WP6
6 - INPG
Optimal design for acoustic performance
4
36
The objective of this WP is to develop and examine different approaches for the optimal design of buildings with respect to their acoustic performance. The topic has begun receiving increasing attention by engineers during the last decades and it is no more limited to structures of special use, such as concert halls or cinemas. In fact, the noisy environment of contemporary towns, as well as the aging of population turn the acoustic response of buildings into a decisive criterion of their quality. However, the mechanical intuition of engineers on the topic is quite limited, mainly due to the complex physics and loadings and, thus, optimization techniques could provide promising solutions. We ai
WP6 - Optimal design for acoustic performance [Months: 4-36]
INPG
Optimizing the acoustic performance of buildings usually refers to achieving a desirable distribution of acoustic pressure.
Depending on the building's function, different goals may be of interest. For example, architects and engineers usually
seek to maximize the acoustic pressure in an auditorium and to minimize it in residential buildings, train stations or
airports, in order to achieve low noise level.
The acoustic-control approach to follow highly depends on the available means (materials, budget, etc.), as well as on the
specific type of application. Structural members that serve only as acoustic regulators are usually easier to be optimized
compared to those that simultaneously serve as load carriers. The optimization method to apply is closely linked to the
specific type of problem and, thus, we propose to use different methodologies according to the application in target.
The work of this WP is organized in the following three Tasks:
Task 6.1: Setting of the optimization problem
In the first part of the WP, the team will define the setting of the optimization problem. First, the acoustic problem must
be defined and be given a mathematical formulation. Possible criteria to be optimized will be discussed. These criteria
shall relate the solution of the acoustic problem with a notion of noise disturbance or comfort. Finally, a solver to use
for the acoustic problem shall be agreed or developed, depending on the difficulty of the proposed equation.
Task 6.2: Parametric optimization of a layered wall
The first optimization approach consists in optimizing the choice of materials and the thickness of different layers
comprising a layered wall of simple geometry. It amounts to a discrete optimization problem, for which gradient-based
methods are not applicable. Therefore, we suggest instead the use of Genetic Algorithms or variants of them, such as
Meta-Heuristic Optimization Algorithms [1], which are particularly suitable for this kind of optimization since they can
treat any type of objective function and design variables.
The optimization of a layered wall can serve as a proof-of-concept for the application of the proposed methodology on
real-life problems of optimal acoustic insulation of buildings. In this last case, a large number of layered walls needs to
be optimized simultaneously, which adds some computational effort, but no conceptual difficulty.
Task 6.3: Design of smart walls and decks using S&T optimization
In several industrial applications, structural members are required to bear vibration loadings, such as working engines. It
is of crucial importance for the functionality of the building that the structural system is designed in such a way so as to
eliminate as much as possible the impact, due to the noise, in the surrounding space. It amounts to a coupled structuralacoustic
problem, where the shape and the topology of the structural system are of dominant role [2]. Several S&T
optimization methods exist in the literature. First, due to the significance of the actual boundary position, at least for
the acoustic problem, geometric methods are preferred to those based on density approaches. In particular, the level-set
method for S&T optimization is suitably fitted in this framework [3]. Compared to the problems described in Task 6.2,
the number of design variables in such an optimization problem can be too large. Taking under consideration that for
every test shape during the optimization process a structural and an acoustic problem need to be solved, the use of the
methods proposed in Task 6.2 is prohibited due to the enormous computational cost. Therefore, gradient-based methods
need to be implemented, based on a notion of shape derivation. An additional possibility, in the same framework, is to
consider the optimization of two phases with different properties [3,4]; one will account for the structural rigidity, while
the other for the acoustic insulation.
