involved Nonlinear Function A nonlinear function is basically the complement of a linear function that is more than a single variable may appear in a single term and the variables may be raised to any power Strictly speaking even if a function satisfies the conditions listed in the de nition of a Dr Bert Bras Telephone 4048949667 Fax 4048949342 Email bertbrasmegatechedu


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