| 1. |
- Bader Eddin, Mohamad, et al.
(författare)
-
Prediction of Sound Insulation Using Artificial Neural Networks—Part II : Lightweight Wooden Façade Structures
- 2022
-
Ingår i: Applied Sciences (Switzerland). - : MDPI AG. - 2076-3417. ; 12:14
-
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.
|
|
| 2. |
- Eddin, Mohamad Bader, et al.
(författare)
-
A comparison of numerical approaches to quantify sound insulation of lightweight wooden floor structures
- 2022
-
Ingår i: Internoise 2022 - 51st International Congress and Exposition on Noise Control Engineering. - 9781906913427
-
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.
|
|
| 3. |
- Eddin, Mohamad Bader, et al.
(författare)
-
Prediction of Sound Insulation Using Artificial Neural Networks—Part I : LightweightWooden Floor Structures
- 2022
-
Ingår i: Acoustics. - : MDPI AG. - 2624-599X. ; 4:1, s. 203-226
-
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.
|
|
| 4. |
- Eddin, Mohamad Bader, et al.
(författare)
-
Sound insulation of lightweight wooden floor structures : ANN model and sensitivity analysis
- 2022
-
Ingår i: Internoise 2022 - 51st International Congress and Exposition on Noise Control Engineering. - 9781906913427
-
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.
|
|
| 5. |
- Ménard, Delphine, et al.
(författare)
-
Plant biomechanics and resilience to environmental changes are controlled by specific lignin chemistries in each vascular cell type and morphotype
- 2022
-
Ingår i: The Plant Cell. - : Oxford University Press. - 1040-4651 .- 1532-298X. ; 34:12, s. 4877-4896
-
Tidskriftsartikel (refereegranskat)abstract
- The biopolymer lignin is deposited in the cell walls of vascular cells and is essential for long-distance water conduction and structural support in plants. Different vascular cell types contain distinct and conserved lignin chemistries, each with specific aromatic and aliphatic substitutions. Yet, the biological role of this conserved and specific lignin chemistry in each cell type remains unclear. Here, we investigated the roles of this lignin biochemical specificity for cellular functions by producing single cell analyses for three cell morphotypes of tracheary elements, which all allow sap conduction but differ in their morphology. We determined that specific lignin chemistries accumulate in each cell type. Moreover, lignin accumulated dynamically, increasing in quantity and changing in composition, to alter the cell wall biomechanics during cell maturation. For similar aromatic substitutions, residues with alcohol aliphatic functions increased stiffness whereas aldehydes increased flexibility of the cell wall. Modifying this lignin biochemical specificity and the sequence of its formation impaired the cell wall biomechanics of each morphotype and consequently hindered sap conduction and drought recovery. Together, our results demonstrate that each sap-conducting vascular cell type distinctly controls their lignin biochemistry to adjust their biomechanics and hydraulic properties to face developmental and environmental constraints.
|
|
| 6. |
- Nilsson, Erik, et al.
(författare)
-
Acoustical Treatments on Ventilation Ducts through Walls : Experimental Results and Novel Models
- 2022
-
Ingår i: Acoustics. - : MDPI AG. - 2624-599X. ; 4:1, s. 276-296
-
Tidskriftsartikel (refereegranskat)abstract
- Sound reduction is complex to estimate for acoustical treatments on ventilation ducts through walls. Various acoustical treatments are available for ventilation ducts, including internal lining (absorption along the inner perimeter), external lagging (external sound insulation), silencer, and suspended ceilings. Previous studies have examined how silencers and the internal lining affect the sound transmission of ventilation ducts. However, there are few theories to predict the effect of external lagging in combination with ventilation ducts and how the total sound reduction is affected. This article aims to investigate different acoustical treatments and develop theoretical models when external lagging with stone wool is used to reduce flanking sound transmission via the surface area of ventilation ducts. Theoretical models are developed for external lagging and compared with measurement data. Measurements and theory are generally in good agreement over the third-octave band range of 100–5000 Hz. The developed models clarify that the distance closest to the wall has the main impact on sound reduction for a combined system with a wall and a ventilation duct. Suspended ceilings and silencers are found to be enough as acoustical treatments for certain combinations of ventilation ducts and walls. However, external lagging seems to be the only effective solution in offices and schools when a large ventilation duct passes through a wall with high sound reduction.
|
|
| 7. |
- Nilsson, Erik, et al.
(författare)
-
Effect of Bearing Direction and Mounting Techniques on Cross-Laminated Timber Elements in the Field
- 2022
-
Ingår i: Internoise 2022 - 51st International Congress and Exposition on Noise Control Engineering. - 9781906913427
-
Konferensbidrag (refereegranskat)abstract
- Vibration reduction index (Kij ) measurements in the field have some challenges compared to laboratory measurements. Firstly, the measurement requires access to a construction site during the short time span when the cross-laminated timber (CLT) elements are apparent. Secondly, building contractors are often on a tight time schedule. Therefore, it is important to find a solution that minimizes the measurement time on site. Moreover, Kij measurements in the field include several types of junctions with different bearing directions which may be of importance. This paper aims to evaluate two different mounting techniques with accelerometers on CLT elements and to discuss how the bearing direction could affect the vibration level difference of junctions. Measurement data indicate few deviations between mounting techniques with bee wax or double-sided adhesive tape when accelerometers are attached to CLT elements. Furthermore, field measurements indicate that the vibration level will decrease with increased lamellas over the same CLT element. Double-sided adhesive tape is an adequate substitute for bee wax in the field for mounting accelerometers on CLT elements, with some limitations at high frequencies. Measurement data concludes that the bearing direction of CLT elements can influence the vibration reduction index of a junction.
|
|
