Sound insulation prediction and optimization
Source: EU Funding & Tenders Portal
With urbanization accelerating on a global scale, airborne and impact sound insulation have become key performance quantities of building elements. Unfortunately, acoustic requirements do not naturally align with structural and thermal requirements. Achieving good sound insulation is difficult, especially for innovative, more sustainable building systems which are typically lightweight. There is a
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | ongoing |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | With urbanization accelerating on a global scale, airborne and impact sound insulation have become key performance quantities of building elements. Unfortunately, acoustic requirements do not naturally align with structural and thermal requirements. Achieving good sound insulation is difficult, especially for innovative, more sustainable building systems which are typically lightweight. There is an urgent need in the construction sector for adequate sound insulation design prediction software. In the ERC Starting Grant VirBAcous, new, dedicated numerical methods for sound insulation prediction have been developed that possess the required combination of a high prediction accuracy and a high computational efficiency. By doing so, they open up the possibility of reliable model-based design optimization. The aim of this ERC Proof of Concept project is to bridge the gap between the fundamental numerical methods from VirBAcous and the construction sector. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
