Scaling effects in angle-ply laminates

The effect of specimen size upon the response and strength of +/- 45 degree angle-ply laminates was investigated for two graphite fiber reinforced plastic systems and several stacking sequences. The first material system was a brittle epoxy based system, AS4 fibers in 3502 epoxy, and the second was a tough thermoplastic based system, AS4 fibers in PEEK matrix. For the epoxy based system, two generic +/- 45 degree lay-ups were studied: (+45 degrees sub n/-45 degrees sub n) sub 2S (blocked plies), and (+45 degrees/-45 degrees) sub 2nS, for n=1 and 2. The in-plane dimensions of the specimens were varied such that the width/length relationship was 12.7 x n/127 x n mm, for m=1, 2, 3, or 4. It is shown that the stress/strain response and the ultimate strength of these angle-ply laminates depends on the laminate thickness and the type of generic lay-up used. Furthermore, it is shown that first ply failure occurs in the surface plies as a result of normal rather than shear stresses. The implications of the experimental findings upon the validity of the +/- 45 degree tensile test which is used to determine the in-plane shear response of unidirectional composites are discussed

Thermally isolated Luttinger liquids with noisy Hamiltonians

We study the dynamics of a quantum-coherent thermally isolated Luttinger liquid with noisy Luttinger parameter. To characterize the fluctuations of the absorbed energy in generic noise-driven systems, we first identify two types of energy moments, which can help tease apart the effects of classical (sample-to-sample) and quantum sources of fluctuations. One type of moment captures the total fluctuations due to both sources, while the other one captures the effect of the classical source only. We then demonstrate that in the Luttinger liquid case, the two types of moments agree in the thermodynamic limit, indicating that the classical source dominates. In contrast to equilibrium thermodynamics, in this driven system the relative fluctuations of energy do not decay with the system size. Additionally, we study the deviations of equal-time correlation functions from their ground-state value, and find a simple scaling behavior.Comment: 11 pages, 2 figure

On (Omega-)regular model checking

peer reviewedChecking infinite-state systems is frequently done by encoding infinite sets of states as regular languages. Computing such a regular representation of, say, the set of reachable states of a system requires acceleration techniques that can finitely compute the effect of an unbounded number of transitions. Among the acceleration techniques that have been proposed, one finds both specific and generic techniques. Specific techniques exploit the particular type of system being analyzed, for example, a system manipulating queues or integers, whereas generic techniques only assume that the transition relation is represented by a finite-state transducer, which has to be iterated. In this article, we investigate the possibility of using generic techniques in cases where only specific techniques have been exploited so far. Finding that existing generic techniques are often not applicable in cases easily handled by specific techniques, we have developed a new approach to iterating transducers. This new approach builds on earlier work, but exploits a number of new conceptual and algorithmic ideas, often induced with the help of experiments, that give it a broad scope, as well as good performances

From clean to diffusive mesoscopic systems: A semiclassical approach to the magnetic susceptibility

We study disorder-induced spectral correlations and their effect on the magnetic susceptibility of mesoscopic quantum systems in the non-diffusive regime. By combining a diagrammatic perturbative approach with semiclassical techniques we perform impurity averaging for non-translational invariant systems. This allows us to study the crossover from clean to diffusive systems. As an application we consider the susceptibility of non-interacting electrons in a ballistic microstructure in the presence of weak disorder. We present numerical results for a square billiard and approximate analytic results for generic chaotic geometries. We show that for the elastic mean free path $\ell$ larger than the system size, there are two distinct regimes of behaviour depending on the relative magnitudes of $\ell$ and an inelastic scattering length.Comment: 7 pages, Latex-type, EuroMacr, 4 Postscript figures, to appear in Europhys. Lett. 199

Optimal Renormalization Group Transformation from Information Theory

Recently a novel real-space RG algorithm was introduced, identifying the relevant degrees of freedom of a system by maximizing an information-theoretic quantity, the real-space mutual information (RSMI), with machine learning methods. Motivated by this, we investigate the information theoretic properties of coarse-graining procedures, for both translationally invariant and disordered systems. We prove that a perfect RSMI coarse-graining does not increase the range of interactions in the renormalized Hamiltonian, and, for disordered systems, suppresses generation of correlations in the renormalized disorder distribution, being in this sense optimal. We empirically verify decay of those measures of complexity, as a function of information retained by the RG, on the examples of arbitrary coarse-grainings of the clean and random Ising chain. The results establish a direct and quantifiable connection between properties of RG viewed as a compression scheme, and those of physical objects i.e. Hamiltonians and disorder distributions. We also study the effect of constraints on the number and type of coarse-grained degrees of freedom on a generic RG procedure.Comment: Updated manuscript with new results on disordered system

"How May I Help You?": Modeling Twitter Customer Service Conversations Using Fine-Grained Dialogue Acts

Given the increasing popularity of customer service dialogue on Twitter, analysis of conversation data is essential to understand trends in customer and agent behavior for the purpose of automating customer service interactions. In this work, we develop a novel taxonomy of fine-grained "dialogue acts" frequently observed in customer service, showcasing acts that are more suited to the domain than the more generic existing taxonomies. Using a sequential SVM-HMM model, we model conversation flow, predicting the dialogue act of a given turn in real-time. We characterize differences between customer and agent behavior in Twitter customer service conversations, and investigate the effect of testing our system on different customer service industries. Finally, we use a data-driven approach to predict important conversation outcomes: customer satisfaction, customer frustration, and overall problem resolution. We show that the type and location of certain dialogue acts in a conversation have a significant effect on the probability of desirable and undesirable outcomes, and present actionable rules based on our findings. The patterns and rules we derive can be used as guidelines for outcome-driven automated customer service platforms.Comment: 13 pages, 6 figures, IUI 201