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Steel Frame Optimal Design Using MHBMO Algorithm
Seied Hosein Afzali,Abbas Darabi,Majid Niazkar 한국강구조학회 2016 International Journal of Steel Structures Vol.16 No.2
Various deterministic and stochastic algorithms have been used as optimization tools in different engineering problems over the last decade. In this regard, the Modified Honey Bee Mating Optimization (MHBMO) algorithm may be considered as a typical swarm-based approach for optimizing numerous problems in engineering fields. In this paper, a design procedure based on the MHBMO technique was developed for discrete optimization of frames consisting W-shapes. The objective function in this research is to obtain the minimum weight of frames subjected to both strength and displacement requirements imposed by the American Institute for Steel Construction (AISC) and Load Resistance Factor Design (LRFD). Several frame examples from the literature were examined to verify not only the suitability of the design procedure but also the robustness of the MHBMO algorithm for frame structure design. The optimum results obtained by the MHBMO algorithm performs the best in comparison with other available techniques in the literature for all three steel frames. In conclusion, the results shows that the MHBMO algorithm is a powerful and applicable optimization method for design of frames consisting W-shapes.
New Nonlinear Variable-parameter Muskingum Models
Majid Niazkar,Seied Hosein Afzali 대한토목학회 2017 KSCE Journal of Civil Engineering Vol.21 No.7
The Muskingum model has been widely utilized for flood routing by water resources engineers for decades. Since the relation between channel storage and weighted summation of inflow and outflow seems to be nonlinear, a constant exponent parameter is used to account for this nonlinearity. On the other hand, the nonlinear Muskingum models with constant parameters cannot address variation of Muskingum parameters during flood period. In this paper, fourteen new Muskingum models with variable parameters are proposed. In these models, the routing period is divided into two or three sub-periods and the proposed versions of the Muskingum models can possess parameters with different values in these sub-periods. This capability enhances the Muskingum flood routing approach to better capture the reach characteristics and subsequently improve the routing results. The flood routing results for the selected data set demonstrate that three variable-parameter model reduces the SSQ value more than 89% comparing with the best three constant-parameter Muskingum model in the literature. Additionally, it was concluded that considering x-parameter as a variable parameter during a flood period affects the parameter estimation more than imposing the K- and m-parameters to be variable.
Development of a New Flow-dependent Scheme for Calculating Grain and Form Roughness Coefficients
Majid Niazkar,Nasser Talebbeydokhti,Seied Hosein Afzali 대한토목학회 2019 KSCE JOURNAL OF CIVIL ENGINEERING Vol.23 No.5
Estimating channel roughness is crucial for whatever engineering plans that have been in mind for any reach under consideration. Not only is resistance coefficient not a measurable quantity, but also various factors affecting on its value make its estimation a challenge. Despite of numerous methods available for roughness estimation, the complexity of some of available iterative schemes particularly with no mechanism for modifying initial guess in each iteration restrain numerical modelers to apply merely outdated resistance equations in practice. In order to improve the estimation of hydraulic resistance, a new straightforward flow-dependent scheme, which is capable of estimating Manning’s coefficient due to grain and form roughness, is introduced. A large data is utilized to calibrate and testify the new scheme. The results of comparing the new scheme with that of different models available in the literature show that it achieves the best estimation results and yields to more than 0.87 and 0.67 for R2, 0.15 and 0.17 for mean absolute relative error for estimating grain and form Manning’s coefficients, respectively. This comparison demonstrates that the results achieved by the new scheme are acceptably accurate in favor of roughness estimation.