This cohort study investigates the long-term effects of simulator-based hazard awareness training (HAT) on learner and novice drivers in the Netherlands, using a dataset of 2,372 participants over a 15-year period. Most prior studies on HAT have measured only immediate post-training outcomes; no longitudinal cohort study with a control group has previously examined both supervised and unsupervised driving outcomes over a multi-year horizon. Although the HAT and control groups showed small but statistically significant differences in gender composition, education level, and fear of driving at the start of training, the effect sizes were negligible (d ≤ 0.09), and these characteristics are addressed as covariates in the analyses.HAT improved performance during simulator training and supervised driving: HAT students’ viewing skills were better during the intersection test, required fewer on-road training hours, passed the driving exam in fewer attempts, and achieved a higher first-attempt pass rate than the control group. These benefits did not persist into unsupervised post-licensing driving. Violations, errors, and accident involvement were comparable between HAT and control group drivers in the first and last year after licensing. Personal characteristics — including gender, licensing age, self-assessed driving competence, and subjective driving difficulty — were stronger and more lasting predictors of post-licensing behaviour than training type. These findings suggest that hazard awareness is a trainable skill, but that training effects on risk-taking behaviour are moderated by individual characteristics that emerge most clearly once drivers operate independently, aligning with findings of a previous study on the same dataset. Teaching higher safety margins during supervised driving may offer a more durable route to reducing accident risk for novice drivers than higher-order skill training alone.

Background: Even though accompanied driving and simulator training are common, clarity on their usage trends and effectiveness is lacking. This research aimed to deepen the understanding of the relationships between personal characteristics, pre-licence accompanied driving, self-reported post-licence driving behaviour, and driving performance scores during simulator lessons. Methods: We used data from a questionnaire completed by simulator and non-simulator students (total n = 3,761). Data were analysed by dividing the sample into two groups based on variables such as gender, age at licensure, education level, fear of driving a car when starting driver education, information-processing style, participation in accompanied driving, and the number of driving simulator lessons completed. Results: Males took fewer on-road lessons and reported lower fear, but they had poorer simulator safety scores than females. Younger learners required fewer lessons and test attempts, were less fearful, and violated traffic rules more than older respondents. Higher-educated respondents had more fear and safer driving scores in the simulator. Thinkers, who were typically more educated, showed more caution in the simulator and on the road, and were older at licensure. Compared to regular students, students participating in accompanied driving were younger at licensure. Moreover, students with a higher driving skill score in the simulator were less fearful and needed slightly fewer attempts to pass the road driving test. Discussion and conclusion: The fear towards driving, which is strongly linked to personal characteristics, provides a logical explanation for the progression of students through driver education. Furthermore, this study illustrated the possibility of considering information-processing styles, education level, and driving simulator performance in driving education. However, in order to conclusively study the safety-effectiveness of accompanied driving and simulator training, further research in the form of a randomised controlled trial is necessary.

Fluidization is widely used in industries and has been extensively studied, both experimentally and theoretically, in the past. However, most of these studies focus on spherical particles while in practice granules are rarely spherical. Particle shape can have a significant effect on fluidization characteristics. It is therefore important to study the effect of particle shape on fluidization behavior in detail. In this study, experiments in pseudo-2D fluidized beds are used to characterize the fluidization of spherocylindrical (rod-like) Geldart D particles of aspect ratio 4. Pressure drop and optical measurement methods (Digital Image Analysis, Particle Image Velocimetry, Particle Tracking Velocimetry) are employed to measure bed height, particle orientation, particle circulation, stacking, and coordination number. The commonly used correlations to determine the pressure drop across a bed of nonspherical particles are compared to experiments. Experimental observations and measurements have shown that rod-like particles are prone to interlocking and channeling behavior. Well above the minimum fluidization velocity, vigorous bubbling fluidization is observed, with groups of interlocked particles moving upwards, breaking up, being thrown high in the freeboard region and slowly raining down as dispersed phase. At high flowrates, a circulation pattern develops with particles moving up through the center and down at the walls. Particles tend to orient themselves along the flow direction.

A novel granular discrete element method (DEM) is introduced to simulate mixtures of particles of any convex shape. To quickly identify pairs of particles in contact, the method first uses a broad-phase and a narrow-phase contact detection strategy. After this, a contact resolution phase finds the contact normal and penetration depth. A new algorithm is introduced to effectively locate the contact point in the geometric center of flat faces in partial contact. This is important for a correct evaluation of the torque on each particle, leading to a much higher stability of stacks of particles than with previous algorithms. The granular DEM is used to generate random packings in a cylindrical vessel. The simulated shapes include non-spherical particles with different aspect ratio cuboids, cylinders and ellipsoids. More complex polyhedral shapes representing sand and woodchip particles are also used. The latter particles all have a unique shape and size, resembling real granular particle packings. All packings are analyzed extensively by investigating positional and orientational ordering.

A stochastic Direct Simulation Monte Carlo (DSMC) method has been extended for handling bubble-bubble and bubble-wall collisions. Bubbly flows are generally characterized by highly correlated velocities due to presence of the surrounding liquid. The DSMC method has been improved to account for these kind of correlated collisions along with a treatment allowing the method to be used also at relatively high volume fractions. The method is first verified with the deterministic Discrete Particle/Bubble Model (DPM/DBM) using two problem cases: (a) dry granular flow of particles through two impinging nozzles and (b) 3D periodic bubble rise for mono-disperse and poly-disperse systems. The verification parameters are the total number of prevailing collisions within the system, the collision frequencies and the time-averaged liquid velocity profiles (only for the 3D-periodic bubble rise). Subsequently the method is applied to a lab-scale bubble column and validated with the experimental data of Deen et al. (2001). A computational performance comparison with the DBM is reported for the 3D periodic bubble rise case with varying overall gas fractions. The DSMC is approximately two orders of magnitude faster than the deterministic approach for the studied dense bubbly flow cases without adverse effects on the quality of the computational results.

Fluidised beds are used in a variety of processes because of their favourable mass and heat transfer characteristics. In this and many other processes, non-spherical particles are commonplace, which can drastically affect the fluidisation behaviour. In this study, we use numerical models to study non-spherical fluidisation behaviour in detail. A crucial step in the development of the numerical model is a detailed validation with experimental data. The validated model can then be used with confidence for further investigations. In this study, the results obtained from CFD-DEM modelling are compared with detailed experiments (Mahajan et al., 2017). The particles used are of spherocylindrical shape with an aspect ratio 4. We discuss the numerical modelling strategy including the DEM contact detection algorithm and accurate voidage calculation algorithm. The non-spherical single particle drag model of Hölzer and Sommerfeld (2008) is compared with a DNS drag model for spherocylindrical particles developed in-house. We propose two new voidage correction models and compare results with the (Di Felice, 1994) model. The pressure drop, bed height, particle orientation, particle circulation, stacking of particles and coordination number obtained from simulations are compared with experiments. The numerical measurements show good agreement with experiments. Similar to experiments, simulations show that rod-like particles are prone to interlocking behaviour. At high gas flow rates above the minimum fluidisation velocity, vigorously bubbling fluidisation is observed, with gas bubbles moving up through the center and particles moving down at the side walls. The orientation of particles in the fluidised state do not match with the experiments when hydrodynamic torque is neglected. The importance of hydrodynamic torque and multi-particle drag in CFD-DEM modelling of non-spherical particles is demonstrated through these results.

Connecting the macroscopic world of continuous fields to the microscopic world of discrete molecular events is important for understanding several phenomena occurring at physical boundaries of systems. An important example is heterogeneous catalysis, where reactions take place at active surfaces, but the effective reaction rates are determined by transport limitations in the bulk fluid and reaction limitations on the catalyst surface. In this work we study the macro-micro connection in a model heterogeneous catalytic reactor by means of stochastic rotation dynamics. The model is able to resolve the convective and diffusive interplay between participating species, while including adsorption, desorption, and reaction processes on the catalytic surface. Here we apply the simulation methodology to a simple straight microchannel with a catalytic strip. Dimensionless Damkohler numbers are used to comment on the spatial concentration profiles of reactants and products near the catalyst strip and in the bulk. We end the discussion with an outlook on more complicated geometries and increasingly complex reactions.

Young and inexperienced drivers are over-involved in traffic violations and car crashes. There is a paucity of research on the use of driving simulators for assessing driving style. This study investigated the relationships between years of licensure and driving style measured with a short simulator-based test. At a motor show, 650 licensed drivers completed a 6.5-min driving style test and responded to a questionnaire about their on-road driving experience. The results showed that participants who had their driving license for a longer period adopted a less risky driving style and drove with slower speeds in the simulator. Furthermore, females and experienced drivers reported more simulator sickness than males and inexperienced drivers, respectively. The present results may be useful in the development of simulator-based driving tests.

Two fluid model simulations based on our recently introduced kinetic theory of granular flow (KTGF) for rough spheres and rough walls, are validated for the first time for full three-dimensional (3D) bubbling fluidized beds. The validation is performed by comparing with experimental data from Magnetic Particle Tracking and more detailed Discrete Particle Model simulations. The effect of adding a third dimension is investigated by comparing pseudo-2D and full 3D bubbling fluidized beds containing inelastic rough particles. Spatial distributions of key hydrodynamic data as well as energy balances in the fluidized bed are compared. In the pseudo-2D bed, on comparison with the KTGF derived by Jenkins and Zhang, we find that the present KTGF improves the prediction of bed hydrodynamics. In the full 3D bed, particles are more homogeneously distributed in comparison with the pseudo-2D bed due to a decrease of the frictional effect from the front and back walls. The new model results are in good agreement with experimental data and discrete particle simulations for the time-averaged bed hydrodynamics.