Safety and reliability are prime concerns in aircraft performance due to the involved costs and risk to lives. Despite the best efforts in design methodology, quality evaluation in production and structural integrity assessment in-service, attainment of one hundred percent safety through development and use of a suitable in-flight health monitoring system is still a farfetched goal. And, evolution of such a system requires, first, identification of an appropriate Technique and next its adoption to meet the challenges posed by newer materials (advanced composites), complex structures and the flight environment. In fact, a quick survey of the available Non-Destructive Evaluation (NDE) techniques suggests Acoustic Emission (AE) as the only available method. High merit in itself could be a weakness - Noise is the worst enemy of AE. So, while difficulties are posed due to the insufficient understanding of the basic behavior of composites, growth and interaction of defects and damage under a specified load condition, high in-flight noise further complicates the issue making the developmental task apparently formidable and challenging. Development of an in-flight monitoring system based on AE to function as an early warning system needs addressing three aspects, viz., the first, discrimination of AE signals from noise data, the second, extraction of required information from AE signals for identification of sources (source characterization) and quantification of its growth, and the third, automation of the entire process. And, a quick assessment of the aspects involved suggests that Artificial Neural Networks (ANN) are ideally suited for solving such a complex problem. A review of the available open literature while indicates a number of investigations carried out using noise elimination and source characterization methods such as frequency filtering and statistical pattern recognition but shows only sporadic attempts using ANN. This may probably be due to the complex nature of the problem involving investigation of a large number of influencing parameters, amount of effort and time to be invested, and facilities required and multi-disciplinary nature of the problem. Hence as stated in the foregoing, the need for such a study cannot be over emphasized. Thus, this thesis is an attempt addressing the issue of analysis and automation of complex sets of AE data such as AE signals mixed with in-flight noise thus forming the first step towards in-flight monitoring using AE. An ANN can in fact replace the traditional algorithmic approaches used in the past. ANN in general are model free estimators and derive their computational efficiency due to large connectivity, massive parallelism, non-linear analog response and learning capabilities. They are better suited than the conventional methods (statistical pattern recognition methods) due to their characteristics such as classification, pattern matching, learning, generalization, fault tolerance and distributed memory and their ability to process unstructured data sets which may be carrying incomplete information at times and hence chosen as the tool. Further, in the current context, the set of investigations undertaken were in the absence of sufficient a priori information and hence clustering of signals generated by AE sources through self-organizing maps is more appropriate. Thus, in the investigations carried out under the scope of this thesis, at first a hybrid network named "NAEDA" (Neural network for Acoustic Emission Data Analysis) using Kohonen self-organizing feature map (KSOM) and multi-layer perceptron (MLP) that learns on back propagation learning rule was specifically developed with innovative data processing techniques built into the network. However, for accurate pattern recognition, multi-layer back propagation NN needed to be trained with source and noise clusters as input data. Thus, in addition to optimizing the network architecture and training parameters, preprocessing of input data to the network and multi-class clustering and classification proved to be the corner stones in obtaining excellent identification accuracy. Next, in-flight noise environment of an aircraft was generated off line through carefully designed simulation experiments carried out in the laboratory (Ex: EMI, friction, fretting and other mechanical and hydraulic phenomena) based on the in-flight noise survey carried out by earlier investigators. From these experiments data was acquired and classified into their respective classes through MLP. Further, these noises were mixed together and clustered through KSOM and then classified into their respective clusters through MLP resulting in an accuracy of 95%- 100% Subsequently, to evaluate the utility of NAEDA for source classification and characterization, carbon fiber reinforced plastic (CFRP) specimens were subjected to spectrum loading simulating typical in-flight load and AE signals were acquired continuously up to a maximum of three designed lives and in some cases up to failure. Further, AE signals with similar characteristics were grouped into individual clusters through self-organizing map and labeled as belonging to appropriate failure modes, there by generating the class configuration. Then MLP was trained with this class information, which resulted in automatic identification and classification of failure modes with an accuracy of 95% - 100%. In addition, extraneous noise generated during the experiments was acquired and classified so as to evaluate the presence or absence of such data in the AE data acquired from the CFRP specimens. In the next stage, noise and signals were mixed together at random and were reclassified into their respective classes through supervised training of multi-layer back propagation NN. Initially only noise was discriminated from the AE signals from CFRP failure modes and subsequently both noise discrimination and failure mode identification and classification was carried out resulting in an accuracy of 95% - 100% in most of the cases. Further, extraneous signals mentioned above were classified which indicated the presence of such signals in the AE signals obtained from the CFRP specimen. Thus, having established the basis for noise identification and AE source classification and characterization, two specific examples were considered to evaluate the utility and efficiency of NAEDA. In the first, with the postulation that different basic failure modes in composites have unique AE signatures, the difference in damage generation and progression can be clearly characterized under different loading conditions. To examine this, static compression tests were conducted on a different set of CFRP specimens till failure with continuous AE monitoring and the resulting AE signals were classified through already trained NAEDA. The results obtained shows that the total number of signals obtained were very less when compared to fatigue tests and the specimens failed with hardly any damage growth. Further, NAEDA was able to discriminate the"noise and failure modes in CFRP specimen with the same degree of accuracy with which it has classified such signals obtained from fatigue tests. In the second example, with the same postulate of unique AE signatures for different failure modes, the differences in the complexion of the damage growth and progression should become clearly evident when one considers specimens with different lay up sequences. To examine this, the data was reclassified on the basis of differences in lay up sequences from specimens subjected to fatigue. The results obtained clearly confirmed the postulation. As can be seen from the summary of the work presented in the foregoing paragraphs, the investigations undertaken within the scope of this thesis involve elaborate experimentation, development of tools, acquisition of extensive data and analysis. Never the less, the results obtained were commensurate with the efforts and have been fruitful. Of the useful results that have been obtained, to state in specific, the first is, discrimination of simulated noise sources achieved with significant success but for some overlapping which is not of major concern as far as noises are concerned. Therefore they are grouped into required number of clusters so as to achieve better classification through supervised NN. This proved to be an innovative measure in supervised classification through back propagation NN. The second is the damage characterization in CFRP specimens, which involved imaginative data processing techniques that proved their worth in terms of optimization of various training parameters and resulted in accurate identification through clustering. Labeling of clusters is made possible by marking each signal starting from clustering to final classification through supervised neural network and is achieved through phenomenological correlation combined with ultrasonic imaging. Most rewarding of all is the identification of failure modes (AE signals) mixed in noise into their respective classes. This is a direct consequence of innovative data processing, multi-class clustering and flexibility of grouping various noise signals into suitable number of clusters. Thus, the results obtained and presented in this thesis on NN approach to AE signal analysis clearly establishes the fact that methods and procedures developed can automate detection and identification of failure modes in CFRP composites under hostile environment, which could lead to the development of an in-flight monitoring system.

<p>A few aspects of aircraft noise were evaluated. These were (i) methods of subjective evaluations, (ii) effects of equalization and (iii) the effects of cognitive aspects.</p><p>In the first paper, sorting algorithms were used instead of conventional paired comparison method in order to reduce the number of pairs in the evaluation of subjective judgments. The quick sorting algorithm method revealed more than 99% correlation coefficient with paired comparison method although the method used N*log(N) evaluations instead of N(N-1)/2.</p><p>In the second paper, equalization effects on perception were evaluated in two steps, first with stationary aircraft sounds and second with non-stationary aircraft sounds.</p><p>The first experiment examined the effects of stationary sound segments respect to three different angle positions of the aircrafts relative to the observer (78.7°, 90° & 101.3°), two different SNR conditions (sounds having original broadband plus tonal components versus control broadband sounds having no tonal components) and two different flight conditions (arrival and take-off). Subjects were asked to scale five perceptual attributes (loudness, annoyance, hardness, power and pitch) using Borg CR100 scale. The angle condition showed highly significant effects on annoyance and hardness. Maximal effects were found at an angle of 78.7°. The SNR revealed a significant impact on loudness, power and pitch.</p><p>The second experiment analyzed the effects of tonal components and the problem of appropriate equalization. The spectrum of the signals was modified in two steps (buzz-saw, isolated BPF tone). Further EPNL-equalization, A-, B-, C-, D- and spectral broadband equalizations were applied to the synthesized sounds. Annoyance, loudness, hardness and pitch in the isolated tone conditions showed significantly stronger effects than the buzz-conditions on the perceived judgments. The EPNL-equalization led to a lower degree of differentiation between the spectral conditions compared to B- and C-level equalization.</p><p>In the third paper, the effects of aircraft sounds on children’s cognitive performance were investigated. Impact of aircraft noise on children cognition was found significantly higher in reading comprehensions than in basic mathematics and problem solving tests. It seems children are very sensitive to the modifications in the aircraft noise but further studies are necessary to compliment such a finding.</p>

Au cours des 30 dernières années, il s'est produit un accroissement important de la demande et de la mise à disposition des transports aériens. Alors que l'on reconnaît, d'une manière générale, l'importance fondamentale de ce mode de transport pour les sociétés et les économies modernes, il retient de plus en plus l'attention de la classe politique par les effets secondaires néfastes qu'il engendre. En effet, les transports aériens sont aussi sources d'externalités environnementales négatives, en particulier la pollution sonore, qu'il convient d'évaluer pour pouvoir mettre en place des politiques correctives (taxes, compensation, etc.).Dans ce contexte, la dépréciation des valeurs immobilières ainsi que le risque de ségrégation sociale susceptible d'être causé par le bruit des avions tiennent un rôle croissant dans les réflexions, qui figurent parmi les préoccupations majeures avec les questions relatives à la santé des riverains. Depuis plusieurs années, de nombreuses études ont été menées dans ces domaines, à l'étranger. Cependant, à ce jour, en France, lesétudes sont encore rarissimes. Cette thèse a donc pour objet de: a) analyser et mesurer les impacts des plateformes aéroportuaires sur les valeurs immobilières et identifier les variables influentes (bruit des avions, distance à l'aéroport, etc.), b) analyser l'éventuelle situation d'inégalité sociale face à l'exposition au bruit des avions ; c) fournir un outil opérationnel et pérenne d'aide à la décision par la création d'un observatoire.Pour atteindre ces objectifs, une méthodologie pluridisciplinaire combinant compétences économiques (méthode des prix hédoniques) et géographique (SIG) a été développée. La principale originalité de cette thèse réside dans sa démarche comparative au niveau national, mettant en exergue les spécificités des différents territoires étudiés. Les territoires d'investigation couvrent toutes les communes situées dans ou à proximité immédiate des zones de bruit (plan d'exposition au bruit ou PEB) de chaque aéroport concerné. Les aéroports étudiés concernent aussi bien les aéroports parisiens (à savoir : Paris Charles-de-Gaulle et Paris-Orly), ainsi que ceux de provinces (Lyon Saint-Exupéry et Toulouse- Blagnac). / Over the past 30 years, there has been a significant increase in the air transportation demand and supply. While the fundamental importance of this mode of transport, for modern societies and economies, are generally recognized, it attracts increasing attention from the political class, because of the negative side effects to which it leads. Indeed, air transports cause also negative environmental externalities, in particular noise pollution, which should be evaluated in order to implement corrective policies (taxes, compensation, etc.).In this context, the depreciation of property values and the risk of social segregation caused by aircraft noise have a growing role in the discussions, which are among the major concerns with the health issues of local residents. For several years now, many studies have been conducted in these areas, abroad. Currently, however, studies are still rare in France.Therefore, this thesis aims to: a) analyze and measure the impact of airport platforms on property values and identify the influential variables (aircraft noise, distance to the airport, etc.), analyze possible social inequality in relation to exposure to aircraft noise, c) provide an operational and sustainable decision support tool by setting up an observatory.To address these objectives, a multidisciplinary methodology combining economic (hedonic price method) and geographic (GIS) expertise has been developed. The main originality of this thesis lies in its comparative approach on a national level, highlighting the specificities of the different territories studied. The territories studied cover all communes located in or close to the noise zones (noise exposure map “Plan d'Exposition au Bruit (PEB)”) of each airport concerned. The airports studied concern both Paris airports (Paris- CDG and Paris-Orly), as well as those of provinces (Lyon Saint-Exupery and Toulouse-Blagnac).

<p>  </p> <p>Aircraft noise is one of the most significant environmental concerns for the aviation industry, and it adversely affects the physical and mental health of community members who are in close proximity to airports. The operations and expansion of airports and land use planning are affected because of the community’s adverse reaction to such annoyances. Aircraft operations and fleet mix information are required when airport managers and stakeholders execute the Aviation Environmental Design Tool (AEDT) to compute the noise metrics; however, these data are unavailable from over 2,000 United States non-primary General Aviation (GA) airports that lack full-time air traffic control facilities or personnel. </p> <p>This study developed a low-cost noise assessment technology for non-towered GA airports. The Automatic Dependent Surveillance-Broadcast (ADS-B) messages were obtained using an inexpensive ADS-B receiver. A barometric pressure calibration was applied to improve the aircraft operations estimation. A fleet mix database was created by linking the collected ADS-B data to an FAA-registered aircraft database containing U.S.-registered aircraft information (such as types of aircraft and engines). Specific aircraft information was obtained by filtering the International Civil Aviation Organization (ICAO) identification code from the obtained ADS-B records. A set of 20 advanced aircraft performance parameters was constructed to determine the operation mode and corresponding power setting. The corresponding noise levels were determined using the EUROCONTROL Aircraft Noise and Performance (ANP) database.</p> <p>The testing and validation results from the case study at the Purdue University Airport (ICAO Code: KLAF) demonstrated the developed low-cost approach could identify aircraft noise events, and the accuracy of modeled noise data was assessed with an average error of 4.50 dBA. Therefore, the developed approach appears to be an affordable means of monitoring aircraft noise at non-towered GA airports.  </p>

A few aspects of aircraft noise were evaluated. These were (i) methods of subjective evaluations, (ii) effects of equalization and (iii) the effects of cognitive aspects. In the first paper, sorting algorithms were used instead of conventional paired comparison method in order to reduce the number of pairs in the evaluation of subjective judgments. The quick sorting algorithm method revealed more than 99% correlation coefficient with paired comparison method although the method used N*log(N) evaluations instead of N(N-1)/2. In the second paper, equalization effects on perception were evaluated in two steps, first with stationary aircraft sounds and second with non-stationary aircraft sounds. The first experiment examined the effects of stationary sound segments respect to three different angle positions of the aircrafts relative to the observer (78.7°, 90° &amp; 101.3°), two different SNR conditions (sounds having original broadband plus tonal components versus control broadband sounds having no tonal components) and two different flight conditions (arrival and take-off). Subjects were asked to scale five perceptual attributes (loudness, annoyance, hardness, power and pitch) using Borg CR100 scale. The angle condition showed highly significant effects on annoyance and hardness. Maximal effects were found at an angle of 78.7°. The SNR revealed a significant impact on loudness, power and pitch. The second experiment analyzed the effects of tonal components and the problem of appropriate equalization. The spectrum of the signals was modified in two steps (buzz-saw, isolated BPF tone). Further EPNL-equalization, A-, B-, C-, D- and spectral broadband equalizations were applied to the synthesized sounds. Annoyance, loudness, hardness and pitch in the isolated tone conditions showed significantly stronger effects than the buzz-conditions on the perceived judgments. The EPNL-equalization led to a lower degree of differentiation between the spectral conditions compared to B- and C-level equalization. In the third paper, the effects of aircraft sounds on children’s cognitive performance were investigated. Impact of aircraft noise on children cognition was found significantly higher in reading comprehensions than in basic mathematics and problem solving tests. It seems children are very sensitive to the modifications in the aircraft noise but further studies are necessary to compliment such a finding.

Le bruit de la circulation routière, et en particulier le bruit des deux-roues motorisés, constituent une importante source de gêne sonore. Afin d’estimer l’exposition sonore dans les villes de plus 100 000 habitants, la directive européenne 2002/49/CE impose la réalisation de cartes de bruit stratégiques, basées sur l’indice Lden. Cet indice est également utilisé dans des relations exposition-réponse, afin de prédire les pourcentages de personnes gênées, notamment par le bruit du trafic routier. En couplant les cartes de bruit stratégiques et ces relations exposition-réponse, des cartes de gêne pourraient être établies. Toutefois, la pertinence de cet indice pour prédire la gêne due au bruit en milieu urbain est souvent remise en cause, car de nombreux facteurs acoustiques influents (e.g. les caractéristiques spectrales et temporelles) ne sont pas pris en compte par cet indice. Cette thèse vise à améliorer la caractérisation de la gêne due au bruit de trafic routier urbain en considérant différentes compositions de trafic et la présence des deux-roues motorisés. Dans ce but, des expériences sont menées en conditions contrôlées. Une première étude a porté sur l’influence de plusieurs facteurs acoustiques relatifs aux périodes de calme et aux bruits de passage de véhicules sur la gêne due au bruit de trafic routier urbain. Cette étude a conclu à l’influence de la présence de périodes de calme et du nombre de véhicules au sein du trafic routier urbain et à l’absence d’influence de l’ordre des véhicules routiers, de la position et de la durée des périodes de calme. Ces résultats ont été utilisés afin de mener la caractérisation physique et perceptive de différentes compositions de trafic routier urbain. La régression multi-niveau a été utilisée pour calculer la gêne, en considérant 1) des facteurs acoustiques influents à l’aide de combinaisons pertinentes d’indices et 2) un facteur non acoustique : la sensibilité au bruit. Dans les villes, le bruit routier est souvent entendu en situation de multi-exposition avec d’autres bruits. Dans le cadre de ces travaux de thèse, les situations de multi-exposition aux bruits routier et d’avion ont été étudiées. Pour cela, un travail semblable à celui mené pour le bruit de trafic routier urbain a été mené pour le bruit d’avion conduisant également à des combinaisons pertinentes d’indices. En vue de caractériser les gênes dues aux bruits de trafic routier et d’avion pour des situations de multi-exposition sonore, les données des précédentes expériences ainsi que celles d’une expérience conduite en situation de multi-exposition à ces bruits combinés ont été utilisées au travers d’une régression multi-niveau adaptée, comme cela a pu être mené dans la littérature. La régression multi-niveau a ainsi permis la proposition de modèles de gêne pour chaque source de bruit. Puis, la gêne totale due à des situations de multi-exposition à ces bruits a été étudiée, afin de mettre en évidence les phénomènes perceptifs mis en jeu. Des modèles de gêne totale ont été proposés, en utilisant les modèles de gêne due à chaque source. Enfin, les modèles de gêne obtenus pour chaque source et les modèles de gêne totale ont été confrontés aux données d’une enquête socio-acoustique. A cet effet, une méthodologie a été proposée afin d’estimer les différents indices des modèles à partir des valeurs du Lden, issues de cartes de bruit et utilisées pour définir l’exposition au bruit des personnes enquêtées. Cette confrontation a montré que les modèles proposés à partir d’expériences menées en laboratoire et couplés à la méthodologie d’estimation des indices à partir des valeurs du Lden permettent une bonne prédiction de la gêne in situ. / Road traffic noise, and in particular powered two-wheeler noise, constitute an important source of noise annoyance. In order to estimate the noise exposure in cities of more than 100 000 inhabitants, the European directive 2002/49/EC requires the elaboration of strategic noise maps, based on the Lden index. This index is also used in exposureresponse relationships, to predict the percentages of annoyed people, by road traffic noise for example. By coupling strategic noise maps and these exposure-response relationships, noise annoyance maps could be established. The relevance of this index to predict noise annoyance in cities is however often questioned, since many influential acoustical factors (e.g. spectral and temporal features) are not considered by this index. The aim of this thesis is to enhance the characterization of noise annoyance due to different compositions of urban road traffic including powered two-wheelers. To achieve this goal, experiments were carried out under controlled conditions. A first study concerned the influence of several acoustical features related to quiet periods and vehicle pass-by noises on the annoyance due to urban road traffic noise. This study demonstrated the influence of the presence of quiet periods and of the number of vehicles within the urban road traffic and to the absence of the influence of the order of the vehicle pass-by noises, the position and duration of quiet periods. These results were used to carry out the physical and perceptual characterization of different compositions of urban road traffic noise. Multilevel regression was used to calculate noise annoyance, by coupling combinations of indices relating to influential acoustical features and an individual factor: noise sensitivity. In cities, road traffic noise is often combined with other noises. In the framework of this thesis, noise exposure to road traffic noise combined with aircraft noise was studied. Therefore, the same work as the one performed for urban road traffic noise was carried out for aircraft noise, leading also to relevant combinations of noise indices. In order to characterize annoyances due to road traffic noise and to aircraft noise in a combined exposure situation, data from the previous experiments and from an experiment dealing with these combined noises were used through an appropriate multilevel regression, as done in literature. The regression allows annoyance models for each noise source to be proposed. Then, total annoyance due to combined noises was studied, in order to highlight the perceptual phenomena related to the combined exposure. Total noise annoyance models were proposed, using proposed annoyance model of each noise source. Finally, these single source annoyance models and total annoyance models were tested using data of a socio-acoustic survey. To do this, a methodology has been proposed to estimate the different indices involved in the annoyance models, from the Lden values obtained from the strategic noise maps and used to define the noise exposure of the respondents. This confrontation showed that the models proposed on the basis of experiments carried out under laboratory conditions and coupled with a methodology of estimation of the noise indices from Lden values, enabled a good prediction of in situ annoyance.

Tato práce se zabývá problematikou zavedení a provozu nadzvukových business jetů. V dnešní době se v civilní letecké přepravě, po ukončení provozu Concordu, žádná nadzvuková letadla nevyskytují. V dnešní době existuje mnoho projektů a organizací, které se zabývají znovuzavedením nadzvukových letounů do civilního letectví a soustředí se převážně na business jety. Hlavní otázkou je, zda je vůbec vhodné, či rozumné se k tomu typu dopravy znovu vracet. Existuje hodně problémů, které toto komplikují. Tyto letouny způsobují příliš velký hluk, mají obrovskou spotřebu paliva a musí řešit nadměrné emise, létají ve vysokých výškách ve kterých může docházet k problémům s přetlakováním kabiny, navigací, radioaktivním zářením apod. Navíc zákaz supersonických letů nad pevninou letové cesty omezuje a prodlužuje. Současně vznikající projekty navíc nedosahují tak velkého doletu jako klasické moderní bussjety, což způsobuje, že se nadzvukové business jety se na delších tratích stávají neefektivní. I přes tyto problémy, je víceméně jisté, že k zavedení nadzvukových business jetů dojde během následujících 10 - 15 let, i kdyby to měla být jen otázka jisté prestiže velmi bohatých lidí.