Mobility in granular materials upon cyclic loading

We investigate the ability to move of large objects—referred to as intruders—embedded in a granular material and subjected to cyclic loadings. A discrete element method is used to simulate the dynamics response of intruders subjected to a vertical uplift cyclic force, exploring a wide range of loading magnitudes and frequencies. The analysis of the intruder and grains displacements over many cycles reveals three mobility regimes. In the first two regimes, called confined and failure the intruder either do not significantly move or consistently moves upward after each cycles. We introduce a physically based model considering an inertial drag force to rationalise the existence of these regimes depending on the loading frequency and magnitude. We further evidence a third intermediate regime of creep, where intruder trajectories exhibit long periods of confinement punctuated by shorter periods of sustained uplift motion. Finally, we observe unexpected failures at low loading magnitudes and specific frequencies, which we attribute to a process of elasto-inertial resonance. These results highlight the important differences in the mobility of intruders upon constant and cyclic loadings.     

Tunable picosecond blue and ultraviolet pulses from a diode-pumped laser system seeded by a gain-switched laser diode

Picosecond pulses emitted from a gain-switched laser diode have been amplified in a Ti:sapphire regenerative amplifier indirectly pumped by a 4-W laser diode. This all-solid-state system produced microjoule pulses tunable from 803 to 840 nm at repetition rates up to 25 kHz with durations of 70-100 ps. By frequency doubling and tripling the output, we generated blue and UV pulses tunable from 401 to 420 nm and from 268 to 280 nm, respectively. Average powers larger than 4 mW were reached in these two wavelength regions.     

Cost optimization of a hybrid composite flywheel rotor with a split-type hub using combined analytical/numerical models

A procedure to find the optimal design of a flywheel with a split-type hub is presented. Since cost plays a decisive role in stationary flywheel energy storage applications, a trade-off between energy and cost is required. Applying a scaling technique, the multi-objective design problem is reduced to the maximization of the energy-per-cost ratio as the single objective. Both an analytical and a finite element model were studied. The latter was found to be more than three orders of magnitude more computationally expensive than the analytical model, while the analytical model can only be regarded as a coarse approximation. Multifidelity approaches were examined to reduce the computational expense while retaining the high accuracy and large modeling depth of the finite element model. Using a surrogate-based optimization strategy, the computational cost was reduced to only one third in comparison to using only the finite element model. A nonlinear interior-point method was employed to find the optimal rim thicknesses and rotational speed. The benefits of the split-type hub architecture were demonstrated.     

On testing for serial correlation of unknown form using wavelet thresholding

Omnibus procedures for testing serial correlation are developed, using spectral density estimation and wavelet shrinkage. The asymptotic distributions of the wavelet coefficients under the null hypothesis of no serial correlation are derived. Under some general conditions on the wavelet basis, the wavelet coefficients asymptotically follow a normal distribution. Furthermore, they are asymptotically uncorrelated. Adopting a spectral approach and using results on wavelet shrinkage, new one-sided test statistics are proposed. As a spatially adaptive estimation method, wavelets can effectively detect fine features in the spectral density, such as sharp peaks and high frequency alternations. Using an appropriate thresholding parameter, shrinkage rules are applied to the empirical wavelet coefficients, resulting in a non-linear wavelet-based spectral density estimator. Consequently, the advocated approach avoids the need to select the finest scale J, since the noise in the wavelet coefficients is naturally suppressed. Simple data-dependent threshold parameters are also considered. In general, the convergence of the spectral test statistics toward their respective asymptotic distributions appears to be relatively slow. In view of that, Monte Carlo methods are investigated. In a small simulation study, several spectral test statistics are compared, with respect to level and power, including versions of these test statistics using Monte Carlo simulations.     

Discrepancy search for the flexible job shop scheduling problem

The flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop problem in which each operation must be processed on a given machine chosen among a finite subset of candidate machines. The aim is to find an allocation for each operation and to define the sequence of operations on each machine, so that the resulting schedule has a minimal completion time. We propose a variant of the climbing discrepancy search approach for solving this problem. We also present various neighborhood structures related to assignment and sequencing problems. We report the results of extensive computational experiments carried out on well-known benchmarks for flexible job shop scheduling. The results demonstrate that the proposed approach outperforms the best-known algorithms for the FJSP on some types of benchmarks and remains comparable with them on other ones.     

Optimal synthesis of planar mechanisms via an extensible-link approach

This paper presents a novel approach to optimize the design of planar mechanisms with revolute joints for function generation or path synthesis. The proposed method is based on the use of an extensible-link mechanism model whose strain energy is minimized to find the optimal rigid design. This enables us to get rid of assembly constraints and the use of natural coordinates makes the objective function simpler. Two optimization strategies are developed and then discussed. The first one relies on alternate optimizations of design parameters and point coordinates. The second one uses multiple partial syntheses as starting point for a full synthesis process. The question of finding the global optimum is also addressed and developed. A simple algorithm is proposed to find several local optima among which the designer may choose the best one taking other criteria into account (e.g. stiffness, collision, size,...). Three applications are presented to illustrate the strategies while mentioning their limits.     

A simple model for laser drilling

A simple mathematical model of laser drilling is proposed. Assuming axi-symmetry of the process around the axis of the laser beam, a one-dimensional formulation is obtained after cross-sectional averaging. The novelty of the approach relies on the fact that even after dimension reduction, the shape of the hole can still be described. The model is derived, implemented and validated for drilling using lasers with intensities in the GW/cm² range and microsecond pulses.     

Project scheduling under resource constraints: Application of the cumulative global constraint in a decision support framework

This paper concerns project scheduling under resource constraints. Traditionally, the objective is to find a unique solution that minimizes the project makespan, while respecting the precedence constraints and the resource constraints. This work focuses on developing a model and a decision support framework for industrial application of the cumulative global constraint. For a given project scheduling, the proposed approach allows the generation of different optimal solutions relative to the alternate availability of outsourcing and resources. The objective is to provide a decision-maker an assistance to construct, choose, and define the appropriate scheduling program taking into account the possible capacity resources. The industrial problem under consideration is modeled as a constraint satisfaction problem (CSP). It is implemented under the constraint programming language CHIP V5. The provided solutions determine values for the various variables associated to the tasks realized on each resource, as well as the curves with the profile of the total consumption of resources on time.