Numerical method for simulating tire rolling noise by the concept of periodically exciting contact force

For the numerical simulation of tire rolling noise, an important subject is the extraction of normal velocity data of the tire surface that are essential for the acoustic analysis. In the current study, a concept of periodically exciting contact force is introduced to effectively extract the tire normal velocity data. The ground contact pressure within contact patch that is obtained by the static tire contact analysis is periodically applied to the whole tread surface of stationary tire. The periodically exciting contact forces are sequentially applied with a time delay corresponding to the tire rolling speed. The tire vibration is analyzed by the mode superposition in the frequency domain, and the acoustic analysis is performed by commercial BEM code. The proposed method is illustrated through the numerical experiment of 3-D smooth tire model and verified from the comparison with experiment, and furthermore the acoustical responses are investigated to the tire rolling speed.     

A relaxed-PPA contraction method for sparse signal recovery

Sparse signal recovery is a topic of considerable interest, and the literature in this field is already quite immense. Many problems that arise in sparse signal recovery can be generalized as a convex programming with linear conic constraints. In this paper, we present a new proximal point algorithm (PPA) termed as relaxed-PPA (RPPA) contraction method, for solving this common convex programming. More precisely, we first reformulate the convex programming into an equivalent variational inequality (VI), and then efficiently explore its inner structure. In each step, our method relaxes the VI-subproblem to a tractable one, which can be solved much more efficiently than the original VI. Under mild conditions, the convergence of the proposed method is proved. Experiments with l ₁ analysis show that RPPA is a computationally efficient algorithm and compares favorably with the recently proposed state-of-the-art algorithms.     

An efficient threshold key-insulated signature scheme

To tackle the key-exposure problem in signature settings, this paper introduces a new cryptographic primitive named threshold key-insulated signature (TKIS) and proposes a concrete TKIS scheme. For a TKIS system, at least k out of n helpers are needed to update a user’s temporary private key. On the one hand, even if up to k−1 helpers are compromised in addition to the exposure of any of temporary private keys, security of the non-exposed periods is still assured. On the other hand, even if all the n helpers are compromised, we can still ensure the security of all periods as long as none of temporary private keys is exposed. Compared with traditional key-insulated signature (KIS) schemes, the proposed TKIS scheme not only greatly enhances the security of the system, but also provides flexibility and efficiency.     

Wind pressure distribution and wind-induced dynamic response for spatial groined latticed vaults

The wind pressure distribution and wind-induced vibration responses of long-span spatial groined latticed vaults (SGLVs) were numerically simulated, which always are ones of the most important problems in the structural wind resistance design. Incompressible visco-fluid model was introduced, and the standard k-εtwo equation model and semi-implicit method for pressure linked equation (SIMPLE) were used to describe the flow turbulence. Furthermore, the structural dynamic equation was set up, which is solved by Newmark-β method. And several sort of wind-induced vibration coefficients such as the wind-induced vibration coefficient corresponding to the nodal displacement responses and wind loads were suggested. In the numerical simulation where the SGLV consisting of the cylindrical sectors with different curved surface was chosen as the example,the influence on the relative wind pressure distribution and structural wind-induced vibration responses of the closed or open SGLV caused by such parameters as the number of cylindrical sectors, structural curvature and the ratio of rise to span was investigated. Finally, some useful conclusions on the local wind pressure distribution on the structural surface and the wind-induced vibration coefficients of SGLV were developed.     

Improvement of the second order approximation of the smoothed particle hydrodynamics

The smoothed particle hydrodynamics (SPH), as a fully Lagrangian particle method, has been successfully applied to astrophysical problems and extended to elastic dynamics and computational fluid dynamics.High order derivatives have to be approximated when elastic dynamics problems are modeled. However, the approximation errors in SPH could lead to computational failure in the case that the order of derivative is high.A novel method was proposed in order to improve the accuracy of SPH method, which shows the relationship between the selected functions and their SPH approximations. The entire involved system was represented by a finite number of particles that carry individual mass and occupy individual space, and the integral interpolation was approximated by a summation interpolation. In addition, error comparison was made between SPH method with and without the present improvement.     

Numerical modeling of ground response during diaphragm wall construction

Construction of diaphragm wall panels may cause considerable stress changes in heavily overconsolidated soil deposits and can induce substantial ground movement. The 3D Lagrangian method was adopted to model the mechanical response of ground, including horizontal normal stress and shear stress, lateral ground displacement and vertical ground surface settlement, during the slurry trenching and concreting of diaphragm wall panels. Numerical results show that slurry trenching leads to horizontal stress relief of ground, reducing the horizontal stress of the ground from initial K0 pressure to hydrostatic betonite pressure. Wet concrete pressure lies between the hydrostatic bentonite pressure and the initial K0 pressure, so it can compensate partially the horizontal stress loss of the ground adjacent to the trench and thus reduce the lateral movement of the trench face as well as the vertical settlement of the ground surface.     

A data model applied to the knowledge-based ICAS

Image-guided computer aided surgery system (ICAS) contributes to safeness and success of surgery operations by means of displaying anatomical structures and showing correlative information to surgeons in the process of operation. Based on analysis of requirements for ICAS, a new concept of clinical knowledge-based ICAS was proposed. Designing a reasonable data structure model is essential for realizing this new concept. The traditional data structure is limited in expressing and reusing the clinical knowledge such as locating an anatomical object, topological relations of anatomical objects and correlative clinical attributes. A data structure model called mixed adjacency lists by octree-path-chain (MALOC) was outlined, which can combine patient's images with clinical knowledge, as well as efficiently locate the instrument and search the objects' information. The efficiency of data structures was analyzed and experimental results were given in comparison to other traditional data structures. The result of the nasal surgery experiment proves that MALOC is a proper model for clinical knowledge-based ICAS that has advantages in not only locating the operative instrument precisely but also proving surgeons with real-time operation-correlative information. It is shown that the clinical knowledge-based ICAS with MALOC model has advantages in terms of safety and success of surgical operations, and help in accurately locating the operative instrument and providing operation-correlative knowledge and information to surgeons in the process of operations.     

Power network parameter estimation method based on data mining technology

The parameter values which actually change with the circumstances, weather and load level etc.produce great effect to the result of state estimation. A new parameter estimation method based on data mining technology was proposed. The clustering method was used to classify the historical data in supervisory control and data acquisition (SCADA) database as several types. The data processing technology was impliedto treat the isolated point, missing data and yawp data in samples for classified groups. The measurement data which belong to each classification were introduced to the linear regression equation in order to gain the regression coefficient and actual parameters by the least square method. A practical system demonstrates the high correctness, reliability and strong practicability of the proposed method.     

Analysis and improvement of authenticatable ring signcryption scheme

We show that the Zhang-Yang-Zhu-Zhang identity-based authenticatable ring signcryption scheme is not secure against chosen plaintext attacks.Furthermore, we propose an improved scheme that remedies the weakness of the Zhang-Yang-Zhu-Zhang scheme.The improved scheme has shorter ciphertext size than the Zhang-Yang-Zhu-Zhang scheme.We then prove that the improved scheme satisfies confidentiality, unforgeability, anonymity and authenticatability.     

Belief and fuzzy theories for driving behavior assessment in case of accident scenarios

The estimation of the overspeed risk before the accident is among the main goals of this paper. The proposed method uses the Energy Equivalent Speed (EES) to assess the severity of an eventual accident. However, the driver behavior evaluation should take into account the parameters related to the Driver, the Vehicle and the Environment (DVE) system. For this purpose, this paper considers a two-level strategy to predict the global risk of an event using the Dempster-Shafer Theory (DST) and the Fuzzy Theory (FT). This paper presents two methods to develop the Expert Model-based Basic Probability Assignment (EM based BPA), which is the most important task in the DST. The first one is based on the accident statistics and the second method deals with the relationship between the Fuzzy and Belief measurements. The experimental data is collected by one driver using our test vehicle and a Micro-intelligent Black Box (Micro-iBB) to collect the driving data. The sensitivity of the developed models is analysed. Our main evaluation concerns the Usage Based Insurance (UBI) applications based on the driving behavior. So, the obtained masses over the defined referential subsets in the DST are used as a score to compute the driver’s insurance premium.