A case study on workstation dependent acoustic characterization of open plan offices

Open-plan space is used in interior building design to create shared functional environments. The basic idea is to foster flexibility, cooperation and spaciousness in indoor environments by eliminating any boundaries hindering sight and speech intelligibility, such as walls. However, the complexity of sound propagation in open-plan spaces makes acoustic modelling a particularly challenging problem. Moreover, in open-plan offices (see Figure 1) the acoustic environment is a mixture of machine- and human-made sounds. Thus employees often feel annoyed by various types of acoustic noise. Examples for typical noise sources are speech, walking sounds, environmental noise and working sounds (eg. typing on keyboards). In contrast to the intention of increased cooperation, for tasks requiring high levels of concentration the acoustic situation of the open-plan space is a drawback. Consequently, a number of studies have begun to examine employees\u27 responses to acoustic noise. At the same time, it is unclear which acoustical treatment is better for open-plan spaces in order to improve the well-being in the working environment. The common practices include applying sound absorbing (meta-) materials on ceilings and baffles or screens, or applying sound masking.It is greatly acknowledged that sound and vibration noise is addressed as an important factor in job satisfaction ratings, which is closely related with perceived health conditions. Therefore, it is important to reduce noise annoyances which may impair cognitive performance. However, the acoustics in open-plan offices remain often an unquantified issue. Even in cases where the acoustics are taken into account it is difficult to relate objective acoustic measurements to the employees\u27 subjective feeling. As a result, in many cases measures to improve the acoustics are not targeted on a precise issue

In situ acoustic characterization of a locally reacting porous material by means of PU measurement and model fitting

Reliable data on acoustical properties of materials are crucial for the design of a desired acoustic environment as well as to obtain accurate results from acoustic simulations. Although the acoustical properties of materials can be obtained via laboratory measurements, situations where in situ measurements are needed are often encountered. However, in situ measurement methods presented so far are limited by their poor portability or inaccuracies in the low-frequency range. In this work, we propose a characterization method that combines an in situ pressure-velocity (PU) measurement with a model fitting procedure using the Delany-Bazley-Miki impedance model for porous materials. The method uses an optimization routine to find the best match of measured and modelled reflection coefficient values within a given frequency range for the optimization parameters: flow resistivity, panel thickness, and probe-sample distance. The optimal parameter values allow, in turn, calculating the porous panel's reflection coefficients for a broad frequency range including frequencies below the lower bounds of the optimization frequency range. The sensitivity of the method to panel width, lower bound of fitting frequency range, and to excluding parasitic reflections by time windowing is studied. The study shows that the proposed method provides characterization results in good agreement with reference data for panels of dimensions larger than 1800 mm and that the method is robust for reduction of one dimension of the panel down to 300 mm. It also shows that the model fitting accuracy is best when the frequency range of analysis is restricted to 1000–5000 Hz

Design and simulation of a benchmark room for room acoustic auralizations

In order to achieve accurate acoustic simulations of a room for obtaining an authentic auralization, the following aspects need to be quantified: the geometrical details of the room, all material properties and the characteristics of the source and the receiver. This paper presents the design of a benchmark room for this purpose, including all this information. The room is a building acoustics transmission chamber with thick concrete walls. This room was then acoustically treated to achieve an acoustic environment close to a day-to-day office room. The surface impedances of the materials additionally installed in the room were measured with both in the impedance tube as well as with a pressure-velocity sensor. Furthermore, the directivity of the measurement source and the binaural receiver were measured in order to be included in the simulations. Impulse responses of this benchmark room have also been obtained from simulations with the in-house time-domain discontinuous Galerkin method (DG) with frequencydependent boundary conditions, including source and receiver directivity. Time and frequency domain results from the both the measurements and simulations are presented, showing a close agreement

Design and simulation of a benchmark room for room acoustic auralizations

In order to achieve accurate acoustic simulations of a room for obtaining an authentic auralization, the following aspects need to be quantified: the geometrical details of the room, all material properties and the characteristics of the source and the receiver. This paper presents the design of a benchmark room for this purpose, including all this information. The room is a building acoustics transmission chamber with thick concrete walls. This room was then acoustically treated to achieve an acoustic environment close to a day-to-day office room. The surface impedances of the materials additionally installed in the room were measured with both in the impedance tube as well as with a pressure-velocity sensor. Furthermore, the directivity of the measurement source and the binaural receiver were measured in order to be included in the simulations. Impulse responses of this benchmark room have also been obtained from simulations with the in-house time-domain discontinuous Galerkin method (DG) with frequencydependent boundary conditions, including source and receiver directivity. Time and frequency domain results from the both the measurements and simulations are presented, showing a close agreement

Derivation of time-domain impedance boundary conditions based on in-situ surface measurement and model fitting

In order to achieve accurate time-domain wave-based simulations of a real room, the acoustical properties of the locally reacting materials within the room have to be implemented as time-domain impedance boundary conditions (TDIBC), in such a way that the behavior of the materials is well-simulated within the wave-based solver. This paper presents the implementation of such TDIBCs of two materials: a porous absorber and an acoustic carpet. Firstly, the material properties were measured both in the impedance tube and in-situ with a pressure-velocity sensor. Advantages and drawbacks experienced with both methods in this context will be presented. Next, the measurement results were fitted to broadband impedance models to extend impedance data to the lower frequency range (20 Hz-300 Hz), resulting in broadband impedance data (20 Hz-4000 Hz). Finally the TDIBCs, in the form of complex reflection coefficients, were fitted as discrete sums of rational functions

A case study on workstation-dependent acoustic characterization of open plan offices

Poster presented at e-Forum Acusticum 2020 (online conference).status: publishe

Derivation of time-domain impedance boundary conditions based on in-situ surface measurement and model fitting

In order to achieve accurate time-domain wave-based simulations of a real room, the acoustical properties of the locally reacting materials within the room have to be implemented as time-domain impedance boundary conditions (TDIBC), in such a way that the behavior of the materials is well-simulated within the wave-based solver. This paper presents the implementation of such TDIBCs of two materials: a porous absorber and an acoustic carpet. Firstly, the material properties were measured both in the impedance tube and in-situ with a pressure-velocity sensor. Advantages and drawbacks experienced with both methods in this context will be presented. Next, the measurement results were fitted to broadband impedance models to extend impedance data to the lower frequency range (20 Hz-300 Hz), resulting in broadband impedance data (20 Hz-4000 Hz). Finally the TDIBCs, in the form of complex reflection coefficients, were fitted as discrete sums of rational functions