• Carbon letters
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• v.21
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• pp.51-60
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• 2017

Isotropic pitch-based fibers produced from coal tar pitch with the melt-blowing method were carbonized at temperatures ranging from 800 to $1600^{\circ}C$ to investigate their crystalline structure and physical properties as a function of the carbonization temperature. The in-plane crystallite size ($L_a$) of the carbonized pitch fiber from X-ray diffraction increased monotonously by increasing the carbonization temperature resulting in a gradual increase in the electrical conductivity from 169 to 3800 S/cm. However, the variation in the $d_{002}$ spacing and stacking height of the crystallite ($L_c$) showed that the structural order perpendicular to the graphene planes got worse in carbonization temperatures from 800 to $1200^{\circ}C$ probably due to randomization through the process of gas evolution; however, structural ordering eventually occurred at around $1400^{\circ}C$. For the carbonized pitch powder without stabilization, structural ordering perpendicular to the graphene planes occurred at around $800-900^{\circ}C$ indicating that oxygen was inserted during the stabilization process. Additionally, the shear stress that occurred during the melt-blowing process might interfere with the crystallization of the CPF.

• Membrane and Water Treatment
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• v.1 no.3
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• pp.181-192
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• 2010

A linear quantitative structure-property relationship (QSPR) model is presented for the prediction of rejection in permeation through membrane. The model was produced by using the multiple linear regression (MLR) technique on the database consisting of retention data of 25 pesticides in 4 different membrane separation experiments. Among the 3224 different physicochemical, topological and structural descriptors that were considered as inputs to the model only 50 were selected using several criteria of elimination. The physical meaning of chosen descriptor is discussed in detail. The accuracy of the proposed MLR models is illustrated using the following evaluation techniques: leave-one-out cross validation procedure, leave-many-out cross validation procedure and Y-randomization.

• Structural Engineering and Mechanics
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• v.90 no.1
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• pp.41-49
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• 2024

In recent years, China's high-speed railway (HSR) line continues to expand into seismically active regions. Analyzing the features of earthquake rail irregularity is crucial in this situation. This study first established and experimentally validated a finite element (FE) model of bridge-track. The FE model was then combined with earthquake record database to generate the earthquake rail irregularity library. The sample library was used to construct a model of desired earthquake rail irregularity based on signal processing (SFT) and hypothesis principle. Finally, the effects of random pier height and random span number on desired irregularity were analyzed. Herein, an equivalent method of calculating earthquake rail irregularities for random structures was proposed. The results of this study show that the amplitude of desired irregularity is found to increase with increasing pier height. When calculating the desired irregularity of a structure with unequal pier heights, the structure can be regarded as that with equal pier heights (taking the largest pier height). For a structure with the span number large than 9, its desired irregularity can be considered equal to that of a 9-span structure. For the structures with both random pier heights and random span number, their desired irregularities are obtained by equivalent calculations for pier height and span number, respectively.

• Smart Structures and Systems
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• v.17 no.6
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• pp.957-980
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• 2016

Structural damage detection (SDD) is a challenging task in the field of structural health monitoring (SHM). As an exploring attempt to the SDD problem, a hybrid self-adaptive Firefly-Nelder-Mead (SA-FNM) algorithm is proposed for the SDD problem in this study. First of all, the basic principle of firefly algorithm (FA) is introduced. The Nelder-Mead (NM) algorithm is incorporated into FA for improving the local searching ability. A new strategy for exchanging the information in the firefly group is introduced into the SA-FNM for reducing the computation cost. A random walk strategy for the best firefly and a self-adaptive control strategy of three key parameters, such as light absorption, randomization parameter and critical distance, are proposed for preferably balancing the exploitation and exploration ability of the SA-FNM. The computing performance of the SA-FNM is evaluated and compared with the basic FA by three benchmark functions. Secondly, the SDD problem is mathematically converted into a constrained optimization problem, which is then hopefully solved by the SA-FNM algorithm. A multi-step method is proposed for finding the minimum fitness with a big probability. In order to assess the accuracy and the feasibility of the proposed method, a two-storey rigid frame structure without considering the finite element model (FEM) error and a steel beam with considering the model error are taken examples for numerical simulations. Finally, a series of experimental studies on damage detection of a steel beam with four damage patterns are performed in laboratory. The illustrated results show that the proposed method can accurately identify the structural damage. Some valuable conclusions are made and related issues are discussed as well.

• Analytical Science and Technology
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• v.28 no.3
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• pp.187-195
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• 2015

The heat of sublimation (HOS) is an essential parameter used to resolve environmental problems in the transfer of organic contaminants to the atmosphere and to assess the risk of toxic chemicals. The experimental measurement of the heat of sublimation is time-consuming, expensive, and complicated. In this study, quantitative structural property relationships (QSPR) were used to develop a simple and predictive model for measuring the heat of sublimation of organic compounds. The population-based forward selection method was applied to select an informative subset of descriptors of learning algorithms, such as by using multiple linear regression (MLR) and the support vector machine (SVM) method. Each individual model and consensus model was evaluated by internal validation using the bootstrap method and y-randomization. The predictions of the performance of the external test set were improved by considering their applicability to the domain. Based on the results of the MLR model, we showed that the heat of sublimation was related to dispersion, H-bond, electrostatic forces, and the dipole-dipole interaction between inter-molecules.