1964
DOI: 10.1177/003754976400300210
|View full text |Cite
|
Sign up to set email alerts
|

The Use of Parameter Influence Coefficients in Computer Analysis of Dynamic Systems

Abstract: A new computer technique is described which yields the partial derivatives of problem variables with respect to pertinent system parameters simultaneously with the solution of the original system differential

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
5
0

Year Published

1965
1965
1979
1979

Publication Types

Select...
5
3

Relationship

0
8

Authors

Journals

citations
Cited by 11 publications
(5 citation statements)
references
References 3 publications
0
5
0
Order By: Relevance
“…Table 5 presents Influence coefficients and the ranking of parameters by influence coefficient for a run based on constant "solid" draft gear stiffnesses (Kcpgi and Kc^cg) of 3 x 10 lbs(force)/inch (see Table 3 and Figures 15 and 16). Table 6 presents results for a simulation run based on "solid" draft gear stiffnesses that varied as functions of the relative displacement X,= X,c -Xp (6) beyond the maximum value of Xj for the "active" state. (See Table 4 and Figures 17 and 18).…”
Section: Parametric and Sensitivity Analysismentioning
confidence: 99%
“…Table 5 presents Influence coefficients and the ranking of parameters by influence coefficient for a run based on constant "solid" draft gear stiffnesses (Kcpgi and Kc^cg) of 3 x 10 lbs(force)/inch (see Table 3 and Figures 15 and 16). Table 6 presents results for a simulation run based on "solid" draft gear stiffnesses that varied as functions of the relative displacement X,= X,c -Xp (6) beyond the maximum value of Xj for the "active" state. (See Table 4 and Figures 17 and 18).…”
Section: Parametric and Sensitivity Analysismentioning
confidence: 99%
“…The term dz/da is known as a "sensitivity coefficient" or "influence coefficient" [16], since it reflects the influence of changes in the model parameter on its output. Let us define…”
Section: Da -mentioning
confidence: 99%
“…10) to the integrator.IV. STEADY -STATE: RANDOM OPTIMIZA TIONA.Performance MeasureParameter optimization for this example is accomplished by determining the values of the variables x, y, and z which produc e a minimum value of f(x,y,z) in Equation(12).…”
mentioning
confidence: 99%