929 resultados para Airport noise


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Mode of access: Internet.

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"June 1983."

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"January 1981."

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Nella tesi si analizzano le principali fonti del rumore aeronautico, lo stato dell'arte dal punto di vista normativo, tecnologico e procedurale. Si analizza lo stato dell'arte anche riguardo alla classificazione degli aeromobili, proponendo un nuovo indice prestazionale in alternativa a quello indicato dalla metodologia di certificazione (AC36-ICAO) Allo scopo di diminuire l'impatto acustico degli aeromobili in fase di atterraggio, si analizzano col programma INM i benefici di procedure CDA a 3° rispetto alle procedure tradizionali e, di seguito di procedure CDA ad angoli maggiori in termini di riduzione di lunghezza e di area delle isofoniche SEL85, SEL80 e SEL75.

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One of the fastest growing industries – aviation – faces serious and compounding challenges in maintaining healthy relationships with community stakeholders. One area in aviation creating community conflict is noise pollution. However, current understandings of the factors that affect noise annoyance of the community are poorly conceptualized. More importantly, the way community needs and expectations could be incorporated in airport governance has been inadequately framed to address the issue of aircraft noise. This paper proposes the util-ity of adopting an integrated strategic asset management (ISAM) framework [1] to explore the dynamic nature of relationships between and airport and its surrounding area. The case of the Gold Coast Airport (OOL) operator and community stakeholders is used. This paper begins with an overview of the ISAM framework in the context of airport governance and sustainable development – as a way to find a balance between economic opportunities and societal concerns through stakeholder engagement. Next, an exploratory case study is adopted as a method to explore the noise-related complaints, complainants, and possible causes. Fol-lowing this, the paper reviews three approaches to community stakeholder engagement in Australia, Japan, and UK and discusses their implications in the con-text of OOL. The paper concludes with a contention that airport governance is likely to be much more effective with the adoption of ISAM framework than without it.

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In this paper, a refined classic noise prediction method based on the VISSIM and FHWA noise prediction model is formulated to analyze the sound level contributed by traffic on the Nanjing Lukou airport connecting freeway before and after widening. The aim of this research is to (i) assess the traffic noise impact on the Nanjing University of Aeronautics and Astronautics (NUAA) campus before and after freeway widening, (ii) compare the prediction results with field data to test the accuracy of this method, (iii) analyze the relationship between traffic characteristics and sound level. The results indicate that the mean difference between model predictions and field measurements is acceptable. The traffic composition impact study indicates that buses (including mid-sizedtrucks) and heavy goods vehicles contribute a significant proportion of total noise power despite their low traffic volume. In addition, speed analysis offers an explanation for the minor differences in noise level across time periods. Future work will aim at reducing model error, by focusing on noise barrier analysis using the FEM/BEM method and modifying the vehicle noise emission equation by conducting field experimentation.

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In this paper, a refined classic noise prediction method based on the VISSIM and FHWA noise prediction model is formulated to analyze the sound level contributed by traffic on the Nanjing Lukou airport connecting freeway before and after widening. The aim of this research is to (i) assess the traffic noise impact on the Nanjing University of Aeronautics and Astronautics (NUAA) campus before and after freeway widening, (ii) compare the prediction results with field data to test the accuracy of this method, (iii) analyze the relationship between traffic characteristics and sound level. The results indicate that the mean difference between model predictions and field measurements is acceptable. The traffic composition impact study indicates that buses (including mid-sized trucks) and heavy goods vehicles contribute a significant proportion of total noise power despite their low traffic volume. In addition, speed analysis offers an explanation for the minor differences in noise level across time periods. Future work will aim at reducing model error, by focusing on noise barrier analysis using the FEM/BEM method and modifying the vehicle noise emission equation by conducting field experimentation.