Probabilistic sizing of laminates with uncertainties

A reliability based design methodology for laminate sizing and configuration for a special case of composite structures is described. The methodology combines probabilistic composite mechanics with probabilistic structural analysis. The uncertainties of constituent materials (fiber and matrix) to predict macroscopic behavior are simulated using probabilistic theory. Uncertainties in the degradation of composite material properties are included in this design methodology. A multi-factor interaction equation is used to evaluate load and environment dependent degradation of the composite material properties at the micromechanics level. The methodology is integrated into a computer code IPACS (Integrated Probabilistic Assessment of Composite Structures). Versatility of this design approach is demonstrated by performing a multi-level probabilistic analysis to size the laminates for design structural reliability of random type structures. The results show that laminate configurations can be selected to improve the structural reliability from three failures in 1000, to no failures in one million. Results also show that the laminates with the highest reliability are the least sensitive to the loading conditions

Distance-two labelings of digraphs

For positive integers $j\ge k$, an $L(j,k)$-labeling of a digraph $D$ is a function $f$ from $V(D)$ into the set of nonnegative integers such that $|f(x)-f(y)|\ge j$ if $x$ is adjacent to $y$ in $D$ and $|f(x)-f(y)|\ge k$ if $x$ is of distant two to $y$ in $D$. Elements of the image of $f$ are called labels. The $L(j,k)$-labeling problem is to determine the $\vec{\lambda}_{j,k}$-number $\vec{\lambda}_{j,k}(D)$ of a digraph $D$, which is the minimum of the maximum label used in an $L(j,k)$-labeling of $D$. This paper studies $\vec{\lambda}_{j,k}$- numbers of digraphs. In particular, we determine $\vec{\lambda}_{j,k}$- numbers of digraphs whose longest dipath is of length at most 2, and $\vec{\lambda}_{j,k}$-numbers of ditrees having dipaths of length 4. We also give bounds for $\vec{\lambda}_{j,k}$-numbers of bipartite digraphs whose longest dipath is of length 3. Finally, we present a linear-time algorithm for determining $\vec{\lambda}_{j,1}$-numbers of ditrees whose longest dipath is of length 3.Comment: 12 pages; presented in SIAM Coference on Discrete Mathematics, June 13-16, 2004, Loews Vanderbilt Plaza Hotel, Nashville, TN, US

Probabilistic Simulation of Stress Concentration in Composite Laminates

A computational methodology is described to probabilistically simulate the stress concentration factors (SCF's) in composite laminates. This new approach consists of coupling probabilistic composite mechanics with probabilistic finite element structural analysis. The composite mechanics is used to probabilistically describe all the uncertainties inherent in composite material properties, whereas the finite element is used to probabilistically describe the uncertainties associated with methods to experimentally evaluate SCF's, such as loads, geometry, and supports. The effectiveness of the methodology is demonstrated by using is to simulate the SCF's in three different composite laminates. Simulated results match experimental data for probability density and for cumulative distribution functions. The sensitivity factors indicate that the SCF's are influenced by local stiffness variables, by load eccentricities, and by initial stress fields

Pollution control can help mitigate future climate change impact on European grayling in the UK

Aim: We compare the performance of habitat suitability models using climate data only or climate data together with water chemistry, land cover and predation pressure data to model the distribution of European grayling (Thymallus thymallus). From these models, we (a) investigate the relationship between habitat suitability and genetic diversity; (b) project the distribution of grayling under future climate change; and (c) model the effects of habitat mitigation on future distributions. Location: United Kingdom. Methods: Maxent species distribution modelling was implemented using a Simple model (only climate parameters) or a Full model (climate, water chemistry, land use and predation pressure parameters). Areas of high and low habitat suitability were designated. Associations between habitat suitability and genetic diversity for both neutral and adaptive markers were examined. Distribution under minimal and maximal future climate change scenarios was modelled for 2050, incorporating projections of future flow scenarios obtained from the Centre for Ecology and Hydrology. To examine potential mitigation effects within habitats, models were run with manipulation of orthophosphate, nitrite and copper concentrations. Results: We mapped suitable habitat for grayling in the present and the future. The Full model achieved substantially higher discriminative power than the Simple model. For low suitability habitat, higher levels of inbreeding were observed for adaptive, but not neutral, loci. Future projections predict a significant contraction of highly suitable areas. Under habitat mitigation, modelling suggests that recovery of suitable habitat of up to 10% is possible. Main conclusions: Extending the climate-only model improves estimates of habitat suitability. Significantly higher inbreeding coefficients were found at immune genes, but not neutral markers in low suitability habitat, indicating a possible impact of environmental stress on evolutionary potential. The potential for habitat mitigation to alleviate distributional changes under future climate change is demonstrated, and specific recommendations are made for habitat recovery on a regional basis

Characterization of Turing diffusion-driven instability on evolving domains

In this paper we establish a general theoretical framework for Turing diffusion-driven instability for reaction-diffusion systems on time-dependent evolving domains. The main result is that Turing diffusion-driven instability for reaction-diffusion systems on evolving domains is characterised by Lyapunov exponents of the evolution family associated with the linearised system (obtained by linearising the original system along a spatially independent solution). This framework allows for the inclusion of the analysis of the long-time behavior of the solutions of reaction-diffusion systems. Applications to two special types of evolving domains are considered: (i) time-dependent domains which evolve to a final limiting fixed domain and (ii) time-dependent domains which are eventually time periodic. Reaction-diffusion systems have been widely proposed as plausible mechanisms for pattern formation in morphogenesis