A new solution model for predicting ternary thermodynamic properties

A new symmetric model for predicting ternary thermodynamic properties from its three binary properties is presented. In comparison with other current models, this new model contains a stronger ternary interaction terms. It is expected that this model will be suitable for the systems, in which the ternary interaction can not be neglected. This model is also easy to compute as R function method is used.     

New local composition model for modeling of thermodynamic and transport properties of binary aqueous electrolyte solutions

A new local composition model, which is an NRF-modified-NRTL (NRF-mNRTL) model, is developed for the representation of the excess Gibbs energy of electrolyte solutions. In this model for excess Gibbs energy the sum of a long-range and a short-range term is used. The contribution of the long-range excess Gibbs energy is represented by the Pitzer-Debye-Hückel model. A new expression based on the local composition concept has been developed to account for the contribution of the short range excess Gibbs energy. The model is applied to correlate the mean ionic activity coefficients and osmotic coefficients of more than respectively 150 and 290 binary aqueous electrolyte solutions at 25 °C. The fitting quality of the new model has been favorably compared with the electrolyte NRTL, Wilson, modified NRTL, NRTL-NRF, NRF-Wilson, UNIQUAC-NRF, Pitzer and TCPC models. Viscosity values of the binary aqueous solution of electrolytes have also successfully been correlated with the proposed local composition model by considering the Eyring absolute rate theory. The validity of the proposed model is specially demonstrated for multivalent electrolyte binary solutions encompassing the entire range of composition.     

电解质溶液相平衡热力学模型研究进展

从电解质溶液理论、活度系数模型和状态方程出发，对用于电解质溶液相平衡关联、预测的成功模型及近年来应用研究的进展，以工程应用模型为重点，进行了综述。从长程静电作用和非静电作用对活度系数的贡献的角度，介绍了活度系数模型中，以Debye-Hueckel理论和MSA理论为基础的长程静电作用项的进展，介绍了Pitzer方程、E-NRTL、E-UNIQUAC以及化学贡献等活度系数模型的研究与应用进展；电解质状态方程则从3个方面总结了近年来的研究进展，即：以三次型方程、微扰理论为基础的电解质溶液状态方程和高温超临界条件下电解质溶液状态方程。     

A simple method for modelling and prediction of the specific heat and density of aqueous electrolyte solutions

A requirement for numerous applications of electrolyte solutions is the knowledge of the properties for as many as possible substances in a maximum range of concentration, although often with limited accuracy. Semiempirical methods, created through the knowledge of similarities in an analogue group of electrolytes offer an easy way to predict certain data for concentration ranges and electrolyte solutions not covered by measurements of these properties.

It could be shown that specific heat and density of aqueous electrolyte solutions can be described by means of a single parameter method, based on the scaling of the molality axis, thus generating a general reference function. Knowing this function and the affiliated scale factor, which gives the so called “effectiveness coefficient”, values of the respective property are available over the whole range of concentration. Also, a method is described to estimate the effectiveness coefficient for uninvestigated electrolytes.     

A pair-wise interaction model of the sigma phase I—thermodynamic properties

The composition dependence of the thermodynamic properties of binary sigma phases is examined on the basis of a simple pair-wise interaction model. The structure is considered in terms of its five sublattices, characterised by sites identified with Kasper-Frank surrounding co-ordinated polyhedra of 12, 12, 14, 14 and 15 respectively. It is assumed that the smallest (CN12) and the largest (CN15) sites are each preferentially occupied by different single alloy components while the intermediate size (CN14) sites are subject to random occupation. The numbers of substitutional defects on the ordered sub-lattices are defined by two independent disorder parameters and the variation of defect concentration and thermodynamic properties with composition is computed. Application of the model is illustrated by reference to thermodynamic and structural data for sigma phases in the V-Fe, V-Co, Cr-Fe, Cr-Co and Mo-Co alloy systems.     

Prediction of liquid–liquid phase diagrams of aqueous salt+PEG systems using a thermodynamic model

In this study a thermodynamic model for the phase behavior of aqueous salt+polymer solutions is developed. The model is based on the solution theory of Hill, which included scaling laws for the polymer molecular mass dependence and Pitzer–Debye–Hückel theory. This model was tested for systems composed of two different molecular mass of polyethylene glycols (PEG) and five different inorganic salts. All the model parameters were determined from independent measurements. The agreement between the experimental and predicted phase diagrams by this model is good.     

A new stabilized generator model for three phase sinewaves

A new three dimensional oscillator model for generating three phases of sinewaves is derived. The model is similar to the previous one (Ref.1) in enabling an undistorted stabilized generation of sinewaves. Its advantages in comparison to the previous model are due to its distinguished structural simplicity and its symmetry which should be of value both in a computer representation of systems and also in hardware realization.     

一种估算CO2和SO2在多元胺水溶液体系中溶解度的数学模型

通过离子反应式和亨利定律建立数学模型,在对模型进行适当简化的基础上再借助编程手段可以得到CO₂-SO₂在H₂O-MDEA-活化胺复杂多元溶液体系中溶解度的数值解。研究表明,在MDEA质量分率30%的水溶液中SO₂比CO₂优先溶解,溶液只有在基本上完全吸收SO₂之后才会吸收CO₂;而且其溶解度比较大,常温常压下1 mol的MDEA可吸收超过1.4mol的SO₂气体。在气体分压为（1～100）kPa范围内,SO₂的溶解度受压力参数的影响较大:而在此压力范围之外,温度参数则成为主要影响因素。在MDEA水溶液中添加MEA或DEA活化剂,随着活化剂质量分率的增加,SO₂的溶解度有较大程度的下降;若同时添加MEA-DEA2种活化剂,SO₂的溶解度会随着MEA质量分率的增加而减小,但减少的幅度并不大。     

A bayesian belief network based model for predicting software faults in early phase of software development process

It is always better to have an idea about the future situation of a present work. Prediction of software faults in the early phase of software development life cycle can facilitate to the software personnel to achieve their desired software product. Early prediction is of great importance for optimizing the development cost of a software project. The present study proposes a methodology based on Bayesian belief network, developed to predict total number of faults and to reach a target value of total number of faults during early development phase of software lifecycle. The model has been carried out using the information from similar or earlier version software projects, domain expert’s opinion and the software metrics. Interval type-2 fuzzy logic has been applied for obtaining the conditional probability values in the node probability tables of the belief network. The output pattern corresponding to the total number of faults has been identified by artificial neural network using the input pattern from similar or earlier project data. The proposed Bayesian framework facilitates software personnel to gain the required information about software metrics at early phase for achieving targeted number of software faults. The proposed model has been applied on twenty six software project data. Results have been validated by different statistical comparison criterion. The performance of the proposed approach has been compared with some existing early fault prediction models.     

A thermodynamic model for carbon trapping in lattice defects

A thermodynamic model in the framework of the CALPHAD method is proposed to describe the distribution of interstitial solute (carbon) atoms in bcc-iron during tempering of martensite. In the model, the crystal defects are introduced as a separate sublattice, which is a highly favored lattice position for carbon compared to undisturbed interstitial sites or precipitate sites in cementite. With the model, which is convenient for multicomponent, multiphase systems, the fraction of carbon atoms trapped by the defects during tempering can be calculated. It is demonstrated that, when martensite is heavily dislocated, the precipitation of cementite on tempering is greatly suppressed because the high dislocation density provides a sufficient number of stressed sites which can trap most of the carbon atoms. The calculations for an alloy steel show that, unlike cementite, the defect density and carbon trapping phenomenon influence the precipitation of stable carbides only marginally.     

A versatile model for predicting the performance of deflection-routing networks

Deflection routing can be used in networks whose stations have the same number of input and output links. Fixed-length packets arrive synchronously on the station's input links at the beginning output link that offers the shortest path to its destination. Since the number of packet buffers at each output link is finite, the simultaneous contention of two packets for the last buffer of the common output link must be resolved by “deflecting” one of the packets according to a specified criterion (e.g. at random, by destination proximity, or by packet age). Deflection routing can therefore be used with as few as one packet buffer per output link.

The potentially unbounded number of routes that a given packet can take makes analyzing the performance of such networks difficult. Using independence assumptions, we develop an efficient, high-fidelity performance model of deflection routing that allows us to estimated the mean end-to-end packet delay in a network that has any given two-connected topology, a single packet buffer at each output port, and an arbitrary traffic matrix.     

A thermodynamic model of amorphous silicates

A thermodynamic model is proposed to provide a physical picture of the glass transition in amorphous silicates. Below the glass transition temperature Tg the model considers the phase to be a random network of oxide compounds which relaxes to provide local structural fluctuationsas the temperature rises above Tg. Thermally activated development of these fluctuations accounts for gradual transition between the “solid”, as existing below Tg and the liquid state appearing above the melting point T_fus. The randomness of the structure and its fluctuation contribute both to the Gibbs energy as estimated near Tg. The model parameters of analytical expressions of Gibbs energy have been adjusted to fit the experimental information. The model has been developed for silicate glasses considered to a first approximation as ideal solution of single amorphous oxides. The relative enthalpy ΔH = H(T) − H(298K) has been calculated for a series of silicate glasses. The computational results agree quite satisfactory with experimental data. The constraints of the model are briefly discussed.     

A new design of evolutionary hybrid optimization of SVR model in predicting the blast-induced ground vibration

This study aims to identify the suitability of hybridizing the firefly algorithm (FA), genetic algorithm (GA), and particle swarm optimization (PSO) with two well-known data-driven models of support vector regression (SVR) and artificial neural network (ANN) to predict blast-induced ground vibration. Here, these combinations are abbreviated using FA–SVR, PSO–SVR, GA–SVR, FA–ANN, PSO–ANN, and GA–ANN models. In addition, a modified FA (MFA) combined with SVR model is also proposed in this study, namely, MFA–SVR. The feasibility of the proposed models is examined using a case study, located in Johor, Malaysia. Then, to provide an objective assessment of performances of the predictive models, their results were compared based on several well known and popular statistical criteria. According to the results, the MFA–SVR with the coefficient of determination (R²) of 0.984 and root mean square error (RMSE) of 0.614 was more accurate model to predict PPV than the PSO–SVR with R² = 0.977 and RMSE = 0.725, the FA–SVR with R² = 0.964 and RMSE = 0.923, the GA–SVR with R² = 0.957 and RMSE = 1.016, the GA–ANN with R² = 0.936 and RMSE = 1.252, the FA–ANN with R² = 0.925 and RMSE = 1.368, and the PSO–ANN with R² = 0.924 and RMSE = 1.366. Consequently, the MFA–SVR model can be sufficiently employed in estimating the ground vibration, and has the capacity to generalize.

     

A new phase extraction algorithm for phase profilometry

This paper describes a new phase extraction algorithm for 3D optical profilometry based on the projection of a periodic light pattern and phase measurement (phase profilometry). The algorithm uses a square wave to demodulate phase and moving averages and comb-shaped filters to extract the phase information from low frequency. The proposed algorithm is compared with the two major profilometry techniques, namely Fourier domain profilometry and signal domain profilometry based on FIR low-pass filtering. Comparison is focused on adaptiveness to changes of the pattern frequency, ability to deal with nonuniform surfaces and computational complexity. Adaptiveness analysis is carried out by means of simulations. The issue of nonuniform surfaces is discussed on the basis of experimental results obtained from application of phase profilometry to on-line 3D printed circuit board inspection. With regard to complexity, theoretical estimates are verified by means of actual computation time measurements. Received: 30 November 1996 / Accepted: 6 June 1997     

A stress-strength interference model for predicting CTD probabilities

A model for predicting the incidence rate of carpal tunnel syndrome (CTS) for a given job, was developed using known biomechanical data, mechanical properties of human tendons and reliability engineering techniques to simplify the problem. In addition, time-dependent stress-strength interference theory was used to quantify the stress on the tendons during a job cycle, based on wrist position and grip strength and to estimate the tendon failure rate (or CTS incidence) for a given job. Higher failure probabilities were predicted for greater wrist deviations, for higher grasp forces, for females as compared to males, for wrist extension as compared to wrist flexion, and for two-fingered pinches as compared to four-fingered grasps. The predictions closely matched previously reported CTS incidence rates for a poultry thigh boning task.     

A probabilistic model for predicting software development effort

Recently, Bayesian probabilistic models have been used for predicting software development effort. One of the reasons for the interest in the use of Bayesian probabilistic models, when compared to traditional point forecast estimation models, is that Bayesian models provide tools for risk estimation and allow decision-makers to combine historical data with subjective expert estimates. In this paper, we use a Bayesian network model and illustrate how a belief updating procedure can be used to incorporate decision-making risks. We develop a causal model from the literature and, using a data set of 33 real-world software projects, we illustrate how decision-making risks can be incorporated in the Bayesian networks. We compare the predictive performance of the Bayesian model with popular nonparametric neural-network and regression tree forecasting models and show that the Bayesian model is a competitive model for forecasting software development effort.     

气相和水相中氯代酚与单线态氧反应机理的研究

用密度泛函理论分别研究气相和水相中的6种氯代酚(2-CP,3-CP,4-CP,2,4-DCP,2,4,6-TCP和PCP)与单线态氧的反应机理。在B3LYP/6-31+G(d,p)水平上,将可能路径上的反应复合物、过渡态和产物分别全优化几何结构和计算频率,通过内禀反应坐标(IRC)的方法验证反应路径,并在B3LYP/6-311+(2df,p)水平上计算单点能。采用极化统一模型(PCM)法探索溶剂效应。结果,不论气相还是水相,1,3加成生成1个烯丙基氢过氧化物和1,4加成生成1个酮类氢过氧化物,在热力学上均是可行的,但是在动力学上前者的能垒比后者更低,是优先路径。热力学更支持在水相中反应,而动力学则相反。能垒随氯代数量的增多而升高。