Calculation on the solid solution forming enthalpies of Re-Mo-Ti gradient alloy in thermodynamics

The idea about preparation of Re-Mo-Ti alloy is put forward because of applications of Re and Mo-Re alloys in aerospace. Basing on the thermodynamics theory, the feasibility of developing a new high temperature alloy Re-Mo-Ti is investigated. The solid solution forming enthalpies of binary alloys Re-Ti, Mo-Ti and Mo-Re are calculated with the Miedema thermodynamics theory. The Miedema theory of binary alloy can be used in ternary alloy through Kohler model or Toop model. The calculated results show that the forming enthalpies of binary alloys Re-Ti, Ti-Mo and Re-Mo are negative, which indicates that binary alloys Re-Ti, Ti-Mo and Re-Mo can form solid solution in wider component area. The forming enthalpies of Re-Mo-Ti ternary alloy are still negative and smaller than those of binary alloys Re-Ti, Ti-Mo or Re-Mo, which indicates it is possible to form large solid solution graph area among ternary alloys of Ti, Mo, Re elements. It is feasible to develop a new high temperature material in thermodynamics, in this material Re-Mo-Ti solid solution as base phase, and the Ti₅Re₂₄ intermetallic compounds or interphase ω (Ti₄Mo₃) as strengthening phase.     

The role of socio-economic,built environment and psychological factors in parental mode choice for their children in an Iranian setting

This research investigated the role of parental psychological and socio-economic factors as well as built environment for the choice of their children’s (primary school pupils, aged 7–9 years) travel mode to school in Rasht, Iran. A total of 1078 questionnaires were distributed (return rate of 80 percent) among pupils in nine primary schools in January 2014. A mixed logit (ML) model was employed due to its ability to test heterogeneity among parents and also to determine its possible sources. Results of random coefficient ML modelling showed that several psychological, socio-economic and built environment characteristics were significant factors in parental mode choice. Only walking time perception to school had a significant random normal distribution coefficient and no other psychological and socio-economic variable had a random effect. Further investigation by random coefficient analysis showed that the possible source of household preference heterogeneity could be to own two or more cars. Regarding psychological variables, strong parental worry about their children walking alone to school had a negative impact on allowing them to walk to school. Parents who evaluated poor contextual and design preconditions for walking tended to choose school service more than private car and walking. Parents with stronger environmental personal norms were more willing to allow their children to walk. The findings suggest that infrastructural measures, such as sidewalk facilities, neighborhood security and safety, encourage parents to allow children to walk to school. Information campaigns targeting environmental norms may increase walking among pupils in an Iranian setting.     

A behavioral choice model of the use of car-sharing and ride-sourcing services

There are a number of disruptive mobility services that are increasingly finding their way into the marketplace. Two key examples of such services are car-sharing services and ride-sourcing services. In an effort to better understand the influence of various exogenous socio-economic and demographic variables on the frequency of use of ride-sourcing and car-sharing services, this paper presents a bivariate ordered probit model estimated on a survey data set derived from the 2014–2015 Puget Sound Regional Travel Study. Model estimation results show that users of these services tend to be young, well-educated, higher-income, working individuals residing in higher-density areas. There are significant interaction effects reflecting the influence of children and the built environment on disruptive mobility service usage. The model developed in this paper provides key insights into factors affecting market penetration of these services, and can be integrated in larger travel forecasting model systems to better predict the adoption and use of mobility-on-demand services.     

Proficiency improvement method in maritime education

The research conducted by the International Maritime Organization (IMO) shows that maritime education not always reaches its pre-established goal. One of the aspects in maritime education development process with the aim to prepare ship officers and other specialists is a thorough selection of the learning content according to real life necessities. Structuring the learning content of the subjects, both significant to profession and conforming to the requirements set by professional bodies, is one of the key issues addressed by curriculum developers. The aim of this research is to create a model for the curriculum development in scientific subjects for outcome-based maritime education. The main criterion which determines the significance/contribution level of the included topic in the curriculum is the anticipated learning outcome increasing the level of proficiency in students. Thus, the present research unveils the necessary steps for the evaluation of the proposed topics in the context of teaching/learning and gives grounds for their selection and the arrangement of topics in a logical order for further implementation in teaching/learning process. The present research is illustrated by a case study concerning the development of teaching/learning content for chemistry curriculum as a study subject in the secondary vocational maritime education programme.     

Analysis of ship drifting in a narrow channel using Automatic Identification System (AIS) data

With maritime transportation has played an important role in global economy development, ship traffic has become more congested. Therefore, ships navigate under risk conditions, and thus maritime accidents have occurred frequently. Especially, ship passing through a narrow channel is even more dangerous. Because, the ships are easy to be affected by external forces such as wind and currents that can cause ship drifts. Many latent risks are present during navigation. In order for the development of a sensible and appropriate traffic model for the safety and efficiency ship navigation, this study has focused on the actual ship behavior to understand the ship drift in the Kurushima Strait, Japan, which is one of the most dangerous routes in Japan. The analysis of ship behavior was carried out using the Automatic Identification System (AIS) data. As a result, the ships drift was understood in detail, and the latent risk was unveiled when ships pass through the narrow route. Moreover, the risk areas were obtained and visualized by the ship drift behavior analysis. The obtained results can be applied to ensure safe navigation and the development of an eco-friendly and economy efficient for ship navigation.     

Analyzing the dispersion of cargo vapors around a ship’s superstructure by means of wind tunnel experiments

In a previous study, it was found that cargo tank operations like cleaning and venting, lead to higher cargo vapor concentrations around the ship’s superstructure. Can wind tunnel experiments confirm these findings? Is there an improvement when using higher outlets at high velocities compared to lower outlets with a low outlet velocity? Is there a relation between relative wind speed and measured concentration? These questions were investigated in the Peutz wind tunnel. By using a tracer gas for the wind tunnel experiments, concentration coefficients have been calculated for various settings. The study shows that using high-velocity outlets is an efficient way to keep concentrations as low as possible. The only exception is for relative wind directions from the bow. In this last case using a manhole as ventilation outlet leads to lower concentrations. With increasing wind speeds the building downwash effect resulted in higher concentration coefficients near the main deck. This study confirms our on-board measurements and suggests the lowering of the ventilation inlet of the accommodation, so that the high-velocity outlet can be used safely at all times.     

Optimization of integrated scheduling of handling and storage operations at automated container terminals

Increasing demand for containerization compels container terminals to improve their performance. Uncoordinated scheduling of operations is one of the main factors accounting for poor performance at automated container terminals (ACTs). To increase land utilization efficiency and lower operational times, a new storage system called the split-platform automated storage/retrieval system (SP-AS/RS) has been introduced for temporary storage of containers. This paper describes a multi-objective mixed-integer programming (MIP) model that is based on a combination of multiple interacting sub-tasks. It is aimed at optimizing the integrated scheduling of handling and storage operations in ACTs. The MIP model objective function is to minimize delays in the loading/unloading tasks of the cranes and the travel time of vehicles and platforms in the SP-AS/RS. At the same time, a simulated annealing algorithm (SAA) that provides near-optimal solutions for the problem in a reasonable computation time is appraised. The results of this study show that the objective function of the MIP model is, on average, 58 % lower than that of the non-integrated scheduling method. On the other hand, the best objective function values obtained by the SAA indicate only a 3.7 % disadvantage in comparison with optimal values determined by the MIP model, demonstrating that the SAA is able to provide near-optimal solutions for the integrated scheduling of handling and storage operations.     

Robust principal component analysis via truncated nuclear norm minimization

Robust principal component analysis(PCA) is widely used in many applications, such as image processing, data mining and bioinformatics. The existing methods for solving the robust PCA are mostly based on nuclear norm minimization. Those methods simultaneously minimize all the singular values, and thus the rank cannot be well approximated in practice. We extend the idea of truncated nuclear norm regularization(TNNR) to the robust PCA and consider truncated nuclear norm minimization(TNNM) instead of nuclear norm minimization(NNM). This method only minimizes the smallest N-r singular values to preserve the low-rank components, where N is the number of singular values and r is the matrix rank. Moreover, we propose an effective way to determine r via the shrinkage operator. Then we develop an effective iterative algorithm based on the alternating direction method to solve this optimization problem. Experimental results demonstrate the efficiency and accuracy of the TNNM method. Moreover, this method is much more robust in terms of the rank of the reconstructed matrix and the sparsity of the error.     

Research on gray system and quantitative model about the fund-raising ability to China private equity fund

It is a rather challenging project to seek the amount of funds raised by funds-raising companies. This paper is focused on China private equity funds that have succeeded in raising their funds. The grey systemic model is applied in the research and a formula is established for the law of fund-raising of the private equity funds in order to sum up the capacity of China private equity investment funds and to establish a model accordingly.     

Bivariate Constant-Stress Accelerated Degradation Model and Inference Based on the Inverse Gaussian Process

Modern highly reliable products may have two or more quality characteristics (QCs) because of their complex structures and abundant functions. Relations between the QCs should be considered when assessing the reliability of these products. This paper conducts a Bayesian analysis for a bivariate constant-stress accelerated degradation model based on the inverse Gaussian (IG) process. We assume that the product considered has two QCs and each of the QCs is governed by an IG process. The relationship between the QCs is described by a Frank copula function. We also assume that the stress on the products affects not only the parameters of the IG processes, but also the parameter of the Frank copula function. The Bayesian MCMC method is developed to calculate the maximum likelihood estimators (MLE) of the model parameters. The reliability function and the mean-time-to-failure (MTTF) are estimated through the calculation of the posterior samples. Finally, a simulation example is presented to illustrate the proposed bivariate constant-stress accelerated degradation model.