Conjugate heat transfer through nano scale porous media to optimize vacuum insulation panels with lattice Boltzmann methods

Due to reduced thermal conductivity, vacuum insulation panels (VIPs) provide significant thermal insulation performance. Our novel vacuum panels operate at reduced pressure and are filled with a powder of precipitated silicic acid to further hinder convection and provide static stability against atmospheric pressure. To obtain an in depth understanding of heat transfer mechanisms, their interactions and their dependencies inside VIPs, detailed microscale simulations are conducted.Particle characteristics for silica are used with a discrete element method (DEM) simulation, using open source software Yade-DEM, to generate a periodic compressed packing of precipitated silicic acid particles. This aggregate packing is then imported into OpenLB (openlb.net) as a fully resolved geometry, and used to study the effects on heat transfer at the microscale. A three dimensional Lattice Boltzmann method (LBM) for conjugated heat transfer is implemented with open source software OpenLB, which is extended to include radiative heat transport. The infrared intensity distribution is solved and coupled with the temperature through the emissivity, absorption and scattering of the studied media using the radiative transfer equation by means of LBM. This new holistic approach provides a distinct advantage over similar porous media approaches by providing direct control and tuning of particle packing characteristics such as aggregate size, shape and pore size distributions and studying their influence directly on conduction and radiation independently. Our aim is to generate one holistic tool which can be used to generate silica geometry and then simulate automatically the thermal conductivity through the generated geometry.     

Derivation of imperfect interface models coupling damage and temperature

In this paper we introduce a model describing a layered structure composed by two thermoelastic adherents and a thin adhesive subject to a degradation process. By an asymptotic expansion method, we derive a model of imperfect interface coupling damage and temperature evolution. Moreover, assuming that the behaviour of the adhesive is ruled by two different regimes, one in traction and one in compression, we derive a second limit model where unilateral contact conditions on the interface are also included.     

Classification of shoreline vegetation in the Western Basin of Lake Erie using airborne hyperspectral imager HSI2, Pleiades and UAV data

Mapping land and aquatic vegetation of coastal areas using remote sensing for better management and conservation has been a long-standing interest in many parts of the world. Due to natural complexity and heterogeneity of vegetation cover, various remote sensing sensors and techniques are utilized for monitoring coastal ecosystems. In this study, two unsupervised and two supervised standard pixel-based classifiers were tested to evaluate the mapping performance of the second-generation airborne NASA Glenn Hyperspectral Imager (HSI2) over the narrow coastal area along the Western Lake Erie’s shoreline. Furthermore, the classification results of HSI2 (using the whole Visible-Near Infrared (VIS+ NIR) hyperspectral dataset, and also the spectral subset of Visible (VIS) spectral bands) were compared to multispectral Pleiades (VIS+ NIR) and Unmanned Aerial Vehicle (UAV) VIS classified images. The goal was to explore how different spectral ranges, and spatial and spectral resolutions impact the unsupervised and supervised classifiers. While the unsupervised classifiers depended more on the spectral range, spectral or spatial resolutions were important for the supervised classifiers. The Support Vector Machine (SVM) was found to perform better than other classification methods for the HSI2 images over all twenty-two study sites with the overall accuracy (OA) ranging from 82.6%–97.5% for VIS, and 81.5%–95.6 % for VIS + NIR. Considerably better performance of the supervised classifiers for the HSI2 VIS data over the Pleiades data (OA = 74.8–83.4%) suggested the importance of spectral resolution over spectral range (VIS vs. VIS+ NIR) for the supervised methods. The unsupervised classifiers exhibited low accuracy for both HSI2 VIS and UAV VIS imagery (OA< 30.0%) while the overall accuracy for the HSI2 VIS+ NIR and Pleiades data ranged from 60.4%–78.4 % and 42.1%–66.4%, respectively, suggesting the importance of spectral range for the unsupervised classifiers.     

Micro molecular tagging velocimetry for analysis of gas flows in mini and micro systems

A new micro molecular tagging velocimetry (μMTV) setup has been developed to analyze velocity fields in confined internal gas flows. MTV is a little-intrusive velocimetry technique. It relies on the properties of molecular tracers which can experience relatively long lifetime luminescence once excited by a laser beam with an appropriate wavelength. The technique has been validated for acetone seeded flows of argon inside a 1 mm depth rectangular minichannel, with a multilayer design offering two optical accesses. Velocity profiles have been obtained using a specific data reduction process, with a resolution in the order of 15 μm. The experimental data are compared to theoretical velocity profiles of compressible pressure-driven flows. A good agreement is observed, except close to the walls, where the accuracy would still need to be improved. Following these first results obtained at atmospheric pressure, the influence of pressure on the luminescence intensity of acetone molecules is analyzed. The obtained data lead to a discussion of MTV applicability to rarefied flows and its possible use for a direct measurement of velocity slip at the channel walls.     

On the Hitting Times of Quantum Versus Random Walks

The hitting time of a classical random walk (Markov chain) is the time required to detect the presence of—or equivalently, to find—a marked state. The hitting time of a quantum walk is subtler to define; in particular, it is unknown whether the detection and finding problems have the same time complexity. In this paper we define new Monte Carlo type classical and quantum hitting times, and we prove several relationships among these and the already existing Las Vegas type definitions. In particular, we show that for some marked state the two types of hitting time are of the same order in both the classical and the quantum case. Then, we present new quantum algorithms for the detection and finding problems. The complexities of both algorithms are related to the new, potentially smaller, quantum hitting times. The detection algorithm is based on phase estimation and is particularly simple. The finding algorithm combines a similar phase estimation based procedure with ideas of Tulsi from his recent theorem (Tulsi A.: Phys. Rev. A 78:012310 2008) for the 2D grid. Extending his result, we show that we can find a unique marked element with constant probability and with the same complexity as detection for a large class of quantum walks—the quantum analogue of state-transitive reversible ergodic Markov chains. Further, we prove that for any reversible ergodic Markov chain P, the quantum hitting time of the quantum analogue of P has the same order as the square root of the classical hitting time of P. We also investigate the (im)possibility of achieving a gap greater than quadratic using an alternative quantum walk. In doing so, we define a notion of reversibility for a broad class of quantum walks and show how to derive from any such quantum walk a classical analogue. For the special case of quantum walks built on reflections, we show that the hitting time of the classical analogue is exactly the square of the quantum walk.     

An A Contrario Decision Method for Shape Element Recognition

Shape recognition is the field of computer vision which addresses the problem of finding out whether a query shape lies or not in a shape database, up to a certain invariance. Most shape recognition methods simply sort shapes from the database along some (dis-)similarity measure to the query shape. Their main weakness is the decision stage, which should aim at giving a clear-cut answer to the question: “do these two shapes look alike?” In this article, the proposed solution consists in bounding the number of false correspondences of the query shape among the database shapes, ensuring that the obtained matches are not likely to occur “by chance”. As an application, one can decide with a parameterless method whether any two digital images share some shapes or not.     

Social Software

Zusammenfassung Ausgehend vom Begriff des Web 2.0 werden die Merkmale und M?glichkeiten sog. Social Software vorgestellt. Der Beitrag erl?utert den Begriff und gibt einen überblick über die unterschiedlichen Arten. Merkmale und Nutzenpotentiale sowie Beispiele werden vorgestellt.     

Responses of the autonomic nervous system during periods of perceived high and low work stress in younger and older female teachers

The aim of this study was to examine the response of the autonomic nervous system in younger (mean age 31 yrs, n=14) and older (mean age 54 yrs, n=14) healthy female teachers during work periods of perceived high and low stress. In the younger participants, heart rate, cortisol excretion rate and psychosomatic symptoms were significantly higher during the high work stress period. The older participants experienced no decrease in their heart rate and cortisol excretion during the low stress period and they exhibited no significant decrease in blood pressure after the work in the evening during both periods. It may be concluded that the recovery from the stress in the older teachers was insufficient particularly in view of their elevated diastolic blood pressure during the low work stress period. Ergonomic and individually tailored measures in terms of work time control, specific relaxation techniques, and a part-time retirement may improve the stress management of older teachers.     

A database model for object dynamics

To effectively model complex applications in which constantly changing situations can be represented, a database system must be able to support the runtime specification of structural and behavioral nuances for objects on an individual or group basis. This paper introduces the role mechanism as an extension of object-oriented databases to support unanticipated behavioral oscillations for objects that may attain many types and share a single object identity. A role refers to the ability to represent object dynamics by seamlessly integrating idiosyncratic behavior, possibly in response to external events, with pre-existing object behavior specified at instance creation time. In this manner, the same object can simultaneously be an instance of different classes which symbolize the different roles that this object assumes. The role concept and its underlying linguistic scheme simplify the design requirements of complex applications that need to create and manipulate dynamic objects. Edited by D. McLeod / Received March 1994 / Accepted January 1996