Search results for: underwater noise
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1275

Search results for: underwater noise

825 Near Bottom Concentrations of Krill in Two Arctic Fjords, Spitsbergen

Authors: Kajetan Deja, Katarzyna Draganska-Deja, Mateusz Ormanczyk, Michał Procajlo

Abstract:

Two glaciated fjords on Spitsbergen (Hornsund 77°N) and Kongsfjorden (79°N) were studied for the occurrence of macroplankton (mostly euphausids, hyperiids, chaetognaths) with the use of drop down the camera. The underwater imagery demonstrates that closer to the glacier front, where turbid and freshwater occurs, most of the macroplankters leave the upper water column and descends to the bottom (about 100m depth). Concentrations of macroplankton in the immediate vicinity of the sediment reach over 500 specimens per m² - what corresponds to the biomass of 10g C/m³. Such concentrations of macroplankton are of prime interest for fish, seals and other carnivores. Conditions in the near-bottom waters are in many respects better than in the upper water column- better oxygenated, cold, fully saline and transparent waters with rich food deposited on the seabed from the surface (sinking microplankton). We suggest that near bottom occurrence of macroplankton is related to the increase of glacier melt and freshwater discharge intensity.

Keywords: arctic, ecosystem, fjords, Krill

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824 Urban Freight Station: An Innovative Approach to Urban Freight

Authors: Amit Kumar Jain, Surbhi Jain

Abstract:

The urban freight in a city constitutes 10 to 18 per cent of all city road traffic, and 40 per cent of air pollution and noise emissions, are directly related to commercial transport. The policy measures implemented by urban planners have sought to restrict rather than assist goods-vehicle operations. This approach has temporarily controlled the urban transport demand during peak hours of traffic but has not effectively solved transport congestion. The solution discussed in the paper envisages the development of a comprehensive network of Urban Freight Stations (UFS) connected through underground conveyor belts in the city in line with baggage segregation and distribution in any of the major airports. The transportation of freight shall be done in standard size containers/cars through rail borne carts. The freight can be despatched or received from any of the UFS. Once freight is booked for a destination from any of the UFS, it would be stuffed in the container and digitally tagged for the destination. The container would reach the destination UFS through a network of rail borne carts. The container would be de-stuffed at the destination UFS and sent for further delivery, or the consignee may be asked to collect the consignment from urban freight station. The obvious benefits would be decongestion of roads, reduction in air and noise pollution, saving in manpower used for freight transportation.

Keywords: congestion, urban freight, intelligent transport system, pollution

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823 Two-Dimensional Modeling of Spent Nuclear Fuel Using FLUENT

Authors: Imane Khalil, Quinn Pratt

Abstract:

In a nuclear reactor, an array of fuel rods containing stacked uranium dioxide pellets clad with zircalloy is the heat source for a thermodynamic cycle of energy conversion from heat to electricity. After fuel is used in a nuclear reactor, the assemblies are stored underwater in a spent nuclear fuel pool at the nuclear power plant while heat generation and radioactive decay rates decrease before it is placed in packages for dry storage or transportation. A computational model of a Boiling Water Reactor spent fuel assembly is modeled using FLUENT, the computational fluid dynamics package. Heat transfer simulations were performed on the two-dimensional 9x9 spent fuel assembly to predict the maximum cladding temperature for different input to the FLUENT model. Uncertainty quantification is used to predict the heat transfer and the maximum temperature profile inside the assembly.

Keywords: spent nuclear fuel, conduction, heat transfer, uncertainty quantification

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822 Measurement of Magnetic Properties of Grainoriented Electrical Steels at Low and High Fields Using a Novel Single

Authors: Nkwachukwu Chukwuchekwa, Joy Ulumma Chukwuchekwa

Abstract:

Magnetic characteristics of grain-oriented electrical steel (GOES) are usually measured at high flux densities suitable for its typical applications in power transformers. There are limited magnetic data at low flux densities which are relevant for the characterization of GOES for applications in metering instrument transformers and low frequency magnetic shielding in magnetic resonance imaging medical scanners. Magnetic properties such as coercivity, B-H loop, AC relative permeability and specific power loss of conventional grain oriented (CGO) and high permeability grain oriented (HGO) electrical steels were measured and compared at high and low flux densities at power magnetising frequency. 40 strips comprising 20 CGO and 20 HGO, 305 mm x 30 mm x 0.27 mm from a supplier were tested. The HGO and CGO strips had average grain sizes of 9 mm and 4 mm respectively. Each strip was singly magnetised under sinusoidal peak flux density from 8.0 mT to 1.5 T at a magnetising frequency of 50 Hz. The novel single sheet tester comprises a personal computer in which LabVIEW version 8.5 from National Instruments (NI) was installed, a NI 4461 data acquisition (DAQ) card, an impedance matching transformer, to match the 600  minimum load impedance of the DAQ card with the 5 to 20  low impedance of the magnetising circuit, and a 4.7 Ω shunt resistor. A double vertical yoke made of GOES which is 290 mm long and 32 mm wide is used. A 500-turn secondary winding, about 80 mm in length, was wound around a plastic former, 270 mm x 40 mm, housing the sample, while a 100-turn primary winding, covering the entire length of the plastic former was wound over the secondary winding. A standard Epstein strip to be tested is placed between the yokes. The magnetising voltage was generated by the LabVIEW program through a voltage output from the DAQ card. The voltage drop across the shunt resistor and the secondary voltage were acquired by the card for calculation of magnetic field strength and flux density respectively. A feedback control system implemented in LabVIEW was used to control the flux density and to make the induced secondary voltage waveforms sinusoidal to have repeatable and comparable measurements. The low noise NI4461 card with 24 bit resolution and a sampling rate of 204.8 KHz and 92 KHz bandwidth were chosen to take the measurements to minimize the influence of thermal noise. In order to reduce environmental noise, the yokes, sample and search coil carrier were placed in a noise shielding chamber. HGO was found to have better magnetic properties at both high and low magnetisation regimes. This is because of the higher grain size of HGO and higher grain-grain misorientation of CGO. HGO is better CGO in both low and high magnetic field applications.

Keywords: flux density, electrical steel, LabVIEW, magnetization

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821 Determinants of Healthcare Team Effectiveness in Subterranean Settings: A Mixed-Methods Study

Authors: Nasra Idilbi, Jalal Tarabeia, Layalleh Masalha, Heiam Shoufani Kassis, Gizell Green

Abstract:

Background: Healthcare professionals working in underground facilities face unique challenges affecting their physical and mental health and team effectiveness. We aimed to examine how an underground work environment affects the physical and mental health and effectiveness of a multi-professional medical team in a medical center under continuous war threats and the contribution of various demographic and professional characteristics. Methods: A cross-sectional survey was disseminated electronically. The questionnaire assessed team effectiveness, the quality of the work, and the health symptoms reported by the team while working in the underground complex. Results: In total, 270 healthcare workers (mean age 40 years, 75.6% females, 88.4% nurses) completed the questionnaire. Women reported statistically significantly higher mean scores of physical strain, fatigue, and eye irritation associated with the work environment compared to men. Multiple regression analysis revealed that psychological distress, noise, and lighting in the underground compound significantly influenced team effectiveness. The qualitative analysis revealed two key themes: the mental health impact of working in an underground environment and the effects of noise and lighting on staff performance. Nurses reported feelings of suffocation, claustrophobia, and difficulty concentrating due to the enclosed space, with some expressing heightened stress levels that impaired their ability to work effectively and safely. Female staff reported more pronounced symptoms of physical strain, fatigue, and eye irritation. Additionally, the underground complex’s poor noise absorption created a highly disruptive work environment, while inadequate lighting hindered accurate patient assessments, leading to potential errors. These challenges were exacerbated by physical symptoms like headaches and nausea, which further impacted job performance. The findings underscore the significant role of environmental factors in influencing both mental health and operational effectiveness, aligning with quantitative data on the predictors of team performance. Conclusions: The underground work environment is crucial in influencing healthcare team effectiveness, with psychological distress, noise, and lighting as key factors. The study highlights the importance of creating a comfortable work environment to foster team efficiency. The findings provide valuable insights for managers in underground healthcare facilities to optimize team performance and well-being.

Keywords: team effectiveness, underground settings, healthcare, environmental factors, a mixed-methods study

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820 Continuous Differential Evolution Based Parameter Estimation Framework for Signal Models

Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

Abstract:

In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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819 Modular Robotics and Terrain Detection Using Inertial Measurement Unit Sensor

Authors: Shubhakar Gupta, Dhruv Prakash, Apoorv Mehta

Abstract:

In this project, we design a modular robot capable of using and switching between multiple methods of propulsion and classifying terrain, based on an Inertial Measurement Unit (IMU) input. We wanted to make a robot that is not only intelligent in its functioning but also versatile in its physical design. The advantage of a modular robot is that it can be designed to hold several movement-apparatuses, such as wheels, legs for a hexapod or a quadpod setup, propellers for underwater locomotion, and any other solution that may be needed. The robot takes roughness input from a gyroscope and an accelerometer in the IMU, and based on the terrain classification from an artificial neural network; it decides which method of propulsion would best optimize its movement. This provides the bot with adaptability over a set of terrains, which means it can optimize its locomotion on a terrain based on its roughness. A feature like this would be a great asset to have in autonomous exploration or research drones.

Keywords: modular robotics, terrain detection, terrain classification, neural network

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818 An Experimental Investigation of Air Entrainment Due to Water Jets in Crossflows

Authors: Mina Esmi Jahromi, Mehdi Khiadani

Abstract:

Vertical water jets discharging into free surface turbulent cross flows result in the ingression of a large amount of air in the body of water and form a region of two-phase air-water flow with a considerable interfacial area. This research presents an experimental study of the two-phase bubbly flow using image processing technique. The air ingression and the trajectories of bubble swarms under different experimental conditions are evaluated. The rate of air entrainment and the bubble characteristics such as penetration depth, and dispersion pattern were found to be affected by the most influential parameters of water jet and cross flow including water jet-to-crossflow velocity ratio, water jet falling height, and cross flow depth. This research improves understanding of the underwater flow structure due to the water jet impingement in crossflow and advances the practical applications of water jets such as artificial aeration, circulation, and mixing where crossflow is present.

Keywords: air entrainment, image processing, jet in cross flow, two-phase flow

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817 Deep Learning to Improve the 5G NR Uplink Control Channel

Authors: Ahmed Krobba, Meriem Touzene, Mohamed Debeyche

Abstract:

The wireless communications system (5G) will provide more diverse applications and higher quality services for users compared to the long-term evolution 4G (LTE). 5G uses a higher carrier frequency, which suffers from information loss in 5G coverage. Most 5G users often cannot obtain high-quality communications due to transmission channel noise and channel complexity. Physical Uplink Control Channel (PUCCH-NR: Physical Uplink Control Channel New Radio) plays a crucial role in 5G NR telecommunication technology, which is mainly used to transmit link control information uplink (UCI: Uplink Control Information. This study based of evaluating the performance of channel physical uplink control PUCCH-NR under low Signal-to-Noise Ratios with various antenna numbers reception. We propose the artificial intelligence approach based on deep neural networks (Deep Learning) to estimate the PUCCH-NR channel in comparison with this approach with different conventional methods such as least-square (LS) and minimum-mean-square-error (MMSE). To evaluate the channel performance we use the block error rate (BLER) as an evaluation criterion of the communication system. The results show that the deep neural networks method gives best performance compared with MMSE and LS

Keywords: 5G network, uplink (Uplink), PUCCH channel, NR-PUCCH channel, deep learning

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816 Analysis of Cardiovascular Diseases Using Artificial Neural Network

Authors: Jyotismita Talukdar

Abstract:

In this paper, a study has been made on the possibility and accuracy of early prediction of several Heart Disease using Artificial Neural Network. (ANN). The study has been made in both noise free environment and noisy environment. The data collected for this analysis are from five Hospitals. Around 1500 heart patient’s data has been collected and studied. The data is analysed and the results have been compared with the Doctor’s diagnosis. It is found that, in noise free environment, the accuracy varies from 74% to 92%and in noisy environment (2dB), the results of accuracy varies from 62% to 82%. In the present study, four basic attributes considered are Blood Pressure (BP), Fasting Blood Sugar (FBS), Thalach (THAL) and Cholesterol (CHOL.). It has been found that highest accuracy(93%), has been achieved in case of PPI( Post-Permanent-Pacemaker Implementation ), around 79% in case of CAD(Coronary Artery disease), 87% in DCM (Dilated Cardiomyopathy), 89% in case of RHD&MS(Rheumatic heart disease with Mitral Stenosis), 75 % in case of RBBB +LAFB (Right Bundle Branch Block + Left Anterior Fascicular Block), 72% for CHB(Complete Heart Block) etc. The lowest accuracy has been obtained in case of ICMP (Ischemic Cardiomyopathy), about 38% and AF( Atrial Fibrillation), about 60 to 62%.

Keywords: coronary heart disease, chronic stable angina, sick sinus syndrome, cardiovascular disease, cholesterol, Thalach

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815 Robust Medical Image Watermarking based on Contourlet and Extraction Using ICA

Authors: S. Saju, G. Thirugnanam

Abstract:

In this paper, a medical image watermarking algorithm based on contourlet is proposed. Medical image watermarking is a special subcategory of image watermarking in the sense that images have special requirements. Watermarked medical images should not differ perceptually from their original counterparts because clinical reading of images must not be affected. Watermarking techniques based on wavelet transform are reported in many literatures but robustness and security using contourlet are better when compared to wavelet transform. The main challenge in exploring geometry in images comes from the discrete nature of the data. In this paper, original image is decomposed to two level using contourlet and the watermark is embedded in the resultant sub-bands. Sub-band selection is based on the value of Peak Signal to Noise Ratio (PSNR) that is calculated between watermarked and original image. To extract the watermark, Kernel ICA is used and it has a novel characteristic is that it does not require the transformation process to extract the watermark. Simulation results show that proposed scheme is robust against attacks such as Salt and Pepper noise, Median filtering and rotation. The performance measures like PSNR and Similarity measure are evaluated and compared with Discrete Wavelet Transform (DWT) to prove the robustness of the scheme. Simulations are carried out using Matlab Software.

Keywords: digital watermarking, independent component analysis, wavelet transform, contourlet

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814 Challenges in the Construction of a 6M Diameter and 1.6km Long Tunnel Under Crossing a Channel in the West of Singapore

Authors: David Loh, Wan Chee Wai, Pei Nan, Chen Zhe

Abstract:

To increase the conveyance capacity to Western Singapore and to meet Singapore’s long-term water needs in a more cost-effective manner, four new transmission pipelines consisting of two 2200 mm diameter water pipes and two 1200mm diameter water pipes will be needed by 2024 to convey water from a Water Reclamation Plant to existing networks in the west region of Singapore. Out of the several possible routes studied, the most cost-effective and technically feasible route was selected to lay the proposed 1.6km-long pipelines that cross a channel via a 6m diameter subsea tunnel. This paper outlines the challenges the team faced throughout the project thus far. It also examined the difficulties such as (1) construction of a 56m-deep launching shaft near a highly sensitive 700mm diameter Gas Transmission Pipeline (GTP) and at a location with high groundwater; (2) manpower and supply disruptions caused by the COVID-19 pandemic situation.

Keywords: underwater tunnel, subsea engineering, subsea tunnel construction, waterpipe construction

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813 Developing Wearable EMG Sensor Designed for Parkinson's Disease (PD) Monitoring, and Treatment

Authors: Bulcha Belay Etana

Abstract:

Electromyography is used to measure the electrical activity of muscles for various health monitoring applications using surface electrodes or needle electrodes. Recent developments in electromyogram signal acquisition using textile electrodes open the door for wearable health monitoring which enables patients to monitor and control their health issues outside of traditional healthcare facilities. The aim of this research is therefore to develop and analyze wearable textile electrodes for the acquisition of electromyography signals for Parkinson’s patients and apply an appropriate thermal stimulus to relieve muscle cramping. In order to achieve this, textile electrodes are sewn with a silver-coated thread in an overlapping zigzag pattern into an inextensible fabric, and stainless steel knitted textile electrodes attached to a sleeve were prepared and its electrical characteristics including signal to noise ratio were compared with traditional electrodes. To relieve muscle cramping, a heating element using stainless steel conductive yarn Sewn onto a cotton fabric, coupled with a vibration system were developed. The system was integrated using a microcontroller and a Myoware muscle sensor so that when muscle cramping occurs, measured by the system activates the heating elements and vibration motors. The optimum temperature considered for treatment was 35.50c, so a Temperature measurement system was incorporated to deactivate the heating system when the temperature reaches this threshold, and the signals indicating muscle cramping have subsided. The textile electrode exhibited a signal to noise ratio of 6.38dB while the signal to noise ratio of the traditional electrode was 7.05dB. The rise time of the developed heating element was about 6 minutes to reach the optimum temperature using a 9volt power supply. The treatment of muscle cramping in Parkinson's patients using heat and muscle vibration simultaneously with a wearable electromyography signal acquisition system will improve patients’ livelihoods and enable better chronic pain management.

Keywords: electromyography, heating textile, vibration therapy, parkinson’s disease, wearable electronic textile

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812 Model Predictive Control with Unscented Kalman Filter for Nonlinear Implicit Systems

Authors: Takashi Shimizu, Tomoaki Hashimoto

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A class of implicit systems is known as a more generalized class of systems than a class of explicit systems. To establish a control method for such a generalized class of systems, we adopt model predictive control method which is a kind of optimal feedback control with a performance index that has a moving initial time and terminal time. However, model predictive control method is inapplicable to systems whose all state variables are not exactly known. In other words, model predictive control method is inapplicable to systems with limited measurable states. In fact, it is usual that the state variables of systems are measured through outputs, hence, only limited parts of them can be used directly. It is also usual that output signals are disturbed by process and sensor noises. Hence, it is important to establish a state estimation method for nonlinear implicit systems with taking the process noise and sensor noise into consideration. To this purpose, we apply the model predictive control method and unscented Kalman filter for solving the optimization and estimation problems of nonlinear implicit systems, respectively. The objective of this study is to establish a model predictive control with unscented Kalman filter for nonlinear implicit systems.

Keywords: optimal control, nonlinear systems, state estimation, Kalman filter

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811 Distributed Optical Fiber Vibration Sensing Using Phase Generated Carrier Demodulation Algorithm

Authors: Zhihua Yu, Qi Zhang, Mingyu Zhang, Haolong Dai

Abstract:

Distributed fiber-optic vibration sensors are gaining extensive attention, for the advantages of high sensitivity, accurate location, light weight, large-scale monitoring, good concealment, and etc. In this paper, a novel optical fiber distributed vibration sensing system is proposed, which is based on self-interference of Rayleigh backscattering with phase generated carrier (PGC) demodulation algorithm. Pulsed lights are sent into the sensing fiber and the Rayleigh backscattering light from a certain position along the sensing fiber would interfere through an unbalanced Michelson Interferometry (MI) to generate the interference light. An improved PGC demodulation algorithm is carried out to recover the phase information of the interference signal, which carries the sensing information. Three vibration events were applied simultaneously to different positions over 2000m sensing fiber and demodulated correctly. Experiments show that the spatial resolution of is 10 m, and the noise level of the Φ-OTDR system is about 10-3 rad/√Hz, and the signal to noise ratio (SNR) is about 30.34dB. This vibration measurement scheme can be applied at surface, seabed or downhole for vibration measurements or distributed acoustic sensing (DAS).

Keywords: fiber optics sensors, Michelson interferometry, MI, phase-sensitive optical time domain reflectometry, Φ-OTDR, phase generated carrier, PGC

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810 Low Power CMOS Amplifier Design for Wearable Electrocardiogram Sensor

Authors: Ow Tze Weng, Suhaila Isaak, Yusmeeraz Yusof

Abstract:

The trend of health care screening devices in the world is increasingly towards the favor of portability and wearability, especially in the most common electrocardiogram (ECG) monitoring system. This is because these wearable screening devices are not restricting the patient’s freedom and daily activities. While the demand of low power and low cost biomedical system on chip (SoC) is increasing in exponential way, the front end ECG sensors are still suffering from flicker noise for low frequency cardiac signal acquisition, 50 Hz power line electromagnetic interference, and the large unstable input offsets due to the electrode-skin interface is not attached properly. In this paper, a high performance CMOS amplifier for ECG sensors that suitable for low power wearable cardiac screening is proposed. The amplifier adopts the highly stable folded cascode topology and later being implemented into RC feedback circuit for low frequency DC offset cancellation. By using 0.13 µm CMOS technology from Silterra, the simulation results show that this front end circuit can achieve a very low input referred noise of 1 pV/√Hz and high common mode rejection ratio (CMRR) of 174.05 dB. It also gives voltage gain of 75.45 dB with good power supply rejection ratio (PSSR) of 92.12 dB. The total power consumption is only 3 µW and thus suitable to be implemented with further signal processing and classification back end for low power biomedical SoC.

Keywords: CMOS, ECG, amplifier, low power

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809 High-Resolution ECG Automated Analysis and Diagnosis

Authors: Ayad Dalloo, Sulaf Dalloo

Abstract:

Electrocardiogram (ECG) recording is prone to complications, on analysis by physicians, due to noise and artifacts, thus creating ambiguity leading to possible error of diagnosis. Such drawbacks may be overcome with the advent of high resolution Methods, such as Discrete Wavelet Analysis and Digital Signal Processing (DSP) techniques. This ECG signal analysis is implemented in three stages: ECG preprocessing, features extraction and classification with the aim of realizing high resolution ECG diagnosis and improved detection of abnormal conditions in the heart. The preprocessing stage involves removing spurious artifacts (noise), due to such factors as muscle contraction, motion, respiration, etc. ECG features are extracted by applying DSP and suggested sloping method techniques. These measured features represent peak amplitude values and intervals of P, Q, R, S, R’, and T waves on ECG, and other features such as ST elevation, QRS width, heart rate, electrical axis, QR and QT intervals. The classification is preformed using these extracted features and the criteria for cardiovascular diseases. The ECG diagnostic system is successfully applied to 12-lead ECG recordings for 12 cases. The system is provided with information to enable it diagnoses 15 different diseases. Physician’s and computer’s diagnoses are compared with 90% agreement, with respect to physician diagnosis, and the time taken for diagnosis is 2 seconds. All of these operations are programmed in Matlab environment.

Keywords: ECG diagnostic system, QRS detection, ECG baseline removal, cardiovascular diseases

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808 An Enhanced SAR-Based Tsunami Detection System

Authors: Jean-Pierre Dubois, Jihad S. Daba, H. Karam, J. Abdallah

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Tsunami early detection and warning systems have proved to be of ultimate importance, especially after the destructive tsunami that hit Japan in March 2012. Such systems are crucial to inform the authorities of any risk of a tsunami and of the degree of its danger in order to make the right decision and notify the public of the actions they need to take to save their lives. The purpose of this research is to enhance existing tsunami detection and warning systems. We first propose an automated and miniaturized model of an early tsunami detection and warning system. The model for the operation of a tsunami warning system is simulated using the data acquisition toolbox of Matlab and measurements acquired from specified internet pages due to the lack of the required real-life sensors, both seismic and hydrologic, and building a graphical user interface for the system. In the second phase of this work, we implement various satellite image filtering schemes to enhance the acquired synthetic aperture radar images of the tsunami affected region that are masked by speckle noise. This enables us to conduct a post-tsunami damage extent study and calculate the percentage damage. We conclude by proposing improvements to the existing telecommunication infrastructure of existing warning tsunami systems using a migration to IP-based networks and fiber optics links.

Keywords: detection, GIS, GSN, GTS, GPS, speckle noise, synthetic aperture radar, tsunami, wiener filter

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807 Vertical Vibration Mitigation along Railway Lines

Authors: Jürgen Keil, Frank Walther

Abstract:

This article presents two innovative solutions for vertical vibration mitigation barriers including experimental and numerical investigations on the completed barriers. There is a continuing growth of exposure to noise and vibration in people´s daily lives due to the quest for more mobility and flexibility. In previous times neglected, immissions caused by vibrations can lead, for example, to secondary noise or damage in the adjacent buildings. Also people can feel very affected by vibrations. But unlike in new construction, in existing infrastructure and buildings action can be taken almost only on the transmission path of those vibrations. In the following two solutions were shown how vibrations on the transmission path can be mitigated. These are the jet grouting method and a new installation method (patent pending) by means of a prefabricated hollow box which is filled with vibration reducing mats and driven down to depth, are presented. The essential results of the numerical and experimental investigations on the completed wave barriers are included as well. This article is based on the results of a field test with the participation of Keller Holding, which was executed in the context of the European research project RIVAS (Railway Induced Vibration Abatement Solutions), and on a thesis done at the Technical University of Dresden with the involvement of BAUGRUND DRESDEN Ingenieurgesellschaft mbH and the Keller Holding GmbH.

Keywords: jet grouting, rail way lines, vertical vibration mitigation, vibration reducing mats

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806 Separating Landform from Noise in High-Resolution Digital Elevation Models through Scale-Adaptive Window-Based Regression

Authors: Anne M. Denton, Rahul Gomes, David W. Franzen

Abstract:

High-resolution elevation data are becoming increasingly available, but typical approaches for computing topographic features, like slope and curvature, still assume small sliding windows, for example, of size 3x3. That means that the digital elevation model (DEM) has to be resampled to the scale of the landform features that are of interest. Any higher resolution is lost in this resampling. When the topographic features are computed through regression that is performed at the resolution of the original data, the accuracy can be much higher, and the reported result can be adjusted to the length scale that is relevant locally. Slope and variance are calculated for overlapping windows, meaning that one regression result is computed per raster point. The number of window centers per area is the same for the output as for the original DEM. Slope and variance are computed by performing regression on the points in the surrounding window. Such an approach is computationally feasible because of the additive nature of regression parameters and variance. Any doubling of window size in each direction only takes a single pass over the data, corresponding to a logarithmic scaling of the resulting algorithm as a function of the window size. Slope and variance are stored for each aggregation step, allowing the reported slope to be selected to minimize variance. The approach thereby adjusts the effective window size to the landform features that are characteristic to the area within the DEM. Starting with a window size of 2x2, each iteration aggregates 2x2 non-overlapping windows from the previous iteration. Regression results are stored for each iteration, and the slope at minimal variance is reported in the final result. As such, the reported slope is adjusted to the length scale that is characteristic of the landform locally. The length scale itself and the variance at that length scale are also visualized to aid in interpreting the results for slope. The relevant length scale is taken to be half of the window size of the window over which the minimum variance was achieved. The resulting process was evaluated for 1-meter DEM data and for artificial data that was constructed to have defined length scales and added noise. A comparison with ESRI ArcMap was performed and showed the potential of the proposed algorithm. The resolution of the resulting output is much higher and the slope and aspect much less affected by noise. Additionally, the algorithm adjusts to the scale of interest within the region of the image. These benefits are gained without additional computational cost in comparison with resampling the DEM and computing the slope over 3x3 images in ESRI ArcMap for each resolution. In summary, the proposed approach extracts slope and aspect of DEMs at the lengths scales that are characteristic locally. The result is of higher resolution and less affected by noise than existing techniques.

Keywords: high resolution digital elevation models, multi-scale analysis, slope calculation, window-based regression

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805 Rotorcraft Performance and Environmental Impact Evaluation by Multidisciplinary Modelling

Authors: Pierre-Marie Basset, Gabriel Reboul, Binh DangVu, Sébastien Mercier

Abstract:

Rotorcraft provides invaluable services thanks to their Vertical Take-Off and Landing (VTOL), hover and low speed capabilities. Yet their use is still often limited by their cost and environmental impact, especially noise and energy consumption. One of the main brakes to the expansion of the use of rotorcraft for urban missions is the environmental impact. The first main concern for the population is the noise. In order to develop the transversal competency to assess the rotorcraft environmental footprint, a collaboration has been launched between six research departments within ONERA. The progress in terms of models and methods are capitalized into the numerical workshop C.R.E.A.T.I.O.N. “Concepts of Rotorcraft Enhanced Assessment Through Integrated Optimization Network”. A typical mission for which the environmental impact issue is of great relevance has been defined. The first milestone is to perform the pre-sizing of a reference helicopter for this mission. In a second milestone, an alternate rotorcraft concept has been defined: a tandem rotorcraft with optional propulsion. The key design trends are given for the pre-sizing of this rotorcraft aiming at a significant reduction of the global environmental impact while still giving equivalent flight performance and safety with respect to the reference helicopter. The models and methods have been improved for catching sooner and more globally, the relative variations on the environmental impact when changing the rotorcraft architecture, the pre-design variables and the operation parameters.

Keywords: environmental impact, flight performance, helicopter, multi objectives multidisciplinary optimization, rotorcraft

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804 Fano-Resonance-Based Wideband Acoustic Metamaterials with Highly Efficient Ventilation

Authors: Xi-Wen Xiao, Tzy-Rong Lin, Chien-Hao Liu

Abstract:

Ventilated acoustic metamaterials have attracted considerable research attention due to their low-frequency absorptions and efficient fluid ventilations. In this research, a wideband acoustic metamaterial with auditory filtering ability and efficient ventilation capacity were proposed. In contrast to a conventional Fano-like resonator, a Fano-like resonator composed of a resonant unit and two nonresonant units with a large opening area of 68% for fluid passages was developed. In addition, the coupling mechanism to improve the narrow bandwidths of conventional Fano-resonance-based meta-materials was included. With a suitable design, the output sound waves of the resonant and nonresonant states were out of phase to achieve sound absorptions in the far fields. Therefore, three-element and five-element coupled Fano-like metamaterials were designed and simulated with the help of the finite element software to obtain the filtering fractional bandwidths of 42.5% and 61.8%, respectively. The proposed approach can be extended to multiple coupled resonators for obtaining ultra-wide bandwidths and can be implemented with 3D printing for practical applications. The research results are expected to be beneficial for sound filtering or noise reductions in duct applications and limited-volume spaces.

Keywords: fano resonance, noise reduction, resonant coupling, sound filtering, ventilated acoustic metamaterial

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803 Ionian Sea Aquarium-Museum in Kefallinia Island, Greece: A Hub Developing the Underwater Natural and Cultural Resources in the Ionian Sea and Advancing the Ocean Literacy to the Public

Authors: Ferentinos George, Papatheodorou George, Belmonte Genuario, Geraga Maria, Christodoulou Dimitris, Fakiris Elias, Iatrou Margarita, Kordella Stravroula, Prevenios Michail, Mentogianis Vassilis, Sotiropoulos Makis

Abstract:

The Ionian Sea Aquarium-Museum in Kefallinia Island, Greece and its twinning with that of Santa Maria al Bagno in the Salento peninsula, Italy, are recently established Hubs in the Ionian Sea funded by the European Territorial Cooperation Programme, Greece-Italy 2007-2013. The objectives of the Ionian Sea Aquarium-Museum are: (i) exhibiting to the public the underwater natural and cultural treasures of the seas surrounding the island, (ii) the functioning of a recreational/vocational hub for all educational levels but also for sea users and stakeholders, to raise their awareness of the seas and engage them in the European notion of the Blue Growth of the Seas and (iii) setting up diving parks in sites of natural and cultural importance. The natural heritage in the Aquarium-Museum is exhibited in five tanks displaying the two most important benthic habitats in the Mediterranean Sea, that is, the Posidonia oceanica and the Coralligene assemblages with the associated rich fauna. The cultural heritage is exhibited in: (i) Dioramas displaying scale model replicas of the three best preserved ancient and historic wrecks. -The Fiscardo Roman wreck dating between 1st cent B.C. and 2nd cent. A.D., which is one of the largest and best preserved in the Mediterranean Sea. -The HMS PERSEUS British submarine, which is known for the second deepest submarine escape from all sunken submarines in WW II, and -A wooden wreck, the Italian ship Alma probably, which was requisitioned by the German army and used for transporting supplies and ammunition. (ii) Documentaries: The first two present the complete story from launching to sinking of: the HMS PERSEUS British submarine, the SS Ardena which is associated with the Italian Aqui Division killed by the German forces in Kefallinia and made known from the book and film “Captain Corelli’s Mandolin” and the third documentary deals with the birth place of seafaring in the world, which took place in the Greek. Archipelago by Neanderthals and modern humans between 115 and 35 thousand years ago. The Aquarium-Museum starts from next year (a) educational programmes for schools and tourists to discover the natural and cultural treasures around Kefallinia island, (b) recreational/vocational holiday activities centered on eco-diving and get involved in mapping and monitoring NATURA 2000 sites around the island and thus actively engaged in the Blue Growth of the seas and (c) summer schools aimed at under/post-graduate students, who are interested in marine archaeology and geo-habitat mapping and are looking for a job in the sustainable management of the seas. The exhibition themes in the Aquarium-Museum as well as the recreational /vocational and educational activities are prepared by the Oceanus Net laboratories of Patras University and were selected after surveying the seafloor using the latest state of art sonar and camera technologies.

Keywords: aquarium-museum, cultural and natural treasures, ionian sea, Kefallinia Island

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802 Optimized Processing of Neural Sensory Information with Unwanted Artifacts

Authors: John Lachapelle

Abstract:

Introduction: Neural stimulation is increasingly targeted toward treatment of back pain, PTSD, Parkinson’s disease, and for sensory perception. Sensory recording during stimulation is important in order to examine neural response to stimulation. Most neural amplifiers (headstages) focus on noise efficiency factor (NEF). Conversely, neural headstages need to handle artifacts from several sources including power lines, movement (EMG), and neural stimulation itself. In this work a layered approach to artifact rejection is used to reduce corruption of the neural ENG signal by 60dBv, resulting in recovery of sensory signals in rats and primates that would previously not be possible. Methods: The approach combines analog techniques to reduce and handle unwanted signal amplitudes. The methods include optimized (1) sensory electrode placement, (2) amplifier configuration, and (3) artifact blanking when necessary. The techniques together are like concentric moats protecting a castle; only the wanted neural signal can penetrate. There are two conditions in which the headstage operates: unwanted artifact < 50mV, linear operation, and artifact > 50mV, fast-settle gain reduction signal limiting (covered in more detail in a separate paper). Unwanted Signals at the headstage input: Consider: (a) EMG signals are by nature < 10mV. (b) 60 Hz power line signals may be > 50mV with poor electrode cable conditions; with careful routing much of the signal is common to both reference and active electrode and rejected in the differential amplifier with <50mV remaining. (c) An unwanted (to the neural recorder) stimulation signal is attenuated from stimulation to sensory electrode. The voltage seen at the sensory electrode can be modeled Φ_m=I_o/4πσr. For a 1 mA stimulation signal, with 1 cm spacing between electrodes, the signal is <20mV at the headstage. Headstage ASIC design: The front end ASIC design is designed to produce < 1% THD at 50mV input; 50 times higher than typical headstage ASICs, with no increase in noise floor. This requires careful balance of amplifier stages in the headstage ASIC, as well as consideration of the electrodes effect on noise. The ASIC is designed to allow extremely small signal extraction on low impedance (< 10kohm) electrodes with configuration of the headstage ASIC noise floor to < 700nV/rt-Hz. Smaller high impedance electrodes (> 100kohm) are typically located closer to neural sources and transduce higher amplitude signals (> 10uV); the ASIC low-power mode conserves power with 2uV/rt-Hz noise. Findings: The enhanced neural processing ASIC has been compared with a commercial neural recording amplifier IC. Chronically implanted primates at MGH demonstrated the presence of commercial neural amplifier saturation as a result of large environmental artifacts. The enhanced artifact suppression headstage ASIC, in the same setup, was able to recover and process the wanted neural signal separately from the suppressed unwanted artifacts. Separately, the enhanced artifact suppression headstage ASIC was able to separate sensory neural signals from unwanted artifacts in mouse-implanted peripheral intrafascicular electrodes. Conclusion: Optimizing headstage ASICs allow observation of neural signals in the presence of large artifacts that will be present in real-life implanted applications, and are targeted toward human implantation in the DARPA HAPTIX program.

Keywords: ASIC, biosensors, biomedical signal processing, biomedical sensors

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801 Taguchi-Based Six Sigma Approach to Optimize Surface Roughness for Milling Processes

Authors: Sky Chou, Joseph C. Chen

Abstract:

This paper focuses on using Six Sigma methodologies to improve the surface roughness of a manufactured part produced by the CNC milling machine. It presents a case study where the surface roughness of milled aluminum is required to reduce or eliminate defects and to improve the process capability index Cp and Cpk for a CNC milling process. The six sigma methodology, DMAIC (design, measure, analyze, improve, and control) approach, was applied in this study to improve the process, reduce defects, and ultimately reduce costs. The Taguchi-based six sigma approach was applied to identify the optimized processing parameters that led to the targeted surface roughness specified by our customer. A L9 orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of feed rate, depth of cut, spindle speed, and surface roughness. The noise factor is the difference between the old cutting tool and the new cutting tool. The confirmation run with the optimal parameters confirmed that the new parameter settings are correct. The new settings also improved the process capability index. The purpose of this study is that the Taguchi–based six sigma approach can be efficiently used to phase out defects and improve the process capability index of the CNC milling process.

Keywords: CNC machining, six sigma, surface roughness, Taguchi methodology

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800 Improved Signal-To-Noise Ratio by the 3D-Functionalization of Fully Zwitterionic Surface Coatings

Authors: Esther Van Andel, Stefanie C. Lange, Maarten M. J. Smulders, Han Zuilhof

Abstract:

False outcomes of diagnostic tests are a major concern in medical health care. To improve the reliability of surface-based diagnostic tests, it is of crucial importance to diminish background signals that arise from the non-specific binding of biomolecules, a process called fouling. The aim is to create surfaces that repel all biomolecules except the molecule of interest. This can be achieved by incorporating antifouling protein repellent coatings in between the sensor surface and it’s recognition elements (e.g. antibodies, sugars, aptamers). Zwitterionic polymer brushes are considered excellent antifouling materials, however, to be able to bind the molecule of interest, the polymer brushes have to be functionalized and so far this was only achieved at the expense of either antifouling or binding capacity. To overcome this limitation, we combined both features into one single monomer: a zwitterionic sulfobetaine, ensuring antifouling capabilities, equipped with a clickable azide moiety which allows for further functionalization. By copolymerizing this monomer together with a standard sulfobetaine, the number of azides (and with that the number of recognition elements) can be tuned depending on the application. First, the clickable azido-monomer was synthesized and characterized, followed by copolymerizing this monomer to yield functionalizable antifouling brushes. The brushes were fully characterized using surface characterization techniques like XPS, contact angle measurements, G-ATR-FTIR and XRR. As a proof of principle, the brushes were subsequently functionalized with biotin via strain-promoted alkyne azide click reactions, which yielded a fully zwitterionic biotin-containing 3D-functionalized coating. The sensing capacity was evaluated by reflectometry using avidin and fibrinogen containing protein solutions. The surfaces showed excellent antifouling properties as illustrated by the complete absence of non-specific fibrinogen binding, while at the same time clear responses were seen for the specific binding of avidin. A great increase in signal-to-noise ratio was observed, even when the amount of functional groups was lowered to 1%, compared to traditional modification of sulfobetaine brushes that rely on a 2D-approach in which only the top-layer can be functionalized. This study was performed on stoichiometric silicon nitride surfaces for future microring resonator based assays, however, this methodology can be transferred to other biosensor platforms which are currently being investigated. The approach presented herein enables a highly efficient strategy for selective binding with retained antifouling properties for improved signal-to-noise ratios in binding assays. The number of recognition units can be adjusted to a specific need, e.g. depending on the size of the analyte to be bound, widening the scope of these functionalizable surface coatings.

Keywords: antifouling, signal-to-noise ratio, surface functionalization, zwitterionic polymer brushes

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799 Seismic Integrity Determination of Dams in Urban Areas

Authors: J. M. Mayoral, M. Anaya

Abstract:

The urban and economic development of cities demands the construction of water use and flood control infrastructure. Likewise, it is necessary to determine the safety level of the structures built with the current standards and if it is necessary to define the reinforcement actions. The foregoing is even more important in structures of great importance, such as dams, since they imply a greater risk for the population in case of failure or undesirable operating conditions (e.g., seepage, cracks, subsidence). This article presents a methodology for determining the seismic integrity of dams in urban areas. From direct measurements of the dynamic properties using geophysical exploration and ambient seismic noise measurements, the seismic integrity of the concrete-faced rockfill dam selected as a case of study is evaluated. To validate the results, two accelerometer stations were installed (e.g., free field and crest of the dam). Once the dynamic properties were determined, three-dimensional finite difference models were developed to evaluate the dam seismic performance for different intensities of movement, considering the site response and soil-structure interaction effects. The seismic environment was determined from the uniform hazard spectra for several return periods. Based on the results obtained, the safety level of the dam against different seismic actions was determined, and the effectiveness of ambient seismic noise measurements in dynamic characterization and subsequent evaluation of the seismic integrity of urban dams was evaluated.

Keywords: risk, seismic, soil-structure interaction, urban dams

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798 Vibroacoustic Modulation of Wideband Vibrations and its Possible Application for Windmill Blade Diagnostics

Authors: Abdullah Alnutayfat, Alexander Sutin, Dong Liu

Abstract:

Wind turbine has become one of the most popular energy productions. However, failure of blades and maintenance costs evolve into significant issues in the wind power industry, so it is essential to detect the initial blade defects to avoid the collapse of the blades and structure. This paper aims to apply modulation of high-frequency blade vibrations by low-frequency blade rotation, which is close to the known Vibro-Acoustic Modulation (VAM) method. The high-frequency wideband blade vibration is produced by the interaction of the surface blades with the environment air turbulence, and the low-frequency modulation is produced by alternating bending stress due to gravity. The low-frequency load of rotational wind turbine blades ranges between 0.2-0.4 Hz and can reach up to 2 Hz for strong wind. The main difference between this study and previous ones on VAM methods is the use of a wideband vibration signal from the blade's natural vibrations. Different features of the vibroacoustic modulation are considered using a simple model of breathing crack. This model considers the simple mechanical oscillator, where the parameters of the oscillator are varied due to low-frequency blade rotation. During the blade's operation, the internal stress caused by the weight of the blade modifies the crack's elasticity and damping. The laboratory experiment using steel samples demonstrates the possibility of VAM using a probe wideband noise signal. A cycle load with a small amplitude was used as a pump wave to damage the tested sample, and a small transducer generated a wideband probe wave. The received signal demodulation was conducted using the Detecting of Envelope Modulation on Noise (DEMON) approach. In addition, the experimental results were compared with the modulation index (MI) technique regarding the harmonic pump wave. The wideband and traditional VAM methods demonstrated similar sensitivity for earlier detection of invisible cracks. Importantly, employing a wideband probe signal with the DEMON approach speeds up and simplifies testing since it eliminates the need to conduct tests repeatedly for various harmonic probe frequencies and to adjust the probe frequency.

Keywords: vibro-acoustic modulation, detecting of envelope modulation on noise, damage, turbine blades

Procedia PDF Downloads 99
797 Performance Comparison of Wideband Covariance Matrix Sparse Representation (W-CMSR) with Other Wideband DOA Estimation Methods

Authors: Sandeep Santosh, O. P. Sahu

Abstract:

In this paper, performance comparison of wideband covariance matrix sparse representation (W-CMSR) method with other existing wideband Direction of Arrival (DOA) estimation methods has been made.W-CMSR relies less on a priori information of the incident signal number than the ordinary subspace based methods.Consider the perturbation free covariance matrix of the wideband array output. The diagonal covariance elements are contaminated by unknown noise variance. The covariance matrix of array output is conjugate symmetric i.e its upper right triangular elements can be represented by lower left triangular ones.As the main diagonal elements are contaminated by unknown noise variance,slide over them and align the lower left triangular elements column by column to obtain a measurement vector.Simulation results for W-CMSR are compared with simulation results of other wideband DOA estimation methods like Coherent signal subspace method (CSSM), Capon, l1-SVD, and JLZA-DOA. W-CMSR separate two signals very clearly and CSSM, Capon, L1-SVD and JLZA-DOA fail to separate two signals clearly and an amount of pseudo peaks exist in the spectrum of L1-SVD.

Keywords: W-CMSR, wideband direction of arrival (DOA), covariance matrix, electrical and computer engineering

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796 Six Sigma-Based Optimization of Shrinkage Accuracy in Injection Molding Processes

Authors: Sky Chou, Joseph C. Chen

Abstract:

This paper focuses on using six sigma methodologies to reach the desired shrinkage of a manufactured high-density polyurethane (HDPE) part produced by the injection molding machine. It presents a case study where the correct shrinkage is required to reduce or eliminate defects and to improve the process capability index Cp and Cpk for an injection molding process. To improve this process and keep the product within specifications, the six sigma methodology, design, measure, analyze, improve, and control (DMAIC) approach, was implemented in this study. The six sigma approach was paired with the Taguchi methodology to identify the optimized processing parameters that keep the shrinkage rate within the specifications by our customer. An L9 orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of the cooling time, melt temperature, holding time, and metering stroke. The noise factor is the difference between material brand 1 and material brand 2. After the confirmation run was completed, measurements verify that the new parameter settings are optimal. With the new settings, the process capability index has improved dramatically. The purpose of this study is to show that the six sigma and Taguchi methodology can be efficiently used to determine important factors that will improve the process capability index of the injection molding process.

Keywords: injection molding, shrinkage, six sigma, Taguchi parameter design

Procedia PDF Downloads 178