Probabilistic Simulation of Multi-Scale Composite Behavior

A methodology is developed to computationally assess the non-deterministic composite response at all composite scales (from micro to structural) due to the uncertainties in the constituent (fiber and matrix) properties, in the fabrication process and in structural variables (primitive variables). The methodology is computationally efficient for simulating the probability distributions of composite behavior, such as material properties, laminate and structural responses. Bi-products of the methodology are probabilistic sensitivities of the composite primitive variables. The methodology has been implemented into the computer codes PICAN (Probabilistic Integrated Composite ANalyzer) and IPACS (Integrated Probabilistic Assessment of Composite Structures). The accuracy and efficiency of this methodology are demonstrated by simulating the uncertainties in composite typical laminates and comparing the results with the Monte Carlo simulation method. Available experimental data of composite laminate behavior at all scales fall within the scatters predicted by PICAN. Multi-scaling is extended to simulate probabilistic thermo-mechanical fatigue and to simulate the probabilistic design of a composite redome in order to illustrate its versatility. Results show that probabilistic fatigue can be simulated for different temperature amplitudes and for different cyclic stress magnitudes. Results also show that laminate configurations can be selected to increase the redome reliability by several orders of magnitude without increasing the laminate thickness--a unique feature of structural composites. The old reference denotes that nothing fundamental has been done since that time

Cryogenic Composite Tank Design for Next Generation Launch Technology

The structural performance of liquid hydrogen tanks made from composites is investigated. A computational method that judiciously combines structural analysis, composite mechanics, progressive fracture algorithm to evaluate damage tolerance, durability, and fatigue and fracture is described. A tank design concept is introduced and evaluated. The composite tank is internally stiffened by incorporating additional stacks of laminates along its length to alternate rows of finite elements. The robustness of the proposed design concept is assessed by damage progression analysis. Damage initiates i the composite at an internal pressure that is nearly two times the design pressure. From the point of damage initiation, the designed tank can tolerate an increase in internal pressure that is nearly three and a half times the design pressure. Low cycle fatigue analysis is also performed to determine the effect of pressurization and de-pressurization on the structural integrity of the tank. Results show that the tank can sustain at least a 100 cycles before any failure take place

An effective hybrid approach to remote-sensing image classification

This article presents a hybrid fuzzy classifier for effective land-use/land-cover (LULC) mapping. It discusses a Bayesian method of incorporating spatial contextual information into the fuzzy noise classifier (FNC). The FNC was chosen as it detects noise using spectral information more efficiently than its fuzzy counterparts. The spatial information at the level of the second-order pixel neighbourhood was modelled using Markov random fields (MRFs). Spatial contextual information was added to the MRF using different adaptive interaction functions. These help to avoid over-smoothing at the class boundaries. The hybrid classifier was applied to advanced wide-field sensor (AWiFS) and linear imaging self-scanning sensor-III (LISS-III) images from a rural area in India. Validation was done with a LISS-IV image from the same area. The highest increase in accuracy among the adaptive functions was 4.1% and 2.1% for AWiFS and LISS-III images, respectively. The paper concludes that incorporation of spatial contextual information into the fuzzy noise classifier helps in achieving a more realistic and accurate classification of satellite images