Statistics of the active temperature and passive concentration advected by the one-dimensional stationary compressible turbulence at Reλ=2.56×106 and Mt=1.0 is investigated by using direct numerical simulation w...
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Statistics of the active temperature and passive concentration advected by the one-dimensional stationary compressible turbulence at Reλ=2.56×106 and Mt=1.0 is investigated by using direct numerical simulation with all-scale forcing. It is observed that the signal of velocity, as well as the two scalars, is full of small-scale sawtooth structures. The temperature spectrum corresponds to G(k)∝k−5/3, whereas the concentration spectrum acts as a double power law of H(k)∝k−5/3 and H(k)∝k−7/3. The probability distribution functions (PDFs) for the two scalar increments show that both δT and δC are strongly intermittent at small separation distance r and gradually approach the Gaussian distribution as r increases. Simultaneously, the exponent values of the PDF tails for the large negative scalar gradients are qθ=−4.0 and qζ=−3.0, respectively. A single power-law region of finite width is identified in the structure function (SF) of δT; however, in the SF of δC, there are two regions with the exponents taken as a local minimum and a local maximum. As for the scalings of the two SFs, they are close to the Burgers and Obukhov-Corrsin scalings, respectively. Moreover, the negative filtered flux at large scales and the time-increasing total variance give evidences to the existence of an inverse cascade of the passive concentration, which is induced by the implosive collapse in the Lagrangian trajectories.
This paper focuses on the problem of fuzzy control for a class of continuous-time T-S fuzzy systems. New methods of stabilization design and H-infinity control are derived based on a relaxed approach in which both fuz...
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This paper focuses on the problem of fuzzy control for a class of continuous-time T-S fuzzy systems. New methods of stabilization design and H-infinity control are derived based on a relaxed approach in which both fuzzy Lyapunov functions and staircase membership functions are used. Through the staircase membership functions approx- imating the continuous membership functions of the given fuzzy model, the membership functions can be brought into the design conditions of fuzzy systems, thereby significantly reducing the conservativeness in the recent fuzzy controller design methods. Unlike some previous fuzzy Lyapunov function approaches reported in the literatures, the proposed design techniques of stabilization and H-infinity control do not depend on the time-derivative of the membership functions that may be pointed out as the main source of conservatism when considering fuzzy Lyapunov functions analysis. Moreover, conditions for the solvability of the controller design given here are written in the form of linear matrix inequalities, but not bilinear matrix inequalities, which are easier to be solved by convex optimization techniques. Simulation examples are given to demonstrate the validity and applicability of the proposed approaches.
Turbulence in the compressible channel flow is studied by direct numerical simulation at Re= 430 with Ma = 1.5,3.0,6.0 and modelled by multi-layer structure *** an extension of the mixing length for incompressible flo...
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Turbulence in the compressible channel flow is studied by direct numerical simulation at Re= 430 with Ma = 1.5,3.0,6.0 and modelled by multi-layer structure *** an extension of the mixing length for incompressible flow,an efficient Reynolds stress is defined and a closure new length order function LM in stream-
In this paper, we study the problem of learning from weakly labeled data, where labels of the training examples are incomplete. This includes, for example, (i) semi-supervised learning where labels are partially known...
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In this paper, we study the problem of learning from weakly labeled data, where labels of the training examples are incomplete. This includes, for example, (i) semi-supervised learning where labels are partially known; (ii) multi-instance learning where labels are implicitly known; and (iii) clustering where labels are completely unknown. Unlike supervised learning, learning with weak labels involves a difficult Mixed-Integer Programming (MIP) problem. Therefore, it can suffer from poor scalability and may also get stuck in local minimum. In this paper, we focus on SVMs and propose the WELLSVM via a novel label generation strategy. This leads to a convex relaxation of the original MIP, which is at least as tight as existing convex Semi-Definite Programming (SDP) relaxations. Moreover, the WELLSVM can be solved via a sequence of SVM subproblems that are much more scalable than previous convex SDP relaxations. Experiments on three weakly labeled learning tasks, namely, (i) semi-supervised learning; (ii) multi-instance learning for locating regions of interest in content-based information retrieval; and (iii) clustering, clearly demonstrate improved performance, and WELLSVM is also readily applicable on large data sets.
The majority of the energy consumption by the sensors is the energy requirement for data transmission in Wireless Sensor Networks （WSNs）. Therefore, introducing mobile collectors to collect data instead of nmlti-hop...
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The majority of the energy consumption by the sensors is the energy requirement for data transmission in Wireless Sensor Networks （WSNs）. Therefore, introducing mobile collectors to collect data instead of nmlti-hop data relay is essential. However, for rmny proposed data gathering ap-proaches, long data deNNy is the train problenm. Hence, the problem of how to decrease the energy consumption and the data deNNy needs to be solved. In this paper, a low deNNy data collection mechanism using multiple mobile collectors is pro- posed. First, a self-organization clustering algorithm is designed. Second, sensor nodes are organized into three-level clusters. Then a collection strategy based on the hierarchical structure is proposed, which includes two rules to dispatch mobile collec- tors rationally. Simulation results show that the proposed mechanism is superior to other existing approaches in terms of the reduction in energy ex-penditure and the decrease in data deNNy.
The effects of thermal pretreatment on pyrolysis behavior of Shengli lignite were investigated in a fixed bed reactor. In comparison with raw coal, the thermally pretreated coal has lower content of hydroxyl group and...
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The effects of thermal pretreatment on pyrolysis behavior of Shengli lignite were investigated in a fixed bed reactor. In comparison with raw coal, the thermally pretreated coal has lower content of hydroxyl group and lower ratio of aromatic-H to aliphatic-H. The yield of pyrolysis water is lowered after thermal pretreatment in N2, N2+O2 and CO2 atmospheres. The pretreatment also causes a higher CO2 content in pyrolysis gas, which thus lowers the heating value of the gas. Pretreating the coal in superheated steam raises the tar yield by 3~4 weight percentage points, and the composition of tar varies with the atmosphere and temperature of the pretreatment. The light fraction (with boiling points below 360°C ) increased by 27 weight percentage points by pretreatment in 200°C -steam. The pretreatments at 200 and 250°C in the mixture of steam and simulated flue gas elevate the light oil and phenol oil fractions in tar by 60 and 42 weight percentage points, respectively.
Chosen-ciphertext security has been well-accepted as a standard security notion for public key encryption. But in a multi-user surrounding, it may not be sufficient, since the adversary may corrupt some users to get t...
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The stream cipher A2U2 proposed by David et al. [7] is one of lightweight cipher primitives. In this paper we present a real-time key recovery attack on A2U2 under the known-plaintext-attack model, which only needs at...
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Traffic signal coordination has long been a hot topic in Intelligent Transportation systems (ITS) research. Simulation-based optimization is an important method to optimize the coordination designs as the traffic syst...
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