One of our other favorites is the new interface in ANSYS Fluent, just making things faster and easier. More capability in the ANSYS Customization Toolkit (ACT) also allows users to get 10x or better improvements in productivity. And for those who work with electronics, a host of ECAD geometry import tools are making that whole process an order of magnitude faster.
Power: the magnitude of the PSD is the mean-square value of the analyzed signal. It does not refer to the physical quantity of power, such as watts or horsepower. However, power is proportional to the mean-square value of some quantity, such as the square of current or voltage in an electrical circuit. The mean-square value of any quantity is the power of that quantity.
In Figure 2.5, the frequency spectrum of a car vibration signal is computed with three different frequency bandwidths. The squared magnitudes of the spectra are proportional to the frequency bandwidth. To overcome this variation, the PSD divides the squared magnitude by the frequency bandwidth to provide a consistent value independent of the bandwidth.
There are cases where individuals confuse the bandwidth-dependent frequency spectrum and the PSD. Make sure to determine if the bandwidth normalized the magnitude, which would be a feature of the PSD calculation.
Wind direction also has a significant effect on pressure magnitude. The wind load on a structure is proportional to the square of the wind speed (Sarkar et al. 2014). And for correct assessment of wind power potential both wind speed and wind direction are equally important and for wind direction analysis, finite mixture of two von Mises distributions has proved to be a suitable candidate for Indian climatology (Gugliani et al. 2017; Gugliani et al. 2018b). Extreme Value Analysis (EVA) of hourly mean wind speed data approach is the most suitable for the region of varied wind climate (Gugliani et al. 2018a).
A lot of work has already been done on CFD simulation of buildings. Computational Fluid Dynamics study is helpful in determining magnitude of pressure coefficients, velocity streamline, velocity vector, numbers of correlated constraint variables, etc. through the model surface (Verma et al. 2015a). CFD simulations are helpful in the investigation of boundary layer separation and wake formation (Verma et al. 2015b). As an alternative to wind tunnel testing, CFD simulation is used nowadays to determine the effects of wind on structures. A fair number of studies have been carried out through the CFD simulation instead of wind tunnel testing and the results obtained from CFD simulations are adequately consistent with experimental results (Bhattacharyya et al. 2014). In experimental and numerical investigations of flat, conical and hemispherical roof models, the hemispherical roof was found to have the most critical pressure field and a good agreement was seen between experimental and numerical outcomes and same was found for the design of API pump (Ayremlouzadeh and Ghafouri 2016; Sajjadi and Sarkardeh 2016; Ozmen and Aksu 2017). Also, CFD simulations have been used to test different aerodynamic mitigation techniques (Aly and Bresowar 2016). In a study of scour process about single and compound bridge piers, CFD results were found under-predicted and over-predicted when two different CFD codes have been used (Alemi and Maia 2016).
The velocity profile of the vertical locations near the building model on the windward side is seen to decrease gradually compared to the lines near the inlet location as shown in Fig. 5. The velocity profile represented in white is at the inlet location and the yellow is near the building model. At the building height, the velocity magnitude is 15% lower than the inlet velocity. As the height from bottom increases, velocity magnitude is similar with other velocity profiles.
From Fig. 7, where area weighted pressure coefficients have been represented graphically, it can be noticed that magnitude of negative pressure or suction is continuously changing with wind direction. From all the graphs, it is clear that when a face will be perpendicular to the wind direction, there will be higher pressure coefficients as compared to the pressure coefficients on parallel faces.
Several deductive investigations indicate the probability of better performance for the influencing factors including void ratio, dimensional accuracy and drainage ability of the new octagonal structure. However, the main scope of the paper is to compare the performance of models during burnout stage (the magnitudes of exerted stresses and strains on ceramic shell). Therefore, a more analytical and practical approach will be a good future research for other mentioned factors.
In this study, harmonic response analysis of isotropic elliptically curved thin plate structures has been conducted. The structure has been excited by a harmonic load, whose maximum magnitude is 100 N. The structure has been considered under fixed from both straight edges boundary conditions. The effect of the elliptical geometry on the harmonic response of the structure in terms of the critical frequency region, phase angle, stress, and displacement has been examined. For this purpose, the vertex to co-vertex ratio has been variated from 3 to 4 by 0.1 intervals. All analyses have been performed via ANSYS Workbench by employing the Mode Superposition Method. The results indicated that the elliptical geometry has a significant impact on the harmonic response of elliptically curved thin plate structures. 2b1af7f3a8