934 resultados para Decomposition of Ranked Models
Resumo:
Fatigue damage calculations of unidirectional polymer composites is presented applying micromechanics theory. An orthotropic micromechanical damage model is integrated with an isotropic fatigue evolution model to predict the micromechanical fatigue damage of the composite structure. The orthotropic micromechanical damage model is used to predict the orthotropic damage evolution within a single cycle. The isotropic fatigue model is used to predict the magnitude of fatigue damage accumulated as a function of the number of cycles. The advantage of using this approach is the cheap determination of model parameters since the orthotropic damage model parameters can be determined using available data from quasi-static loading tests. Decomposition of the state variables down to the constituent scale is accomplished by micromechanics theory. Phenomenological damage evolution models are then postulated for each constituent and for interphase among them. Comparison between model predictions and experimental data is presented.
Resumo:
A new model for damage evolution in polymer matrix composites is presented. The model is based on a combination of two constituent-level models and an interphase model. This approach reduces the number of empirical parameters since the two constituent- level models are formulated for isotropic materials, namely fiber and matrix. Decomposition of the state variables down to the micro-scale is accomplished by micromechanics. Phenomenological damage evolution models are then postulated for each constituent. Determination of material parameters is made from available experimental data. The required experimental data can be obtained with standard tests. Comparison between model predictions and additional experimental data is presented.
Resumo:
A new model for fatigue damage evolution of polymer matrix composites (PMC) is presented. The model is based on a combination of an orthotropic damage model and an isotropic fatigue evolution model. The orthotropic damage model is used to predict the orthotropic damage evolution within a single cycle. The isotropic fatigue model is used to predict the magnitude of fatigue damage accumulated as a function of the number of cycles. This approach facilitates the determination of model parameters since the orthotropic damage model parameters can be determined from available data from quasi-static-loading tests. Then, limited amount of fatigue data is needed to adjust the fatigue evolution model. The combination of these two models provides a compromise between efficiency and accuracy. Decomposition of the state variables down to the constituent scale is accomplished by micro-mechanics. Phenomenological damage evolution models are then postulated for each constituent and for the micro-structural interaction among them. Model parameters are determined from available experimental data. Comparison between model predictions and additional experimental data is presented.
Resumo:
Computer-assisted topology predictions are widely used to build low-resolution structural models of integral membrane proteins (IMPs). Experimental validation of these models by traditional methods is labor intensive and requires modifications that might alter the IMP native conformation. This work employs oxidative labeling coupled with mass spectrometry (MS) as a validation tool for computer-generated topology models. ·OH exposure introduces oxidative modifications in solvent-accessible regions, whereas buried segments (e.g., transmembrane helices) are non-oxidizable. The Escherichia coli protein WaaL (O-antigen ligase) is predicted to have 12 transmembrane helices and a large extramembrane domain (Pérez et al., Mol. Microbiol. 2008, 70, 1424). Tryptic digestion and LC-MS/MS were used to map the oxidative labeling behavior of WaaL. Met and Cys exhibit high intrinsic reactivities with ·OH, making them sensitive probes for solvent accessibility assays. Overall, the oxidation pattern of these residues is consistent with the originally proposed WaaL topology. One residue (M151), however, undergoes partial oxidation despite being predicted to reside within a transmembrane helix. Using an improved computer algorithm, a slightly modified topology model was generated that places M151 closer to the membrane interface. On the basis of the labeling data, it is concluded that the refined model more accurately reflects the actual topology of WaaL. We propose that the combination of oxidative labeling and MS represents a useful strategy for assessing the accuracy of IMP topology predictions, supplementing data obtained in traditional biochemical assays. In the future, it might be possible to incorporate oxidative labeling data directly as constraints in topology prediction algorithms.