Quality evaluation of car window motors using sound quality metrics

In this paper, a method to establish a decision criterion to evaluate the quality of small window motors using sound quality (SQ) metrics is suggested. Although the sound level radiated from the motor is relatively small compared to other sounds in a car, the sound from an abnormal motor gives an uncomfortable feeling and the impression of abnormal operation, which can lead to customer complaints. To construct an objective decision criterion, the correlation between the SQ metrics and the subjective decision on the passing or failure of the motor were investigated. Four representative SQ metrics, viz., loudness, sharpness, roughness, and fluctuation strength, were calculated for the collected samples. It was observed that the loudness and roughness of the motor sample group classified as abnormal was higher than those of the normal motors. For a single figure rating for motor quality, an evaluation index for the motor sound was generated by combining the correlated SQ metrics with proper weightings. Evaluation results on the specimens that were not employed in generating the quality evaluation index showed a reasonable agreement with the subjective test at 73%. The suggested quality check method can replace the current subjective decision procedure to identify the faulty motors.     

Damper modeling for dynamic simulation of a large bus with MR damper

In this study, a large bus is tested to measure its dynamic response by the single-lane change test and the rapid stop test. A full car model is established by ADAMS/Car for computer simulation. For multibody modeling of a large bus, user-defined templates are used in the simulation. Simulation results of the single-lane change test and the rapid braking test are compared to the results of the physical experiments, in which several sensors are installed to measure the vehicle’s responses. The results obtained from the simulation show good agreement with the tests’ results. A dynamic model for the MR(magnetic-rheological) damper is also developed by employing the Magic Formula model, which is widely used in the nonlinear modeling of a tire. Bump simulation of a full car with the MR damper is carried out to verify the performance of the MR damper. The comparison of the simulation results obtained with the MR damper model to the results obtained with the traditional passive damper model showed improved response of the vehicle with the MR damper.     

Effect of fuel stratification on initial flame development: Part 3-high swirl condition

This paper discusses the final investigation into the effect of fuel stratification on flame propagation. In previous works, the characteristics under the no port-generated swirl condition and the low-swirl condition were considered. For this purpose, the initial flame development and propagation were visualized under different axially stratified states in a modified optical single-cylinder SI engine. The images were captured by an intensified CCD camera through the quartz window mounted in the piston. Stratification was controlled by the combination of the port swirl ratio and injection timing. These were averaged and processed to characterize the flame propagation. The flame stability was estimated by the weighted average of flame area and luminosity. The stability was also evaluated through the standard deviation of flame area and propagation distance and through the mean absolute deviation of the propagation direction. The results show that the LML is expanded remarkably under the high-swirl cases up to the highest relative AFRs of 1.71 and 1.75 between 140 and 160CA. In addition, similar to the low-swirl condition, the flame-flow interaction determines the direction of flame propagation, and the governing roles of the two factors vary according to the swirl level; the flow is more important at the higher swirl conditions, and the flame is more important at the lower swirl condition. Finally, fast and stable flame propagation can be achieved under the preferably stratified condition, which is induced by the suitable combination of the high swirl and injection timing.     

出行者特征要素对公交服务模式的影响分析

公共交通是面向大众的服务,公共交通服务模式的制定与完善需要重点考虑出行者的出行需求,才能从根本上提高公共交通的竞争力。借鉴服务经济学的理论将公共交通服务模式分为公交服务标准、出行者界面、公交服务环境和技术4个维度。基于攀枝花市居民出行调查与公交专项调查数据,应用SPSS定量分析出行者特征要素与公交服务选择的相关性,以考察研究出行者对于公交服务的需求,并提出改善策略。通过研究表明,出行目的、出行时间、职业和年龄与公交服务模式的相关性较大。     

The precautionary principle in maritime affairs

Since the 1980s, the precautionary principle has been drawing more and more international attention. This became particularly clear during the series of Conferences on the Protection of the North Sea, which addressed marine environmental protection, and initiated the application of the principle into maritime affairs. Although a unified concept of the precautionary principle is lacking, some typical formulations have been concluded in regional treaties and international documents, and components of the principle can be summarised (Part I and Part II). The precautionary principle has been adopted by international documents involving different fields of law of the sea, and been addressed by international courts and tribunals (Part III). While the precautionary principle is still not part of customary international law (Part IV), its increasing level of worldwide acceptance suggests that it will become a customary international law in the future.     

Experimental Investigation of TARMAX Model for Modeling of Hydrodynamic Forces on Cylinder-like Structures

A new approach that models lift and drag hydrodynamic force signals operating over cylindrical structures was developed and validated. This approach is based on stochastic auto regressive moving average with exogenous (ARMAX) input and its time-varying form, TARMAX. Model structure selection and parameter estimation were discussed while considering the validation stage. In this paper, the cylindrical structure was considered as a dynamic system with an incoming water wave and resulting forces as the input a...     

A frequency-based maritime container assignment model

This paper transfers the classic frequency-based transit assignment method of Spiess and Florian to containers demonstrating its promise as the basis for a global maritime container assignment model. In this model, containers are carried by shipping lines operating strings (or port rotations) with given service frequencies. An origin–destination matrix of full containers is assigned to these strings to minimize sailing time plus container dwell time at the origin port and any intermediate transhipment ports. This necessitated two significant model extensions. The first involves the repositioning of empty containers so that a net outflow of full containers from any port is balanced by a net inflow of empty containers, and vice versa. As with full containers, empty containers are repositioned to minimize the sum of sailing and dwell time, with a facility to discount the dwell time of empty containers in recognition of the absence of inventory. The second involves the inclusion of an upper limit to the maximum number of container moves per unit time at any port. The dual variable for this constraint provides a shadow price, or surcharge, for loading or unloading a container at a congested port. Insight into the interpretation of the dual variables is given by proposition and proof. Model behaviour is illustrated by a simple numerical example. The paper concludes by considering the next steps toward realising a container assignment model that can, amongst other things, support the assessment of supply chain vulnerability to maritime disruptions.     

A single-period analysis of a two-echelon inventory system with dependent supply uncertainty

Disruptions and random supplies have been important sources of uncertainty that should be considered in the design and control of supply chains. There have been many real world examples in which a single catastrophic event has simultaneously degraded the capabilities of several suppliers leading to considerable erosion of profits and goodwill for a company. However, the literature on analytical models that account for the dependence nature of disruptions and its impact on supply chain performance is sparse.In this paper, we consider an m-manufacturer, 1-retailer, newsvendor inventory system with stochastically dependent manufacturing capacities, caused by random disruptions that may simultaneously inflict damages to the capacities of the manufacturers. We develop the structural/analytical properties of key performance measures and optimal inventory policies for the multi-source and assembly inventory systems. We show that stochastic dependence in disruptions can have opposite effects on system performance in the multi-source and assembly systems. While risk diversification is preferred in the multi-source system, risk concentration is preferred in the assembly system. Our results also suggest that, if the retailer ignores the effect of dependent disruptions, then in the multi-source structure, it would underestimate the cost, overestimate the fill rate, and order more units than the optimum; however, in the assembly structure, the opposite would happen. We perform a comprehensive numerical study to validate our analytical results and generate useful managerial and operational insights for effective risk management of supply chains in the presence of dependent supply uncertainty.     

A generic class of first order node models for dynamic macroscopic simulation of traffic flows

Node models for macroscopic simulation have attracted relatively little attention in the literature. Nevertheless, in dynamic network loading (DNL) models for congested road networks, node models are as important as the extensively studied link models. This paper provides an overview of macroscopic node models found in the literature, explaining both their contributions and shortcomings. A formulation defining a generic class of first order macroscopic node models is presented, satisfying a list of requirements necessary to produce node models with realistic, consistent results. Defining a specific node model instance of this class requires the specification of a supply constraint interaction rule and (optionally) node supply constraints. Following this theoretical discussion, specific macroscopic node model instances for unsignalized and signalized intersections are proposed. These models apply an oriented capacity proportional distribution of the available supply over the incoming links of a node. A computationally efficient algorithm to solve the node models exactly is included.     

Large-scale application of MILATRAS: case study of the Toronto transit network

This paper documents the efforts to operationalize the conceptual framework of MIcrosimulation Learning-based Approach to TRansit Assignment (MILATRAS) and its component models of departure time and path choices. It presents a large-scale real-world application, namely the multi-modal transit network of Toronto which is operated by the Toronto Transit Commission (TTC). This large-scale network is represented by over 500 branches with more than 10,000 stops. About 332,000 passenger-agents are modelled to represent the demand for the TTC in the AM peak period. A learning-based departure time and path choice model was adopted using the concept of mental models for the modelling of the transit assignment problem. The choice model parameters were calibrated such that the entropy of the simulated route loads was optimized with reference to the observed route loads, and validated with individual choices. A Parallel Genetic Algorithm engine was used for the parameter calibration process. The modelled route loads, based on the calibrated parameters, greatly approximate the distribution underlying the observed loads. 75% of the exact sequence of transfer point choices were correctly predicted by the off-stop/on-stop choice mechanism. The model predictability of the exact sequence of route transfers was about 60%. In this application, transit passengers were assumed to plan their transit trip based on their experience with the transportation network; with no prior (or perfect) knowledge of service performance.