Development of a knowledge-based and collaborative engineering design agent

In order to avoid errors in engineering design that affect the later product life cycle, especially the manufacturing process, an analysis or evaluation has to be performed at the earliest possible stage. As this evaluation is very knowledge-intensive and often this knowledge is not directly available to the engineer, this paper presents an approach for a knowledge-based and collaborative engineering design agent. The technology based on multi-agent systems enables problem-solving support by an autonomous knowledge-based system which has its own beliefs, goals, and intentions. The presented approach is embedded in a CAD development environment and validated on an application example from engineering design

Utilising Assured Multi-Agent Reinforcement Learning within safety-critical scenarios

Multi-agent reinforcement learning allows a team of agents to learn how to work together to solve complex decision-making problems in a shared environment. However, this learning process utilises stochastic mechanisms, meaning that its use in safety-critical domains can be problematic. To overcome this issue, we propose an Assured Multi-Agent Reinforcement Learning (AMARL) approach that uses a model checking technique called quantitative verification to provide formal guarantees of agent compliance with safety, performance, and other non-functional requirements during and after the reinforcement learning process. We demonstrate the applicability of our AMARL approach in three different patrolling navigation domains in which multi-agent systems must learn to visit key areas by using different types of reinforcement learning algorithms (temporal difference learning, game theory, and direct policy search). Furthermore, we compare the effectiveness of these algorithms when used in combination with and without our approach. Our extensive experiments with both homogeneous and heterogeneous multi-agent systems of different sizes show that the use of AMARL leads to safety requirements being consistently satisfied and to better overall results than standard reinforcement learning

Convolution surfaces with varying radius: Formulae for skeletons made of arcs of circles and line segments

International audienceWe develop closed form formulae for the computation of the defining fields of convolutions surfaces. The formulae are obtained for power inverse kernels with skeletons made of line segments or arcs of circle. To obtain the formulae we use Creative Telescoping and describe how this technique can be used for other families of kernels and skeleton primitives. We apply the new formulae to obtain convolution surfaces around $\mathcal{G}^1$ skeletons, some of them closed curves. We showcase how the use of arcs of circles greatly improves the visualization of the surface around a general curve compared with a segment based approach

Preface

International audienc

Energy Transfer Between Coherently Delocalized States in Thin Films of the Explosive Pentaerythritol Tetranitrate (PETN) Revealed by Two-Dimensional Infrared Spectroscopy

Pentaerythritol tetranitrate (PETN) is a common secondary explosive and has been used extensively to study shock initiation and energy propagation in energetic materials. We report 2D IR measurements of PETN thin films that resolve vibrational energy transfer and relaxation mechanisms. Ultrafast anisotropy measurements reveal a sub-500 fs reorientation of transition dipoles in thin films of vapor-deposited PETN that is absent in solution measurements, consistent with intermolecular energy transfer. The anisotropy is frequency dependent, suggesting spectrally heterogeneous vibrational relaxation. Cross peaks are observed in 2D IR spectra that resolve a specific energy transfer pathway with a 2 ps time scale. Transition dipole coupling calculations of the nitrate ester groups in the crystal lattice predict that the intermolecular couplings are as large or larger than the intramolecular couplings. The calculations match well with the experimental frequencies and the anisotropy, leading us to conclude that the observed cross peak is measuring energy transfer between two eigenstates that are extended over multiple PETN molecules. Measurements of the transition dipole strength indicate that these vibrational modes are coherently delocalized over at least 15–30 molecules. We discuss the implications of vibrational relaxation between coherently delocalized eigenstates for mechanisms relevant to explosives

Epidemiology of a major honey bee pathogen, deformed wing virus: potential worldwide replacement of genotype A by genotype B

The western honey bee (Apis mellifera) is of major economic and ecological importance, with elevated rates of colony losses in temperate regions over the last two decades thought to be largely caused by the exotic ectoparasitic mite Varroa destructor and deformed wing virus (DWV), which the mite transmits. DWV currently exists as two main genotypes: the formerly widespread DWV-A and the more recently described and rapidly expanding DWV-B. It is an excellent system to understand viral evolution and the replacement of one viral variant by another. Here we synthesise published results on the distribution and prevalence of DWV-A and -B over the period 2008–2021 and present novel data for Germany, Italy and the UK to suggest that (i) DWV-B has rapidly expanded worldwide since its first description in 2004 and (ii) that it is potentially replacing DWV-A. Both genotypes are also found in wild bee species. Based on a simple mathematical model, we suggest that interference between viral genotypes when co-infecting the same host is key to understanding their epidemiology. We finally discuss the consequences of genotype replacement for beekeeping and for wild pollinator species

Diffusion-Assisted Photoexcitation Transfer in Coupled Semiconducting Carbon Nanotube Thin Films

We utilize femtosecond transient absorption spectroscopy to study dynamics of photo­excitation migration in films of semi­conducting single-wall carbon nanotubes. Films of nanotubes in close contact enable energy migration such as needed in photovoltaic and electro­luminescent devices. Two types of films composed of nanotube fibers are utilized in this study: densely packed and very porous. By comparing exciton kinetics in these films, we characterize excitation transfer between carbon nanotubes inside fibers <i>versus</i> between fibers. We find that intrafiber transfer takes place in both types of films, whereas interfiber transfer is greatly suppressed in the porous one. Using films with different nanotube composition, we are able to test several models of exciton transfer. The data are inconsistent with models that rely on through-space interfiber energy transfer. A model that fits the experimental results postulates that interfiber transfer occurs only at intersections between fibers, and the excitons reach the intersections by diffusing along the long-axis of the tubes. We find that time constants for the inter- and intrafiber transfers are 0.2–0.4 and 7 ps, respectively. In total, hopping between fibers accounts for about 60% of all exciton downhill transfer prior to 4 ps in the dense film. The results are discussed with regards to transmission electron micrographs of the films. This study provides a rigorous analysis of the photophysics in this new class of promising materials for photovoltaics and other technologies