Structural damage detection using the optimal weights of the approximating artificial neural networks

This work presents a novel neural network‐based approach to detect structural damage. The proposed approach comprises two steps. The first step, system identification, involves using neural system identification networks (NSINs) to identify the undamaged and damaged states of a structural system. The partial derivatives of the outputs with respect to the inputs of the NSIN, which identifies the system in a certain undamaged or damaged state, have a negligible variation with different system errors. This loosely defined unique property enables these partial derivatives to quantitatively indicate system damage from the model parameters. The second step, structural damage detection, involves using the neural damage detection network (NDDN) to detect the location and extent of the structural damage. The input to the NDDN is taken as the aforementioned partial derivatives of NSIN, and the output of the NDDN identifies the damage level for each member in the structure. Moreover, SDOF and MDOF examples are presented to demonstrate the feasibility of using the proposed method for damage detection of linear structures. Copyright © 2001 John Wiley & Sons, Ltd.     

Identification, definition and quantification of goods and services provided by marine biodiversity: implications for the ecosystem approach

This paper identifies and defines ecosystem goods and services provided by marine biodiversity. Case studies have been used to provide an insight into the practical issues associated with the assessment of marine ecosystem goods and services at specific locations. The aim of this research was to validate the definitions of goods and services, and to identify knowledge gaps and likely difficulties of quantifying the goods and services. A validated theoretical framework for the assessment of goods and services is detailed, and examples of the goods and services at a variety of case study areas are documented. These results will enable future assessments of marine ecosystem goods and services. It is concluded that the utilisation of this goods and services approach has the capacity to play a fundamental role in the Ecosystem Approach, by enabling the pressures and demands of society, the economy and the environment to be integrated into environmental management.     

生物共现网络原理及其在淡水生态系统评估中的应用

快速有效的生物监测指标对于评估、保护、管理和恢复淡水生态系统至关重要.传统评估方法主要利用指示生物或类群的出现率和多度信息,但是忽略了水体环境中“生物”与“生物”,以及“生物”与“环境”间相互作用的复杂关系,而这些相互作用对淡水生态系统的生物多样性、生态系统服务功能以及生态系统对环境变化的响应有着深刻影响.生物共现网络是群落水平物种互作的结构模型,通过物种在群落出现及丰度数据,描述了物种间潜在的相互作用、群落的基本结构,反映群落在生态系统的功能和结构特性.生物共现网络展示了淡水生态系统中所有生物体之间潜在的相互作用关系,其拓扑结构特性可与特定的生态系统状态相关联,能够揭示生态系统的组织规律及其功能,可作为早期的、灵敏的生物指标,是一种很有应用前景的评估淡水生态系统状态和稳定性的工具.     

Erratum to: An improved constraint method in optimal estimation of CO_2 from GOSAT SWIR observations

<正>This article is intentionally published to make erratum to the print version and the online version of Vol.60(2017)NO.2(https://link.springer.com/article/10.1007/s11430-015-0247-9).Citations of the following publications should be added to the list of Reference for TCCON data use:Wennberg P O,Roehl C M,Wunch D,Toon G C,Blavier J F,Washenfelder R A,Keppel-Aleks G,Allen N T,Ayers J.2014.TCCON data from Park Falls,Wisconsin,USA,Release GGG2014R0.TCCON data archive,hosted by the Carbon Dioxide     

人工神经网络技术在结构损伤诊断中的应用

本文对人工神经网络技术在结构损伤诊断中的应用原理进行阐述,文中回顾了人工神经网络技术在结构损伤诊断领域中应用的发展历程,总结了国内外的主要研究成果,提出了目前尚未解决的难点,最终对应用人工神经网络技术进行结构损伤诊断研究的方向进行了展望。     

Spatial patterns of simulated transpiration response to climate variability in a snow dominated mountain ecosystem

Transpiration is an important component of soil water storage and stream‐flow and is linked with ecosystem productivity, species distribution, and ecosystem health. In mountain environments, complex topography creates heterogeneity in key controls on transpiration as well as logistical challenges for collecting representative measurements. In these settings, ecosystem models can be used to account for variation in space and time of the dominant controls on transpiration and provide estimates of transpiration patterns and their sensitivity to climate variability and change. The Regional Hydro‐Ecological Simulation System (RHESSys) model was used to assess elevational differences in sensitivity of transpiration rates to the spatiotemporal variability of climate variables across the Upper Merced River watershed, Yosemite Valley, California, USA. At the basin scale, predicted annual transpiration was lowest in driest and wettest years, and greatest in moderate precipitation years (R² = 0·32 and 0·29, based on polynomial regression of maximum snow depth and annual precipitation, respectively). At finer spatial scales, responsiveness of transpiration rates to climate differed along an elevational gradient. Low elevations (1200–1800 m) showed little interannual variation in transpiration due to topographically controlled high soil moistures along the river corridor. Annual conifer stand transpiration at intermediate elevations (1800–2150 m) responded more strongly to precipitation, resulting in a unimodal relationship between transpiration and precipitation where highest transpiration occurred during moderate precipitation levels, regardless of annual air temperatures. Higher elevations (2150–2600 m) maintained this trend, but air temperature sensitivities were greater. At these elevations, snowfall provides enough moisture for growth, and increased temperatures influenced transpiration. Transpiration at the highest elevations (2600–4000 m) showed strong sensitivity to air temperature, little sensitivity to precipitation. Model results suggest elevational differences in vegetation water use and sensitivity to climate were significant and will likely play a key role in controlling responses and vulnerability of Sierra Nevada ecosystems to climate change. Copyright © 2008 John Wiley & Sons, Ltd.     

Alkylphenols in marine environments: Distribution monitoring strategies and detection considerations

The presence of alkylphenols (APs) in coastal and marine ecosystems is not as well-documented as it is in freshwater ecosystems. This paper reviews reported concentrations of alkylphenol ethoxylates (APEOs) and APs in seawater, sediments and organisms of marine environments such as estuaries, coastal lagoons, bights, harbours or deep sea in order to study their distribution. Overall contamination of marine aquatic compartments by APs and APEOs has been observed, while coastal areas in the vicinity of wastewater discharges are more impacted than deep sea environments, but to a lesser extent than freshwater sites. Sediments act as sinks for APs and APEOs, especially around wastewater discharge sites. Reported AP concentrations in marine organisms are higher in bivalves and gastropods than in fishes. As nonylphenols and octylphenols are estrogenomimetic, biological responses induced in marine organisms are discussed. Finally, we describe the cell bioassay approach for the biodetection of APs.     

Long-term ecosystem monitoring at Huntington Forest: Integrating hydrology,biogeochemistry and climatic controls on watershed processes

Located in the Adirondack Mountains of northern New York State, Huntington Wildlife Forest (HWF) is a 6000-ha research and education facility operated by SUNY ESF (State University of New York, College of Environmental Science and Forestry) with continuous long-term monitoring (LTM) programs spanning over six decades. One of the ‘cradles’ of acid rain research in North America, HWF was in the first cohort of National Atmospheric Deposition Program (NADP) sites beginning in 1978. HWF is currently the only location (NY-20) in New York with the full suite of NADP programs in operation, including atmospheric mercury speciation (AMNet), along with EPA CASTNET. Nearby to NY-20 at HWF, Arbutus Lake and its forested watershed have been the focus of intensive LTM since installation of v-notch weirs at the lake outlet and inlet in 1991 and 1994, respectively. Discharge at these locations has been monitored continuously at 15-min intervals since 1999. Lake outlet water chemistry samples were collected starting in 1983. Weekly sampling of water chemistry at both weirs began in 1995 and was expanded to include two headwater streams and groundwater wells in 2007. More recently, LTM programs at HWF have been augmented by participation in the PhenoCam Network since 2008, collection of high-resolution LiDAR in 2009, and installation of a precision NY Mesonet weather station in 2016. In 2018, we installed sensor networks that continuously monitor soil microclimate and snow depth. Lastly, we improved data access via a new website ( www.adk-ltm.org ) where users can create custom queries and visualize outputs.     

Seasonal patterns and environmental control of ecosystem respiration in subtropical and temperate forests in China

Continuous measurement of carbon dioxide exchange using the eddy covariance (EC) technique was made at two ChinaFLUX forest sites including the young subtropical Pinus plantation (Qianyanzhou) and old temperate broad-leaved Korean pine mixed forest (Changbai Mountains) as part of the ChinaFLUX network. Seasonal patterns and environmental control of ecosystem respiration in the subtropical and temperate forests were evaluated by the often-used multiplicative model and Q10 model as a function of temperature and soil water content. The resuits suggested that ( i ) temperature was found to be a dominant factor in the ecosystem respiration, and most of the temporal variability of ecosystem respiration was explained by temperature. However, in the drought-stressed ecosystem, soil water content controlled the temporal variability of ecosystem respiration other than temperature effects, and soil water content became a dominat factor when severe drought affected the ecosystem respiration; (ii) the regression models analysis revealed that in the drier soil, ecosystem respiration was more sensitive to soil moisture than was expressed by the often-used multiplicative model. It was possible to accurately estimate the seasonal variation of ecosystem respiration based on the Q10 model; and (iii)annual ecosystem respiration derived from the often-used multiplicative model was 1209 g C m-2and 1303 g C m-2, and was consistently a little higher than the Q10 model estimates of 1197 g C m-2 and 1268 g C m-2 for Qianyanzhou and Changbai Mountains, respectively.     

Paleolatitudes of the Kerguelen hotspot: new paleomagnetic results and dynamic modeling

The Kerguelen Plateau, a Large Igneous Province in the southern Indian Ocean, was formed as a product of the Kerguelen hotspot in several eruptive phases during the last 120 Myr. We obtained new paleolatitudes for the central and northern Kerguelen Plateau from paleomagnetic investigations on basalts, which were drilled during ODP Leg 183 to the Kerguelen Plateau-Broken Ridge. The paleolatitudes coincide with paleolatitudes from previous investigations at the Kerguelen Plateau and Ninetyeast Ridge (the track of the Kerguelen hotspot) and indicate a difference between paleolatitudes and present position at 49°S of the Kerguelen hotspot. We show that true polar wander, the global motion between the mantle and the rotation axis, cannot explain this difference in latitudes. We present numerical model results of plume conduit motion in a large-scale mantle flow and the resulting surface hotspot motion. A large number of models all predict southward motion between 3° and 10° for the Kerguelen hotspot during the last 100 Myr, which is consistent with our paleomagnetic results.     

Moored shellfish cages for pollution monitoring: Design and operational experience

Environmental bioassay utilizing bivalve molluscs moored in floating cages is a well accepted monitoring tool. Cages built from existing designs proved unsuitable even in relatively sheltered waters. The need to monitor long sea outfalls in the comparatively exposed outer Firth of Clyde led to the development of a more robust construction based on a fibreglass spar buoy. This new design has now been tested for two seasons and has proved to be a useful compromise between a size large enough to dissuade casual pilfering and small enough to keep costs down while allowing ready handling by ship's booms and hydraulic cranes.     

桥梁健康监测及诊断研究综述

本文分析了桥梁结构健康监测和诊断的必要性和紧迫性，对桥梁结构损伤探测的方法进行了详细的分类及论述。提出了桥梁健康监测和诊断的研究新领域——无线监测系统。最后指出了桥梁健康监测和诊断中存在的问题及发展趋势。     

Australia''s first deepwater sewage outfalls: Design considerations and environmental performance monitoring

The discharge of sewage to the ocean can be an issue of public and scientific concern. Such has been the case in Sydney over at least the past 25 years. In this paper, the history of Sydney's sewage discharge is outlined, and the decisions taken to address concerns about the environmental effects of shoreline discharge of large volumes of primary treated sewage effluent are described. Design criteria are described for deepwater outfall systems that, since 1990–1991, have discharged 80% of Sydney's sewage after primary treatment at North Head, Bondi and Malabar Sewage Treatment Plants (STP). The integrated elements of a comprehensive five year Environmental Monitoring Programme (EMP) are set out. Other papers in this volume describe the result of EMP component studies. The five year EMP was designed to provide the basis to assess the environmental performance of the new deepwater outfall systems during the first two years of their operation and to provide a baseline against which further change may be measured.     

Application of artificial neural networks in optimal tuning of tuned mass dampers implemented in high-rise buildings subjected to wind load

High-rise buildings are usually considered as flexible structures with low inherent damping. Therefore, these kinds of buildings are susceptible to wind-induced vibration. Tuned Mass Damper (TMD) can be used as an effective device to mitigate excessive vibrations. In this study, Artificial Neural Networks is used to find optimal mechanical properties of TMD for high-rise buildings subjected to wind load. The patterns obtained from structural analysis of different multi degree of freedom (MDF) systems are used for training neural networks. In order to obtain these patterns, structural models of some systems with 10 to 80 degrees-of-freedoms are built in MATLAB/SIMULINK program. Finally, the optimal properties of TMD are determined based on the objective of maximum displacement response reduction. The Auto-Regressive model is used to simulate the wind load. In this way, the uncertainties related to wind loading can be taken into account in neural network’s outputs. After training the neural network, it becomes possible to set the frequency and TMD mass ratio as inputs and get the optimal TMD frequency and damping ratio as outputs. As a case study, a benchmark 76-story office building is considered and the presented procedure is used to obtain optimal characteristics of the TMD for the building.