1,723,764 research outputs found
Large Eddy Simulation of Spanwise Rotating Turbulent Channel Flow with Subgrid-Scale Eddy Viscosity Model Based on Helicity
No full textFully developed rotating turbulent channel flow (RTCF) has been numerically investigated using large-eddy simulation (LES). The subgrid-scale (SGS) eddy viscosity model is base on an SGS helicity dissipation balance and the spectral relative helicity. Posterior test has been implemented to an RTCF with rotation in spanwise direction. The friction Reynolds number Re-tau = u(tau)delta / nu based on wall shear velocity u(tau) half width of the channel delta and the kinematic viscosity nu is 180. Two rotation numbers Ro(tau) =2 Omega delta / u(tau) equal to 22 and 80 have been computed with respective grid resolution. The results from dynamic Smagorinsky model (DSM) and direct numerical simulation (DNS) are used as references. The results demonstrate that the eddy viscosity model can predict both the precise velocity profile and the turbulent intensity
Cohomological rank functions on abelian varieties
Full text linkGeneralizing the continuous rank function of Barja-Pardini-Stoppino, in this paper
we consider cohomological rank functions of Q-twisted (complexes of) coherent sheaves on abelian varieties. They satisfy a natural transformation formula with respect to the Fourier-Mukai-Poincaré transform, which has several consequences. In many concrete geometric contexts these functions provide
useful invariants. We illustrate this with two different applications, the first one to GV-subschemes and
the second one to multiplication maps of global sections of ample line bundles on abelian varieties
A set based probabilistic approach to threshold design for optimal fault detection
No full textTraditional deterministic robust fault detection threshold designs, such as the norm-based or limit-checking method, are plagued by high conservativeness, which leads to poor fault detection performance. On one side they are ill-suited at tightly bounding the healthy residuals of uncertain nonlinear systems, as such residuals can take values in arbitrarily shaped, possibly non-convex regions. On the other hand, they must be robust even to worst-case, rare values of the modeling and measurement uncertainties. In order to maximize performance of detection, we propose two innovative ideas. First, we introduce threshold sets, parametrized in a way to bound arbitrarily well the residuals produced in healthy condition by an observer-based residual generator. Secondly, we formulate a chance-constrained cascade optimization problem to determine such a set, leading to optimal detection performance of a given class of faults, while guaranteeing robustness in a probabilistic sense. We then provide a computationally tractable framework by using randomization techniques, and a simulation analysis where a well-known three-tank benchmark system is considered.Accepted Author ManuscriptTeam Tamas KeviczkyTeam Jan-Willem van Wingerde
Crack Propagation and Intelligent Prediction in Asphalt Pavements Under Moving Loads
No full textAsphalt pavements are prone to crack initiation and propagation under the interaction of moving loads and natural environmental conditions, significantly reducing their performance and lifespan. Guided by fracture mechanics theory, this study investigates the mechanisms and key influencing factors of crack propagation in asphalt pavements subjected to moving loads through an integrated approach combining finite element simulation with back propagation (BP) neural network-based prediction. A three-dimensional pavement model containing a longitudinal crack was developed in ABAQUS to analyze the evolution of stress intensity factors KI and KII at the crack tip. The influences of vehicle speed, load level, and structural parameters, including the thickness and elastic modulus of the surface, base, and sub-base layers, were examined. The results show that low-speed driving and overloading markedly increase the peak values of KI and KII, thereby accelerating crack propagation. A decrease in the thickness of the surface layer or an increase in its elastic modulus greatly raises stress intensity factors, while the influence of base and sub-base parameters is relatively limited. A decrease in surface layer thickness or an increase in its elastic modulus significantly elevates the stress intensity factors, whereas the effects of base and sub-base parameters are relatively minor. The developed BP neural network-based prediction model achieves accurate estimation of KI and KII, with average errors below 3%, thereby offering a practical and efficient tool for rapid assessment of pavement cracking resistance. These findings furnish a theoretical foundation for the optimized design of asphalt pavements and the development of maintenance strategies, while also establishing a basis for future research on crack propagation under multi-factor coupling conditions
AE monitoring of crack evolution on UHPC deck layer of a long-span cable-stayed bridge
Full text linkThe UHPC deck layer may be susceptible to cracking during construction, raising concerns for bridge engineering utilizing this advanced material. Addressing the issue of drying shrinkage cracking observed on the UHPC deck layer of a cable-stayed bridge, a real-time investigation into crack evolution was conducted. This study employed acoustic emission (AE) technique with in-situ data processing, focusing on AE time series analysis. Additionally, triangulation techniques were utilized to determine the AE source positions of active cracks. The results showed continuous crack evolution on the UHPC deck layer, mainly due to construction vehicles, with two major instances of crack propagation and arrest. AE signals correlated with measured crack propagation, with two major AE events matching recorded crack jumps. Later AE sources indicated a step-by-step crack tip advancement. This paper underscores the effectiveness of the AE technique for crack identification and real-time monitoring of in-service bridges
Dual-wavelength digital holographic phase reconstruction based on a polarizationmultiplexing configuration
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