Continuation of a physical model of brass instrument: application to trumpet categorization

International audienceThe system formed by the couple {player-trumpet} falls into the class of non-linear dynamical systems likely to be studied using different numerical tools such as numerical continuation methods. In this study we illustrate the interest of this approach for the categorization of Bb trumpets in the space of some performance descriptors obtained from continuation by the ANM method combined to the Harmonic Balance Method (HBM)

Durability of Composite Materials under Severe Temperature Conditions: Influence of Moisture Content and Prediction of Thermo-Mechanical Properties During a Fire

The main objective of the present study was to develop a fire thermal model able to predict the evolution of the temperature and decomposition gradient across a laminated composite structure when exposed to fire. The thermal response of composite laminate made of organic polymer matrix was investigated under severe temperature conditions as samples were exposed to high temperatures up to 750 °C. The highlight is that a behavior law for water is included in our thermo-mechanical model to estimate effects due to a moisture content field on the thermal response of composite laminates. In particular, porosity and gas pressure are strongly influenced by the presence of water in the material and modify the thermal behavior accordingly. This enabled us to propose a new approach that can be used for the prediction of hygro-thermo-chemico-mechanical post-combustion properties in a very large number of material and fire scenarios

CONTRIBUTION OF MACHINE LEARNING AND PHYSICS-BASED SOUND SIMULATIONS FOR THE CHARACTERIZATION OF BRASS INSTRUMENTS

International audienceSound simulations by physical modelling are interesting to transcribe the physics underlying the functioning of a musical instrument. These simulations make it possible to listen to a virtual instrument with a mode of operation representative of the musician-instrument interaction. The work consists of studying the contribution of machine learning (ML) methods in the understanding of the relationships between the shape of a trumpet and the sound simulated. The physical model used is based on an acoustical modeling of the resonator, a mechanical model of the excitator, and an aeroelastic coupling between the excitator and the resonator. From different samples of the input impedance of the resonator, time domain simulations are generated to constitute a training set of sounds. Supervised learning is next trained to the data, with the impedance as input and sound descriptors as outputs, using classical ML methods (neural networks). The ML model is finally used to optimize the sound descriptors levels, according to the input impedance. To illustrate the approach, different "targets" for the sound features are considered (brightness, intonation), and a validation is conducted with the simulations. The approach is a first stage toward a "customization" of an instrument according to different perceptual dimensions

Towards the Prediction of Sandwich Composites Durability in Severe Condition of Temperature: A New Numerical Model Describing the Influence of Material Water Content during a Fire Scenario

An advanced fire thermal model was developed to predict the evolution of the temperature and decomposition gradient across a sandwich composite structure when exposed to high temperatures (fire). This model allows the prediction of a large numbers of parameters, such as thermal expansion, gas mass storage, porosity, permeability, density, and internal pressure. The highlight of this model is that we consider, in the sandwich constituents (core and skins), additional parameters, such as changing volume porosities, other coupled constituents (as infused resin in the balsa core), and what make the main originality of the present approach: moisture content (free and bounded water). The time dependence of many parameters, i.e., among others, the combustion advancing front and mechanical properties, can be predicted in a large number of material and fire scenarios. The proposed approach was validated in the case of sandwich panels, with glass/polyester or glass/vinyl ester skins and balsa core, exposed to high temperatures up to 750 °C. The influence of water on the thermal and mechanical responses is also highlighted

CONTRIBUTION OF MACHINE LEARNING AND PHYSICS-BASED SOUND SIMULATIONS FOR THE CHARACTERIZATION OF BRASS INSTRUMENTS

International audienceSound simulations by physical modelling are interesting to transcribe the physics underlying the functioning of a musical instrument. These simulations make it possible to listen to a virtual instrument with a mode of operation representative of the musician-instrument interaction. The work consists of studying the contribution of machine learning (ML) methods in the understanding of the relationships between the shape of a trumpet and the sound simulated. The physical model used is based on an acoustical modeling of the resonator, a mechanical model of the excitator, and an aeroelastic coupling between the excitator and the resonator. From different samples of the input impedance of the resonator, time domain simulations are generated to constitute a training set of sounds. Supervised learning is next trained to the data, with the impedance as input and sound descriptors as outputs, using classical ML methods (neural networks). The ML model is finally used to optimize the sound descriptors levels, according to the input impedance. To illustrate the approach, different "targets" for the sound features are considered (brightness, intonation), and a validation is conducted with the simulations. The approach is a first stage toward a "customization" of an instrument according to different perceptual dimensions

Synchronous Multimodal Measurements on Lips and Glottis: Comparison Between Two Human-Valve Oscillating Systems

International audienceThe brass instrument-player and the human voice production systems are both composed of a vibrating " human valve " coupled to an acoustic resonator and can be modelled by very similar dynamical systems. Moreover, lips and glottis are both difficult to access during sound production without disturbing their mechanical behaviour and vibration characteristics. In this article, we introduce a common measurement and analysis framework in order to study and compare the vibration of lips and glottis during sound production. Based on previous studies conducted on vibrating vocal folds, our measurement system is composed of three synchronous measurements –electrical admittance (electroglottography and electrolabiography), high-speed video recording and sound recording– and allows relatively non-intrusive measurements to be performed on singers and trombone players. Analysis of the collected data highlights the interpretability of electrolabiographic signals. Furthermore, similarities and differences between the two valve systems are investigated with regard to high speed imaging, electrical admittance and basic characteristics of the radiated sound

Confrontation de résultats numériques avec l’évaluation perceptive de trompettistes

La modélisation d’instruments à vent, et l’étude de ces modèles au moyen de méthodes d’analyse des systèmes dynamiques, permet d’extraire de l’information quantitative relative au comportement de l’instrument. Ces données sont particulièrement pertinentes dans le but de comparer des instruments aux caractéristiques techniques (perce) assez proches, sur la base de descripteurs liés au jeu (« critères objectifs opérationnels »). Néanmoins, la question se pose de la validation de ces résultats numériques, au regard du ressenti du musicien. Cette question n’est pas triviale car elle nécessite de mettre en œuvre des protocoles d’évaluation permettant de recueillir une information perceptive en lien avec des grandeurs physiques souvent étrangères au vocabulaire et/ou à l’imaginaire du musicien lorsqu’il joue de son instrument. Dans ce travail nous présentons des premiers résultats d’évaluations conduites avec des trompettistes professionnels afin de recueillir des évaluations perceptives en lien avec des grandeurs calculées sur différentes trompettes par continuation numérique (seuils de pression, phénomènes d’hystérésis, variation de paramètres d’excitation). Nous discuterons les stratégies et protocoles mis en œuvre, les biais et difficultés identifiées, et présenterons les résultats de cette première série de tests en les confrontant aux prédictions numériques

Parameter identification of a physical model of brass instruments by constrained continuation

Numerical continuation using the Asymptotic Numerical Method (ANM), together with the Harmonic Balance Method (HBM), makes it possible to follow the periodic solutions of non-linear dynamical systems such as physical models of wind instruments. This has been recently applied to practical problems such as the categorization of musical instruments from the calculated bifurcation diagrams [V. Fréour et al. Journal of the Acoustical Society of America 148 (2020) https://doi.org/10.1121/10.000160

Creation of an experimental database, for the validation of resonator models, comparison of geometries and materials, and quantification of measurement errors

International audienceWith an objective of providing wind instrument makers with design and simulation tools, many methods for both characterization and simulation of the behavior of acoustic properties have been developed. Some of these tools are made available to makers via softwares and devices. In parallel with a benchmark of numerical approaches for their verification detailed in a companion paper, an experimental campaign is presented here in order to create a reference database for the validation of models, and to estimate the uncertainties associated with the input impedance measurements. In particular, the random inter / intra sample uncertainty is quantified. The experimental campaign is based on batches of five specimens each of tubes and cones. The experimental plan allows to obtain consolidated experimental results concerning materials and making processes. The specimens produced are tested in different laboratories with varying characterization methods. The campaigns that took place defined a measurement protocol and evaluated biases and irreducible uncertainties. These measurements give first estimates of the variability of the results and provide precision thresholds of modifications to be significantly measured. Generally, for a batch of five specimens made with the same process, the orders of magnitude for the coefficient of variation is equal to 5 cents and 5 dB