Comparison study on characteristics of nano-sized particle number distribution by using condensation particle counter calibrated with spray and soot type particle generation methods

In the year 2011, the Particle Measurement Program (PMP) in Europe started the regulation of the diesel vehicle’s nano-sized particle number density (PN) due to its high degree of harm to the human body. Concretely, the standard level of PN emission was introduced in the Euro 5+ and 6 emissions regulation with a limit (<6.0 × 10¹¹#/km) for diesel light-duty vehicle. Therefore, the determination of suitable and sophisticated instruments for reliable particle sampling and analysis was essential in taking exact experimental data. Now, among the PN emission measuring devices suggested by the PMP, condensation particle counter (CPC) is a key equipment for measuring the particle number density in real time and it has been used extensively. However, CPC can cause different results depending on operating conditions of the saturator and condensation that induce different rates of particle growth. This study was conducted to analyze the effect of CPC calibrated by a two-particle generator with spray and soot type methods applied on the nano-sized particle distribution’s parameters such as number concentration and linearity. Also, in order to ensure the reliability for particle sensor system named as PPS, which had emerged as a useful diagnostic to making spatially and temporally resolved quantitative measurements of diesel PN concentration, it was compared with calibrated CPC system. As a result, nano-sized particle measuring system with CPC calibrated by spray type particle generator had a much higher counting efficiency, indicating a larger nano size available than soot type particle generator. And, comparative experimental results on the correlation between the particle number of CPC to a reflectance PPS system showed that above 5,000 #/cm ³ in number concentrations measured by CPC as well as PPS were found to be similar with good linear relationship.     

Fuel economy comparison of conventional drive trains series and parallel hybrid electric step vans

A hybrid electric vehicle (HEV) is a vehicle that combines a conventional propulsion system with an on-board rechargeable energy storage system to achieve better fuel economy than a conventional vehicle HEVs do not have limited ranges like battery electric vehicles, which use batteries charged by an external source. The different propulsion power systems may have common subsystems or components. The objective of this study is to compare the fuel economies of a conventional step van, a series hybrid electric step van (HESV), and a parallel HESV by calculating the fuel consumption using the ADVISOR software by NREL. We also showed the results of the vehicles in different driving cycles including the Central Business District bus cycles, the New York City Cycle, and the US EPA City and Highway cycles.     

Association rule learning to improve deficiency inspection in port state control

ABSTRACT

The inspection of foreign ships in national ports is a critical measure in port state control (PSC), preventing substandard ships from entering national ports. Multifarious inspection items, limited inspection time and inspector manpower are challenging PSC inspection. This research applies data mining to analyze historical PSC inspection records in Taiwan’s major ports to extract potential valuable information for PSC onboard inspections. Using the Apriori Algorithm, the analysis identifies many useful association rules among PSC deficiencies in terms of specific ship characteristics, such as ship types, societies, and flags. The general rules identified show that the items ‘Water/Weathertight conditions’ and ‘Fire safety’ are significantly related. Besides, in the analysis of the various ship types, several different rules are found. After comparing the analysis of ship types and ship societies, it can be observed that the association rules for specific ship types, such as oil tankers, have a better effect than those for individual ship societies do. These identified rules can not only help inspectors effectively spot the associated deficiencies, but also improve the efficiency of PSC inspection. The ports other than Taiwan’s ports can apply a similar analysis method to identify corresponding association rules suitable for their own inspections.     

Characterization and evolution of spatial density patterns in urban areas

This paper examines the spatial patterns of population density, household automobile ownership and other socio-demographic variables that affect urban travel, as a function of distance from the central city core. Spatial density functions provide a useful characterization of urban structure, and of its evolution when taken at different time intervals. Analysis of the data from four case cities (Austin, Atlanta, Dallas, Phoenix) for 1960, 1970 and 1980 reveals continuing overall dispersion away from the traditional central core, accompanied by the densification of formerly low-density suburbs. This presents implications for high congestion levels in the densifying suburban communities, comparable to those typically associated with the CBD. In addition, the analysis has captured the continuing growth of average household automobile ownership and revealed a distinct spatial pattern that seems to be robust across the case areas considered, as well as within radial corridors in the one case that was so analyzed (Austin).List of symbols Y gross population density in census tractt - X _t distance in miles from the center of tract to the CBD - parameter representing the central business district density - y density gradient parameter - X₀, X₁, X2, and X3 locations of the knots in a three segment division of the x-axis - D_i dummy variable defined for thei-th segment - ₁ normally distributed disturbance term,a _i,b _i,c _i,d _i,i = 1, 2, 3 — parameters to be estimated - A _t area of census tractt     

Comparison analysis for subjective and objective weights of financial positions of container shipping companies

This paper explores the positions of financial ratios identified utilizing both subjective and objective weighting methods—the consistent fuzzy preference relation (CFPR) and entropy—based on questionnaires collected from experts and the financial statements of major shipping companies in Taiwan and Korea. The comparison of perceptions of financial ratios by country and by expert group illuminates some financial aspects that experts may have ignored or not paid close attention to during the business operating process, especially in today’s turbulent world shipping market. The major results of this paper show that experts in the two countries have different perceptions of the debt-to-equity ratio and that by combining the results of objective and subjective weights, categorization of financial ratios by quadrant can help decision-makers find business options and strategies to improve the financial performance of their companies. This research approach may be applied to other business entities, improving on the direct rating method used in previous studies.     

Mean Value WGT Diesel Engine Calibration Model for Effective Simulation Research

Recently, to improve vehicle fuel economy, as well as the performance of internal combustion engines, optimized system matching between a vehicle’s drivetrain and engine has become a very important technical issue. For this reason, the need for simulation research on engine and vehicle performance improvement has increased. But in general, since both engine simulation and vehicle simulation require initial engine calibration map input, a simple engine calibration method is required for the efficient configuration of various virtual engine calibration map setups. On this background, in this study, an example of waste gate turbocharger (WGT) cooled — exhaust gas recirculation (EGR) Diesel engine calibration using a test-based mean value engine model is presented as a suitable engine calibration map setting method. Also, the feasibility of an engine calibration model is confirmed through various engine tests. Using the simple model presented here, it is possible for diverse engine operating conditions and engine performance maps to be acquired.     

Requirement-based testing of an automotive ECU considering the behavior of the vehicle

HILS (Hardware In the Loop Simulation) and RBT (Requirement-Based Testing) are widely used to evaluate the performance and reliability of automotive ECUs (Electronic Control Units). The HILS method is used to predict the behavior of ECU-installed vehicles and to evaluate the performance of ECU controllers. RBT evaluates whether the embedded system satisfies the pre-defined requirements. In this study, the behavior of a vehicle is regarded as a system requirement, and an embedded system test procedure that evaluates the system requirement is proposed. In particular, a new method is introduced, which integrates HILS with RBT. Using the proposed method, the behavior of an articulated vehicle equipped with an AWS (All Wheel Steering) ECU is evaluated with RBT software.     

Robust optimization for emergency logistics planning: Risk mitigation in humanitarian relief supply chains

This paper proposes a methodology to generate a robust logistics plan that can mitigate demand uncertainty in humanitarian relief supply chains. More specifically, we apply robust optimization (RO) for dynamically assigning emergency response and evacuation traffic flow problems with time dependent demand uncertainty. This paper studies a Cell Transmission Model (CTM) based system optimum dynamic traffic assignment model. We adopt a min–max criterion and apply an extension of the RO method adjusted to dynamic optimization problems, an affinely adjustable robust counterpart (AARC) approach. Simulation experiments show that the AARC solution provides excellent results when compared to deterministic solution and sampling based stochastic programming solution. General insights of RO and transportation that may have wider applicability in humanitarian relief supply chains are provided.     

Development of an Operability Evaluation Framework for Remotely Controlled Ground Combat Vehicles in a Simulated Environment

This paper proposes a systematic framework for operability evaluation of remotely controlled ground combat systems (RGCS) in a simulated environment. The popular human-robot interaction metric used in unmanned vehicle systems is called fan-out (FO) and represents the maximum number of robots/vehicles that could be controlled by a single human operator. However, FO is inappropriate for systems with a lower level of automation where vehicles are remotely controlled by a human, such as RGCS. The theoretical background of the suggested framework is based on McRuer’s crossover model that was initially developed in the aviation domain for explaining pilot handling issues. In this study, an evaluation/analysis software prototype was developed, known as the RGCS operability evaluation tool in a simulated environment (ROPES). The ROPES was designed to be a simple tool for use by officers or researchers who only have intuitive understanding on the human adaptability. The ROPES includes two sub-modules; 1) an interactive interface for the configuration of the RGCS dynamic parameters and user interfaces and 2) a time-varying graphical display of system and human performance. Examples case studies demonstrate the advantage of the ROPES, and improvement points were identified for future development.