ODTLES: A multi-scale model for 3D turbulent flow based on one-dimensional turbulence modeling

A novel multi-scale approach for extending the one-dimensional turbulence (ODT) model of [A.R. Kerstein. One-dimensional turbulence: model formulation and application to homogeneous turbulence, shear flows, and buoyant stratified flows, J. Fluid Mech. 392 (1999) 277] to treat turbulent flow in three-dimensional (3D) domains is described. In this model, here called ODTLES, 3D aspects of the flow are captured by embedding three, mutually orthogonal, one-dimensional ODT domain arrays within a coarser 3D mesh. The ODTLES model is obtained by developing a consistent approach for dynamically coupling the different ODT line sets to each other and to the large scale processes that are resolved on the 3D mesh. The model is implemented computationally and its performance is tested by performing simulations of decaying isotropic turbulence at two different Reynolds numbers and comparing to the experimental data of [H. Kang, S. Chester, C. Meneveau. Decaying turbulence in an active-grid-generated flow and comparisons with large-eddy simulations, J. Fluid Mech. 480 (2003) 129; G. Comte-Bellot, S. Corrsin, Simple Eulerian correlation of full-and narrow band velocity signals in grid-generated ’isotropic’ turbulence, J. Fluid Mech. 48 (1971) 273].     

Large-area assessment of impervious surface based on integrated analysis of single-date Landsat-7 images and geospatial vector data

Driven by a constantly accelerating increase of urban population in recent decades urban sprawl has become one of the most dynamic processes in the context of global land use transformations. The expansion of urban agglomerations is closely associated with a substantial increase of impervious surface. In Europe, methods for an accurate, fast and cost-effective mapping and assessment of impervious surface on a state-wide or national scale have not been established so far. This study presents an approach for estimating the impervious surface based on a combined analysis of single-date Landsat images and road network and railway vector data using Support Vector Machines and functionalities of geographic information processing. The modeling aims at the provision of data on the impervious surface for the total of residential, industrial and transportation-related areas. The derived information is provided for the administrative units of communities. The output of the procedure is a vector data file providing the ‘percent impervious surface of built-up areas’ (PIS_B) and the ‘percent impervious surface of the total of built-up and transportation-related areas’ (PIS_BT) for the administrative units of communities. The developed method is tested for a study area covering almost one third of the German territory. The results prove the suitability of the approach for a widely automated and area-wide mapping of impervious surfaces. Using reference data sets of three cities (Leipzig, Ludwigshafen, Passau) we realized a mean absolute error of 19.8% and an average error of 6.4% for the percent impervious surface modeled on the basis of the Landsat images. The final product resulting from a combination of the imperviousness raster derived from the satellite images with the transportation-related vector information showed a mean difference of 1% to 4% compared to corresponding reference data and results of previous studies. For the year 2000 our research shows that 45.3% of the area occupied by settlements and transport infrastructure in the German federal state of Bavaria, 44.6% in the state of Baden-Württemberg and 42.6% in the state of Saxony was covered by impervious surface.     

Morphological Counterparts of Linear Shift-Invariant Scale-Spaces

It is well-known that there are striking analogies between linear shift-invariant systems and morphological systems for image analysis. So far, however, the relations between both system theories are mainly understood on a pure convolution / erosion level. A formal connection on the level of differential or pseudodifferential equations and their induced scale-spaces is still missing. The goal of our paper is to close this gap. We present a simple and fairly general dictionary that allows to translate any linear shift-invariant evolution equation into its morphological counterpart and vice versa. It is based on a scale-space representation by means of the symbol of its (pseudo)differential operator. Introducing a novel transformation, the Cramér–Fourier transform, puts us in a position to relate the symbol to the structuring function of a morphological scale-space of Hamilton–Jacobi type. As an application of our general theory, we derive the morphological counterparts of many linear shift-invariant scale-spaces, such as the Poisson scale-space, \(\alpha \)-scale-spaces, summed \(\alpha \)-scale-spaces, relativistic scale-spaces, and their anisotropic variants. Our findings are illustrated by experiments.     

Theory blending: extended algorithmic aspects and examples

In Cognitive Science, conceptual blending has been proposed as an important cognitive mechanism that facilitates the creation of new concepts and ideas by constrained combination of available knowledge. It thereby provides a possible theoretical foundation for modeling high-level cognitive faculties such as the ability to understand, learn, and create new concepts and theories. Quite often the development of new mathematical theories and results is based on the combination of previously independent concepts, potentially even originating from distinct subareas of mathematics. Conceptual blending promises to offer a framework for modeling and re-creating this form of mathematical concept invention with computational means. This paper describes a logic-based framework which allows a formal treatment of theory blending (a subform of the general notion of conceptual blending with high relevance for applications in mathematics), discusses an interactive algorithm for blending within the framework, and provides several illustrating worked examples from mathematics.     

Land cover classification with coarse spatial resolution data to derive continuous and discrete maps for complex regions

Regularly updated land cover information at continental or national scales is a requirement for various land management applications as well as biogeochemical and climate modeling exercises. However, monitoring or updating of map products with sufficient spatial detail is currently not widely practiced due to inadequate time-series coverage for most regions of the Earth. Classifications of coarser spatial resolution data can be automatically generated on an annual or finer time scale. However, discrete land cover classifications of such data cannot sufficiently quantify land surface heterogeneity or change. This study presents a methodology for continuous and discrete land cover mapping using moderate spatial resolution time series data sets. The method automatically selects sample data from higher spatial resolution maps and generates multiple decision trees. The leaves of decision trees are interpreted considering the sample distribution of all classes yielding class membership maps, which can be used as estimates for the diversity of classes in a coarse resolution cell. Results are demonstrated for the heterogeneous, small-patch landscape of Germany and the bio-climatically varying landscape of South Africa. Results have overall classification accuracies of 80%. A sensitivity analysis of individual modules of the classification process indicates the importance of appropriately chosen features, sample data balanced among classes, and an appropriate method to combine individual classifications. The comparison of classification results over several years not only indicates the method's consistency, but also its potential to detect land cover changes.     

How to calculate symmetries of Petri nets

Symmetric net structure yields symmetric net behaviour. Thus, knowing the symmetries of a net, redundant calculations can be skipped. We present a framework for the calculation of symmetries for several net classes including place/transition nets, timed nets, stochastic nets, self–modifying nets, nets with inhibitor arcs, and many others. Our approach allows the specification of different symmetry groups. Additionally it provides facilities either to calculate symmetries on demand while running the actual analysis algorithm, or to calculate them in advance. For the latter case we define and calculate a ground set of symmetries. Such a set has polynomial size and is sufficient for an efficient implementation of the for all symmetries loop and the partition of net elements into equivalence classes. These two constructions are the usual way to integrate symmetries into an analysis algorithm. Received 7 July 1997 / 10 August 1999     

Miniaturization and integration of photoacoustic detection with amicrofabricated chemical reactor system

Photoacoustic spectroscopy is a useful technique for monitoring chemical composition in mesoscale analysis systems because the detection limit scales favorably with miniaturization. The key element of a photoacoustic spectrometry system is the detector. This work focuses on the miniaturization of photoacoustic detection. In particular, we are using 3.4 μm light to detect propane in a carbon dioxide background-a system that is useful for monitoring combustion reactions. Two systems have been developed. In the first, a miniature photoacoustic cell has been machined into the mounting block of a microfabricated chemical reactor, demonstrating the integration of a photoacoustic detector with a microsystem. The cell used a hearing aid microphone and an infrared diode that was modulated at the first acoustic resonance of the cell. As the gas composition of the cell changed from carbon dioxide to propane the resonance peak was observed to shift and increase, as was expected from theory. This work also presents the first demonstration of a microfabricated photoacoustic detection cell. The cell used an optical microphone and laser excitation brought into the cell via an optical fiber. The light was modulated at a frequency far below the first acoustic resonance, and a signal of 0.05 Pa was observed in the presence of propane     

Software Architectures for Reducing Priority Inversion and Non-determinism in Real-time Object Request Brokers

There is increasing demand to extend Object RequestBroker (ORB) middleware to support distributed applications withstringent real-time requirements. However, conventional ORB implementations,such as CORBA ORBs, exhibit substantial priority inversion andnon-determinism, which makes them unsuitable for applicationswith deterministic real-time requirements. This paper providestwo contributions to the study and design of real-time ORB middleware.First, it illustrates empirically why conventional ORBs do notyet support real-time quality of service. Second, it evaluatesconnection and concurrency software architectures to identifystrategies that reduce priority inversion and non-determinismin real-time CORBA ORBs. The results presented in this paperdemonstrate the feasibility of using standard OO middleware likeCORBA to support certain types of real-time applications overthe Internet.