Numerical Modelling of the Turbulent Flow Developing Within and Over a 3-D Building Array, Part I: A High-Resolution Reynolds-Averaged Navier—Stokes Approach

A study of the neutrally-stratified flow within and over an array of three-dimensional buildings (cubes) was undertaken using simple Reynolds-averaged Navier—Stokes (RANS) flow models. These models consist of a general solution of the ensemble-averaged, steady-state, three-dimensional Navier—Stokes equations, where the k-ε turbulence model (k is turbulence kinetic energy and ε is viscous dissipation rate) has been used to close the system of equations. Two turbulence closure models were tested, namely, the standard and Kato—Launder k-ε models. The latter model is a modified k-ε model designed specifically to overcome the stagnation point anomaly in flows past a bluff body where the standard k-ε model overpredicts the production of turbulence kinetic energy near the stagnation point. Results of a detailed comparison between a wind-tunnel experiment and the RANS flow model predictions are presented. More specifically, vertical profiles of the predicted mean streamwise velocity, mean vertical velocity, and turbulence kinetic energy at a number of streamwise locations that extend from the impingement zone upstream of the array, through the array interior, to the exit region downstream of the array are presented and compared to those measured in the wind-tunnel experiment. Generally, the numerical predictions show good agreement for the mean flow velocities. The turbulence kinetic energy was underestimated by the two different closure models. After validation, the results of the high-resolution RANS flow model predictions were used to diagnose the dispersive stress, within and above the building array. The importance of dispersive stresses, which arise from point-to-point variations in the mean flow field, relative to the spatially-averaged Reynolds stresses are assessed for the building array.     

Urban heat island diagnosis using ASTER satellite images and ‘in situ’ air temperature

This study demonstrates that thermal satellite images combined with ‘in situ’ ground data can be used to examine models of heat island genesis and thus identify the main causes of urban heat islands (UHIs). The models, although proposed over 30 years ago, have not been thoroughly evaluated due to a combination of inadequate ground data and the low resolution of thermal satellite data. Also there has been limited understanding of the relevance of satellite-derived surface temperatures to local and regional scale air temperatures. A cloud-free ASTER thermal image of urban and rural areas of Hong Kong was obtained on a winter night with a well-developed heat island, accompanied by a 148 km vehicle traverse of air temperatures. Over the whole traverse a high R² of 0.80 was observed between surface and air temperatures, with the two datasets showing a similar amplitude and general trend, but with the surface exhibiting much higher local variability than air temperature. Gradients in both surface and air temperature could be related to differences in land cover, with little evidence of large scale advection, thus supporting the population/physical structure model of UHI causation, rather than the advection model. However, the much higher surface and air temperatures observed over the largest urban area, Kowloon, than over any smaller urban centre with similar physical structure in the New Territories, would seem more indicative of the advection model. The image and ground data suggest that Kowloon's urban canopy layer climate is mainly influenced by local city structure, but it is also modified by a strongly developed, regional scale urban boundary layer which has developed over the largest urban centre of Kowloon, and reinforces heating from both above and below.     

An adaptive compromise programming method for multi-objective path optimization

Network routing problems generally involve multiple objectives which may conflict one another. An effective way to solve such problems is to generate a set of Pareto-optimal solutions that is small enough to be handled by a decision maker and large enough to give an overview of all possible trade-offs among the conflicting objectives. To accomplish this, the present paper proposes an adaptive method based on compromise programming to assist decision makers in identifying Pareto-optimal paths, particularly for non-convex problems. This method can provide an unbiased approximation of the Pareto-optimal alternatives by adaptively changing the origin and direction of search in the objective space via the dynamic updating of the largest unexplored region till an appropriately structured Pareto front is captured. To demonstrate the efficacy of the proposed methodology, a case study is carried out for the transportation of dangerous goods in the road network of Hong Kong with the support of geographic information system. The experimental results confirm the effectiveness of the approach.     

An intelligent expert system shell for knowledge-based Geographical Information Systems: 1. The tools

Abstract

An intelligent expert system shell for the development of knowledge-based geographical information systems (GIS) is examined in this two-part article. Basic concepts and the overall architecture of the shell are discussed in the present part. Fuzzy logic and expert systems technology are demonstrated to be appropriate methods for approximating human reasoning and enhancing the level of intelligence in GIS. The shell can be employed as an effective and efficient tool for developing knowledge-based GIS.     

A rough set approach to the discovery of classification rules in spatial data

This paper proposes a novel rough set approach to discover classification rules in real‐valued spatial data in general and remotely sensed data in particular. A knowledge induction process is formulated to select optimal decision rules with a minimal set of features necessary and sufficient for a remote sensing classification task. The approach first converts a real‐valued or integer‐valued decision system into an interval‐valued information system. A knowledge induction procedure is then formulated to discover all classification rules hidden in the information system. Two real‐life applications are made to verify and substantiate the conceptual arguments. It demonstrates that the proposed approach can effectively discover in remotely sensed data the optimal spectral bands and optimal rule set for a classification task. It is also capable of unraveling critical spectral band(s) discerning certain classes. The framework paves the road for data mining in mixed spatial databases consisting of qualitative and quantitative data.     

Points of interest recommendation from GPS trajectories

Recently, points of interest (POIs) recommendation has evolved into a hot research topic with real-world applications. In this paper, we propose a novel semantics-enhanced density-based clustering algorithm SEM-DTBJ-Cluster, to extract semantic POIs from GPS trajectories. We then take into account three different factors (popularity, temporal and geographical features) that can influence the recommendation score of a POI. We characterize the impacts caused by popularity, temporal and geographical information, by using different scoring functions based on three developed recommendation models. Finally, we combine the three scoring functions together and obtain a unified framework PTG-Recommend for recommending candidate POIs for a mobile user. To the best of our knowledge, this work is the first that considers popularity, temporal and geographical information together. Experimental results on two real-world data sets strongly demonstrate that our framework is robust and effective, and outperforms the baseline recommendation methods in terms of precision and recall.     

Seasonal variations of imposex indices and butyltin concentrations in the rock shell Thais clavigera collected from Hong Kong waters

This study investigated butyltin contamination in Hong Kong waters using the rock shell Thais clavigera as a biomonitor. We collected rock shells from nine coastal sites in both winter 2005 and summer 2006 to examine the spatial and seasonal patterns. The relative penis size index (RPSI) and vas deferens sequence index (VDSI) were determined following a standard protocol, while the tissue concentrations of butyltins (i.e., mono-, di- and tri-butyltin) were measured using gas chromatography. The results showed that imposex was particularly severe in T. clavigera collected from Victoria Harbour, Pak Sha Wan and Sai Kung Pier where shipping activities were frequent. Both imposex indices had a positive correlation with tissue concentration of tributyltin in T. clavigera. While VDSI exhibited little seasonal variation, RPSI of winter specimens was significantly higher than that of summer specimens. Thus, sampling season should be standardised when using RPSI as a biomarker.     

Effects of environmental stresses on the responses of mangrove plants to spent lubricating oil

The influence of different environmental stresses, including salinity (5-35‰), tidal cycle (6/6, 12/12 and 24/24 h of high/low tidal regimes) and nutrient addition (1-6 times background nitrogen and phosphorus content) on Bruguiera gymnorrhiza and Aegiceras corniculatum grown in sediment contaminated with spent lubricating oil (7.5 L m(-2)) were investigated. The oil-treated 1-year-old mangrove seedlings subject to low (5‰) and high (35‰) salinity had significantly more reduction in growth, more release of superoxide radical (O2·-) and higher activity of superoxide dismutase (SOD) than those subject to moderate salinity (15‰). Extended flooding (24/24 h of high/low tidal regime) enhanced O2·- release and malondialdehyde (MDA) content in both oil-treated species but had little negative effects on biomass production (P>0.05) except the stem of A. corniculatum (P=0.012). The addition of nutrients had no beneficial or even posed harmful effects on the growth and cellular responses of the oil-treated seedlings.     

Electro-Osmotic Consolidation Studies on Peat and Clayey Silt Using Electric Vertical Drain

Peat and soft soil deposits are abundant in Malaysia. Studies using electrokinetic geosynthetics (EKG) such as prefabricated electric vertical drains (EVD or ePVD) have shown the potential for the application of these materials in electrokinetic strengthening of soft clays and increasing solids content in mining tailings and sludges. There are no studies reported on the effectiveness of electro-osmosis using EVD in peat. Laboratory experiments were carried out to investigate the effectiveness of electro-osmotic stabilization of two peat samples and a slightly organic clayey silt sample, from the North Sarawak region. Commercially available EVD was used to induce electro-osmosis and drainage of pore water. The influence of voltage gradient, organic content, initial water content, anode–cathode configuration and presence of roots on electro-osmotic consolidation was investigated. Electro-osmotic consolidation using EVDs was effective in the improvement of peat, over a large range of initial water contents. An increase in the voltage gradient generally improved consolidation. The maximum voltage gradient for optimum results appeared to be in the region 120 V/m. The 2anodes-1cathode configuration performed better than the 1anode-1cathode configuration. The presence of roots reduced the electro-osmosis effect.     

Variations of methane induced pyrite formation in the accretionary wedge sediments offshore southwestern Taiwan

The accretionary wedge of offshore southwestern Taiwan contains abundant deposits of gas hydrate beneath the sea floor. High concentrations of methane in pore waters are observed at several locations with little data concerning historical methane venting available. To understand temporal variation of methane venting in sediments over geologic time, a 23-m-long Calypso piston core (MD05-2911) was collected on the flank of the Yung-An Ridge. Pore water sulfate, dissolved sulfide, dissolved iron, methane, sedimentary pyrite, acid volatile sulfide, reactive iron, organic carbon and nitrogen as well as carbonate δ¹³C were analyzed.Three zones with markedly different pyrite concentration were found at the study site. Unit I sediments (>20 mbsf) were characterized with a high amount of pyrite (251–380 μmol/g) and a δ¹³C-depleted carbonate, Unit II sediments (15–20 mbsf) with a low pyrite (15–43 μmol/g) and a high content of iron oxide mineral and Unit III sediments (<10 mbsf) by a present-day sulfate–methane interface (SMI) at 5 m with a high amount of pyrite (84–221 μmol/g) and a high concentration of dissolved sulfide.The oscillation records of pyrite concentrations are controlled by temporal variations of methane flux. With an abundant supply of methane to Unit I and III, anaerobic methane oxidation and associated sulfate reduction favor diagenetic conditions conducive for significant pyrite formation. No AOM signal was found in Unit II, characterized by typical organically-limited normal marine sediments with little pyrite formation. The AOM induced pyrite formation near the SMI generates a marked pyrite signature, rendering such formation of pyrite as a useful proxy in identifying methane flux oscillation in a methane flux fluctuate environment.