Dynamic stability of externally pressurized elastic rings subjected to high rates of loading

Of interest here is the influence of loading rate on the stability of structures where inertia is taken into account, with particular attention to the comparison between static and dynamic buckling. This work shows the importance of studying stability via perturbations of the initial conditions, since a finite velocity governs the propagation of disturbances. The method of modal analysis that determines the fastest growing wavelength, currently used in the literature to analyze dynamic stability problems, is meaningful only for cases where the velocity of the perfect structure is significantly lower than the associated wave propagation speeds.     

Josephson effect through an isotropic magnetic molecule

We study the Josephson effect through a quantum dot magnet whose spin is isotropic and which is coupled to the dot electron spin via exchange coupling. We calculate the Andreev levels and the supercurrent and examine the intertwined effect of the exchange coupling, Kondo correlation, and superconductivity. The former suppresses Kondo correlations, which triggers phase transitions from the 0 to the pi state, but strong antiferromagnetic coupling restores the 0 state. The asymmetric phase diagram in the exchange coupling suggests that the coupling sign could be determined in experiments.     

An asymptotic Reissner–Mindlin plate model

A mathematical study via variational convergence of a periodic distribution of classical linearly elastic thin plates softly abutted together shows that it is not necessary to use a different continuum model nor to make constitutive symmetry hypothesis as starting points to deduce the Reissner–Mindlin plate model.     

Routing a mix of conventional,plug-in hybrid,and electric vehicles

We introduce an electric vehicle routing problem combining conventional, plug-in hybrid, and electric vehicles. Electric vehicles are constrained in their service range by their battery capacity, and may require time-consuming recharging operations at some specific locations. Plug-in hybrid vehicles have two engines, an internal combustion engine and an electric engine using a built-in rechargeable battery. These vehicles can avoid visits to recharging stations by switching to fossil fuel. However, this flexibility comes at the price of a generally higher consumption rate and utility cost.To solve this complex problem variant, we design a sophisticated metaheuristic which combines a genetic algorithm with local and large neighborhood search. All route evaluations, within the approach, are based on a layered optimization algorithm which combines labeling techniques and greedy evaluation policies to insert recharging stations visits in a fixed trip and select the fuel types. The metaheuristic is finally hybridized with an integer programming solver, over a set partitioning formulation, so as to recombine high-quality routes from the search history into better solutions. Extensive experimental analyses are conducted, highlighting the good performance of the algorithm and the contribution of each of its main components. Finally, we investigate the impact of fuel and energy cost on fleet composition decisions. Our experiments show that a careful use of a mixed fleet can significantly reduce operational costs in a large variety of price scenarios, in comparison with the use of a fleet composed of a single vehicle class.     

Implicit depot assignments and rotations in vehicle routing heuristics

Vehicle routing variants with multiple depots and mixed fleet present intricate combinatorial aspects related to sequencing choices, vehicle type choices, depot choices, and depots positioning. This paper introduces a dynamic programming methodology for efficiently evaluating compound neighborhoods combining sequence-based moves with an optimal choice of vehicle and depot, and an optimal determination of the first customer to be visited in the route, called rotation. The assignment choices, making the richness of the problem, are thus no more addressed in the solution structure, but implicitly determined during each move evaluation. Two meta-heuristics relying on these concepts, an iterated local search and a hybrid genetic algorithm, are presented. Extensive computational experiments demonstrate the remarkable performance of these methods on classic benchmark instances for multi-depot vehicle routing problems with and without fleet mix, as well as the notable contribution of the implicit depot choice and positioning methods to the search performance. New state-of-the-art results are obtained for multi-depot vehicle routing problems (MDVRP), and multi-depot vehicle fleet mix problems (MDVFMP) with unconstrained fleet size. The proposed concepts are fairly general, and widely applicable to many other vehicle routing variants.     

An Efficient RuII–RhIII–RuII Polypyridyl Photocatalyst for Visible‐Light‐Driven Hydrogen Production in Aqueous Solution

The development of multicomponent molecular systems for the photocatalytic reduction of water to hydrogen has experienced considerable growth since the end of the 1970s. Recently, with the aim of improving the efficiency of the catalysis, single‐component photocatalysts have been developed in which the photosensitizer is chemically coupled to the hydrogen‐evolving catalyst in the same molecule through a bridging ligand. Until now, none of these photocatalysts has operated efficiently in pure aqueous solution: a highly desirable medium for energy‐conversion applications. Herein, we introduce a new ruthenium–rhodium polypyridyl complex as the first efficient homogeneous photocatalyst for H₂ production in water with turnover numbers of several hundred. This study also demonstrates unambiguously that the catalytic performance of such systems linked through a nonconjugated bridge is significantly improved as compared to that of a mixture of the separate components.