Finite element based meta-modeling of ship-ice interaction at shoulder and midship areas for ship performance simulation

The climate change has made the transit through Arctic area more feasible, which demands reliable methods to evaluate ship performance. Ship performance in ice is a cross-scale problem, where the desired output such as ship speed lies in larger scale while the actual ship-ice interaction happens in smaller scale. Due to insufficient knowledge in ice mechanics and the demand for computational efficiency, existing approaches for modelling ship-ice interaction from ship performance perspective are mostly either (semi-) empirical, or simplified analytical, with reduced dimensions and extensively simplified mechanics. This paper presents a novel approach to model ship-ice interaction, which maintains the accuracy of the modelling with Finite Element Method (FEM) in ship-ice interaction scale, while being computationally very cheap, therefore is capable to be applied in ship scale simulations. The ice failure is firstly qualitatively investigated through full-scale and model-scale observations, as well as a numerical simulation with Extended Finite Element Method (XFEM). The model is then simplified and executed by Abaqus to automatically run a large database. A neural network is used to fit the results to get a simulation-free tool for ship-ice interaction calculation. Finally, the uncertainty in the results due to an important assumption is quantified. The results show that the obtained neural network fits the database with excellent performance. Therefore, it can be applied in ship scale simulations with improved accuracy compared to empirical or analytical approaches.     

An empirical investigation on consumers’ intentions towards autonomous driving

Major steps towards implementation of autonomous and connected transport are being taken nowadays. The trend of automation technology being used in vehicles by the most important vehicle manufacturing industries is expected to move closer to high or fully Autonomous Vehicles (AVs) through technological advancements in sectors of robotics and artificial intelligence. Vehicles with autonomous driving capabilities are planning to be available on market, in full scale, in the next years. In the longer term substantial benefits are mainly expected for accessibility to transport, safety, traffic flow, emissions, fuel use and comfort. All these potential societal benefits will not be achieved unless AVs are accepted and used by a critical mass of people. Addressing these challenges, this paper: (a) proposes a technology acceptance modelling process by extending the original Technology Acceptance Model (TAM) to explain and predict consumers’ intensions towards AVs, (b) based on the proposed TAM-extended framework, a 30-question survey was conducted in order to investigate the factors influencing consumers’ intensions to use and accept AVs. Results show that the constructs of perceived usefulness, perceived ease to use, perceived trust and social influence, are all useful predictors of behavioral intentions to have or use AVs, with perceived usefulness having the strongest impact. The insights derived from this study could significantly contribute to ongoing research related to technology acceptance of AVs and are expected to allow automobile industries to improve their design and technology.     

Dynamic modelling of a two-wheeled vehicle: Jourdain formalism

This paper presents a motorcycle direct dynamic formulation by the Jourdain's principle approach. This vehicle is considered as an assembly of six rigid bodies and the resulting equation of motion allows to simulate 11 degrees of freedom. The vehicle geometry is described and a step-by-step procedure is introduced to evaluate the kinematics and the generalised efforts of the considered vehicle. In addition, to simulate the equation of motion, a Lyapunov-based stabilisation is developed to assess the vehicle behaviour in response to a propulsion/braking torque applied on the vehicle's wheels and a rider torque exerted on the motorcycle's handlebar. Simulation results reveal some dynamic features such as load transfer and counter-steering phenomena.     

Stochastic modelling of quadratic wave components

This paper deals with stochastic wave models and their influence on wave load modelling of marine structures. The need for more refined theories is underlined for some applications and an entirely new quadratic model for the wave elevation is outlined. Finally, a number of physical phenomena relevant to waves are illustrated which are likely to be important for marine structures and could, in the near future, require ad hoc modelling.     

阀控对称缸位置系统神经网络建模

本文分析了传统建模方法对电液们厥系统建模存在的问题；用神经网络建立了一个实际电液伺服系统的教学模型，并对神经网络建模的一些问题进行了研究与探索。     

Tyre-force estimation by Kalman inverse filtering: applications to off-highway mining trucks

Kalman inverse filtering is used to develop a methodology for real-time estimation of forces acting at the interface between tyre and road on large off-highway mining trucks. The system model formulated is capable of estimating the three components of tyre-force at each wheel of the truck using a practical set of measurements and inputs. Good tracking is obtained by the estimated tyre-forces when compared with those simulated by an ADAMS virtual-truck model. A sensitivity analysis determines the susceptibility of the tyre-force estimates to uncertainties in the truck's parameters.     

Capturing tour mode and activity choice interdependencies: A co-evolutionary logit modelling approach

It is generally assumed that the choice of transport mode and the choice of including intermediate activities on a work tour are interrelated, but little is known about the nature of the causal relationship. To shed light on this, this paper addresses the question of whether transport mode choice is dependent on the activity choice or vice-versa. A new methodology, referred to as the co-evolutionary approach, is combined with a set of MNL models, one for each choice facet involved, to derive an indication of the order of decisions on an individual level. The models are estimated based on the work tours of a large sample of individuals in the Netherlands. The results suggest that there is substantial variation in the order of the transport mode and activity decisions. However, in the majority of cases the activity decision is made before the mode decision, suggesting that the transport mode and, in particular, the choice between car and public transport is most often ‘adjusted’ to the choice of trip chaining rather than the other way round.     

Analysis of wheel speed vibrations for road friction classification

ABSTRACT

With higher level of vehicle automation, it becomes increasingly important to know the maximum possible tyre forces during normal driving. An interesting method in this respect is estimating the tyre–road friction from the resonance peak in the wheel speed signal, excited by road roughness. A simulation environment using the MF-Swift tyre model is proposed, which gives insight in the correctness and functioning of this method. From implementing the estimation algorithm and considering the tyre torsional vibration system, it is concluded that frequencies and damping ratios can be estimated with reasonable accuracy and that the trends observed with changing road friction are consistent. Furthermore, the proposed simulation environment gives opportunity to investigate other issues like robustness of the estimation method to road roughness. Additionally, the tyre modelling aspect of the estimation method is analysed and improvements are proposed.     

Slip-based terrain estimation with a skid-steer vehicle

In this paper, a novel approach for online terrain characterisation is presented using a skid-steer vehicle. In the context of this research, terrain characterisation refers to the estimation of physical parameters that affects the terrain ability to support vehicular motion. These parameters are inferred from the modelling of the kinematic and dynamic behaviour of a skid-steer vehicle that reveals the underlying relationships governing the vehicle-terrain interaction. The concept of slip track is introduced as a measure of the slippage experienced by the vehicle during turning motion. The proposed terrain estimation system includes common onboard sensors, that is, wheel encoders, electrical current sensors and yaw rate gyroscope. Using these components, the system can characterise terrain online during normal vehicle operations. Experimental results obtained from different surfaces are presented to validate the system in the field showing its effectiveness and potential benefits to implement adaptive driving assistance systems or to automatically update the parameters of onboard control and planning algorithms.     

Optimal tyre usage for a Formula One car

Variations in track temperature, surface conditions and layout have led tyre manufacturers to produce a range of rubber compounds for race events. Each compound has unique friction and durability characteristics. Efficient tyre management over a full race distance is a crucial component of a competitive race strategy. A minimum lap time optimal control calculation and a thermodynamic tyre wear model are used to establish optimal tyre warming and tyre usage strategies. Lap time sensitivities demonstrate that relatively small changes in control strategy can lead to significant reductions in the associated wear metrics. The illustrated methodology shows how vehicle setup parameters can be optimised for minimum tyre usage.