HAL Id: hal-03235236
https://hal.archives-ouvertes.fr/hal-03235236
Submitted on 13 Jun 2021
HAL is a multi-disciplinary open access
archive for the deposit and dissemination of
sci-entific research documents, whether they are
pub-lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.
L’archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d’enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.
Improving the acoustic quality of a food court by using
rate spatial decay
Dario d’Orazio, Giulia Fratoni, Elena Rossi
To cite this version:
Dario d’Orazio, Giulia Fratoni, Elena Rossi. Improving the acoustic quality of a food court by using
rate spatial decay. Forum Acusticum, Dec 2020, Lyon, France. pp.3053-3054, �10.48465/fa.2020.0488�.
�hal-03235236�
IMPROVING THE ACOUSTIC QUALITY OF A FOOD COURT BY USING
RATE SPATIAL DECAY
Dario D’Orazio
1Giulia Fratoni
1Elena Rossi
1,21
DIN University of Bologna, Viale Risorgimento 2, 40126 Bologna, Italy
2Studio Sound Service, Via Torricella 22/a, 50023 Impruneta, Italy
ABSTRACT
The human noise due to several people speaking at the same time in eating establishments is a well-known phe-nomenon. The topic is debated in scientific literature but rarely addressed in standardized requirements. The issue is particularly complicated because people are individual and dynamic sound sources: the more they talk, the more the environment is affected by this noise, and ultimately this make the people raise their voice. As a consequence, the speech sound level increases with the overall noise. More-over, human noise is affected in a non-linear way by the number of visitors and by the changing of the boundary conditions in the room.
In large restaurants the high number of people may re-turn a background noise equal to 70 dB(A), which is a sound pressure level that undermines verbal communica-tion. Therefore, theoretical models - often based on the diffuse field assumption [1–3] - were developed to predict the human noise propagation for a correct acoustic design of those spaces. Nevertheless, in room acoustics the fully diffused sound field is a rarely verified condition because of several factors: the geometry of the space, the preferred directions of noise propagation (e.g. in industrial spaces or large food courts), the attenuation due to screens (e.g. the exhibition panels in museums) [4]. The sound propagation of human noise in eating establishments has received par-ticular attention from scholars because of the demonstrated correlation between acoustic comfort, food perception and overall impression of the environment [5, 6].
The present study proposes a formula to predict the hu-man noise based on the rate spatial decay DL2. In this
approach, the predictive formula of human noise depends on: the occupancy (N), the group-size (g), the Lombard-slope - as the Rindel’s model - the DL2value, and the mean
distance between customers (¯r). The model is independent of metrics derived from the diffuse sound field assumption, such as the reverberation time and the equivalent absorbing areas. A large food court with low height compared to the other dimensions - which leads to a preferred direction of propagation - was used as a case study to validate this ap-proach. The human noise was firstly measured in the food court during lunchtime (before the COVID-19 outbreak). The occupancy during the measurements was around 120 people and the equivalent sound pressure level, averaged
over four positions, was around 70 dB(A). Secondly, the sound level decay of the hall was measured after dinner using a pink noise source and moving the receivers along a line, according to ISO 14257. The measured levels are shown in figure 1, returning a rate spatial decay of about 4.5 dB. 1 2 3 4 5 10 20 30 4050 −25 −20 −15 −10 −5 Source-receiver distance (m) Lp − Lp, 1 m (dB)
Figure 1. Spatial decay curve measured in the food court at mid frequencies. The resulting value of DL2 is about
4.5 dB.
A parametric model also used in a previous work [4] has been developed to randomly arrange people inside the food court area, to evaluate the mean distance between all the customers. In accordance with the occupancy during the acoustic measurements, N value was set equal to 120.
Algorithm 1: distances matrix between each visi-tor and all the remaining visivisi-tors
Input: A useful area, N occupancy Output: rij; i = 1, . . . , N ; j = 1, . . . , N ; 1 random N points p in A 2 for i = 1 : N do 3 for j = 1 : N, j! = i do 4 rij = distance (pi, pj) 5 end 6 end
0 5 10 15 20 25 0 20 40 60 80 source-receiver distance (m) occurrences 0 5 10 15 20 25 0 2 · 10−2 4 · 10−2 6 · 10−2 8 · 10−2 0,1
Figure 2. Occurrences of distances among N = 120 points simulated in Algorithm 1.
The algorithm performs the following steps. Starting from the plan of the hall, it defines the useful area A in which customers can seat. After setting the geometric limits, a random population of points p, representing cus-tomers’ positions, is generated. Each point is a bidimen-sional vector, i.e. a couple of bidimenbidimen-sional coordinates. Each vector p contains a couples of bidimensional coordi-nates, representing the visitors which were randomly gen-erated. The Algorithm 1 returns the distance-matrix be-tween all the N simulated sitting people randomly sparse. The source-receiver distances between all the sitting peo-ple in the food court can be assumed as a log-normal dis-tribution. Due to definition of group-size (g), it can also be expected that the distances between talking people follows the same statistic distribution.
Once obtained the parameters of the non-diffuse envi-ronment (DL2and ¯r), it is possible to check the behaviour
of the customers, respectively the group-size and the Lom-bard slope. The background-noise level measured dur-ing the dinner hour suggests a group-size g = 3.5 and a Lombard slope c = 0.4, being the values comparable with previous findings and taking into account the high background-noise level.
Table 1. Human-noise mitigation strategies evaluated in the case under study
Mitigation strategy Add. surface DL2 T30,M
(m2) (dB) (s)
No mitigation 0 4.5 1.86 Wall absorption 360 4.9 1.38 Baffles 82 (x 2) 5.7 1.53 Furthermore, the study shows how this type of approach could be useful in the design phase. Three configurations of the food court were simulated in a ray-tracing software: the original configuration, a mitigation with absorbent ma-terials on the walls, and a mitigation by hanging vertical baffles. Even if the second configuration reaches a lower T30value (see table 1), the proposed method seems to
con-firm how the hanging baffles allow a more confortable en-vironment (lower human noise level, see figure 3).
There-0 50 100 150 200 250 50 60 70 80 Occupancy N LN ,A (dB)
no mitig. (non diffuse) no mitig. (diffuse) walls (non diffuse) walls (diffuse) baffles (non diffuse) baffles (diffuse)
Figure 3. Comparison between the predictive model based on non-diffuse model and the Rindel’s model based on dif-fuse model. An arbitrary volume was set in the Rindel’s model in order to reach a comparable no-mitigation curve. fore, a lower use of absorbent material installed in baffles can be more effective than a greater quantity of material installed on the walls. In conclusion, by means of non-diffuse field parameters, the larger the food court (in other words, the higher ¯r value), the higher the DL2required to
achieve an adequate acoustic comfort. 1. REFERENCES
[1] S.K. Tang, D.W.T. Chan, K.C. Chan, Prediction of sound-pressure level in an occupied enclosure. J. Acoust. Soc. Am. 101, 1997, 2990-2993.
[2] M. Hodgson, G. Steiniger, Z. Razavi, Measurement and prediction of speech and noise levels and the Lom-bard effect in eating establishments. J. Acoust. Soc. Am. 121, 2007, 2023-2033.
[3] Rindel, J. H. (2010). Verbal communication and noise in eating establishments. Appl. Acoust., 71(12), 1156-1161.
[4] D. D’Orazio, F. Montoschi, M. Garai, Acoustic com-fort in highly attended museums: A dynamical model, Build. Environ., 183, 2020, 107176
[5] P. Bottalico, Lombard effect, ambient noise, and will-ingness to spend time and money in a restaurant, J. Acoust. Soc. Am. 144 (3), EL209–214, September 2018.
[6] Fiegel, A.; Meullenet, J.-F.; Harrington, R.J.; Hum-ble, R.; Seo, H.-S. Background music genre can modu-late flavor pleasantness and overall impression of food stimuli. Appetite 2014, 76, 144-152.
