M. Elahi’s research while affiliated with The University of Tennessee Medical Center at Knoxville and other places

This article provides an overview on the effects of fluids onthe deformation and durability of polymeric composites. This subject isimportant for the ever-increasing application of composites in offshorestructures, submersibles, and civil infrastructure. Since weight-gaindata abound in the literature, it may be useful to recognize that acertain degree of correlation exists between some characteristicfeatures of weight-gain data and the ability of a particular compositeto retain its integrity under specified exposures to a certain fluid. Inaddition, this article provides records of fluid effects on deformationas well as on fluid-affected levels of static fatigue and fatigue livesin some specific circumstances.

This report presents data on the creep response of a polymeric composite that is a candidate material for automotive applications. The above data were used to establish the basis for the mechanical characterization of the material's response over a wide range of stresses and temperatures, as well as under cyclic loading and due to exposure to distilled water. A constitutive model based upon fundamental principles of irreversible thermodynamics and continuum mechanics was employed to encompass the above mentioned database and to predict the response under more complex inputs. These latter tests verified the validity of the model.

This article concerns the mechanical response of random glass fiber strand swirl-mat/urethane matrix composite under static and cyclic loads as well as under elevated temperatures. The article presents an extensive amount of experimental data as well as predictions based upon a coupled damage/viscoelastic constitutive formulation generated specifically to model the behavior of the material at hand. Damage evolution relations are derived from an empirical relationship. This work extends previously published results.

This report concerns the mechanical response of random glass fiber strand swirl-mat/urethane matrix composite under static and cyclic loads as well as under elevated temperatures and exposure to distilled water. The article presents an extensive amount of experimental data as well as predictions based on a couple damage/viscoelastic constitutive formulation generated to model the specific behavior of the material at hand. Damage evolution relations are derived from an empirical relationship. This work extends previously published results. It is shown that the current model has the capability to predict long-term response on the basis of short-term data and account for time-varying stresses and temperatures.

This article presents data on the creep response of a polymericcomposite that is a candidate material for automotive applications. Theabove data established the basis for the mechanical characterization ofmaterial''s response over a wide range of stresses and temperatures, aswell as under cyclic tensile loading. A constitutive model based uponfundamental principles of irreversible thermodynamics and continuummechanics was employed to encompass the abovementioned database and topredict the response under more complex inputs. These latter testsverified the validity of the model.

Swirl-mat polymeric composites are considered as representative materials for application in the automotive industry. This article summarizes a three-year long effort to characterize, model, and predict the deformation of these composites under stress, temperature, cyclic loadings, and the ingress of fluids. The effort involved several hundred characterization tests of various kinds and the formulation of a constitutive model based upon fundamental principles of irreversible thermodynamics and continuum mechanics. The above-mentioned experiments and model development were performed interactively. Subsequently, the model was employed in a predictive manner to anticipate experimental data collected under complex load and temperature histories, as well as to predict long-term behavior from short-term data.