User Guide#
Getting started#
INSUL is a program for predicting the sound insulation of walls, floors, ceilings and windows.
INSUL is based on theoretical models that require only minimal information but can make reasonable estimates of the sound transmission loss (TL) and Sound Transmission Class (STC) for use in sound insulation calculations, or design of intertenancy partitions etc. INSUL can be used to quickly evaluate new materials or systems or investigate the effects of changes to existing designs.
It models materials using the simple mass law and critical frequency approach and models more complex partitions using work by B.H. Sharp, Cremer and others. It has evolved over several versions into an easy to use tool and has refined the theoretical models by continued comparison with laboratory tests to provide acceptable accuracy for a wide range of constructions.
Users should be aware of its limitations, like any prediction tool it is not a substitute for test data. Comparisons with test data show that it generally within 3 STC/Rw points for most.
To get started with INSUL, take a look at this example.
User Guide Versions
The INSUL Version 9 User Guide is available here.
Extra features#
INSUL can also be used for a range of calculations and modelling tasks associated with sound insulation, including:
- Predicting impact sound pressure levels
- Predicting rain noise
- Predicting sound insulation of leaks
- Calculating composite transmission loss or sound reduction
- Calculating outdoor to indoor sound levels
Modelling Accuracy#
Comparisons with test data show that its generally within 3 STC/Rw points for most constructions. The accuracy is, however, less for triple panel constructions for which the estimated uncertainty of 5 STC/Rw or more is likely.
Important
Users should be aware of its limitations, like any prediction tool it is not a substitute for test data.
The following papers provide detailed discussions of INSUL's prediction accuracy.
Model |
Paper |
|---|---|
| Airborne | Ballagh, K. O. (2004). Accuracy of prediction methods for sound transmission loss |
| Glazing | Emms, G. & Chung, H. (2022) Accuracy of a prediction method for sound transmission loss of glazing. In Conference of the Acoustical Society of New Zealand 2022 |
| Impact | Griffin, D. (2014). Accuracy of prediction methods for impact sound pressure levels |
| Griffin, D. (2017). Accuracy of prediction methods for the improvement in impact sound pressure levels using floor coverings. In INTER-NOISE 2017 Conference Proceedings | |
| Rain | Griffin, D., & Ballagh, K. (2012). A consolidated theory for predicting rain noise |
| Griffin, D. (2016). Accuracy of prediction methods for rain noise. In INTER-NOISE 2016 Conference Proceedings | |
| Leaks | Griffin, D. (2018). Accuracy of prediction methods for sound reduction of circular and slit-shaped apertures. In International Congress on Sound and Vibration 25 |