MANUFACTURING RESEARCH AND DEVELOPMENT IN A PERIPHERAL REGION: THE CASE OF LIMBURG,BELGIUM *

The scope of manufacturing research and development (R&D) in the intermetropolitan region of Limburg, Belgium, is analyzed within the context of the spatial, organizational, and size-theoretical attributes of R&D and of the core-periphery model. In spite of its peripheral location, Limburg exhibits vivid R&D activity associated with the trickled-down manufacturing from neighboring West European industrial cores. R&D in Limburg is mostly centered in multinational/locational branch plants, but also in a few modernizing, old sector establishments engaged in high and medium-level “off the shelf” technology processes. R&D was significant in terms of spending, number of newly developed prototypes, and number of patents registered. It revealed strong sector concentration with relatively dispersed spatial patterns. R&D departments and spending disclosed a positive correlation with plant size, but showed particularly high concentration coefficients when medium-size high- and medium-level technology plants were considered.     

The Concordia station on the Antarctic plateau: The best site on earth for the 21st century astronomers

On the Antarctic plateau, a joint project of French and Italian polar programmes is nearing completion: the Concordia station will be open for winter-over operation in 2005. The high altitude and high latitude of this site, the exceptionally cold, clear and stable atmosphere, its incredible astronomical seeing, the almost indefinitely flat snow surface and the not-so-difficult access make this site the most promising on Earth for future ground-based astronomical projects in various fields, including long term photometry, infrared high sensitivity imaging and high angular resolution and high contrast imaging.     

Effects of the Upstream-Flow Regime and Canyon Aspect Ratio on Non-linear Interactions Between a Street-Canyon Flow and the Overlying Boundary Layer

Large-scale structures within a rough-wall boundary layer generated over a cube array have recently been linked to small-scale fluctuations close to the roughness through a dynamical mechanism similar to amplitude modulation. Demonstrating the existence of this mechanism for different roughness types is a crucial step towards the development of a generic model for wind fluctuations in the urban canopy. Here the influence of the upstream roughness geometry (two-dimensional (2D) and three-dimensional (3D)) and planform packing density (\( \lambda_{p} \)) and street-canyon aspect ratio on the non-linear interactions between large-scale momentum regions and the small scales induced by the presence of the roughness is studied within a wind tunnel using combined particle-image velocimetry and hot-wire anemometry. A multi-time delay linear stochastic estimation is used to decompose the flow into large scales that participate in modulation and the remaining small scales. Using three different upstream roughness configurations composed of either 3D cubes or 2D rectangular blocks it is shown that the upstream roughness configuration has an influence on the non-linear interactions in the rough-wall boundary layer. Analysis of the turbulence skewness decomposition shows a change in the location of the maximum of the term \( \overline{{u_{L}^{\prime} u_{S}^{\prime 2}}} \), which represents the influence of the large-scale momentum regions on the small scales, whilst the temporal correlation shows a modification of the interaction located closer to the roughness with a change from 3D to 2D roughness. Furthermore, a two-point spatio–temporal correlation demonstrates that the non-linear relationship is significantly modified in the wake-interference-flow regime compared to the skimming-flow regime. Through skewness decomposition and temporal correlations the canyon aspect ratio is shown to have no influence on the non-linear interactions, indicating that the mechanism depends only on the flow developing upstream. Finally, although the upstream roughness configuration is shown to influence the non-linear interactions, the nature of the mechanism remains the same in all configurations.     

Multiple component end-member mixing model of dilution: hydrochemical effects of construction water at Yucca Mountain, Nevada, USA

The standard dual-component and two-member linear mixing model is often used to quantify water mixing of different sources. However, it is no longer applicable whenever actual mixture concentrations are not exactly known because of dilution. For example, low-water-content (low-porosity) rock samples are leached for pore-water chemical compositions, which therefore are diluted in the leachates. A multicomponent, two-member mixing model of dilution has been developed to quantify mixing of water sources and multiple chemical components experiencing dilution in leaching. This extended mixing model was used to quantify fracture-matrix interaction in construction-water migration tests along the Exploratory Studies Facility (ESF) tunnel at Yucca Mountain, Nevada, USA. The model effectively recovers the spatial distribution of water and chemical compositions released from the construction water, and provides invaluable data on the matrix fracture interaction. The methodology and formulations described here are applicable to many sorts of mixing-dilution problems, including dilution in petroleum reservoirs, hydrospheres, chemical constituents in rocks and minerals, monitoring of drilling fluids, and leaching, as well as to environmental science studies.     

Deformation-induced polymorphic transformation: experimental deformation of kyanite, andalusite, and sillimanite

Torsion experiments were performed on the Al₂SiO₅ polymorphs in the sillimanite stability field to determine basic rheological characteristics and the effect of deformation on polymorphic transformation. The experiments resulted in extensive transformation of andalusite and kyanite to sillimanite. No transformation occurred during the hot-press (no deformation) stage of sample preparation, which was carried out at similar P–T conditions and duration as the torsion experiments. Experiments were conducted on fine-grained (< 15 µm) aggregates of natural andalusite, kyanite and sillimanite at 1250 °C, 300 MPa, and a constant shear strain rate of 2 × 10^− 4/s to a maximum shear strain of 400%. Electron back-scattered diffraction (EBSD) analysis of the experiments revealed development of lattice-preferred orientations, with alignment of sillimanite and andalusite [001] slightly oblique to the shear plane. The kyanite experiment could not be analyzed using EBSD because of near complete transformation to sillimanite. Very little strain ( 30%) is required to produce widespread transformation in kyanite and andalusite. Polymorphic transformation in andalusite and kyanite experiments occurred primarily along 500 µm wide shear bands oriented slightly oblique and antithetic to the shear plane and dominated by sub-µm (100–150 nm) fibrolitic sillimanite. Shear bands are observed across the entire strain field preserved in the torsion samples. Scanning transmission electron microscope imaging shows evidence for transformation away from shear bands; e.g. fibrolitic rims on relict andalusite or kyanite. Relict grains typically have an asymmetry that is consistent with shear direction. These experimental results show that sillimanite is by far the weakest of the polymorphs, but no distinction can yet be made on the relative strengths of kyanite and andalusite. These observations also suggest that attaining high bulk strain energy in strong materials such as the Al₂SiO₅ polymorphs is not necessary for triggering transformation. Strain energy is concentrated along grain boundaries, and transformation occurs by a dynamic recrystallization type process. These experiments also illustrate the importance of grain-size sensitive creep at high strains in a system with simultaneous reaction and deformation.     

Terra Populus’ architecture for integrated big geospatial services

Big geospatial data is an emerging sub‐area of geographic information science, big data, and cyberinfrastructure. Big geospatial data poses two unique challenges. First, raster and vector data structures and analyses have developed on largely separate paths for the last 20 years. This is creating an impediment to geospatial researchers seeking to utilize big data platforms that do not promote heterogeneous data types. Second, big spatial data repositories have yet to be integrated with big data computation platforms in ways that allow researchers to spatio‐temporally analyze big geospatial datasets. IPUMS‐Terra, a National Science Foundation cyberInfrastructure project, addresses these challenges by providing a unified framework of integrated geospatial services which access, analyze, and transform big heterogeneous spatio‐temporal data. As IPUMS‐Terra's data volume grows, we seek to integrate geospatial platforms that will scale geospatial analyses and address current bottlenecks within our system. However, our work shows that there are still unresolved challenges for big geospatial analysis. The most pertinent is that there is a lack of a unified framework for conducting scalable integrated vector and raster data analysis. We conducted a comparative analysis between PostgreSQL with PostGIS and SciDB and concluded that SciDB is the superior platform for scalable raster zonal analyses.     

A Genetic Algorithm for Tributary Selection with Consideration of Multiple Factors

Drainage systems are important components in cartography and Geographic Information Systems (GIS), and achieve different drainage patterns based on the form and texture of their network of stream channels and tributaries due to local topography and subsurface geology. The drainage pattern can reflect the geographical characteristics of a river network to a certain extent. To preserve the drainage pattern during the generalization process, this article proposes a solution to deal with many factors, such as the tributary length and the order in river tributary selection. This leads to a multi‐objective optimization problem solved with a Genetic Algorithm. In the multi‐objective model, different weights are used to aggregate all objective functions into a fitness function. The method is applied on a case study to evaluate the importance of each factor for different types of drainage and results are compared with a manually generalized network. The result can be controlled by assigning different weights to the factors. From this work, different weight settings according to drainage patterns are proposed for the river network generalization.