| 1. |
- Bader Eddin, Mohamad, et al.
(författare)
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A sound insulation prediction model for floor structures in wooden buildings using neural networks approach
- 2021
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Ingår i: Proceedings of INTER-NOISE 2021 - 2021 International Congress and Exposition of Noise Control Engineering. - 0736-2935. - 9781732598652
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Reliable prediction tools are yet to be developed for estimating the accurate acoustic performance of lightweight structures, which are vital especially in the design process. This paper presents a sound insulation prediction model based on artificial Neural Networks (NN) to estimate acoustic performance for airborne and impact sound insulation of floor structures. At an initial stage, the prediction model was developed and tested for a small amount of data, specifically 67 laboratory measurement curves in one third octave bands. The results indicate that the model can predict the weighted airborne reduction index Rw for various floors with a maximum error of 1 dB. The accuracy decreases with errors up to 9 dB for the weighted index for impact sound Ln,w, in cases of complex floor configurations due to large error deviations in high frequency bands between the real and estimated values. The model also shows a very good accuracy in predicting the airborne and impact sound insulation curves in the low frequencies, which are of higher interest usually in building acoustics.
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| 2. |
- Bader Eddin, Mohamad, et al.
(författare)
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Prediction of Sound Insulation Using Artificial Neural Networks—Part II : Lightweight Wooden Façade Structures
- 2022
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Ingår i: Applied Sciences (Switzerland). - : MDPI AG. - 2076-3417. ; 12:14
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Tidskriftsartikel (refereegranskat)abstract
- A prediction model based on artificial neural networks is adapted to forecast the acoustic performance of airborne sound insulation of various lightweight wooden façade walls. A total of 100 insulation curves were used to develop the prediction model. The data are laboratory measurements of façade walls in one-third-octave bands (50 Hz–5 kHz). For each façade wall, geometric and physical information (material type, dimensions, thicknesses, densities, and more) are used as input parameters. The model shows a satisfactory predictive capability for airborne sound reduction. A higher accuracy is obtained at middle frequencies (250 Hz–1 kHz), while lower and higher frequency ranges often show higher deviations. The weighted airborne sound reduction index ((Formula presented.)) of façades can be estimated with a maximum difference of 3 dB. Sometimes, the model shows high variations within fundamental and critical frequencies that influence the predictive precision. A sensitivity analysis is implemented to investigate the significance of parameters in insulation estimations. The material density (i.e., cross-laminated timber panel, gypsum board), thickness of the insulation materials, thickness and spacing between interior studs and the total density of façades are factors of significant weight on predictions. The results also emphasize the importance of façade thickness and the total density of the clustered exterior layers.
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| 3. |
- Bard, Delphine, et al.
(författare)
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Challenges for acoustic calculation models in "silent timber build", Part 1- FEM
- 2014
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Ingår i: INTERNOISE 2014 - 43rd International Congress on Noise Control Engineering : Improving the World Through Noise Control - Improving the World Through Noise Control. - 9781634398091 - 9780909882037 ; , s. 4424-4429
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Konferensbidrag (refereegranskat)abstract
- The project "Silent Timber Build" will develop new prediction tools for timber structures. There are several challenges that have to be overcome to provide a full prediction tool. The differences in weight, stiffness and density for wooden structures compared to traditional, heavy and more homogeneous structural material have repercussions on how the sound propagates throughout the structures, affecting the sound and vibration insulation performance and also theories to be used in prediction models. Finite element simulations have proved to be useful in the design phase in a certain low and very low frequency range. By further developing reliable finite element tools for low frequencies, the performance of future wooden constructions can be predicted in a full frequency range, saving both time and money as all calculations, and modifications can be done during the design phase. However the upper limit for using FEM has to be further investigated and then be merged with statistical methods. This article, following another article Part 2, will focus on medium and high frequency range calculations. For full-scale building, Virtual SEA method, as analytic and SEA approaches will be used in frequencies low enough in order to optimize the overlap to FEM.
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| 4. |
- Eddin, Mohamad Bader, et al.
(författare)
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A comparison of numerical approaches to quantify sound insulation of lightweight wooden floor structures
- 2022
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Ingår i: Internoise 2022 - 51st International Congress and Exposition on Noise Control Engineering. - 9781906913427
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Konferensbidrag (refereegranskat)abstract
- Quantifying air-borne and structure-borne sound insulation is an important design consideration for the indoor comfort in a building. Although sound insulation performance is commonly measured experimentally, numerical methods can have time-saving and economic benefits. Further, numerical methods can be incorporated within building simulations to provide an estimate of the acoustic environment. In response, this paper evaluates three different computational approaches for quantifying sound insulation in one-third octave bands (50 Hz -5 kHz) of a lightweight floor including: an analytical (theoretical) model, a finite element model (FEM), and an artificial neural network (ANN) model. The three numerical methods are tested on the sound insulation of a cross laminated timber (CLT) floor. The results of this study show that the ANN model is able to accurately predict the air-borne and impact sound insulation performance at frequencies above 250 Hz, but over-predicts the air-borne performance and under-predicts the impact performance at low frequencies. However, the analytical and FEM strategies provide acceptable estimations, useful during the conceptual design stage, but with higher deviations than ANN model across all frequencies. While no model is able to accurately represent acoustic behavior across all frequencies, this work highlights the advantages and disadvantages when applied to predicting the sound insulation of a CLT floor.
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| 5. |
- Eddin, Mohamad Bader, et al.
(författare)
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Prediction of Sound Insulation Using Artificial Neural Networks—Part I : LightweightWooden Floor Structures
- 2022
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Ingår i: Acoustics. - : MDPI AG. - 2624-599X. ; 4:1, s. 203-226
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Tidskriftsartikel (refereegranskat)abstract
- The artificial neural networks approach is applied to estimate the acoustic performance for airborne and impact sound insulation curves of different lightweight wooden floors. The prediction model is developed based on 252 standardized laboratory measurement curves in one-third octave bands (50-5000 Hz). Physical and geometric characteristics of each floor structure (materials, thickness, density, dimensions, mass and more) are utilized as network parameters. The predictive capability is satisfactory, and the model can estimate airborne sound better than impact sound cases especially in the middle-frequency range (250-1000 Hz), while higher frequency bands often show high errors. The forecast of the weighted airborne sound reduction index Rw was calculated with a maximum error of 2 dB. However, the error increased up to 5 dB in the worse case prediction of the weighted normalized impact sound pressure level Ln,w. The model showed high variations near the fundamental and critical frequency areas which affect the accuracy. A feature attribution analysis explored the essential parameters on estimation of sound insulation. The thickness of the insulation materials, the density of cross-laminated timber slab and the concrete floating floors and the total density of floor structures seem to affect predictions the most. A comparison between wet and dry floor solution systems indicated the importance of the upper part of floors to estimate airborne and impact sound in low frequencies.
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| 6. |
- Eddin, Mohamad Bader, et al.
(författare)
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Sound insulation of lightweight wooden floor structures : ANN model and sensitivity analysis
- 2022
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Ingår i: Internoise 2022 - 51st International Congress and Exposition on Noise Control Engineering. - 9781906913427
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Konferensbidrag (refereegranskat)abstract
- The study aims to develop an artificial neural networks (ANN) model to estimate the acoustic performance for airborne and impact sound insulation curves of different lightweight wooden floors. The prediction model is developed using 252 standardized laboratory measurement curves in one-third octave bands (50 − 5000 Hz). Each floor structure has been divided into three parts in the database: upper, main and ceiling parts. Physical and geometric characteristics (materials, thickness, density, dimensions, mass, and more) are used as network parameters. The results demonstrated that the predictive ability of the model is satisfactory. The forecast of the weighted airborne sound reduction index Rw was calculated with a maximum error of 2 dB. However, it is increased up to 5 dB in the worst case prediction of the weighted normalized impact sound pressure level Ln,w. A sensitivity analysis explored the essential parameters on sound insulation estimation. The thickness and the density of upper and main parts of the floors seem to affect estimations the most in all frequencies. In addition, no remarkable attribution has been found for the thickness and density of the ceiling part of the structures.
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| 7. |
- Kouyoumji, Jean Luc, et al.
(författare)
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Challenges for acoustic calculation models in "Silent Timber Build", Part 2
- 2014
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Ingår i: 43rd International Congress on Noise Control Engineering (INTERNOISE 2014) : Improving the World Through Noise Control - Improving the World Through Noise Control. - 9781634398091 - 9780909882037 ; , s. 3054-3061
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Konferensbidrag (refereegranskat)abstract
- The project "Silent Timber Build" will develop new prediction tools for timber structures. There are several challenges that have to be overcome to provide a full prediction tool. The differences in weight, stiffness and density for wooden structures compared to traditional, heavy and more homogeneous structural material have repercussions on how the sound propagates throughout the structures, affecting the sound and vibration insulation performance and also theories to be used in prediction models. The project will use Finite element simulations (FEM) and Statistical Energy Analysis (SEA) approaches to predict acoustical behavior of light weight timber constructions. This article, following another article Part 1, will focus on medium and high frequency range calculations. Statistical methods will be used in the medium and high frequency, where the acoustic performance of wooden building components (walls and floors) is generally limited by the presence of structural links and couplings. Statistical Energy Analysis (SEA) has proven to be an efficient approach, providing robust vibroacoustic models in this frequency region. The extension of statistical methods towards the low frequencies has to be evaluated, especially regarding time responses of impact noise on floor systems. For full-scale building, Virtual SEA method will be used as well as analytic SEA approach in frequencies low enough in order to optimize the overlap to FEM.
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| 8. |
- Qian, Cheng, et al.
(författare)
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Calibration of the ISO tapping machine for finite-element prediction tool on a wooden-base floor
- 2019
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Ingår i: Building Acoustics. - 1351-010X. ; 26:3, s. 157-167
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Tidskriftsartikel (refereegranskat)abstract
- One important challenge of the wooden constructions is to achieve a high quality of acoustic insulation, especially decreasing the impact noise in the low-frequency range. In order to avoid over-designed solutions and expensive experimental tests in the design phase, reliable prediction tools are called for. This article is an initial investigation of modeling the ISO standardized tapping machine on a cross-laminated timber floor, using finite element method. The wooden-based floor was first calibrated in terms of its dynamic properties. The influence of the material properties of the cross-laminated timber floor was discussed. The force generated by the tapping machine was then introduced in the established cross-laminated timber model. The model was finally validated by comparing the simulation results with the measured accelerations.
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| 9. |
- Salzer, Corinna, 1984, et al.
(författare)
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Sustainability of Social Housing in Asia: A Holistic Multi-Perspective Development Process for Bamboo-Based Construction in the Philippines
- 2016
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Ingår i: Sustainability. - : MDPI AG. - 2071-1050. ; 8:2
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Tidskriftsartikel (refereegranskat)abstract
- This paper highlights the need for a more inclusive and sustainable development of social housing in rapidly developing countries of Asia, Latin America, and Africa. At the example of the Philippines, a multi-perspective development process for a bamboo-based building systemis developed. Sustainability Assessment Criteria are defined through literature review, field observations and interviews with three stakeholder clusters: (1) Builders and users of traditional bamboo houses in the Philippines; (2) Stakeholders involved in using forest products for housing in other countries around the world; and (3) Stakeholders in the field of social housing in the Philippines. Through coding and sorting of data in a qualitative content analysis, 15 sustainability assessment criteria are identified clustered into the dimensions society, ecology, economy, governance, and technology. Guided by the sustainability criteria and four implementation strategies: (A) Research about and (B) Implementation of the building technology; (C) Participation and Capacity Buildingof Stakeholders; and (D) Sustainable Supply Chains, a strategic roadmap was created naming, in total, 28 action items. Through segmentation of the complex problem into these action items, the paper identifies one-dimensional methods leading to measurable, quantitative endpoints. In this way, qualitative stakeholder data is translated into quantitative methods, forming a pathway for a holistic assessment of the building technologies. A mid-point, multi-criteria, or pareto decision-making method comparing the 28 endpoints of the alternative to currently practiced conventional solutions is suggested as subject for further research. This framework paper is a contribution to how sustainable building practices can become more inclusive, incorporating the building stock of low-income dwellers. It bridges the gap between theoretical approach and practical applications of sustainability and underlines the strength of combining multi-dimensional development with stakeholder participation.
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