Abstract
In this study, a square rectangular tall building is considered to investigate the effects of turbulence integral length scale and turbulence intensity on the along-wind responses, across-wind responses and torsional responses of the tall building by Large Eddy Simulation (LES). A recently proposed inflow turbulence generator called the discretizing and synthesizing random flow generation (DSRFG) approach is applied to simulate turbulent flow fields. It has been proved that the approach is able to generate a fluctuating turbulent flow field satisfying any given spectrum, desired turbulence intensity and wind speed profiles. Five profiles of turbulence integral length scale and turbulence intensity are respectively generated for the inflow fields by the DSRFG approach for investigating the effects of turbulence integral length scale and turbulence intensity on the wind-induced responses of the tall building. The computational results indicate that turbulence integral length scale does not have significant effect on the along-wind (displacement, velocity and acceleration) responses, across-wind displacement and velocity responses, while
the across-wind acceleration and torsional responses vary without a clear rule with the parameter. On the
other hand, the along-wind, across-wind and torsional responses increase with the growth of turbulence
intensity.
Key Words
turbulence integral length scale; turbulence intensity; tall building; wind-induced response;CFD; LES
Address
Q.S. Li, G. Hu and Bo-wen Yan: Department of Civil and Architectural Engineering, City University of Hong Kong, Hong Kong
Abstract
This paper proposes new criteria to fix hidden neuron in Multilayer Perceptron Networks for wind speed prediction in renewable energy systems. To fix hidden neurons, 101 various criteria are examined based on the estimated mean squared error. The results show that proposed approach performs better in terms of testing mean squared errors. The convergence analysis is performed for the various
proposed criteria. Mean squared error is used as an indicator for fixing neuron in hidden layer. The proposed
criteria find solution to fix hidden neuron in neural networks. This approach is effective, accurate with
minimal error than other approaches. The significance of increasing the number of hidden neurons in multilayer perceptron network is also analyzed using these criteria. To verify the effectiveness of the proposed method, simulations were conducted on real time wind data. Simulations infer that with minimum mean squared error the proposed approach can be used for wind speed prediction in renewable energy systems.
Key Words
hidden neurons; mean squared error; multilayer perceptron; neural networks; wind speed prediction
Address
K. Gnana Sheela and S.N. Deepa: Anna University, Regional Centre, Coimbatore, India
Abstract
The uncertainty of extreme wind speeds is one key contributor to the uncertainty of wind loads and their effects on structures. The probability distribution of annual extreme wind speeds may be characterized using a classical Gumbel Type distribution. The expression that establishes the relationship between the extreme wind speeds at different recurrence periods and the corresponding coefficients of variation is formulated, and its efficacy is validated. The coefficients of variation are calibrated to be about 0.125 and 0.184 according to defined Chinese and US design specifications, respectively. Based on the wind data of 54 cities in China, 49 meteorological stations in the US, 3 stations in Singapore, the coefficients span intervals of (0.1, 0.35), (0.08, 0.20) and (0.06, 0.14), respectively. For hurricanes in the US, the coefficients range approximately from 0.3 to 0.4. This convenient technique is recommended as one alternative tool for coefficient of variation analyses in the future revisions of related codes. The sensitivities of coefficients of variation for 49 meteorological stations in the US are quantified and demonstrated. Some contradictions and incompatibilities can be clearly detected and illustrated by comparing the coefficients of variation obtained with different combinations of recurrence period wind data.
Key Words
extreme wind speed; coefficient of variation; recurrence coefficient; sensitivity analysis; design code
Address
Fuyou Xu and Zhe Zhang: School of Civil Engineering, Dalian University of Technology, Dalian 116024, China
Chunsheng Cai: Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge 70803, USA
Abstract
Wind tunnel tests are conducted to investigate the wind loads on vertical fixed-roof cylindrical tanks with a very low aspect ratio of 0.275, which is a typical ratio for practical tanks with a volume of 100,000 m3. Both the flat-roof tank and the dome-roof tank are investigated in present study. The first four moments of the measured wind pressure, including the mean and normalized deviation pressure, kurtosis and skewness of the pressure signal, are obtained to study the feature of the wind loads. It is shown that the wind loads are closely related to the behavior of flow around the structure. For either tank, the mean wind pressures on the cylinder are positive on the windward area and negative on the sides and the wake area, and the mean wind pressures on the whole roof are negative. The roof configurations have no considerable influence on the mean pressure distributions of cylindrical wall in general. Highly non-Gaussian feature is found in either tank. Conditional sampling technique, envelope method, and the proper orthogonal decomposition (POD) analysis are employed to investigate the characteristics of wind loads on the cylinder in more detail. It is shown that the patterns of wind pressure obtained from conditional sampling are similar to the mean pressure patterns.An instantaneous pressure coefficient can present a wide range from the maximum value to the minimum value. The quasi-steady assumption is not valid for structures considered in
this paper according to the POD analysis.
Key Words
wind load; fixed-roof tank; wind tunnel test; non-Gaussian feature; conditional sampling; POD analysis
Address
Yin Lin and Yang Zhao:Spatial Structures Research Center, Zhejiang University, Hangzhou 310058, China
Abstract
Since low-rise residential buildings are the most common and vulnerable structures in coastal areas, a reliable prediction of their performance under hurricanes is necessary. The present study focuses on developing a refined finite element model that is able to more rigorously represent the load distributions or redistributions when the building behaves as a unit or any portion is overloaded. A typical 5:12 sloped low-rise residential building is chosen as the prototype and analyzed under wind pressures measured in the wind tunnel. The structural connections, including the frame-to-frame connections and sheathing-to-frame connections, are modeled extensively to represent the critical structural details that secure the load paths for the entire building system as well as the boundary conditions provided to the building envelope. The nail withdrawal, the excessive displacement of sheathing, the nail head pull-through, the sheathing in-plane shear, and the nail load-slip are found to be responsible for the building envelope damage. The uses of the nail type with a high withdrawal capacity, a thicker sheathing panel, and an optimized nail edge distance are observed to efficiently enhance the building envelope performance based on the present numerical damage
predictions.
Key Words
low rise; buildings; hurricane; wind tunnel; finite element
Address
F. Pan, C.S. Cai and B. Kong:Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, Louisiana 70803, USA
W. Zhang:Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, Louisiana 70803, USA;
Department of Civil and Environmental Engineering, Univ. of Connecticut, Storrs, CT 06269-3037, USA
Abstract
Stochastic processes are used to represent phenomena in many diverse fields. Numerical simulation method is widely applied for the solution to stochastic problems of complex structures when alternative analytical methods are not applicable. In some practical applications the stochastic processes show non-Gaussian properties. When the stochastic processes deviate significantly from Gaussian, techniques for their accurate simulation must be available. The various existing simulation methods of non-Gaussian stochastic processes generally can only simulate super-Gaussian stochastic processes with the high-peak characteristics. And these methodologies are usually complicated and time consuming, not sufficiently intuitive. By revealing the inherent coupling effect of the phase and amplitude part of discrete Fourier representation of random time series on the non-Gaussian features (such as skewness and kurtosis) through theoretical analysis and simulation experiments, this paper presents a novel approach for the
simulation of non-Gaussian stochastic processes with the prescribed amplitude probability density function (PDF) and power spectral density (PSD) by amplitude modulation and phase reconstruction. As compared to previous spectral representation method using phase modulation to obtain a non-Gaussian amplitude distribution, this non-Gaussian phase reconstruction strategy is more straightforward and efficient, capable of simulating both super-Gaussian and sub-Gaussian stochastic processes. Another attractive feature of the method is that the whole process can be implemented efficiently using the Fast Fourier Transform. Cases studies demonstrate the efficiency and accuracy of the proposed algorithm.
Key Words
stochastic simulation; non-Gaussian; amplitude modulation; phase reconstruction
Address
Yu Jiang and Junyong Tao: Laboratory of Science and Technology on Integrated Logistics Support, College of Mechatronic Engineering & Automation, National University of Defense Technology, Changsha 410073, China
Dezhi Wang: Centre for Engineering Dynamics, University of Liverpool, Liverpool, UK
