scholarly journals Investigation into wind effects on fire spread on inclined wooden rods by multi-spectrum and schlieren imaging

2021 ◽  
pp. 103513
Author(s):  
Yufeng Lai ◽  
Xiao Wang ◽  
Thomas B.O. Rockett ◽  
Jon R. Willmott ◽  
Yang Zhang
2012 ◽  
Vol 11 (8) ◽  
pp. 1475-1480 ◽  
Author(s):  
Omer Kucuk ◽  
Ertugrul Bilgili ◽  
Serkan Bulut ◽  
Paulo M. Fernandes

2015 ◽  
Vol 14 (9) ◽  
pp. 2255-2262 ◽  
Author(s):  
Elena Axinte ◽  
Georgeta Vasie ◽  
Elena-Carmen Teleman ◽  
Victoria-Elena Ro.ca ◽  
Andrei-Octav Axinte

Buildings ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 237
Author(s):  
Aiman Albatayneh ◽  
Dariusz Alterman ◽  
Adrian Page ◽  
Behdad Moghtaderi

To design energy-efficient buildings, energy assessment programs need to be developed for determining the inside air temperature, so that thermal comfort of the occupant can be sustained. The internal temperatures could be calculated through computational fluid dynamics (CFD) analysis; however, miniscule time steps (seconds and milliseconds) are used by a long-term simulation (i.e., weeks, months) that require excessive time for computing wind effects results even for high-performance personal computers. This paper examines a new method, wherein the wind effect surrounding the buildings is integrated with the external air temperature to facilitate wind simulation in building analysis over long periods. This was done with the help of an equivalent temperature (known as Tnatural), where the convection heat loss is produced in an equal capacity by this air temperature and by the built-in wind effects. Subsequently, this new external air temperature Tnatural can be used to calculate the internal air temperature. Upon inclusion of wind effects, above 90% of the results were found to be within 0–3 °C of the perceived temperatures compared to the real data (99% for insulated cavity brick (InsCB), 91% for cavity brick (CB), 93% for insulated reverse brick veneer (InsRBV) and 94% for insulated brick veneer (InsBV) modules). However, a decline of 83–88% was observed in the results after ignoring the wind effects. Hence, the presence of wind effects holds greater importance in correct simulation of the thermal performance of the modules. Moreover, the simulation time will expectedly reduce to below 1% of the original simulation time.


2021 ◽  
Vol 13 (4) ◽  
pp. 2136
Author(s):  
Sayaka Suzuki ◽  
Samuel L. Manzello

Wildland fires and wildland urban-interface (WUI) fires have become a significant problem in recent years. The mechanisms of home ignition in WUI fires are direct flame contact, thermal radiation, and firebrand attack. Out of these three fire spread factors, firebrands are considered to be a main driving force for rapid fire spread as firebrands can fly far from the fire front and ignite structures. The limited experimental data on firebrand showers limits the ability to design the next generation of communities to resist WUI fires to these types of exposures. The objective of this paper is to summarize, compare, and reconsider the results from previous experiments, to provide new data and insights to prevent home losses from firebrands in WUI fires. Comparison of different combustible materials around homes revealed that wood decking assemblies may be ignited within similar time to mulch under certain conditions.


Author(s):  
Emil Simiu ◽  
Rene D. Gabbai

Current approaches to the estimation of wind-induced wind effects on tall buildings are based largely on 1970s and 1980s technology, and were shown to result in some cases in errors of up to 40%. Improvements are needed in: (i) the description of direction-dependent aerodynamics; (ii) the description of the direction-dependent extreme wind climate; (iii) the estimation of inertial wind effects induced by fluctuating aerodynamic forces acting on the entire building envelope; (iv) the estimation of uncertainties inherent in the wind effects; and (v) the use of applied wind forces, calculated inertial forces, and uncertainty estimates, to obtain via influence coefficients accurate and risk-consistent estimates of wind-induced internal forces or demand-to-capacity ratios for any individual structural member. Methods used in current wind engineering practice are especially deficient when the distribution of the wind loads over the building surface and their effects at levels other than the building base are not known, as is the case when measurements are obtained by the High-Frequency Force Balance method, particularly in the presence of aerodynamic interference effects due to neighboring buildings. The paper describes a procedure that makes it possible to estimate wind-induced internal forces and demand-to-capacity ratios in any individual member by: developing aerodynamic and wind climatological data sets, as well as aerodynamic/climatological directional interaction models; significantly improving the quality of the design via rigorous structural engineering methods made possible by modern computational resources; and properly accounting for knowledge uncertainties. The paper covers estimates of wind effects required for allowable stress design, wherein knowledge uncertainties pertaining to the parameters that determine the wind loading are not considered, as well as estimates required for strength design, in which these uncertainties need to be accounted for explicitly.


2021 ◽  
pp. 110585
Author(s):  
Alexander Jung ◽  
Wolfram Müller ◽  
Mikko Virmavirta

2021 ◽  
Vol 11 (4) ◽  
pp. 1642
Author(s):  
Yuxiang Zhang ◽  
Philip Cardiff ◽  
Jennifer Keenahan

Engineers, architects, planners and designers must carefully consider the effects of wind in their work. Due to their slender and flexible nature, long-span bridges can often experience vibrations due to the wind, and so the careful analysis of wind effects is paramount. Traditionally, wind tunnel tests have been the preferred method of conducting bridge wind analysis. In recent times, owing to improved computational power, computational fluid dynamics simulations are coming to the fore as viable means of analysing wind effects on bridges. The focus of this paper is on long-span cable-supported bridges. Wind issues in long-span cable-supported bridges can include flutter, vortex-induced vibrations and rain–wind-induced vibrations. This paper presents a state-of-the-art review of research on the use of wind tunnel tests and computational fluid dynamics modelling of these wind issues on long-span bridges.


Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 294
Author(s):  
Nicholas F. McCarthy ◽  
Ali Tohidi ◽  
Yawar Aziz ◽  
Matt Dennie ◽  
Mario Miguel Valero ◽  
...  

Scarcity in wildland fire progression data as well as considerable uncertainties in forecasts demand improved methods to monitor fire spread in real time. However, there exists at present no scalable solution to acquire consistent information about active forest fires that is both spatially and temporally explicit. To overcome this limitation, we propose a statistical downscaling scheme based on deep learning that leverages multi-source Remote Sensing (RS) data. Our system relies on a U-Net Convolutional Neural Network (CNN) to downscale Geostationary (GEO) satellite multispectral imagery and continuously monitor active fire progression with a spatial resolution similar to Low Earth Orbit (LEO) sensors. In order to achieve this, the model trains on LEO RS products, land use information, vegetation properties, and terrain data. The practical implementation has been optimized to use cloud compute clusters, software containers and multi-step parallel pipelines in order to facilitate real time operational deployment. The performance of the model was validated in five wildfires selected from among the most destructive that occurred in California in 2017 and 2018. These results demonstrate the effectiveness of the proposed methodology in monitoring fire progression with high spatiotemporal resolution, which can be instrumental for decision support during the first hours of wildfires that may quickly become large and dangerous. Additionally, the proposed methodology can be leveraged to collect detailed quantitative data about real-scale wildfire behaviour, thus supporting the development and validation of fire spread models.


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