The surface energy balance and the mixing height in urban areas—activities and recommendations of COST-Action 715

The specific problems of determining and simulating the surface energy balance (SEB) and the mixing height (MH) over urban areas are examined. The SEB and MH are critical components of algorithms and numerical models for the urban boundary layer, though the constituent parts of the SEB and the MH are not routinely measured by national weather services. Parameterisations are thus needed in applications. In this investigation, several recently developed algorithms and models for estimating the SEB and MH were applied to new datasets and assessed. Results are discussed in terms of the need for spatial resolution and the parameters needed to describe the urban atmosphere. Limitations of models are identified and recommendations for further development and observations are given. Having identified gaps in knowledge, key findings from new urban experiments and numerical modelling for the SEB and MH are given. The diurnal cycle for the SEB is significantly different from rural conditions—urban heat storage is needed in urban parameterisations. The urban MH is increased over the rural MH, as shown by several numerical schemes and careful sodar analyses. This work has been carried out within the COST-715 Action “Meteorology applied to urban air pollution problems (1998–2004). COST 715 reached a consensus proposing representatively sited measurements of meteorological parameters and turbulent fluxes above roof-tops, and recognised that such data are needed to improve numerical models of the urban surface processes.     

Advances in discrete element modelling of underground excavations

The paper presents advances in the discrete element modelling of underground excavation processes extending modelling possibilities as well as increasing computational efficiency. Efficient numerical models have been obtained using techniques of parallel computing and coupling the discrete element method with finite element method. The discrete element algorithm has been applied to simulation of different excavation processes, using different tools, TBMs and roadheaders. Numerical examples of tunnelling process are included in the paper, showing results in the form of rock failure, damage in the material, cutting forces and tool wear. Efficiency of the code for solving large scale geomechanical problems is also shown.     

Mapping the porosity of international border to pedestrian traffic: a comparative data classification approach to a study of the border region in Austria,Italy, and Slovenia

National borders play an important role in everyday life. Interest in border studies has increased with recent changes in geographical locations of the border or the fluctuation of the permeability of the border between some countries, such as in the European Union. Whether the nations are trying to increase traffic flow of the border or to implement stricter border control, having appropriate information of the border is crucial for effective policymaking.

The objective of this research was to identify areas of high porosity, or high permeability, for pedestrians along the southern national border region in Carinthia, Austria using terrain, land use, and road data along with geocomputational methods. Two unsupervised classification methods, the fuzzy K-means clustering and the Self-Organizing Map, were applied to segment the border into homogeneous zones according to topographic and infrastructural attributes. The fuzzy K-means clustering method was chosen for its ability to allow for a continuous approach to classification. With this method, an object can belong, with different degrees of membership, to multiple classes, which is a more realistic reflection of the natural world than discrete clustering, where each object can only belong to one class. However, the fuzzy K-means clustering method does have disadvantages, i.e. the user must determine the number of classes and the input parameters are required to be in continuous format. The second classification method, the Self-Organizing Map, is a type of artificial neural network and was chosen for its ability to automatically determine the number of classes and handle categorical data. The Self-Organizing Map is unique because it can transform high dimensional data into low dimensional display while preserving the topology and spatial distribution of the input parameters. The results of the two classification methods suggest that the fuzzy K-means classification is more effective than the Self-Organizing Map for this situation. However, more research is needed to determine the fit of these algorithms for particular spatial data classification tasks.

The results obtained from this research provide an insight into the permeability of the border region of Carinthia, Slovenia, and Italy to pedestrian traffic and can be potentially useful for decision making processes for tourism development and road transportation management in that region. Furthermore, the approach presented in this article can be applied to other national borders to identify zones permeable to pedestrian traffic.     

A meta-modeling approach for spatio-temporal uncertainty and sensitivity analysis: an application for a cellular automata-based Urban growth and land-use change model

The paper presents a computationally efficient meta-modeling approach to spatially explicit uncertainty and sensitivity analysis in a cellular automata (CA) urban growth and land-use simulation model. The uncertainty and sensitivity of the model parameters are approximated using a meta-modeling method called polynomial chaos expansion (PCE). The parameter uncertainty and sensitivity measures obtained with PCE are compared with traditional Monte Carlo simulation results. The meta-modeling approach was found to reduce the number of model simulations necessary to arrive at stable sensitivity estimates. The quality of the results is comparable to the full-order modeling approach, which is computationally costly. The study shows that the meta-modeling approach can significantly reduce the computational effort of carrying out spatially explicit uncertainty and sensitivity analysis in the application of spatio-temporal models.     

Pounding of superstructure segments in isolated elevated bridge during earthquakes

Past severe earthquakes indicate that pounding may cause considerable damage or even lead to collapse of colliding structures. The aim of this paper is to present an analysis of pounding between superstructure segments of an isolated elevated bridge induced by the propagating seismic wave. High-damping rubber bearings (HDRBs), used as isolation devices, are modelled by proposed non-linear formulation and the significance of the bearings model for pounding is indicated. The results of the study show that pounding leads to the increase or decrease of the forces acting on piers, depending on the gap size between superstructure segments. © 1998 John Wiley & Sons, Ltd.     

A Simplified, Accurate and Fast Method for Lithium Isotope Analysis of Rocks and Fluids, and δ7Li Values of Seawater and Rock Reference Materials

We report a new approach to conduct fast and accurate lithium isotope ratio measurements by MC-ICP mass spectrometry after wet chemical sample preparation. In contrast to most previously published methods our MC-ICP-MS set-up did not use a desolvating system to achieve appropriate ion beam intensities and, therefore, was less affected by matrix-induced shifts of the instrumental mass bias. As the total lithium background and build-up in the sample introduction system was low, previous sample residues could be washed out by an extended uptake of the new sample. Elimination of a nitric acid rinse step increased the sample throughput by a factor of two and allowed the instrumental mass bias drift to be tracked more precisely. δ⁷Li values of powdered silicate rock reference materials and seawater obtained in this study revealed good accuracy and an overall analytical uncertainty of typically 0.5‰ (2s). On the basis of a comparison between our lithium isotope data and compiled literature data, we recommend preliminary average δ⁷Li values for seawater (+30.8‰) and several silicate rock reference materials (BHVO-1: +5.0‰; JA-1: +5.6‰; JB-2: +4.8‰). The compilation of published δ⁷Li values for seawater suggests that the observed large lithium isotope differences are due to inter-method and/or interlaboratory bias. Most recently published δ⁷Li values for seawater show little variation and confirm a constant lithium isotope composition (at the sub ‰ level) of seawater in well mixed ocean basins.