New design equations for assessment of load carrying capacity of castellated steel beams: a machine learning approach

This paper presents an innovative machine learning approach for the formulation of load carrying capacity of castellated steel beams (CSB). New design equations were developed to predict the load carrying capacity of CSB using linear genetic programming (LGP), and an integrated search algorithm of genetic programming and simulated annealing, called GSA. The load capacity was formulated in terms of the geometrical and mechanical properties of the castellated beams. An extensive trial study was carried out to select the most relevant input variables for the LGP and GSA models. A comprehensive database was gathered from the literature to develop the models. The generalization capabilities of the models were verified via several criteria. The sensitivity of the failure load of CSB to the influencing variables was examined and discussed. The employed machine learning systems were found to be effective methods for evaluating the failure load of CSB. The prediction performance of the optimal LGP model was found to be better than that of the GSA model.     

The Investigation of the Weak Link Behavior in the Niobium (Nb) Doped Bi1.6Pb0.4Sr2Ca2Cu3O δ Superconductor

The Nb substitution effect on structural, DC electrical resistivity, and AC susceptibility properties of polycrystalline Bi_1.6Pb_0.4Sr₂Ca₂Cu₃O _δ samples is investigated. The behavior of weak link and intergranular coupling in the substituted samples is discussed. While the Bi-2223 phase concentration increases in the X-ray diffraction (XRD) pattern, the intragrain transition temperature remains nearly unchanged in the substituted samples. The intergrain transition temperature is changed with Nb substitution.     

Prediction of the effect of artificial aging heat treatment on the yield strength of an open-cell aluminum foam

The effect of artificial aging on the compression yield strength of an open-cell AA6101 foam is studied using both experimental and modeling approaches. Isothermal calorimetry is used to analyze the precipitation kinetics of the foam. The modeling work combines the established approaches for predicting the yield strength of open-cell metallic foams as a function of the relative density and normalized strength, as well as the age hardening behavior of AA6101 alloy. The foam yield strength is related to the evolution of precipitate content during aging and is modeled for artificial aging at 180 and 220 °C. It is shown that the model predictions match very well with the experimentally determined yield strength values. The overall results suggest that the presented analytical and modeling approaches can effectively be used to predict the precipitation hardening behavior and/or optimize processing and properties of AA6101 foams.     

Eggshell nano-particle potential for methyl violet and mercury ion removal: Surface study and field application

A nano-scale sorbent was produced from eggshell wastes for sorption of Hg(II) and methyl violet (MV) from aqueous solutions and real wastewaters. The properties of the nano-particles were fully determined using SEM, DLS, FTIR, XRD, BET, TGA, AFM, EDAX, mapping, and TEM analyses. The adsorbent structure mainly contained carbonate and silica. The effects of influential parameters including temperature, contact time, initial contaminants concentration, sorbent dose, and initial pH on the removal efficiency were investigated. The maximum sorption efficiency of Hg(II) and MV occurred at pH of 6 and 9 and temperatures of 25 °C and 55 °C, respectively. Freundlich model could be interpreted the equilibrium data of the sorption process of both contaminants. The maximum sorption capacity of Hg(II) and MV using eggshell nano-particles was obtained as 116.27 mg/g and 123.45 mg/g, respectively. The dynamic behavior of the process was studied using two kinetic models. The sorption system performance was also examined and t_1/2 were determined as 4.34 min for Hg(II) and 4.97 min for MV. The sorption process of Hg(II) and MV was exothermic and endothermic, respectively. Effective sorption after seven cycles and successful treatment of landfill leachate and textile wastewater with eggshell nano-particles confirms its adequacy.     

The Minimum Average Code for Finite Memoryless Monotone Sources

The problem of selecting a code for finite monotone sources with N symbols is considered. The selection criterion is based on minimizing the average redundancy (called Minave criterion) instead of its maximum (i.e., Minimax criterion). The average probability distribution P^Nmacr, whose associated Huffman code has the minimum average redundancy, is derived. The entropy of the average distribution (i.e., H(P^Nmacr)) and the average entropy of the monotone distributions (i.e., H(P^Nmacr)) are studied. It is shown that both logN-H(P^Nmacr) and logN-H(P^Nmacr) are asymptotically equal to a constant (sime0.61). Therefore, there is only a negligible penalty (at most 1.61 bits/symbol) in using a simple fixed-length code with respect to the optimal code. An efficient near-optimal encoding technique is also proposed. The consequences of the two approaches, i.e., Minave and Minimax, are compared in terms of their associated distributions and associated codes. In order to evaluate the average performance of the Minimax code, we prove that the informational divergence of the average distribution and Minimax distribution asymptotically grows as -2.275+loglogN     

Effects of vibration in desert area caused by moving trains

Railway Engineering Science - The ballast layer, filled with fine particles like blown sand, is one of the important problems of ballasted railway tracks in desert areas. Blown sand, as a...     

Deformation-mechanism map for Ti-6wt% Al alloy

A micro-computer program was developed to plot deformation mechanism maps for metals and substitutional solid solutions such as Ti-6 wt% Al. The package written in Turbo Basic is versatile and can be run to print out maps, using the related stored data files. In modelling the maps, the rate equations governing different deformation mechanisms were employed to find the dominant mechanisms and strain rate contours. In particular, the map for Ti-6 wt% Al was generated and it was found that the power law creep dominated over a wider range of stresses and temperatures than that of pure titanium. It is concluded that the strengthening effect of aluminium has shifted the iso-strain rate contours to higher stresses and temperatures.     

On gamma-ray spectrometry pulses real time digital shaping and processing

In gamma-ray medical imaging and nuclear spectroscopy instruments, deployment of high speed reconfigurable field programmable gate arrays circuits make it possible to implement signal processing algorithms for pulse shaping, pile up detection and correction, and determination of pulse amplitude and its time of detection in real time. Based on this idea, we have developed a digital pulse processing board for use in a gamma ray spectroscopy and later in positron emission tomography. The proposed digital pulse-processing core relies on digital trapezoidal or triangular pulse shaping, an automatic baseline correction and pileup rejection methods, all of which are implemented in FPGA to permit on-line event processing. Experimental results show that because of its pulse shaping method, system throughput and energy resolution significantly outperforms analog pulse processing systems.