983 resultados para Industrial noise
Resumo:
The study was undertaken to generate socio-economic information on fish market systems and performance of the industrial processing industry, which will guide the processes leading to modernization of the fisheries sector and, sustainability of Lake Victoria fisheries. The main objective of this study was to evaluate the socio-economic implications of the fish marketing systems with particular emphasis on fish export market in Uganda. The study thus, analysed the socio-economic characteristics of fishers and examinined fish marketing systems and the impacts on the fishing activities, food security, employment opportunities and incomes of fisher-folk communities.
Resumo:
In this paper, phase noise analysis of a mechanical autonomous impact oscillator with a MEMS resonator is performed. Since the circuit considered belongs to the class of hybrid systems, methods based on the variational model for the evaluation of either phase noise or steady state solutions cannot be directly applied. As a matter of fact, the monodromy matrix is not defined at impact events in these systems. By introducing saltation matrices, this limit is overcome and the aforementioned methods are extended. In particular, the unified theory developed by Demir is used to analyze the phase noise after evaluating the asymptotically stable periodic solution of the system by resorting to the shooting method. Numerical results are presented to show how noise sources affect the phase noise performances. © 2011 IEEE.
Resumo:
To calculate the noise emanating from a turbulent flow using an acoustic analogy knowledge concerning the unsteady characteristics of the turbulence is required. Specifically, the form of the turbulent correlation tensor together with various time and length-scales are needed. However, if a Reynolds Averaged Navier-Stores calculation is used as the starting point then one can only obtain steady characteristics of the flow and it is necessary to model the unsteady behavior in some way. While there has been considerable attention given to the correct way to model the form of the correlation tensor less attention has been given to the underlying physics that dictate the proper choice of time-scale. In this paper the authors recognize that there are several time dependent processes occurring within a turbulent flow and propose a new way of obtaining the time-scale. Isothermal single-stream flow jets with Mach numbers 0.75 and 0.90 have been chosen for the present study. The Mani-Gliebe-Balsa-Khavaran method has been used for prediction of noise at different angles, and there is good agreement between the noise predictions and observations. Furthermore, the new time-scale has an inherent frequency dependency that arises naturally from the underlying physics, thus avoiding supplementary mathematical enhancements needed in previous modeling.
Resumo:
Over the past 50 years, economic and technological developments have dramatically increased the human contribution to ambient noise in the ocean. The dominant frequencies of most human-made noise in the ocean is in the low-frequency range (defined as sound energy below 1000Hz), and low-frequency sound (LFS) may travel great distances in the ocean due to the unique propagation characteristics of the deep ocean (Munk et al. 1989). For example, in the Northern Hemisphere oceans low-frequency ambient noise levels have increased by as much as 10 dB during the period from 1950 to 1975 (Urick 1986; review by NRC 1994). Shipping is the overwhelmingly dominant source of low-frequency manmade noise in the ocean, but other sources of manmade LFS including sounds from oil and gas industrial development and production activities (seismic exploration, construction work, drilling, production platforms), and scientific research (e.g., acoustic tomography and thermography, underwater communication). The SURTASS LFA system is an additional source of human-produced LFS in the ocean, contributing sound energy in the 100-500 Hz band. When considering a document that addresses the potential effects of a low-frequency sound source on the marine environment, it is important to focus upon those species that are the most likely to be affected. Important criteria are: 1) the physics of sound as it relates to biological organisms; 2) the nature of the exposure (i.e. duration, frequency, and intensity); and 3) the geographic region in which the sound source will be operated (which, when considered with the distribution of the organisms will determine which species will be exposed). The goal in this section of the LFA/EIS is to examine the status, distribution, abundance, reproduction, foraging behavior, vocal behavior, and known impacts of human activity of those species may be impacted by LFA operations. To focus our efforts, we have examined species that may be physically affected and are found in the region where the LFA source will be operated. The large-scale geographic location of species in relation to the sound source can be determined from the distribution of each species. However, the physical ability for the organism to be impacted depends upon the nature of the sound source (i.e. explosive, impulsive, or non-impulsive); and the acoustic properties of the medium (i.e. seawater) and the organism. Non-impulsive sound is comprised of the movement of particles in a medium. Motion is imparted by a vibrating object (diaphragm of a speaker, vocal chords, etc.). Due to the proximity of the particles in the medium, this motion is transmitted from particle to particle in waves away from the sound source. Because the particle motion is along the same axis as the propagating wave, the waves are longitudinal. Particles move away from then back towards the vibrating source, creating areas of compression (high pressure) and areas of rarefaction (low pressure). As the motion is transferred from one particle to the next, the sound propagates away from the sound source. Wavelength is the distance from one pressure peak to the next. Frequency is the number of waves passing per unit time (Hz). Sound velocity (not to be confused with particle velocity) is the impedance is loosely equivalent to the resistance of a medium to the passage of sound waves (technically it is the ratio of acoustic pressure to particle velocity). A high impedance means that acoustic particle velocity is small for a given pressure (low impedance the opposite). When a sound strikes a boundary between media of different impedances, both reflection and refraction, and a transfer of energy can occur. The intensity of the reflection is a function of the intensity of the sound wave and the impedances of the two media. Two key factors in determining the potential for damage due to a sound source are the intensity of the sound wave and the impedance difference between the two media (impedance mis-match). The bodies of the vast majority of organisms in the ocean (particularly phytoplankton and zooplankton) have similar sound impedence values to that of seawater. As a result, the potential for sound damage is low; organisms are effectively transparent to the sound – it passes through them without transferring damage-causing energy. Due to the considerations above, we have undertaken a detailed analysis of species which met the following criteria: 1) Is the species capable of being physically affected by LFS? Are acoustic impedence mis-matches large enough to enable LFS to have a physical affect or allow the species to sense LFS? 2) Does the proposed SURTASS LFA geographical sphere of acoustic influence overlap the distribution of the species? Species that did not meet the above criteria were excluded from consideration. For example, phytoplankton and zooplankton species lack acoustic impedance mis-matches at low frequencies to expect them to be physically affected SURTASS LFA. Vertebrates are the organisms that fit these criteria and we have accordingly focused our analysis of the affected environment on these vertebrate groups in the world’s oceans: fishes, reptiles, seabirds, pinnipeds, cetaceans, pinnipeds, mustelids, sirenians (Table 1).
Resumo:
Industrialists have few example processes they can benchmark against in order to choose a multi-agent development kit. In this paper we present a review of commercial and academic agent tools with the aim of selecting one for developing an intelligent, self-serving asset architecture. In doing so, we map and enhance relevant assessment criteria found in literature. After a preliminary review of 20 multiagent platforms, we examine in further detail those of JADE, JACK and Cougaar. Our findings indicate that Cougaar is well suited for our requirements, showing excellent support for criteria such as scalability, persistence, mobility and lightweightness. © 2010 IEEE.