Analysis of tall building for across wind response

Vyavahare, Arvind Y.; Godbole, P.N.; Nikose, Trupti

doi:10.6088/ijcser.00202030024

Cited by 3 publications

(4 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[27] A notable deviation between IS and NALD becomes observed in that case also while computing the C fs . This inadequateness and silence of the Indian standard for crosswind spectrum was further investigated by Arvind in 2012 [20] based on mode generalized across-wind force spectrum and its fluctuation by Kareem (1984). [28] Few back propagation ANN models are proposed with varying number of hidden layers in accordance with the AS/NZ code of practice, but again it kept the models' specifications limited within the same aspect ratios mentioned in the Indian standard and could not establish its uniformity and diversity.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Effect of aspect ratio subjected to wind hazard in tall buildings situated along the coastal line of India

Ghosh

Sil

2022

Structural Design Tall Build

View full text Add to dashboard Cite

Summary The escalating growth of the tall buildings as well as the increasing number of extreme wind events in the Indian coastal region have certainly arisen the question of the safety and stability of these buildings situated in the metropolitan cities along the coastline. In such a scenario where there have been a constant focus on more researches for a unified wind code, however a comprehensive comparative study is required not only to assess and analyze the dynamic peak factors of the tall building models due to wind load, but also to enlighten the differences in the obtained results as well as their patterns respectively. The aspect ratio of buildings essentially governs the stability as well as contributes to a great extent on the dynamic responses in terms of base shear, base moment and torsional effects at the base. However, a framework based on the Indian wind database could ease the complexity of such parametric survivability studies of such structures. Distinguished variations in the dynamic responses for a series of models of tall buildings with varying aspect ratios along the height are analyzed as well as discussed in the present study, and the pattern of the deviation of the results with a parallel framework is also addressed to propose a mechanism for assessing the behaviors of tall buildings under specific wind speed predominant in the Indian coastal region that would help to ensure the safety and stability of structures subjected to wind hazards in Indian context in future.

show abstract

Section: Resultsmentioning

confidence: 99%

“…Arvind [20] enlightened on the uses of neural networks in determining the crosswind coefficient and proposed a few models with some appreciable coefficient of regression, but still it is not codified as well as established as a part of standard practice to be followed because of its limitations.…”

Section: Across-wind Loads and Responsesmentioning

confidence: 99%

Effect of aspect ratio subjected to wind hazard in tall buildings situated along the coastal line of India

Ghosh

Sil

2022

Structural Design Tall Build

View full text Add to dashboard Cite

show abstract

“…Tall structures that fulfill the lateral drift standards of the code can nonetheless waver in high winds. As a result, a study of the computation strategies currently in use for determining wind load is required [7]. So, it is important to be able to predict the area affected by the plume resulting from an accidental or deliberate release of a dangerous substance inside a city and the concentrations of the pollutant in the area [8][9].…”

Section: Literature Reviewmentioning

confidence: 99%

Structural Behavior of an RC Building Frame due to Wind Pressure in Bangladesh

Arafat

2022

Malaysian J. Sci. Adv. Tech.

View full text Add to dashboard Cite

Since the necessity for larger and slimmer structures has arisen in Bangladesh, wind engineering has become increasingly important. The traditional approach of manual high-rise building design is time-consuming and prone to human mistakes. ETABS is a structural program that is currently widely used by structural engineers to handle common problems such as static analysis, wind analysis, and confirming multiple codes using various load combinations. The study's purpose is to compare wind pressure's impacts on eight distinct places in Bangladesh. ETABS 9.6 software with the BNBC provision was used to conduct this research on a 106-foot residential building. The study's major goal is to examine the reactions of stories, narrative displacement, and drift under the influence of wind in eight major distinct areas out of five divisions of Bangladeshi areas. Based on the investigation findings, we attempted to determine their attitude to various wind pressures. Analysis shows that wind pressure in the South-East and South-West is higher than in the North-East and North-West and most of it is found in the South-East.

show abstract

“…ANN was utilized to predict wind spectra and to calculate wind loadings for rectangular cross-section buildings [25]. Further, to present an innovative method for investigating the seismic vulnerability of the existing concrete structures with moment resisting frames (MRF) [26] and to generalize the across wind response of tall and slender buildings from the inadequate existing data so that across wind response can be attained for a building with specified (h:b:d) ratio [27], ANN was adopted. Neural nets were used to estimate mean external surface pressure coefficients of tall buildings [28] and to propose a simplified approach for estimating the dynamic along-wind response of tall buildings based on Indian Wind Code [29,30].…”

Section: Introductionmentioning

confidence: 99%

Prognosis of Wind-tempted Mean Pressure Coefficients of Cross-shaped Tall Buildings Using Artificial Neural Network

Paul

Dalui

2020

Period. Polytech. Civil Eng.

View full text Add to dashboard Cite

The present paper focuses on the study of wind-induced responses of cross-plan shaped tall buildings. Initially, three parametric building models are studied for the purpose with a constant plan area 22500 mm2. The length and velocity scales are taken as 1:300 and 1:5, respectively. Wind angle of attack (WAA) is considered from 0° to 330° with an increment of 30°. At first, the external surface pressure coefficients (Cp) at different faces of the models are carried out for different wind occurrence angles employing Computational Fluid Dynamics method of simulated wind flow. Again, Fast Fourier Transform (FFT) fitted expressions as the sine and cosine function of WAA are proposed for attaining mean wind pressure coefficient on the building faces. The accuracy of the Fourier series expansions is justified by presenting histograms of sum square error (SSE), R2 value and root mean square error (RMSE). The results are also compared by training Artificial Neural Networks (ANN). Training is continued till Regression (R) values are more than 0.99 and Mean Squared Error (MSE) tends to 0, ensuring a close relationship among the outputs and targets. The face-wise value of (Cp) obtained using all three methods, are plotted. The error histograms of the ANN models show that the fitting data errors are spread within a reasonably good range. It is observed that the deviation in the result is not more than 5% in any case. Finally, the ANN predictions are presented for nine parametric models to cover a wide range of possible cross-shaped buildings.

show abstract

Analysis of tall building for across wind response

Cited by 3 publications

References 7 publications

Effect of aspect ratio subjected to wind hazard in tall buildings situated along the coastal line of India

Effect of aspect ratio subjected to wind hazard in tall buildings situated along the coastal line of India

Structural Behavior of an RC Building Frame due to Wind Pressure in Bangladesh

Prognosis of Wind-tempted Mean Pressure Coefficients of Cross-shaped Tall Buildings Using Artificial Neural Network

Contact Info

Product

Resources

About