Exploring design variations of the Titian Stradivari violin using a finite element model

Torres, Jean Orejarena; Soto, Carlos A.; Torres-Torres, D.

doi:10.1121/10.0001952

Cited by 31 publications

(30 citation statements)

References 19 publications

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“…Inspecting matrix P in the same figure, it can be noticed that the addition of the f-holes has a relevant impact on the amplitudes, in particular for peaks 1, 4 and 5. The sensitivity of FRFs to f-holes detected in the feature vectors agrees with [16], where a systemic analysis of these components was performed.…”

Section: Fea Simulations Of Stradivarius' Titiansupporting

confidence: 70%

“…To show the effectiveness of the feature-based representations presented in Section 2, two case studies are proposed. The first dataset is composed by bridge admittances predicted by means of Finite Element Analysis (FEA) using the Stradivarius' Titian violin as reference [16]. The second application analyzes similarities between experimental acquisitions taken on a set of contemporary violins.…”

Section: Resultsmentioning

confidence: 99%

“…Variations in signature modes of violins due to changes in the soundbox geometry were analyzed in [16]. An efficient parametric FEA model was defined in order to perform before/after comparisons concerning frequency responses and mode shapes.…”

Section: Fea Simulations Of Stradivarius' Titianmentioning

confidence: 99%

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Feature-based Representation for Violin Bridge Admittances

Malvermi,

Gonzalez,

Quintavalla

et al. 2021

Preprint

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Frequency Response Functions (FRFs) are one of the cornerstones of musical acoustic experimental research. They describe the way in which musical instruments vibrate in a wide range of frequencies and are used to predict and understand the acoustic differences between them. In the specific case of stringed musical instruments such as violins, FRFs evaluated at the bridge are known to capture the overall body vibration. These indicators, also called bridge admittances, are widely used in the literature for comparative analyses. However, due to their complex structure they are rather difficult to quantitatively compare and study. In this manuscript we present a way to quantify differences between FRFs, in particular violin bridge admittances, that separates the effects in frequency, amplitude and quality factor of the first resonance peaks characterizing the responses. This approach allows us to define a distance between FRFs and clusterise measurements according to this distance. We use two case studies, one based on Finite Element Analysis and another exploiting measurements on real violins, to prove the effectiveness of such representation. In particular, for simulated bridge admittances the proposed distance is able to highlight the different impact of consecutive simulation 'steps' on specific vibrational properties and, for real violins, gives a first insight on similar styles of making, as well as opposite ones.

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Section: Fea Simulations Of Stradivarius' Titiansupporting

confidence: 70%

Section: Resultsmentioning

confidence: 99%

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Feature-based Representation for Violin Bridge Admittances

Malvermi,

Gonzalez,

Quintavalla

et al. 2021

Preprint

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“…The authors concluded that the response frequency increases when the height of the arch, the thickness of the front plate, the prestress of the front plate or the contact stiffness of the sound post increases. In a recent noteworthy study [72], the design variations of a Titian Stradivari violin were explored via FEM modeling. The model is parametric; hence, its design and material properties varied in both the frequency and time domains.…”

Section: Bowed Musical Instrumentsmentioning

confidence: 99%

A Review of Finite Element Studies in String Musical Instruments

et al. 2022

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String instruments are complex mechanical vibrating systems, in terms of both structure and fluid–structure interaction. Here, a review study of the modeling and simulation of stringed musical instruments via the finite element method (FEM) is presented. The paper is focused on the methods capable of simulating (I) the soundboard behavior in bowed, plucked and hammered string musical instruments; (II) the assembled musical instrument box behavior in bowed and plucked instruments; (III) the fluid–structure interaction of assembled musical instruments; and (IV) the interaction of a musical instrument’s resonance box with the surrounding air. Due to the complexity and the high computational demands, a numerical model including all the parts and the full geometry of the instrument resonance box, the fluid–structure interaction and the interaction with the surrounding air has not yet been simulated.

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“…In the state of the art, the most used simulation method to study real musical instruments is the Finite Element Method (FEM) [5], which is a very powerful but also time-consuming process. The main advantage of our approach lies in the fact that, using neural networks, we can compute and optimize the vibrational response of a violin top plate in few seconds, taking much less time than with a FEM analysis.…”

Section: Introductionmentioning

confidence: 99%

Parametric Optimization of Violin Top Plates using Machine Learning

Salvi¹,

González²,

Antonacci³

et al. 2021

Preprint

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We recently developed a neural network that receives as input the geometrical and mechanical parameters that define a violin top plate and gives as output its first ten eigenfrequencies computed in free boundary conditions. In this manuscript, we use the network to optimize several error functions, with the goal of analyzing the relationship between the eigenspectrum problem for violin top plates and their geometry. First, we focus on the violin outline. Given a vibratory feature, we find which is the best geometry of the plate to obtain it. Second, we investigate whether, from the vibrational point of view, a change in the outline shape can be compensated by one in the thickness distribution and vice versa. Finally, we analyze how to modify the violin shape to keep its response constant as its material properties vary. This is an original technique in musical acoustics, where artificial intelligence is not widely used yet. It allows us to both compute the vibrational behavior of an instrument from its geometry and optimize its shape for a given response. Furthermore, this method can be of great help to violin makers, who can thus easily understand the effects of the geometry changes in the violins they build, shedding light on one of the most relevant and, at the same time, less understood aspects of the construction process of musical instruments.

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Exploring design variations of the Titian Stradivari violin using a finite element model

Cited by 31 publications

References 19 publications

Feature-based Representation for Violin Bridge Admittances

Feature-based Representation for Violin Bridge Admittances

A Review of Finite Element Studies in String Musical Instruments

Parametric Optimization of Violin Top Plates using Machine Learning

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