Research on vibration characteristics of L-shaped plate using a mobility power flow approach

L-shaped plates have become an important focuses in structural vibration research. To determine their vibration characteristics, this paper applied a mobility power flow method. Firstly, the L-shaped plate was divided into two substructures to simplify analysis. The coupled bending moment was then deduced by applying a continuous vibration property on the common edge. Next, the response on any point of the plate and the input and transmitted power flow formulas were calculated. Numerical simulations showed the distribution of the coupled bending moment and the response of the whole structure. The validity of this method was verified by the SEA approach.     

Modeling a high output marine steam generator feedwater control system which uses parallel turbine-driven feed pumps

Parallel turbine-driven feedwater pumps are needed when ships travel at high speed. In order to study marine steam generator feedwater control systems which use parallel turbine-driven feed pumps, a mathematical model of marine steam generator feedwater control system was developed which includes mathematical models of two steam generators and parallel turbine-driven feed pumps as well as mathematical models of feedwater pipes and feed regulating valves. The operating condition points of the parallel ttu-bine-driven feed pumps were calculated by the Chebyshev curve fit method. A water level controller for the steam generator and a rotary speed controller for the turbine-driven feed pumps were also included in the model. The accuracy of the mathematical models and their controllers was verified by comparing their results with those from a simulator.     

Risk management modeling and its application in maritime safety

Quantified risk assessment （QRA） needs mathematicization of risk theory. However, attention has been paid almost exclusively to applications of assessment methods, which has led to neglect of research into fundamental theories, such as the relationships among risk, safety, danger, and so on. In order to solve this problem, as a first step, fundamental theoretical relationships about risk and risk management were analyzed for this paper in the light of mathematics, and then illustrated with some charts. Second, man-machine-environment-management （MMEM） theory was introduced into risk theory to analyze some properties of risk. On the basis of this, a three-dimensional model of risk management was established that includes： a goal dimension; a management dimension; an operation dimension. This goal management operation （GMO） model was explained and then emphasis was laid on the discussion of the risk flowchart （operation dimension）, which lays the groundwork for further study of risk management and qualitative and quantitative assessment. Next, the relationship between Formal Safety Assessment （FSA） and Risk Management was researched. This revealed that the FSA method, which the international maritime organization （IMO） is actively spreading, comes from Risk Management theory. Finally, conclusion were made about how to apply this risk management method to concrete fields efficiently and conveniently, as well as areas where further research is required.     

Review of containership stowage plans for full routes

Containership stowage plans are a pivotal teaches in the system of container transportation. With the increasing containers shipping, planning containership stowage has become more and more complicated. So intelligent stowage planning for containerships is of great significance. An effective stowage plan may improve efficiency of transportation system. First, the progress of containership stowage plan at home and abroad is reviewed, including the latest developments, such as the application of various optimization methods and computer techniques to the problem. Then, the complexities of the problem are discussed and areas where investigations are still needed are pointed out. This will provide a reference for further research on the subject.     

Advanced FNN control of mini underwater vehicles

Fuzzy neural networks （FNN） based on Gaussian membership functions can effectively control the motion of underwater vehicles. However, their operating processes and training algorithms are complicated, placing great demands on embedded hardware. This paper presents an advanced FNN with an S membership function matching the motion characteristics of mini underwater vehicles with wings. A leaming algorithm was then developed. Simulation results showed that the modified FNN is a simpler algorithm with faster calculations and improves responsiveness, compared with a Gaussian membership function-based FNN. It is applicable for mini underwater vehicles that don＇t need accurate positioning but must have good maneuverability.     

Fatigue crack growth rates of rotor steel at elevated temperatures

Low fatigue samples were obtained from the outer edges of rotor steel （30CrlMolV） which had operated under different temperatures conditions. Based on this data, the effects of temperature on fatigue crack growth rates were investigated. This paper presents a derivation of the superposition expression of two natural logarithms governing crack growth rates and also discusses the relationship between a material’s constants and temperature. These results can provide experimental and theoretical references for fatigue life design of rotor steel in steam turbines.     

Integrating land use and transport knowledge in strategy-making

There is broad and growing consensus regarding the central place of integrated Land Use and Transport (LUT) strategy development in establishing more efficient and sustainable urban environments. However, empirical evidence shows that such integration is hard to achieve in daily planning practice, due to many institutional barriers and substantive differences. More specifically, the tools developed to support LUT strategy development have very low implementation rates in daily planning practice. This paper introduces the concept of ‘knowledge generation’ as a potentially useful mechanism for closing the gap between support tools and planning practice. Through two specific Dutch planning cases, we analyze the applicability of this concept in supporting integrated LUT strategy development. The paper focuses on the developed strategies, how these differ from current practice, and how knowledge generation supported their development. We argue that socialization produces shared strategies and that effective socialization needs to be supported by efficient mutual exchange between tacit and explicit knowledge. We conclude by discussing the implications of this argument for the wider practice of LUT planning integration.     

A joint flexible econometric model system of household residential location and vehicle fleet composition/usage choices

Modeling the interaction between the built environment and travel behavior is of much interest to transportation planning professionals due to the desire to curb vehicular travel demand through modifications to built environment attributes. However, such models need to take into account self-selection effects in residential location choice, wherein households choose to reside in neighborhoods and built environments that are conducive to their lifestyle preferences and attitudes. This phenomenon, well-recognized in the literature, calls for the specification and estimation of joint models of multi-dimensional land use and travel choice processes. However, the estimation of such model systems that explicitly account for the presence of unobserved factors that jointly impact multiple choice dimensions is extremely complex and computationally intensive. This paper presents a joint GEV-based logit regression model of residential location choice, vehicle count by type choice, and vehicle usage (vehicle miles of travel) using a copula-based framework that facilitates the estimation of joint equations systems with error dependence structures within a simple and flexible closed-form analytic framework. The model system is estimated on a sample derived from the 2000 San Francisco Bay Area Household Travel Survey. Estimation results show that there is significant dependency among the choice dimensions and that self-selection effects cannot be ignored when modeling land use-travel behavior interactions.     

Scrutinizing individuals’ leisure-shopping travel decisions to appraise activity-based models of travel demand

Activity-based models for modeling individuals’ travel demand have come to a new era in addressing individuals’ and households’ travel behavior on a disaggregate level. Quantitative data are mainly used in this domain to enable a realistic representation of individual choices and a true assessment of the impact of different Travel Demand Management measures. However, qualitative approaches in data collection are believed to be able to capture aspects of individuals’ travel behavior that cannot be obtained using quantitative studies, such as detailed decision making process information. Therefore, qualitative methods may deepen the insight into human’s travel behavior from an agent-based perspective. This paper reports on the application of a qualitative semi-structured interview method, namely the Causal Network Elicitation Technique (CNET), for eliciting individuals’ thoughts regarding fun-shopping related travel decisions, i.e. timing, shopping location and transport mode choices. The CNET protocol encourages participants to think aloud about their considerations when making decisions. These different elicited aspects are linked with causal relationships and thus, individuals’ mental representations of the task at hand are recorded. This protocol is tested in the city centre of Hasselt in Belgium, using 26 young adults as respondents. Response data are used to apply the Association Rules, a fairly common technique in machine learning. Results highlight different interrelated contexts, instruments and values considered when planning a trip. These findings can give feedback to current AB models to raise their behavioral realism and to improve modeling accuracy.     

Temporal transferability of updated alternative-specific constants in disaggregate mode choice models

Methods of updating disaggregate discrete choice models have been proposed as a means of obtaining better transferability. However, the temporal transferability of models updated for better spatial transferability has rarely been analysed, and the factors affecting temporal transferability have not been determined. This paper deals with one updating method—the use of disaggregate data to update alternative-specific constants—and investigates the factors affecting the temporal transferability of the updated constants. In the analysis, repeated cross-section data collected in the Chukyo metropolitan area are divided, efficiently generating many application areas. The analysis showed that the factors can depend on regional characteristics and past travel behaviours (inertia), and are anti-symmetric and path-dependent of changes in the level of service.