Simulation of Landing and Take-Off Noise for Supersonic Transport Aircraft at a Conceptual Design Fidelity Level

The German Aerospace Center has launched an internal project to assess the noise impact associated with supersonic transport aircraft during approach and departure. A dedicated simulation process is established to cover all relevant disciplines, i.e., aircraft and engine design, engine installation effects, flight simulation, and system noise prediction. The core of the simulation process is comprised of methods at the complexity and fidelity level of conceptual aircraft design, i.e., typical overall aircraft design methods and a semi-empirical approach for the noise modeling. Dedicated interfaces allow to process data from high fidelity simulation that will support or even replace initial low fidelity results in the long run. All of the results shown and discussed in this study are limited to the fidelity level of conceptual design. The application of the simulation process to the NASA 55t Supersonic Technology Concept Aeroplane, i.e., based on non-proprietary data for this vehicle, yields similar noise level predictions when compared to the published NASA results. This is used as an initial feasibility check of the new process and confirms the underlying methods and models. Such an initial verification of the process is understood as an essential step due to the lack of available noise data for supersonic transport aircraft in general. The advantageous effect of engine noise shielding on the resulting system noise is demonstrated based on predicted level time histories and certification noise levels. After this initial verification, the process is applied to evaluate a conceptual supersonic transport design based on a PhD thesis with two engines mounted under the wing, which is referred to as aircraft TWO. Full access to this vehicle’s design and performance data allows to investigate the influence of flight procedures on the resulting noise impact along approach and departure. These noise results are then assembled according to proposed Federal Aviation Agency regulations in their Notice of Proposed Rulemaking, e.g., speed limitations, for Supersonic transport noise certification and the regulations from Noise Chapters of the Annex 16 from the International Civil Aviation Organization in order to evaluate the resulting levels as a function of the flight procedure.

A REVIEW OF PRACTICAL METHODS FOR REDUCING UNDERWATER NOISE POLLUTION FROM LARGE COMMERCIAL VESSELS

The paper provides an interesting and rather complete overview of the reasons for reducing shipping noise and the possible ways to achieve this. It is in particular interesting to note that the majority of noise impact is probably caused by the noisiest 10% of ships, and that the ambient noise level in the oceans increased by around 20 dB compared to pre-industrial conditions.

Prediction of Aircraft Noise Impact with Application to Hong Kong International Airport

As part of a collective research effort towards greener aviation, the present study focuses on the noise impact of aircraft operations around major airports. To this end, an aircraft noise prediction platform is developed, which relies on state-of-the-art functionalities as well as more specific, innovative features. Originally built upon the Aircraft Noise and Performance (ANP) database and its Noise–Power–Distance (NPD) table, the method is further refined to alleviate most of their inherent limitations (e.g., standardized and simplified aircraft noise scenarios). The resulting aircraft noise prediction platform is validated against benchmark cases of increasing complexity, being then applied to real-life situations involving actual aircraft operations around Hong Kong International Airport (HKIA). Specific comparative analyses are conducted, which allow highlighting the variability of the noise impact by aircraft, depending on their type (A330, B777) and/or operational conditions (power settings, meteorological conditions, routes, banks, etc.). The study delivers insightful outcomes, whether phenomenological (aircraft noise impact) or methodological (aircraft noise prediction). As a by-product, it illustrates how noise prediction methods/platforms such as the present one may help in guiding the further expansion of airport operations and/or infrastructures (as is currently the case with HKIA).

Sound Art: Hearing in Particular

Extoling and promoting listening is deeply ingrained in sound art practice and discourse, even on occasion its raison d’être, where listening is understood as a wholly congenial, benign activity. This can be seen through the routine use of affirmative tropes such as, through listening we: connect, locate, are embodied, discern, are immersed or enveloped. And through specific listening methods such as Deep Listening, we are offered ‘expand[ed] consciousness to the whole space/time continuum of sound/silences’ (Oliveros, 2005, p. xxiv). Refocusing from the act of listening to the audiological—the mechanisms related to the sense of hearing—from the findings of the author’s recent research, in particular his review on the noise impact of high-speed hand dryers (Drever, 2013), the author feels obliged to assert that the contrary is a reality for many—hearing, from time to time or incessantly: perturbs, isolates, excludes, disconnects, disembodies, and dislocates, hearing hurts! This will be familiar for those living with hyperacusis, misophonia, and phonophobia, but it can also be the case for those with particular hearing needs such as the partially sighted, hearing aid users or those with sensitive hearing such as infants and ASD. Bringing audiology into the sphere of sound art, this chapter recognizes a prevailing sensitization of hearing in the culture at large, and proposes a paradigm for situating hearing that diverges from a singular, idealized, symmetrical model of hearing, the auraltypical, that has predominated. In its place, we are beginning to enjoy a fluidity and openness to diverse forms of hearing and sensitive hearers in sound art, on embracing the emerging agenda of auraldiversity.

Monte Carlo method for uncertainty evaluation of noise annoyance prevalence

When a decision-making process relies on the information provided by a measurement or simulation result, the right decision demands a good quality result, in other words, a low uncertainty result. In order to establish public policies for environmental noise control, it is essential to identify the impact of each type of noise pollution (e.g. road, aircraft and rail transportation noise) on the population affected. One of the noise impact metrics that can be used is the number of highly noise annoyed people in a region whose estimated value is obtained from the corresponding exposure-response function and noise and population density maps. However, an estimated value of the noise impact metric with high uncertainty makes it difficult to realize the actual severity of the problem and its priority in relation to other public health issues. In this work, a Monte Carlo simulation method is used to assess the uncertainty of a noise impact metric result, namely the number of people highly disturbed by road noise in a city. This article also presents a sensitivity analysis of uncertainty sources that allows quantification of the main uncertainty components, which supports improvements in noise impact metric results.

Enhancing Noise Management Strategy: Recommendations from the strategy literature.

Airports are required to manage noise impact owing to their requirement to obtain a social license to operate, and to comply with legislation such as the ICAO Balanced Approach and Environmental Noise Directive. Research has however shown that noise management actions and interventions often take a techno-centric approach, are implemented in silos, and that their success beyond noise metrics is rarely evaluated. Moreover, the success of Noise Action Plans in driving long-term noise management outcomes has also been critiqued at a number of levels. In the context of this background, this paper outlines the case for more strategic approaches to noise management and, drawing on the academic strategic literature, outlines approaches to developing such strategies that can be followed by airports. The aim of such approaches is to complement existing noise management guidance by providing step-processes that can aid airports in developing robust, repeatable, evaluable, and successful noise management strategies that are consistent with wider airport strategy and that are sympathetic to the needs of airport residents.

Exemplification case studies as a focus for the implementation of best practices related to aircraft noise management at airports

The current study presents the analysis of seven airport exemplification case studies undertaken in the European project "Aviation Noise Impact Management through Novel Approaches - ANIMA". Best practices related to aircraft noise management at airports in individual airport contexts were implemented and evaluated. Case studies on communication and community engagement in airport noise management were investigated at Heathrow (Great Britain), Ljubljana (Slovenia) and Rotterdam The Hague (The Netherlands) airports. For Zaporizhzhia (Ukraine) and Iasi (Romania) airports, the implementation of interventions related to land use planning was examined. The interdependencies between noise and emissions were studied for Cluj (Romania) and Catania (Italy) airports. All case studies were performed under the scope of the corresponding national legislation and guidelines. Individual characteristics of airport operations were taken into account. The case studies were aligned with expectations and priorities of all involved stakeholders, such as representatives of airport operators, local communities, civil aviation authorities and policy makers. The efficacy of the noise management case studies is assessed in terms of: the capacity to negotiate consensus outcomes, the extent to which noise impact reductions were achieved; and the participants' satisfaction with the process and outcomes. Experience gained from these studies will be used to distill best practices for future intervention.