Three-dimensional modelling on the hydrodynamics of a circulating fluidised bed

The rapid depletion of oil and the environmentalimpact of combustion has motivated the search for cleancombustion technologies. Fluidised bed combustion (FBC)technology works by suspending a fuel over a fast air inletwhilst sustaining the required temperatures. Using biomassor a mixture of coal/biomass as the fuel, FBC provides alow-carbon combustion technology whilst operating at lowtemperatures. Understanding the hydrodynamic processes influidised beds is essential as the flow behaviours causing heatdistributions and mixing determine the combustion processes.The inlet velocities and different particle sizes influence theflow behaviour significantly, particularly on the transitionfrom bubbling to fast fluidising regimes. Computationalmodelling has shown great advancement in its predictive capabilityand reliability over recent years. Whilst 3D modellingis preferred over 2D modelling, the majority of studies use2D models for multiphase models due to computational costconsideration. In this paper, two-fluid modelling (TFM) isused to model a 3D circulating fluidised bed (CFB) initiallyfocussing on fluid catalytic cracker (FCC) particles. Thetransition from bubbling to fast fluidisation over a rangeof velocities is explored, whilst the effects on the bubblediameter, particle distributions and bed expansion for differentparticle properties including particle sizes are compared. Dragmodels are also compared to study the effects of particleclustering at the meso-scale

Learning Deep CNN Denoiser Prior for Image Restoration

Model-based optimization methods and discriminative learning methods have been the two dominant strategies for solving various inverse problems in low-level vision. Typically, those two kinds of methods have their respective merits and drawbacks, e.g., model-based optimization methods are flexible for handling different inverse problems but are usually time-consuming with sophisticated priors for the purpose of good performance; in the meanwhile, discriminative learning methods have fast testing speed but their application range is greatly restricted by the specialized task. Recent works have revealed that, with the aid of variable splitting techniques, denoiser prior can be plugged in as a modular part of model-based optimization methods to solve other inverse problems (e.g., deblurring). Such an integration induces considerable advantage when the denoiser is obtained via discriminative learning. However, the study of integration with fast discriminative denoiser prior is still lacking. To this end, this paper aims to train a set of fast and effective CNN (convolutional neural network) denoisers and integrate them into model-based optimization method to solve other inverse problems. Experimental results demonstrate that the learned set of denoisers not only achieve promising Gaussian denoising results but also can be used as prior to deliver good performance for various low-level vision applications.Comment: Accepted to CVPR 2017. Code: https://github.com/cszn/ircn

Cascaded uncoupled dual-ring modulator

We demonstrate that by coherent driving two uncoupled rings in same direction, the effective photon circulating time in the dual ring modulator is reduced, with increased modulation quality. The inter-ring detuning dependent photon dynamics, Q-factor, extinction ratio and optical modulation amplitude of two cascaded silicon ring resonators are studied and compared with that of a single ring modulator. Experimentally measured eye diagrams, together with coupled mode theory simulations, demonstrate the enhancement of dual ring configuration at 20 Gbps with a Q ~ 20,000

Numerical and experimental investigations of self-piercing riveting

Self-pierce riveting (SPR) is a new high-speed mechanical fastening technique which is suitable for point joining dissimilar sheet materials, as well as coated and pre-painted sheet materials. With increasing application of SPR in different industrial fields, the demand for a better understanding of the knowledge of static and dynamic characteristics of the SPR joints is required. In this paper, the SPR process has been numerically simulated using the commercial finite element (FE) software LS-Dyna. For validating the numerical simulation of the SPR process, experimental tests on specimens made of aluminium alloy have been carried out. The online window monitoring technique was introdu introdu ced in the tests for evaluating the quality of SPR joints. Good agreements between the simulations and the tests have been found, both with respect to the force-travel (time) curves as well as the deformed shape on the cross-section of SPR joint. Monotonic tensile tests were carried out to measure the ultimate tensile strengths for SPR joints with different material combinations. Deformation and failure of the SPR joints under monotonic tensile loading were studied. The normal hypothesis tests were performed to examine the rationality of the test data. This work was also aimed at evaluating experimentally and comparing the strength and energy absorption of SPR joints and SPR-bonded hybrid joints

Topological flat band models with arbitrary Chern numbers

We report the theoretical discovery of a systematic scheme to produce topological flat bands (TFBs) with arbitrary Chern numbers. We find that generically a multi-orbital high Chern number TFB model can be constructed by considering multi-layer Chern number C=1 TFB models with enhanced translational symmetry. A series of models are presented as examples, including a two-band model on a triangular lattice with a Chern number C=3 and an $N$-band square lattice model with $C=N$ for an arbitrary integer $N$. In all these models, the flatness ratio for the TFBs is larger than 30 and increases with increasing Chern number. In the presence of appropriate inter-particle interactions, these models are likely to lead to the formation of novel Abelian and Non-Abelian fractional Chern insulators. As a simple example, we test the C=2 model with hardcore bosons at 1/3 filling and an intriguing fractional quantum Hall state is observed.Comment: 8 pages, 7 figure