结构动力学基于摄动法的高阶非线性随机有限元方法研究(英文)

Several algorithms were proposed relating to the development of a framework of the perturbation-based stochastic finite element method (PSFEM) for large variation nonlinear dynamic problems. For this purpose, algorithms and a framework related to SFEM based on the stochastic virtual work principle were studied. To prove the validity and practicality of the algorithms and framework, numerical examples for nonlinear dynamic problems with large variations were calculated and compared with the Monte-Carlo Simulation method. This comparison shows that the proposed approaches are accurate and effective for the nonlinear dynamic analysis of structures with random parameters.     

Nonlinear Robust Control of Torque Converter Clutch Slip System for Passenger Vehicles Using Advanced Torque Estimation Algorithms

In this paper, a torque-estimation-based robust controller for passenger car torque converter clutch slip system is presented. The proposed robust controller uses only the measurements available from inexpensive sensors that are installed in current passenger vehicles for torque estimation and feedback control. A conventional full state observer along with a neural-network-based open-loop hydraulic actuator observer is designed to estimate the unknown driving load, and a neural-network-based turbine torque estimator considering the temperature of oil circulating the torque converter is developed for improved turbine torque estimation accuracy. The stability of the internal dynamics is also investigated, and the performance and robustness of the robust controller is validated by simulation studies.     

Major sources of hydrocarbon emissions in a premixed charge compression ignition engine

Although premixed charge compression ignition (PCCI) combustion engines are praised for potentially high efficiency and clean exhaust, experimental engines built to date emit more hydrocarbons (HCs) and carbon monoxide (CO) than the conventional machines. These compounds are not only strictly controlled components of the exhaust gas of road vehicles but are also an energy loss indicator. The prime objective of this study was to investigate the major sources of the HCs formed in the combustion chamber of an experimental PCCI engine in order to suggest some effective technologies for HC reduction. In this study, to explore the dominant sources of HC emissions in both operation modes, a single cylinder engine was prepared such that it could operate using either conventional diesel combustion or PCCI combustion. Specifically, the contributions of the top-ring crevice volume in the combustion chamber and the bulk quenching of the lean mixture were investigated. To understand the influence of the shape and magnitude of the crevice on HC emissions, the engine was operated with 12 specially prepared pistons with different top-ring crevices installed one after another. The engine emitted proportionally more HCs as the depth of the crevice increased as long as the width remained narrower than the prevailing quench distance. The top-ring-crevice-originated exhaust HCs comprised approximately 31% of the total HC emissions in the baseline condition. In a series of tests to estimate the effects of bulk quench on exhaust HC emissions, intake air was heated from 300K to 400K in steps of 25K. With the intake air heated, HC and CO emissions decreased with a gradually diminishing rate to zero at 375K. In conclusion, the most dominant sources of HC emissions in PCCI engines were the crevice volumes in the combustion chamber and the bulk quenching of the lean mixtures. The key methods for reducing HC emissions in PCCI engines are minimizing crevice volume in the combustion chamber and maximizing intake air temperature allowed based on the permissible NOx level.     

Aerodynamic design optimization of rear body shapes of a sedan for drag reduction

This study proposes an aerodynamically optimized outer shape of a sedan by using an Artificial Neural Network (ANN), which focused on modifying the rear body shapes of the sedan. To determine the optimization variables, the unsteady flow field around the sedan driving at very fast speeds was analyzed by CFD simulation, and fluctuations of the drag coefficient (C _D ) and pressure around the car were calculated. After consideration of the baseline result of CFD, 6 local parts from the end of the sedan were chosen as the design variables for optimization. Moreover, an ANN approximation model was established with 64 experimental points generated by the D-optimal methodology. As a result, an aerodynamically optimized shape for the rear end of the sedan in which the aerodynamic performance is improved by about 5.64% when compared to the baseline vehicle is proposed. Finally, it is expected that within the accepted range of shape modifications for a rear body, the aerodynamic performance of a sedan can be enhanced so that the fuel efficiency of the sedan can be improved. The YF SONATA, a sedan manufactured by Hyundai Motors Corporate, played a major role in this research as the baseline vehicle.     

A self-powering system based on tire deformation during driving

Tire intelligence is vital in the improvement of the safety of vehicles because the tire supports the car body and is the contact point between the vehicle and the road. To create an intelligent tire, sensors must be installed to measure the behavior of the tire. However, it is difficult to apply a wired sensor system on the wheel of the tire. Hence, it is necessary to implement a self-powering, wireless system (a type of energy harvesting system) that can be mounted inside the tire. The purpose of this study is to convert the strain energy caused by deformation of the tire while driving into useful electrical energy to supply the sensor system. A flexible piezofiber is utilized for the energy conversion. The variation in strain, due to changes in speed, load, and the internal pressure of the tire, was measured along two axial directions to evaluate the amount of available strain energy. The amount of strain changed from 0.15% to 0.8%. To predict the amount of available energy from a tire, we perform an analysis of the relationship between the strain and the voltage. In addition, experiments for impedance matching between piezofiber and related circuits were conducted to optimize the external loads for transferring energy efficiently. Based on the procedure mentioned above, at least 0.58 mJ of electrical energy can be generated by using the laterally oriented strain (1500 to 2500 micro strain). The result of this study is expected to enhance the potential realization of self-generating wireless sensor systems for so-called ??intelligent?? tires.     

An application of a rank ordered probit modeling approach to understanding level of interest in autonomous vehicles

Surveys of behavior could benefit from information about people’s relative ranking of choice alternatives. Rank ordered data are often collected in stated preference surveys where respondents are asked to rank hypothetical alternatives (rather than choose a single alternative) to better understand their relative preferences. Despite the widespread interest in collecting data on and modeling people’s preferences for choice alternatives, rank-ordered data are rarely collected in travel surveys and very little progress has been made in the ability to rigorously model such data and obtain reliable parameter estimates. This paper presents a rank ordered probit modeling approach that overcomes limitations associated with prior approaches in analyzing rank ordered data. The efficacy of the rank ordered probit modeling methodology is demonstrated through an application of the model to understand preferences for alternative configurations of autonomous vehicles (AV) using the 2015 Puget Sound Regional Travel Study survey data set. The methodology offers behaviorally intuitive model results with a variety of socio-economic and demographic characteristics, including age, gender, household income, education, employment and household structure, significantly influencing preference for alternative configurations of AV adoption, ownership, and shared usage. The ability to estimate rank ordered probit models offers a pathway for better utilizing rank ordered data to understand preferences and recognize that choices may not be absolute in many instances.     

Are millennials more multimodal? A latent-class cluster analysis with attitudes and preferences among millennial and Generation X commuters in California

Transportation - Millennials tend to use a variety of travel modes more often than older birth cohorts. Two potential explanations for this phenomenon prevail in the literature. According to the...     

Improving the coexistence of offshore wind farms and shipping: an international comparison of navigational risk assessment processes

The continued growth and evolution of the offshore wind industry, and the emergence of other novel marine uses such as wave and tidal generators, have upped the ante for spatial planners, as well as consenting and approval authorities in various coastal states. These stakeholders rely on processes such as navigational risk assessments (NRAs) to balance safety and efficiency requirements and to make optimal decisions over use of space. Given the increasingly complex and crowded seascape, however, there are some apprehensions about potential shortcomings in these NRA processes. There is also some concern that these inadequacies may lead to unsafe or inefficient marine spatial use. To understand how NRA processes can be improved further, a literature review is conducted, followed by a survey of respondents who are involved in the planning, consenting and/or approval of offshore wind farms across seven different countries. A summary of the NRA processes in these seven countries is presented, and several shortcomings are identified. Based on the findings of the survey, a list of recommendations is presented to enhance existing NRA processes—and to improve the coexistence of shipping and offshore wind farms (OWFs).