999 resultados para Acoustic buildings


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Acoustic emission technique has become a significant and powerful structural health monitoring tool for structures. Researches to date have been done on crack location, fatigue crack propagation in materials and severity assessment of failure using acoustic emission technique. Determining severity of failure in steel structures using acoustic emission technique is still a challenge to accurately determine the relationship between the severity of crack propagation and acoustic emission activities. In this study three point bending test on low carbon steel samples along with acoustic emission technique have been used to determine crack propagation and severity. A notch is introduced at the tension face of the loading point to the samples to initiate the crack. The results show that the percentage of load drop of the steel specimen has a reciprocal relationship with the crack opening i.e. crack opening zones are influenced by the loading rate. In post yielding region, common acoustic emission signal parameters such as, signal strength, energy and amplitudes are found to be higher than those at pre-yielding and at yielding.

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Bats are an important component of mammalian biodiversity and fill such a wide array of ecological niches that they may offer an important multisensory bioindicator role in assessing ecosystem health. There is a need to monitor population trends of bats for their own sake because many populations face numerous environmental threats related to climate change, habitat loss, fragmentation, hunting, and emerging diseases. To be able to establish bat ultrasonic biodiversity trends as a reliable indicator, it is important to standardize monitoring protocols, data management, and analyses. This chapter discusses the main issues to be considered in developing a bat ultrasonic indicator. It focuses on the results from indicator bats program (iBats), a system for the global acoustic monitoring of bats, in Eastern Europe. Finally, the chapter reviews the strengths and weaknesses of the Program and considers the opportunities and threats that it may face in the future.

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We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

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Effective fuel injector operation and efficient combustion are two of the most critical aspects when Diesel engine performance, efficiency and reliability are considered. Indeed, it is widely acknowledged that fuel injection equipment faults lead to increased fuel consumption, reduced power, greater levels of exhaust emissions and even unexpected engine failure. Previous investigations have identified fuel injector related acoustic emission activity as being caused by mechanisms such as fuel line pressure build-up; fuel flow through injector nozzles, injector needle opening and closing impacts and premixed combustion related pulses. Few of these investigations however, have attempted to categorise the close association and interrelation that exists between fuel injection equipment function and the acoustic emission generating mechanisms. Consequently, a significant amount of ambiguity remains in the interpretation and categorisation of injector related AE activity with respect to the functional characteristics of specific fuel injection equipment. The investigation presented addresses this ambiguity by detailing a study in which AE signals were recorded and analysed from two different Diesel engines employing the two commonly encountered yet fundamentally different types of fuel injection equipment. Results from tests in which faults were induced into fuel injector nozzles from both indirect-injection and direct-injection engines show that functional differences between the main types of fuel injection equipment results in acoustic emission activity which can be specifically related to the type of fuel injection equipment used.

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We present a new approach for creating and implementing an ad-hoc underwater acoustic sensor network based on connecting a small processor to the serial port of a commercial CDMA acoustic modem. The processor acts as a "node controller" providing the networking layer that the modems lack. The ad-hoc networking protocol is based on a modified dynamic source routing (DSR) approach and can be configured for maximising information throughput or minimising energy expenditure. The system was developed in simulation and then evaluated during field trials using a 10 node deployment. Experimental results show reliable multi-hop networking under a variety of network configurations, with the added ability to determine internode ranges to within 1.5 m for localisation.

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The lateral amygdala (LA) receives information from auditory and visual sensory modalities, and uses this information to encode lasting memories that predict threat. One unresolved question about the amygdala is how multiple memories, derived from different sensory modalities, are organized at the level of neuronal ensembles. We previously showed that fear conditioning using an auditory conditioned stimulus (CS) was spatially allocated to a stable topography of neurons within the dorsolateral amygdala (LAd) (Bergstrom et al, 2011). Here, we asked how fear conditioning using a visual CS is topographically organized within the amygdala. To induce a lasting fear memory trace we paired either an auditory (2 khz, 55 dB, 20 s) or visual (1 Hz, 0.5 s on/0.5 s off, 35 lux, 20 s) CS with a mild foot shock unconditioned stimulus (0.6 mA, 0.5 s). To detect learning-induced plasticity in amygdala neurons, we used immunohistochemistry with an antibody for phosphorylated mitogen-activated protein kinase (pMAPK). Using a principal components analysis-based approach to extract and visualize spatial patterns, we uncovered two unique spatial patterns of activated neurons in the LA that were associated with auditory and visual fear conditioning. The first spatial pattern was specific to auditory cued fear conditioning and consisted of activated neurons topographically organized throughout the LAd and ventrolateral nuclei (LAvl) of the LA. The second spatial pattern overlapped for auditory and visual fear conditioning and was comprised of activated neurons located mainly within the LAvl. Overall, the density of pMAPK labeled cells throughout the LA was greatest in the auditory CS group, even though freezing in response to the visual and auditory CS was equivalent. There were no differences detected in the number of pMAPK activated neurons within the basal amygdala nuclei. Together, these results provide the first basic knowledge about the organizational structure of two different fear engrams within the amygdala and suggest they are dissociable at the level of neuronal ensembles within the LA

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Internal heat sources may not only consume energy directly through their operation (e.g. lighting), but also contribute to building cooling or heating loads, which indirectly change building cooling and heating energy. Through the use of building simulation technique, this paper investigates the influence of building internal load densities on the energy and thermal performance of air conditioned office buildings in Australia. Case studies for air conditioned office buildings in major Australian capital cities are presented. It is found that with a decrease of internal load density in lighting and/or plug load, both the building cooling load and total energy use can be significantly reduced. Their effect on overheating hour reduction would be dependent on the local climate. In particular, it is found that if the building total internal load density is reduced from the base case of “medium” to “extra–low, the building total energy use under the future 2070 high scenario can be reduced by up to 89 to 120 kWh/m² per annum and the overheating problem could be completely avoided. It is suggested that the reduction in building internal load densities could be adopted as one of adaptation strategies for buildings in face of the future global warming.

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This study aimed to develop a multi-component model that can be used to maximise indoor environmental quality inside mechanically ventilated office buildings, while minimising energy usage. The integrated model, which was developed and validated from fieldwork data, was employed to assess the potential improvement of indoor air quality and energy saving under different ventilation conditions in typical air-conditioned office buildings in the subtropical city of Brisbane, Australia. When operating the ventilation system under predicted optimal conditions of indoor environmental quality and energy conservation and using outdoor air filtration, average indoor particle number (PN) concentration decreased by as much as 77%, while indoor CO2 concentration and energy consumption were not significantly different compared to the normal summer time operating conditions. Benefits of operating the system with this algorithm were most pronounced during the Brisbane’s mild winter. In terms of indoor air quality, average indoor PN and CO2 concentrations decreased by 48% and 24%, respectively, while potential energy savings due to free cooling went as high as 108% of the normal winter time operating conditions. The application of such a model to the operation of ventilation systems can help to significantly improve indoor air quality and energy conservation in air-conditioned office buildings.

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The purpose of this article is to assess the viability of blanket sustainability policies, such as Building Rating Systems in achieving energy efficiency in university campus buildings. We analyzed the energy consumption trends of 10 LEED-certified buildings and 14 non-LEED certified buildings at a major university in the US. Energy Use Intensity (EUI) of the LEED buildings was significantly higher (EUILEED= 331.20 kBtu/sf/yr) than non-LEED buildings (EUInon-LEED=222.70 kBtu/sf/yr); however, the median EUI values were comparable (EUILEED= 172.64 and EUInon-LEED= 178.16). Because the distributions of EUI values were non-symmetrical in this dataset, both measures can be used for energy comparisons—this was also evident when EUI computations exclude outliers, EUILEED=171.82 and EUInon-LEED=195.41. Additional analyses were conducted to further explore the impact of LEED certification on university campus buildings energy performance. No statistically significant differences were observed between certified and non-certified buildings through a range of robust comparison criteria. These findings were then leveraged to devise strategies to achieve sustainable energy policies for university campus buildings and to identify potential issues with portfolio level building energy performance comparisons.

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This thesis is concerned with the detection and prediction of rain in environmental recordings using different machine learning algorithms. The results obtained in this research will help ecologists to efficiently analyse environmental data and monitor biodiversity.

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The purpose of this research is to assess daylight performance of buildings with climatic responsive envelopes with complex geometry that integrates shading devices in the façade. To this end two case studies are chosen due to their complex geometries and integrated daylight devices. The effect of different parameters of the daylight devices is analysed through Climate base daylight metrics.

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This paper examines the feasibility of using vertical light pipes to naturally illuminate the central core of a multilevel building not reached by window light. The challenges addressed were finding a method to extract and distribute equal amounts of light at each level and designing collectors to improve the effectiveness of vertical light pipes in delivering low elevation sunlight to the interior. Extraction was achieved by inserting partially reflecting cones within transparent sections of the pipes at each floor level. Theory was formulated to estimate the partial reflectance necessary to provide equal light extraction at each level. Designs for daylight collectors formed from laser cut panels tilted above the light pipe were developed and the benefits and limitations of static collectors as opposed to collectors that follow the sun azimuth investigated. Performance was assessed with both basic and detailed mathematical simulation and by observations made with a five level model building under clear sky conditions.