Scientia Iranica
Volume:18 Issue: 5, 2011

The disaggregation of coarser Precipitation data will help to adjust the deficit of unavailability of data in non-recording gauge stations. The Artificial Neural Network (ANN) facilitates to adjust the rainfall time steps into desired small scales. At first, the Geostatistical method of co-kriging was used for mapping purposes to find the missing duration and depth of rainfall of some incomplete data stations in Sydney Australia. Then, since there was no information about the breakpoint data in non-recording target central station 7261, a process was performed to disaggregate the data of recording gauge station sited besides this non-recording one. Definitely, a similar station was delineated, firstly Thiessen polygon was used instead of station 7261 and then the results of applying two different ANN models (a feed forward back propagation multilayer perceptron (MLP) and a Radial Basis Function (RBF) network) were evaluated to disaggregate the data of this station, and the best disaggregation model was introduced.

The significance of the Soil Water Characteristic Curve (SWCC) or soil retention curve in understanding the unsaturated soils behavior such as shear strength, volume change and permeability has resulted in many attempts for its prediction. In this regard, the authors had previously developed two models, namely. Genetic-Based Neural Network (GBNN) and Genetic Programming (GP). These two models have identical set of input parameters. These parameters include void ratio, initial water content, clay fraction, silt content and logarithm of suction normalized with respect to air pressure. In this paper, performance of these two models is further investigated using additional test data. For this purpose, soil samples from 14 different locations in Shiraz city in the Fars province of Iran are tested and their SWCCs are established, using a pressure plate apparatus. Next, the results are used to demonstrate the suitability of the previously proposed models and to evaluate relative importance of the input parameters. Assessment of the results indicates that predictions from GBNN model have relatively higher accuracy as compared to GP model.

Urmiyeh Lake is the largest super salt water situated in the north-west of Iran. A causeway embankment has been constructed in the narrowest part of the lake from both sides about 13.5 km, in order to connect two provincial capital cities of Tabriz and Urmiyeh of eastern and western Azerbaijan provinces to Europe through Turkey, while a 1280 m opening in between linked up by a bridge. Based on soil classification methods, utilizing CPTu data and soil sampling, the lake sediments consist of 150 m of soft and very sensitive clay. In order to evaluate the bearing capacity of driven piles of the bridge, eight long steel piles with diameters of 813 and 66 m and lengths of 75 m have been instrumented and monitored based on static and dynamic load testing program. Piezocone (CPTu) results are also available from adjacent pile locations. Results of pile capacity calculation based on direct CPT and CPTu methods demonstrate that reasonable accuracy can be achieved in reference to dynamic testing. Therefore, combination of CPTu data with dynamic testing results can be considered by engineers for predicting bearing capacity of piles in offshore and bridge structures, where the static pile load testing is difficult, time consuming and expensive in marine environment.

The main aim of this paper is to propose an efficient soft computing based methodology to achieve optimal shape design of arch dams subjected to natural frequency constraints. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) as two popular metaheuristics are employed to perform optimization task. As in the present paper fluid–structure interaction is considered, computing the natural frequencies by Finite Element Analysis (FEA) during the optimization process is time consuming. In order to reduce the computational burden, Back Propagation (BP) and Radial Basis Function (RBF) neural networks are used to predict the arch dam natural frequencies. The numerical results show that PSO incorporating BP provides the best results.

In this study, the effect of temperature on compressive strength, spalling and mass loss of High Strength Concretes (HSCs) by MPa is discussed. Average compressive strength of the HSCs was from 65 to 93 MPa, which was optimized by Taguchi’s method as a powerful tool for optimizing the performance characteristic of a product/process. This paper presents results of an experimental program on the effects of elevated temperature exposure on the mechanical properties and potential for explosive spalling of HSCs. Effects of four parameters; water to cement ratio (w/c), sand ratio, silica fume ratio and amount of silica fume (sf) addition are considered in tests. Mechanical properties of HSCs were measured by heating 150×300 mm cylinders at 20∘ C/min to temperatures of up to 800∘ C. The tests include sixteen mixtures; twelve contain sf and four are without sf that are selected by Taguchi’s method. The paper presents results of measurement that indicate the effect of sf, cement, fine aggregate, coarse aggregate and water on residual strength, spalling and mass loss of the HSCs. The presence of silica fume had no statistically significant effect on the relative compressive strength while it had an overall statistically significant effect on increasing spalling. The type of aggregate had a significant influence on the thermal properties of HSCs at elevated temperatures. In most cases, by increasing sand ratio, residual compressive strength increased while this trend is inversed for coarse aggregate.

The integration of Transportation Demand Management (TDM) policies is a challenging issue in urban policy studies. Interactions between policies that are not addressed broadly in the integration context play a main role in the outcome of TDM policy packages. However, different individual daily trip purposes, city development, variations in land use and different levels of decision making about transportation often lead to the implementation of more than one TDM policy at a time. This study examined the role of TDM policy interactions on the macro and micro levels. On the macro level, this study showed that the introduction of two-way interactions in the model could improve the goodness of fit by 15%. On the micro level, we developed the concept of synergy for all levels of two policies. The results show that generally synergy is a function of policies’ levels, and the integration of increasing parking cost with either cordon pricing or increasing fuel cost has greater synergy at higher levels of the two policies. In contrast, the integration of other two policies (i.e. cordon pricing and increasing fuel cost) had no synergy in the examined ranges.

The calculation of null basis for equilibrium matrix is the main part of the finite elements analysis via force method. For an optimal analysis, the selected null basis matrices should be sparse and banded corresponding to sparse, banded and well-conditioned flexibility matrices. There are many algorithms for the formation of null basis among which the algebraic methods benefit from the generality. However, the efficiency of these methods is highly dependent on the size of problems, and their computational times are very high for such problems. In this paper, a graph-theoretical method is presented for the formation of sparse, banded and highly accurate null basis matrices for finite element models with triangular and rectangular bending elements. These bases are generated much faster than those obtained by the algebraic methods. The efficiency of the present method is illustrated through some example.

The major guidance documents for seismic assessment of existing buildings are ASCE 41-06 in US, Eurocode 8 Part 3 in Europe, and NZSEE recommendations in New Zealand. All of these guidelines have proposed using nonlinear static analysis as a tool for seismic assessment of buildings. In New Zealand recommendations there is a parameter %NBS which means percentage of new building standard, the building with %NBS = 100 is a building that satisfies standards of a new building. NZSEE recommendations have proposed force based, displacement based and consolidated force/displacement based methods for seismic assessment of existing buildings. Consolidated force/displacement based method is a combination of force based and displacement based methods. Displacement based method has a direct emphasis on estimating the ultimate displacement capacity of the structure. In this paper, 5- and 10-story steel moment resisting frames have been designed with %NBS approximately equal to 100, calculated by displacement based and consolidated force/displacement based methods. In these methods, the nonlinear static analysis is used for estimating strength and deformation capacity of steel moment resisting frames. Nonlinear dynamic analysis procedure is applied to assess the seismic performance of these structures according to ASCE 41-06.

A robust and effective flux-vector splitting method is utilized to simulate dam-break problems based on a finite-volume method on a Cartesian grid. The method combines the effectiveness of Flux-Difference Splitting (FDS) methods and the robustness of Flux-Vector Splitting (FVS) methods to precisely estimate the numerical flux at each cell interface. A nonlinear second-order term, which is evaluated in local characteristics field, is added to decomposed fluxes to enhance the accuracy of the scheme. Several classical dam-break problems including 1D dam-break problem, hypothetical 2D dam-break problem with non-symmetric breach, circular dam-break problem and 2D dam-break problem with a baffle in the floodplain have been tested by the model. The results show very satisfactory agreement with analytical solutions and other numerical methods. The paper shows the accuracy, effectiveness and robustness of the hybrid FVS and FDS methods, both over wet and dry bed.