A passive acoustic monitoring method applied to observation and group size estimation of finless porpoises

The present study aimed at determining the detection capabilities of an acoustic observation system to recognize porpoises under local riverine conditions and compare the results with sighting observations. Arrays of three to five acoustic data loggers were stationed across the main channel of the Tian-e-zhou Oxbow of China's Yangtze River at intervals of 100-150 m to record sonar. signals of free-ranging finless porpoises (Neophocaena phocaenoides). Acoustic observations, concurrent with visual observations, were conducted at two occasions on 20-22 October 2003 and 17-19 October 2004. During a total of 42 h of observation, 316 finless porpoises were sighted and 7041 sonar signals were recorded by loggers. The acoustic data loggers recorded ultrasonic signals of porpoises clearly, and detected the presence of porpoises with a correct detection level of 77.6% and a false alarm level of 5.8% within an effective distance of 150 m. Results indicated that the stationed passive acoustic observation method was effective in detecting the presence of porpoises and showed potential in estimating the group size. A positive linear correlation between the number of recorded signals and the group size of sighted porpoises was indicated, although it is faced with some uncertainty and requires further investigation. (C) 2005 Acoustical Society of America.

Monitoring and preventing numerical oscillations in 3D simulations with coupled Monte Carlo codes

Previous studies have reported that different schemes for coupling Monte Carlo (MC) neutron transport with burnup and thermal hydraulic feedbacks may potentially be numerically unstable. This issue can be resolved by application of implicit methods, such as the stochastic implicit mid-point (SIMP) methods. In order to assure numerical stability, the new methods do require additional computational effort. The instability issue however, is problem-dependent and does not necessarily occur in all cases. Therefore, blind application of the unconditionally stable coupling schemes, and thus incurring extra computational costs, may not always be necessary. In this paper, we attempt to develop an intelligent diagnostic mechanism, which will monitor numerical stability of the calculations and, if necessary, switch from simple and fast coupling scheme to more computationally expensive but unconditionally stable one. To illustrate this diagnostic mechanism, we performed a coupled burnup and TH analysis of a single BWR fuel assembly. The results indicate that the developed algorithm can be easily implemented in any MC based code for monitoring of numerical instabilities. The proposed monitoring method has negligible impact on the calculation time even for realistic 3D multi-region full core calculations. © 2014 Elsevier Ltd. All rights reserved.

Analysis of structural health monitoring data from hammersmith flyover

There has recently been considerable research published on the applicability of monitoring systems for improving civil infrastructure management decisions. Less research has been published on the challenges in interpreting the collected data to provide useful information for engineering decision makers. This paper describes some installed monitoring systems on the Hammersmith Flyover, a major bridge located in central London (United Kingdom). The original goals of the deployments were to evaluate the performance of systems for monitoring prestressing tendon wire breaks and to assess the performance of the bearings supporting the bridge piers because visual inspections had indicated evidence of deterioration in both. This paper aims to show that value can be derived from detailed analysis of measurements from a number of different sensors, including acoustic emission monitors, strain, temperature and displacement gauges. Two structural monitoring systems are described, a wired system installed by a commercial contractor on behalf of the client and a research wireless deployment installed by the University of Cambridge. Careful interpretation of the displacement and temperature gauge data enabled bearings that were not functioning as designed to be identified. The acoustic emission monitoring indicated locations at which rapid deterioration was likely to be occurring; however, it was not possible to verify these results using any of the other sensors installed and hence the only method for confirming these results was by visual inspection. Recommendations for future bridge monitoring projects are made in light of the lessons learned from this monitoring case study. © 2014 This work is made available under the terms of the Creative Commons Attribution 4.0 International license,.

Seismic behaviour of barrel vault systems

In this paper, the experimental study on the rocking behaviour of a full scale barrel vaulted structure undergo cyclic horizontal loading is discussed. The study is the first part of an ongoing experimental and theoretical research program, developed by the University of Brescia, concerning the seismic behaviour of masonry buildings. The scope of the paper is to provide some evidence of the rocking mechanism experienced by barrel vaulted structures undergo horizontal loading. Understanding of the behaviour of such structural systems is fundamental for their seismic vulnerability assessment, as well as for the correct design of possible strengthening techniques. The structural behaviour is also investigated by means of non linear finite element analyses. Numerical results are validated through comparison with experimental results. After validation, the FE model can be applied to different case studies.

Fibre optic monitoring of a deep circular excavation

This paper describes part of the monitoring undertaken at Abbey Mills shaft F, one of the main shafts of Thames Water's Lee tunnel project in London, UK. This shaft, with an external diameter of 30 m and 73 m deep, is one of the largest ever constructed in the UK and consequently penetrates layered and challenging ground conditions (Terrace Gravel, London Clay, Lambeth Group, Thanet Sand Formation, Chalk Formation). Three out of the twenty 1-2 m thick and 84 m deep diaphragm wall panels were equipped with fibre optic instrumentation. Bending and circumferential hoop strains were measured using Brillouin optical time-domain reflectometry and analysis technologies. These measurements showed that the overall radial movement of the wall was very small. Prior to excavation during a dewatering trial, the shaft may have experienced three-dimensional deformation due to differential water pressures. During excavation, the measured hoop and bending strains of the wall in the chalk exceeded the predictions. This appears to be related to the verticality tolerances of the diaphragm wall and lower circumferential hoop stiffness of the diaphragm walls at deep depths. The findings from this case study provide valuable information for future deep shafts in London. © ICE Publishing: All rights reserved.

Investigation of the polyetherketone guest-host DR1/PEK-c polymer films by real-time monitoring of the second-harmonic generation

The real-time monitoring of the second-harmonic generation (SHG) was used to optimize the poling condition and to study the nonlinear optical (NLO) properties of the polyetherketone (PEK-c) guest-host polymer films. The high second-order NLO coefficient chi(33)((2)) = 11.02 pm/v measured at 1.064 mu m was achieved when the weight percent of DR1 guest in the polymer system is 20%. The NLO activity of the poled DR1/PEK-c polymer film can maintain more than 80% of its initial value when temperature is under 100 degrees C, and the normalized second-order NLO coefficient can maintain more than 85% after 2400 s at 80 degrees C. (C) 2000 Elsevier Science Ltd. All rights reserved.

Ground target detection, classification and sensor fusion in distributed fiber seismic sensor network - art. no. 683015

This paper describes the ground target detection, classification and sensor fusion problems in distributed fiber seismic sensor network. Compared with conventional piezoelectric seismic sensor used in UGS, fiber optic sensor has advantages of high sensitivity and resistance to electromagnetic disturbance. We have developed a fiber seismic sensor network for target detection and classification. However, ground target recognition based on seismic sensor is a very challenging problem because of the non-stationary characteristic of seismic signal and complicated real life application environment. To solve these difficulties, we study robust feature extraction and classification algorithms adapted to fiber sensor network. An united multi-feature (UMF) method is used. An adaptive threshold detection algorithm is proposed to minimize the false alarm rate. Three kinds of targets comprise personnel, wheeled vehicle and tracked vehicle are concerned in the system. The classification simulation result shows that the SVM classifier outperforms the GMM and BPNN. The sensor fusion method based on D-S evidence theory is discussed to fully utilize information of fiber sensor array and improve overall performance of the system. A field experiment is organized to test the performance of fiber sensor network and gather real signal of targets for classification testing.

Wavelet denoising and feature extraction of seismic signal for footstep detection

Seismic sensors are widely used to detect moving target in ground sensor networks. Footstep detection is very important for security surveillance and other applications. Because of non-stationary characteristic of seismic signal and complex environment conditions, footstep detection is a very challenging problem. A novel wavelet denoising method based on singular value decomposition is used to solve these problems. The signal-to-noise ratio (SNR) of raw footstep signal is greatly improved using this strategy. The feature extraction method is also discussed after denosing procedure. Comparing, with kurtosis statistic feature, the wavelet energy feature is more promising for seismic footstep detection, especially in a long distance surveillance.

Experiment on Qinghai-Tibet railroad subgrade temperature monitoring based on FBG sensors

Qinghai-Tibet Railway is the longest and highest plateau railway in the world. A long term monitoring system of the stability of the subgrade in the permafrost regions should be put forward immediately to prevent damage to the railway. As it's very difficult to set up the long-distance automatic monitoring system which contains a lot of measure points along the 550 kilometers railway in the permafrost area, we present a subgrade temperature monitor system based on fiber Bragg grating (FBG). In this paper the principles of the FBG was presented, and the feasibility of the FBG sensors in the permafrost area of Qinghai-Tibet plateau was analysized. We embedded fifteen FBG temperature sensors and thermal resistance temperature sensors. A contrast experiment is made while the two kinds of sensors are arranged in the same position. The result of the experiment shows that the accuracy of the FBG temperature sensors is less than 0.1 degrees C. and the FBG sensors can do well in the measurement of pattern which the temperature varies with the depth of the permafrost soil. The result also shows the stability of the FBG sensors in the bad environmental condition of Qinghai-Tibet plateau, which proves the feasibility of the application of FBG sensors and our monitoring system on the Qinghai-Tibet railway.