Geoff Rideout

Prof. Geoff Rideout


Research Focus & Metrics

Academic Career Length

26Years (2001-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 July 2015 in Journal of Petroleum Science and Engineering
Verified
Journal Article
Closed access
AGAhmad Ghasemloonia
Ahmad Ghasemloonia
GRGeoff Rideout
Geoff Rideout
SBStephen D. Butt
Stephen D. Butt

1 September 2003 in Journal of Mechanical Design
Verified
Journal Article
Closed access
PDF file
HKHyung Min Kim
Hyung Min Kim
GRGeoff Rideout
Geoff Rideout
PPPanos Y. Papalambros
Panos Y. Papalambros
JSJeffrey L. Stein
Jeffrey L. Stein
Target cascading in product development is a systematic effort to propagate the desired top-level system design targets to appropriate specifications for subsystems and components in a consistent and efficient manner. If analysis models are available to represent the consequences of the relevant design decisions, analytical target cascading can be formalized as a hierarchical multilevel optimization problem. The article demonstrates this complex modeling and solution process in the chassis design of a sport-utility vehicle. Ride quality and handling targets are cascaded down to systems and subsystems utilizing suspension, tire, and spring analysis models. Potential incompatibilities among targets and constraints throughout the entire system can be uncovered and the trade-offs involved in achieving system targets under different design scenarios can be quantified.

25 September 2008 in Journal of Dynamic Systems, Measurement, and Control
Verified
Journal Article
Closed access
PDF file
TETulga Ersal
Tulga Ersal
HFHosam K. Fathy
Hosam K. Fathy
GRGeoff Rideout
Geoff Rideout
Loucas S. LoucaLoucas S. Louca
Loucas S. Louca
JSJeffrey L. Stein
Jeffrey L. Stein
A dynamic system model is proper for a particular application if it achieves the accuracy required by the application with minimal complexity. Because model complexity often—but not always—correlates inversely with simulation speed, a proper model is often alternatively defined as one balancing accuracy and speed. Such balancing is crucial for applications requiring both model accuracy and speed, such as system optimization and hardware-in-the-loop simulation. Furthermore, the simplicity of proper models conduces to control system analysis and design, particularly given the ease with which lower-order controllers can be implemented compared to higher-order ones. The literature presents many algorithms for deducing proper models from simpler ones or reducing complex models until they become proper. This paper presents a broad survey of the proper modeling literature. To simplify the presentation, the algorithms are classified into frequency, projection, optimization, and energy based, based on the metrics they use for obtaining proper models. The basic mechanics, properties, advantages, and limitations of the methods are discussed, along with the relationships between different techniques, with the intention of helping the modeler to identify the most suitable proper modeling method for a given application.

25 March 2013 in Journal of Energy Resources Technology
Verified
Journal Article
Closed access
PDF file
AGAhmad Ghasemloonia
Ahmad Ghasemloonia
GRGeoff Rideout
Geoff Rideout
Stephen D. ButtStephen D. Butt
Stephen D. Butt

1 April 2014 in Journal of Petroleum Science and Engineering
Verified
Journal Article
Closed access
AGAhmad Ghasemloonia
Ahmad Ghasemloonia
GRGeoff Rideout
Geoff Rideout
SBStephen D. Butt
Stephen D. Butt

1 February 2017 in Journal of Petroleum Science and Engineering
Verified
Journal Article
Closed access
MSMejbahul Sarker
Mejbahul Sarker
GRGeoff Rideout
Geoff Rideout
SBStephen D. Butt
Stephen D. Butt