We describe a technique for particle-based simulations of heterogeneous catalysis in open-cell foam structures, which is based on isotropic Stochastic Rotation Dynamics (iSRD) together with Constructive Solid Geometry (CSG). The approach is validated by means of experimental results for the low temperature water-gas shift reaction in an open-cell foam structure modeled as inverse sphere packing. Considering the relation between Sherwood and Reynolds number, we find two distinct regimes meeting approximately at the strut size Reynolds number 10. For typical parameters from the literature, we find that the catalyst density in the washcoat can be reduced considerably without a notable loss of conversion efficiency. We vary the porosity to determine optimum open-cell foam structures, which combine low flow resistance with high conversion efficiency and find large porosity values to be favorable not only in the mass transfer limited regime but also in the intermediate regime.

Aeroelasticity simulations increase in importance for aircraft design, requiring an efficient coupling of computational fluid dynamics (CFD) with computational structure mechanics (CSM) solvers. This contribution investigates the scalability of a high-fidelity CFD-CSM toolchain on modern high-performance computing (HPC) architectures. It consists of DLR's TAU solver for fluid dynamics simulations [1], and FlowSimulator [2] components for the incorporation of precomputed structural normal mode data, as well as for the underlying mesh deformations. The computational performance of the entire simulation pipeline is evaluated using a single measurement suite, allowing to identify bottlenecks of individual components and differences in their scalability. Preliminary improvements are realized via hybrid parallelization. Although this study focuses on a specific toolchain, key findings about scalability issues are relevant for complex CFD-CSM or other coupled simulations in general.

We describe a new computational method for the numerically stable particle-based simulation of open-boundary flows, including volume conserving chemical reactions. The novel method is validated for the case of heterogeneous catalysis against a reliable reference simulation and is shown to deliver identical results while the computational efficiency is significantly increased.

Particle tracking, that is, the repeated localization of particles within a grid by means of tracking the particles’ trajectories, is routinely applied in particle-based schemes where the domain is described by an unstructured polyhedral grid. A range of tracking algorithms are available in the literature, which are inherently similar to algorithmic approaches common both in event-driven particle dynamics (EDPD) and ray-tracing methods. We propose a reformulation of existing particle tracking algorithms in the context of EDPD. On the one hand, this resolves inconsistencies in the mapping between particle positions and grid cells triggered, e.g., by imperfect grids. More importantly, it allows the specification of solid objects via constructive solid geometry (CSG), a standard technique for the modeling of solids in computer-aided design. While usually considered contrary approaches, our description of the computational domain as the combination of a bounding volume defined by an unstructured grid and solids modeled via CSG embedded into this volume can be highly advantageous. The two different approaches of modeling the computational domain complement each other perfectly, as the CSG representation is not only efficient in terms of memory and computing time, but also avoids the challenges of generating finely resolved unstructured grids in the presence of complicated boundaries. These benefits, as well as the positive impact of several algorithmic optimizations of the extended tracking algorithm, are exemplified via a particle-based simulation of a gas flow through a highly porous medium.

In this paper we introduce an Intelligent Transport System (ITS), designed for enabling cooperative driving manoeuvres in mixed traffic scenarios considering heterogeneous communications and cloud infrastructure systems. We present an architecture that enables connected vehicles to access ITS services independent of their underlying communication technology. This is achieved by introducing a large scale communication system including the road-side infrastructure as well as a heterogeneous cloud. We present insights from the Automated Connected Vehicle (ACV) concept and examine human factors elaborating on the experience of two aspects: driving in an ACV as well as driving in a Non-Automated Connected Vehicle (NACV), interacting with an ACV. Furthermore, we present insights of initial demonstrations, emphasizing that the system works well in real traffic scenarios.

Cooperative Intelligent Transport Systems (C-ITS) have seen increased interest in recent years, with several ongoing activities and first practical implementations. While clearly V2X-communication will play a significant role in all C-ITS deployments, several key components, such as the wireless communication technology and the message formats, are still evolving. This calls for a modular approach when designing C-ITS infrastructure, especially when considering a real world urban environment. Such environments are characterized by heterogeneous traffic light hardware and traffic management systems. This paper focuses on the modular architecture of the C-ITS pilot in Dresden. For example, a highly flexible communication stack is developed for this special purpose. It fully supports the message types standardized by European Telecommunications Standards Institute (ETSI) on the one hand, while on the other hand allowing the rapid implementation and test of novel message types and contents. This went hand in hand with the development of a modular roadside unit, enabling the rapid implementation of service applications on its central processing unit. In combination with a cloud-based backend, a real-time C-ITS service platform with a hybrid communication concept is developed. This paper presents a modular architecture and best practice guidelines based on experiences of the C-ITS pilot in Dresden. First results of research topics, such as latency measurements, are shown. The ongoing C-ITS deployment in Dresden is part of the initiative "Synchrone Mobilität 2023", which aims at advancing Intelligent Transport Systems. Focusing on automated and connected driving in urban areas, the research and development projects under its umbrella initiate scientific and technological developments and provide comprehensive test facilities. Automated and connected driving in urban areas requires not only simulations and test drives on test sites but also enormous testing effort under real traffic conditions. The Dresden Testbed offers outstanding conditions to conduct real-world test with a multitude of test kilometers and the experience of different traffic scenarios.

The aim of Green Light Optimized Speed Advisory (GLOSA) systems is to assist individual vehicles approaching an intersection with speed advices (either as single target speed or as complex speed-distance relation) in order to fulfill a given objective. Common objectives include the minimization of fuel usage, emissions and/or delay. The literature provides a wide selection of GLOSA-algorithms addressing different aspects of a real world application, like surrounding traffic, fixed time or actuated traffic lights and mode of communication. However, previous research usually addressed only a subset of possible aspects. Therefore, our goal is to investigate how the existing algorithms hold up in a scenario under largely realistic conditions. We measure the performance (in terms of overall fuel usage, carbon dioxide emissions and delay) of the different GLOSA-algorithms and identify potential shortcomings.

Stochastic rotation dynamics (SRD) is a widely used method for the mesoscopic modeling of complex fluids, such as colloidal suspensions or multiphase flows. In this method, however, the underlying Cartesian grid defining the coarse-grained interaction volumes induces anisotropy. We propose an isotropic, lattice-free variant of stochastic rotation dynamics, termed iSRD. Instead of Cartesian grid cells, we employ randomly distributed spherical interaction volumes. This eliminates the requirement of a grid shift, which is essential in standard SRD to maintain Galilean invariance. We derive analytical expressions for the viscosity and the diffusion coefficient in relation to the model parameters, which show excellent agreement with the results obtained in iSRD simulations. The proposed algorithm is particularly suitable to model systems bound by walls of complex shape, where the domain cannot be meshed uniformly. The presented approach is not limited to SRD but is applicable to any other mesoscopic method, where particles interact within certain coarse-grained volumes.

Heterogeneous catalysis in metallic or ceramic foam structures represents a very promising alternative to catalysis in packed beds or monoliths. Due to high porosity, specific surface and tortuosity these structures provide excellent mass transport properties at moderate pressure drops [1]. Simulating catalysis in foam structures requires to merge reaction kinetics into gas dynamics within complex geometries. Particle based simulation methods are eminently suitable for this, allowing us to decouple the simulation grid and the boundary representation using constructive solid geometry. In order to completely eliminate the influence of the simulation grid, we propose an essentially grid-free variant of stochastic rotation dynamics, a popular numerical method for the modelling of fluids on mesoscopic scale [2, 3]. Instead of Cartesian grid cells, we use spherical coarse-grained interaction volumes, which we randomly distribute over the domain [4]. Employing this method together with constructive solid geometry, we investigate heterogeneous catalysis in open-cell foam structures, modelled by inverse sphere packings [5]. As prototype reaction we have chosen the low temperature water gas shift following the LangmuirHinshelwood reaction mechanism [6]. The foam structure serves as substrate and is assumed to be coated with CuO/ZnO/Al2O3 washcoat. The effective reaction rate in the washcoat layer is computed using precomputed look-up tables for the effectiveness factor [7]. Among other parameters, the effective reaction rate depends on the partial surface pressures of the reactants, which can be computed from the collision fluxes on the surface. Hence, the relevant quantities are evaluated exactly at the reactive boundary. Concerning particle based methods, pressure boundary conditions often suffer from instabilities, if not implemented carefully [8]. Therefore, we connect inlet and outlet via an extended periodic boundary condition allowing for discontinuities in the concentration field, while the density, temperature and the velocity fields are strictly periodic. In order to drive the flow, an external acceleration is applied. reactant concentration flow velocity u/umax

An algorithm for the exact calculation of the overlap volume of a sphere and a tetrahedron, wedge, or hexahedron is described. The method can be used to determine the exact local solid fractions for a system of spherical, non-overlapping particles contained in a complex mesh, a question of significant relevance for the numerical solution of many fluid-solid interaction problems. While challenging due to the limited machine precision, a numerically robust version of the calculation maintaining high computational efficiency is devised. The method is evaluated with respect to the numerical precision and computational cost. It is shown that the exact calculation is only limited by the machine precision and can be applied to a wide range of size ratios, contrary to previously published methods. Eliminating this constraint enables the usage of meshes with higher resolution near the system boundaries for coupled CFD–DEM simulations. The numerical robustness is further illustrated by applying the method to highly deformed mesh elements. The full source code of the reference implementation is made available under an open-source license.

We investigate the average turbulent wind field over a barchan dune by means of Computational Fluid Dynamics. We find that the fractional speed-up ratio of the wind velocity over the three-dimensional barchan shape differs from the one obtained from two-dimensional calculations of the airflow over the longitudinal cut along the dune’s symmetry axis — that is, over the equivalent transverse dune of same size. This finding suggests that the modeling of the airflow over the central slice of barchan dunes is insufficient for the purpose of the quantitative description of barchan dune dynamics as three-dimensional flow effects cannot be neglected.

Event-driven particle dynamics is a fast and precise method to simulate particulate systems of all scales. In this work it is demonstrated that, despite the high accuracy of the method, the finite machine precision leads to simulations entering invalid states where the dynamics are undefined. A general event-detection algorithm is proposed which handles these situations in a stable and efficient manner. This requires a definition of the dynamics of invalid states and leads to improved algorithms for event-detection in hard-sphere systems.

We study the mechanism leading to the formation of stripe-like patterns in a rectangular container filled with a sub-monolayer of frictional spherical particles when it is subjected to horizontal oscillations. By means of Molecular Dynamics simulations we could reproduce the experimental results. Systematic simulations allow to identify friction to be responsible for the pattern formation, that is, the tangential interaction between contacting particles and between the particles and the floor of the container. When particles are in contact with the floor and other adjacent particles simultaneously, there emerges a frustrated situation in which the particles are prevented from rolling on the floor. This effect leads to local jamming and eventually to stripe-like pattern formation. In the long time evolution, the stripes are unstable. Stripes may merge as well as disintegrate.

Event-Driven Particle Dynamics is a fast and precise method to simulate particulate systems of all scales. These advantages arise from the analytical solution of the dynamics required by the discrete-potential models used. Despite the high precision solution, the finite calculation-precision of computers will still cause the simulation to enter invalid states which, if left unchecked, can lead to unresolvable errors. In this work, the treatment of these marginal invalid-states is discussed and a general event-detection algorithm is proposed which stably handles these situations. This requires a definition of the dynamics of invalid states and leads to improved algorithms for event-detection in spherically symmetric systems, including the well-established hard-sphere and square-well models. Finally, the Event-Driven Particle Dynamics technique is extended to allow the study of systems with complex spherical-mesh boundary conditions and distance constraints as a demonstration of the generality of the proposed algorithm.