Greening as strategic development in industrial change - Why companies participate in eco-networks

Networking between companies and other regional key actors has grown into a widespread instrument for economic development since the 1990s. Participatory networks have formed the concept for many activities of Local Agenda 21. Simultaneously, economic geography has focused on network theories to explain innovation in and the economic success of regions.This article focuses on the reasons why individual actors participate in environmentally oriented information networks. The questions approached are: Does the concept of learning within networks influence a firm’s development? How do the participants interact with each other? What effects do the networks have on their environment (arenas)?The changing arenas of a firm are analysed with regard to environmental concerns. These changes need to be anticipated for reliable strategies. To gain information and knowledge about current behaviour and activities, the functions of networks as learning platforms are discussed. Drawing upon arguments from different network theories, the motivations of participating in a network are threefold: actor and firm oriented, network internal (inter-firm), and network external. From these, a generic target cube of network motivations and actions is set up.The concept is reviewed by examining 12 ‘regional environmental information-oriented corporation networks’ (RUN) in the Greater Munich Area. The empirical material reveals that this type of network does not provide a guarantee for significant improvements in a firm’s environmental behaviour. However, participants learn about best practices while pursuing explicit or implicit aims as to influence their arenas.     

Flood hazard delineation combining geomorphological and hydrological methods: an example in the Northern Iberian Peninsula

Flood mapping requires the combination and integration of geomorphological and hydrological-hydraulic methods; however, despite this, there is very little scientific literature that compares and validates both methods. Two types of analysis are addressed in the present article. On the one hand, maps of flood plains have been elaborated using geomorphological evidence and historical flood data in the mountainous area of northwestern Spain, covering an area of more then 232 km² of floodplains. On the other hand, a hydrometeorological model has been developed (Clark semidistributed unit hydrograph) in the Sarria River basin (155 km², NW Spain). This basin is not gauged, hence the model was subjected to a goodness-of-fit test of its parameter (curve number) by means of Monte Carlo simulation. The peak flows obtained by means of the hydrological model were used for hydraulic modeling (one-phase, one-dimensional and steady flow) in a 4 km² urban stretch of the river bed. The delineation of surface areas affected by floods since 1918, as well as those analyzed subsequent to the geomorphological study, reveals a high degree of reliability in the delineation of the flooded areas with frequent recurrence intervals (<50 years). If we compare these flooded surface areas with the estimate obtained by the hydrological-hydraulic method we can see that the latter method overestimates the extent of the surface water by 144% for very frequent recurrence intervals (>10 years) and underestimates it as the recurrence interval increases, by up to 80% less floodplain for exceptional events (>500 years). Finally, a management map is put forth combining the most reliable results available by integrating both methods. Originally presented at the Sixth International Conference on Geomorphology.     

Numerical estimation of REV and permeability tensor for fractured rock masses by composite element method

The Monte Carlo method is used to generate parent stochastic discrete fracture network, from which a series of fractured rock samples of different sizes and orientations are extracted. The fracture network combined with a regular grid forms composite element mesh of the fractured rock sample, in which each composite element is composed of sub‐elements incised by fracture segments. The composite element method (CEM) for the seepage is implemented to obtain the nodal hydraulic potential as well as the seepage flow rates through the fractured rock samples. The application of CEM enables a large quantity of stochastic tests for the fractured rock samples because the pre‐process is facilitated greatly. By changing the sizes and orientations of the samples, the analysis of the seepage characteristics is realized to evaluate the variation of the permeability components, the existence of the permeability tensor and the representative element volume. The feasibility and effectiveness are illustrated in a numerical example. Copyright © 2008 John Wiley & Sons, Ltd.     

Implementation of reconstructed geomorphologic units in landslide susceptibility mapping: the Melen Gorge (NW Turkey)

In the international literature, although considerable amount of publications on the landslide susceptibility mapping exist, geomorphology as a conditioning factor is still used in limited number of studies. Considering this factor, the purpose of this article paper is to implement the geomorphologic parameters derived by reconstructed topography in landslide susceptibility mapping. According to the method employed in this study, terrain is generalized by the contours passed through the convex slopes of the valleys that were formed by fluvial erosion. Therefore, slope conditions before landsliding can be obtained. The reconstructed morphometric and geomorphologic units are taken into account as a conditioning parameter when assessing landslide susceptibility. Two different data, one of which is obtained from the reconstructed DEM, have been employed to produce two landslide susceptibility maps. The binary logistic regression is used to develop landslide susceptibility maps for the Melen Gorge in the Northwestern part of Turkey. Due to the high correct classification percentages and spatial effectiveness of the maps, the landslide susceptibility map comprised the reconstructed morphometric parameters exhibits a better performance than the other. Five different datasets are selected randomly to apply proper sampling strategy for training. As a consequence of the analyses, the most proper outcomes are obtained from the dataset of the reconstructed topographical parameters and geomorphologic units, and lithological variables that are implemented together. Correct classification percentage and root mean square error (RMSE) values of the validation dataset are calculated as 86.28% and 0.35, respectively. Prediction capacity of the different datasets reveal that the landslide susceptibility map obtained from the reconstructed parameters has a higher prediction capacity than the other. Moreover, the landslide susceptibility map obtained from the reconstructed parameters produces logical results.     

陕西白河县月儿潭绿松石与次生磷钙铝矾研究

对陕西省白河县月儿潭风化严重的绿松石样品进行了岩石薄片观察、化学成分测试、X射线粉晶衍射和红外吸收光谱分析等研究.结果表明,绿松石风化分解由天蓝色退色成黄绿色,最后变成白色,结构也由致密细腻变得松散多孔,主要原因是发生了硫酸根对磷酸根的交代作用,最终的交代产物主要是磷钙铝矾.     

Re-Os同位素对峨眉山大火成岩省成因制约的探讨

峨眉山大火成岩省（ELIP）主要由玄武岩、玄武质火山碎屑岩及少量的苦橄岩（包括越南的科马提岩）、长英质岩石以及层状岩体和岩墙组成,其物质来源直接关系到其成因是否与地幔柱活动有关。Re-Os同位素体系是地核、地幔和地壳物质的最佳示踪剂。前人对ELIP内的Re-Os同位素研究表明,低Ti玄武岩的Os含量为0．006&#215;10^-9-0．40010^-9,^187Os／^188Os初始值为0．1371～1．403,并提出其与地幔柱活动有关;而高Ti玄武岩的Os含量为0．00410^-9～0．56010^-9,^187Os／^188Os初始值为0．1271～5．19,认为起源于大陆岩石圈地幔或地幔柱上升过程中受到大量岩石圈地幔“混染”（xu JF et al．,2007）;科马提岩的0s含量为1．2410^-9～7．0010^-9,^187Os／^188Os初始值为0．1251～0．1261,苦橄岩的Os含量为0．3210^-9～2．32910^-9,^187Os／^188Os初始值为0．1233～0．1266,指示苦橄岩和科马提岩均来自亏损地幔源区（Hanski et al．,2004;陈雷等,2007）。本文利用Os含量最低、^187Os／^188Os最高的高Ti玄武岩作为地壳端员,用铁质陨石、原始上地幔（PUM）和亏损地幔（DMM）作为地核和各种地幔端员,分别做二元混合计算,结果显示绝大多数玄武岩和所有苦橄岩及科马提岩均落在地壳和DMM混合曲线附近,并且邻区特提斯洋地幔岩与DMM具有相近的Os含量和^187Os／^188Os组成,据此推测峨眉山火成岩的形成与特提斯洋的活动有关,主要受控于地壳和亏损地幔的相互作用。     

Reduction of hydroelastic responses of a very-long floating structure by a floating oscillating-water-column breakwater system

The hydroelastic responses of a very-long floating structure (VLFS) placed behind a reverse T-shape freely floating breakwater with a built-in oscillating water column (OWC) chamber are analyzed in two dimensions. The Bernoulli–Euler beam equation is coupled with the equations of rigid and elastic motions of the breakwater and the VLFS. The interaction of waves between the floating rigid breakwater and the elastic VLFS is formulated in a consistent manner. It has been shown numerically that the structural deflections of the VLFS can be reduced significantly by a suitably designed reverse T-shape floating breakwater.     

Numerical study of the motions and drift force of a floating OWC device

The motion and the drift force of a floating OWC (oscillating water column) wave energy device in regular waves are studied taking account of the oscillating surface-pressure due to the pressure drop across the duct of the air chamber. The potential problem inside the chamber is formulated by making use of the Green integral equation associated with the Rankine-type Green function while the outer problem with the Kelvin-type Green function. The added mass, wave damping and excitation coefficients as well as the motion and drift force of the OWC device are calculated for various values of parameter related to the pressure drop.     

165°E赤道太平洋溶解氧垂直分布异常分析

根据1986—1990中美热带西太平洋海气相互作用8个航次合作综合调查资料，分析了1987年10月赤道中西太平洋165°E（10°N－6°S）次表层水形成溶解氧最大值的原因。1986－1987年E1Nino衰退时期，该海域赤道附近在E1Nino强盛时期下沉的次表层水开始回升，短时期内形成了类似于中、高纬度海域的理化环境，使浮游生物在混合层内聚集生长，最终导致溶解氧含量在次表层出现最大值和过饱和含量。     

Prediction of local scour around circular piles under waves using a novel artificial intelligence approach

Abstract

The scour phenomena around vertical piles in oceans and under waves may influence the structure stability. Therefore, accurately predicting the scour depth is an important task in the design of piles. Empirical approaches often do not provide the required accuracy compared with data mining methods for modeling such complex processes. The main objective of this study is to develop three data-driven methods, locally weighted linear regression (LWLR), support vector machine (SVR), and multivariate linear regression (MLR) to predict the scour depth around vertical piles due to waves in a sand bed. It is the first effort to develop the LWLR to predict scour depth around vertical piles. The models simulate the scour depth mainly based on Shields parameter, pile Reynolds number, grain Reynolds number, Keulegan–Carpenter number, and sediment number. 111 laboratory datasets, derived from several experimental studies, were used for the modeling. The results indicated that the LWLR provided highly accurate predictions of the scour depths around piles (R?=?0.939 and RMSE = 0.075). Overall, this study demonstrated that the LWLR can be used as a valuable tool to predict the wave-induced scour around piles.