Brass Instruments Design Using Physics-Based Sound Simulation Models and Surrogate-Assisted Derivative-Free Optimization

被引:11
作者
Tournemenne, Robin [1 ]
Petiot, Jean-Francois [1 ]
Talgorn, Bastien [2 ,3 ]
Kokkolaras, Michael [2 ,3 ]
Gilbert, Joel [4 ]
机构
[1] Ecole Cent Nantes, Inst Rech Commun & Cybernet Nantes, UMR CNRS 6597, 1 rue Noe, F-44300 Nantes, France
[2] Gerad, Dept Mech Engn, Montreal, PQ H3T 1J4, Canada
[3] McGill Univ, Montreal, PQ H3T 1J4, Canada
[4] Univ Maine, UMR CNRS 6613, Acoust Lab, F-72085 Le Mans, France
关键词
MUSICAL-INSTRUMENTS; INPUT IMPEDANCE; ALGORITHM;
D O I
10.1115/1.4035503
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
This paper presents a method for design optimization of brass wind instruments. The shape of a trumpet's bore is optimized to improve intonation using a physics-based sound simulation model. This physics-based model consists of an acoustic model of the resonator, a mechanical model of the excitator, and a model of the coupling between the excitator and the resonator. The harmonic balance technique allows the computation of sounds in a permanent regime, representative of the shape of the resonator according to control parameters of the virtual musician. An optimization problem is formulated in which the objective function to be minimized is the overall quality of the intonation of the different notes played by the instrument. The design variables are the physical dimensions of the resonator. Given the computationally expensive function evaluation and the unavailability of gradients, a surrogate-assisted optimization framework is implemented using the mesh adaptive direct search algorithm (MADS). Surrogate models are used both to obtain promising candidates in the search step of MADS and to rank-order additional candidates generated by the poll step of MADS. The physics-based model is then used to determine the next design iterate. Two examples (with two and five design optimization variables) demonstrate the approach. Results show that significant improvement of intonation can be achieved at reasonable computational cost. Finally, the perspectives of this approach for computer-aided instrument design are evoked, considering optimization algorithm improvements and problem formulation modifications using for instance different design variables, multiple objectives and constraints or objective functions based on the instrument's timbre.
引用
收藏
页数:9
相关论文
共 33 条
[21]   Optimization of brasswind instruments and its application in bore reconstruction [J].
Kausel, W .
JOURNAL OF NEW MUSIC RESEARCH, 2001, 30 (01) :69-82
[22]   Algorithm 909: NOMAD: Nonlinear Optimization with the MADS Algorithm [J].
Le Digabel, Sebastien .
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 2011, 37 (04)
[23]   Mixture surrogate models based on Dempster-Shafer theory for global optimization problems [J].
Muller, Juliane ;
Piche, Robert .
JOURNAL OF GLOBAL OPTIMIZATION, 2011, 51 (01) :79-104
[24]  
Noreland D., 2013, THESIS
[25]   Comparison of Trumpets' Sounds Played by a Musician or Simulated by Physical Modelling [J].
Petiot, Jean-Francois ;
Gilbert, Joel .
ACTA ACUSTICA UNITED WITH ACUSTICA, 2013, 99 (04) :629-641
[26]   Integration of user perceptions in the design process: Application to musical instrument optimization [J].
Poirson, Emilie ;
Petiot, Jean-Francois ;
Gilbert, Joeel .
JOURNAL OF MECHANICAL DESIGN, 2007, 129 (12) :1206-1214
[27]   Surrogate-based analysis and optimization [J].
Queipo, NV ;
Haftka, RT ;
Shyy, W ;
Goel, T ;
Vaidyanathan, R ;
Tucker, PK .
PROGRESS IN AEROSPACE SCIENCES, 2005, 41 (01) :1-28
[28]   Statistical Surrogate Formulations for Simulation-Based Design Optimization [J].
Talgorn, Bastien ;
Le Digabel, Sebastien ;
Kokkolaras, Michael .
JOURNAL OF MECHANICAL DESIGN, 2015, 137 (02)
[29]   The Capacity for Simulation by Physical Modeling to Elicit Perceptual Differences Between Trumpet Sounds [J].
Tournemenne, Robin ;
Petiot, Jean-Francois ;
Gilbert, Joel .
ACTA ACUSTICA UNITED WITH ACUSTICA, 2016, 102 (06) :1072-1081
[30]   Bias in error estimation when using cross-validation for model selection [J].
Varma, S ;
Simon, R .
BMC BIOINFORMATICS, 2006, 7 (1)