Aeroelastic simulations of stores in weapon bays using Detached-Eddy simulation

Detached-Eddy Simulations of flows in weapon bays with a generic store at different positions in the cavity and with flexible fins are presented in this paper. Simulations were carried out to better understand the fluid–structure interactions of the unsteady, turbulent flow and the store. Mach and Reynolds numbers (based on the missile diameter) were 0.85 and 326.000 respectively. Spectral analysis showed few differences in the frequency content in the cavity between the store with rigid and flexible fins. However, a large effect of the store position was seen. When the store was placed inside the cavity, the noise reduction reached 7 dB close to the cavity ceiling. The closer the store to the carriage position, the more coherent and quieter was the cavity. To perform a more realistic simulation, a gap of 0.3% of the store diameter was introduced between the fin root and the body of the store. Store loads showed little differences between the rigid and flexible fins when the store was inside and outside the cavity. With the store at the shear layer, the flexible fins were seen to have a reduction in loads with large fluctuations in position about a mean. Fin-tip displacements of the store inside the cavity were of the range of 0.2% of the store diameter, and in the range of 1–2% of store diameter when at the shear layer

Knowledge Spaces and the Completeness of Learning Strategies

We propose a theory of learning aimed to formalize some ideas underlying Coquand's game semantics and Krivine's realizability of classical logic. We introduce a notion of knowledge state together with a new topology, capturing finite positive and negative information that guides a learning strategy. We use a leading example to illustrate how non-constructive proofs lead to continuous and effective learning strategies over knowledge spaces, and prove that our learning semantics is sound and complete w.r.t. classical truth, as it is the case for Coquand's and Krivine's approaches

Topological aspects of poset spaces

We study two classes of spaces whose points are filters on partially ordered sets. Points in MF spaces are maximal filters, while points in UF spaces are unbounded filters. We give a thorough account of the topological properties of these spaces. We obtain a complete characterization of the class of countably based MF spaces: they are precisely the second-countable T_1 spaces with the strong Choquet property. We apply this characterization to domain theory to characterize the class of second-countable spaces with a domain representation.Comment: 29 pages. To be published in the Michigan Mathematical Journa

CFD and aeroelastic analysis of the MEXICO wind turbine

This paper presents an aerodynamic and aeroelastic analysis of the MEXICO wind turbine, using the compressible HMB solver of Liverpool. The aeroelasticity of the blade, as well as the effect of a low-Mach scheme were studied for the zero-yaw 15m/s wind case and steady- state computations. The wake developed behind the rotor was also extracted and compared with the experimental data, using the compressible solver and a low-Mach scheme. It was found that the loads were not sensitive to the Mach number effects, although the low-Mach scheme improved the wake predictions. The sensitivity of the results to the blade structural properties was also highlighted

04351 Abstracts Collection -- Spatial Representation: Discrete vs. Continuous Computational Models

From 22.08.04 to 27.08.04, the Dagstuhl Seminar 04351 ``Spatial Representation: Discrete vs. Continuous Computational Models\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Learning, Generalization, and Functional Entropy in Random Automata Networks

It has been shown \citep{broeck90:physicalreview,patarnello87:europhys} that feedforward Boolean networks can learn to perform specific simple tasks and generalize well if only a subset of the learning examples is provided for learning. Here, we extend this body of work and show experimentally that random Boolean networks (RBNs), where both the interconnections and the Boolean transfer functions are chosen at random initially, can be evolved by using a state-topology evolution to solve simple tasks. We measure the learning and generalization performance, investigate the influence of the average node connectivity $K$, the system size $N$, and introduce a new measure that allows to better describe the network's learning and generalization behavior. We show that the connectivity of the maximum entropy networks scales as a power-law of the system size $N$. Our results show that networks with higher average connectivity $K$ (supercritical) achieve higher memorization and partial generalization. However, near critical connectivity, the networks show a higher perfect generalization on the even-odd task

Unsharp Values, Domains and Topoi

The so-called topos approach provides a radical reformulation of quantum theory. Structurally, quantum theory in the topos formulation is very similar to classical physics. There is a state object, analogous to the state space of a classical system, and a quantity-value object, generalising the real numbers. Physical quantities are maps from the state object to the quantity-value object -- hence the `values' of physical quantities are not just real numbers in this formalism. Rather, they are families of real intervals, interpreted as `unsharp values'. We will motivate and explain these aspects of the topos approach and show that the structure of the quantity-value object can be analysed using tools from domain theory, a branch of order theory that originated in theoretical computer science. Moreover, the base category of the topos associated with a quantum system turns out to be a domain if the underlying von Neumann algebra is a matrix algebra. For general algebras, the base category still is a highly structured poset. This gives a connection between the topos approach, noncommutative operator algebras and domain theory. In an outlook, we present some early ideas on how domains may become useful in the search for new models of (quantum) space and space-time.Comment: 32 pages, no figures; to appear in Proceedings of Quantum Field Theory and Gravity, Regensburg (2010