Evaluation of Stiffened End-Plate Moment Connection through Optimized Artificial Neural Network

This study involves the development of an analytical model for understanding the behavior of the extended, stiffened end-plate moment connections with eight high strength bolts. Modeling of the connection as an assemblage of finite elements (FE) used for load deformation analysis, with material, and contact nonlinearities are developed. Results from the FE mathematical model are verified with results from the ANSYS computer program as well as with the test results. Sensitivity and feasibility studies are carried out. Significant geometry and force related variables are introduced;and by varying the geometric variables of the connections within a practical range, a matrix of test cases is obtained. Maximum end-plate separation, maximum bending stresses in the end-plate, and the forces from the connection bolts for these test cases are obtained. From the FE analysis, a database is produced to collect results for the artificial neural network analysis. Finally, salient features of the optimized Artificial Neural Network (ANN) via Genetic Algorithm (GA) analysis are introduced and implemented with the aim of predicting the overall behavior of the connection.

Droughts and the Impacts of Dry Spells in North of Iraq

Different sets of dry spell length such as complete series, monthlymaximum, seasonal maximum, and annual maximum are applied andmodeled with different probability distribution functions (such as GumbelMax, generalized extreme value, Log-Logistic, generalized logistic, inverseGaussian, Log-Pearson 3, generalized Pareto) to recognize in whichduration, dry spells cause drought. The drought situation and temporalanalysis in the North of Iraq region were done using the SPI index andby software of DrinC at a time scale of 3.6 and 12 months. Because ofapplicability, availability of data and the aim of the study, SPI is selectedto analyze the dry spells in this study. Based on the maximum length ofthe available statistical period, the statistics for the years 1980 to 2019were used from nine meteorological stations for analysis. The results of thestudy showed the severity of drought during the study period which relatedto dry spells. The results of this research confirm the variation of droughtoccurrence with varying degrees in different time and different dry spellscondition in Iraq.

Hybrid global gridded snow products and conceptual simulations of distributed snow budget:evaluation of different scenarios in a mountainous watershed

Considering snowmelt in mountainous areas as the important source of streamflow,the snow accumulation/melting processes are vital for accurate simulation of the hydrological regimes.The lack of snow-related data and its uncertainties/conceptual ambiguity in snowpack modeling are the different challenges of developing hydroclimatological models.To tackle these challenges,Global Gridded Snow Products(GGSPs)are introduced,which effectively simplify the identification of the spatial characteristics of snow hydrological variables.This research aims to investigate the performance of multisource GGSPs using multi-stage calibration strategies in hydrological modeling.The used GGSPs were Snow-Covered Area(SCA)and Snow Water Equivalent(SWE),implemented individually or jointly to calibrate an appropriate water balance model.The study area was a mountainous watershed located in Western Iran with a considerable contribution of snowmelt to the generated streamflow.The results showed that using GGSPs as complementary information in the calibration process,besides streamflow time series,could improve the modeling accuracy compared to the conventional calibration,which is only based on streamflow data.The SCA with NSE,KGE,and RMSE values varying within the ranges of 0.47–0.57,0.54–0.65,and 4–6.88,respectively,outperformed the SWE with the corresponding metrics of 0.36–0.59,0.47–0.60,and 5.22–7.46,respectively,in simulating the total streamflow of the watershed.In addition to the superiority of the SCA over SWE,the twostage calibration strategy reduced the number of optimized parameters in each stage and the dependency of internal processes on the streamflow and improved the accuracy of the results compared with the conventional calibration strategy.On the other hand,the consistent contribution of snowmelt to the total generated streamflow(ranging from 0.9 to 1.47)and the ratio of snow melting to snowfall(ranging from 0.925 to 1.041)in different calibration strategies and models resulted in a reliable simulation of the model.

Parallel boron nitride nanoribbons and etch tracks formed through catalytic etching

One-dimensional （1D） catalytic etching was investigated in few-layer hexagonal boron nitride （hBN） films. Etching of hBN was shown to share a number of similarities with that of graphitic films. As in graphitic films, etch tracks in hBN commenced at film edges and occurred predominantly along certain crystal directions of its lattice, though it was shown that the tracks were generally narrower than those of few-layer graphene under similar processing conditions. It was also shown that catalytic hydrogenation can occur completely through a few-layer hBN film, demonstrating that this process can be used in the formation of isolated low-dimensional nanoscale structures from other layered 2D materials beyond graphene. This ability for thin hBN films to be etched completely through allowed for a crystalline substrate to guide the etching process, which was demonstrated with the successful etch track formation of few-layer hBN on single-crystalline sapphire substrates. The substrate-guided etching resulted in parallel few-layer hBN nanoribbons having an average width of 32 nm and spacing of 13 nm.