H
Hassan Jalali
Researcher at Arak University
Publications - 38
Citations - 608
Hassan Jalali is an academic researcher from Arak University. The author has contributed to research in topics: Nonlinear system & Finite element method. The author has an hindex of 11, co-authored 35 publications receiving 460 citations. Previous affiliations of Hassan Jalali include Northumbria University & Swansea University.
Papers
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Journal ArticleDOI
Identification of bolted lap joints parameters in assembled structures
Hamid Ahmadian,Hassan Jalali +1 more
TL;DR: In this article, a nonlinear model for bolted lap joints and interfaces is proposed capable of representing the dominant physics involved in the joint such as micro/macro-slip, and the joint interface is modelled using a combination of linear and nonlinear springs and a damper to simulate the damping effects of the joint.
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Identification of nonlinear bolted lap-joint parameters by force-state mapping
TL;DR: In this paper, the parameters of an assumed nonlinear joint model are identified by force-state mapping from time-domain acceleration records in response to single-frequency excitation close to the first natural frequency.
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Generic element formulation for modelling bolted lap joints
Hamid Ahmadian,Hassan Jalali +1 more
TL;DR: In this article, a non-linear generic element formulation is developed for modeling bolted lap joints, which is formed by satisfying all conditions that are known for a joint interface and hence providing a nonlinear parametric formulation for the families of allowable joint models.
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An equivalent model of a nonlinear bolted flange joint
TL;DR: Comparing the hysteresis loops obtained from the detailed and equivalent models verifies the accuracy of the joint model used to represent the contact interface and the identification approach proposed for parameter quantification.
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Nonlinear model identification of a frictional contact support
TL;DR: In this article, the dependency of restoring forces in a frictional contact to the vibration amplitude level is identified using experimental observations, and the identified nonlinear restoring forces are then employed to specify parameters of a predictive contact model for the boundary support.