Joint probability distribution of winds and waves from wave simulation of 20 years (1989-2008) in Bohai Bay

The joint probability distribution of wind speed and significant wave height in the Bohai Bay was investigated by comparing the Gurnbel logistic model, the Gumbel-Hougaard （GH） copula function, and the Clayton copula function. Twenty years of wind data from 1989 to 2008 were collected from the European Centre for Medium-Range Weather Forecasts （ECMWF） database and the blended wind data of the Quick Scatterometer （QSCAT） satellite data set and re-analysis data from the United States National Centers for Environmental Prediction （NCEP）. Several typhoons were taken into account and merged with the background wind fields from the ECMWF or QSCAT/NCEP database. The 20-year data of significant wave height were calculated with the unstructured-grid version of the third-generation wind wave model Simulating WAves Nearshore （SWAN） under extreme wind process conditions. The Gumbel distribution was used for univariate and marginal distributions. The distribution parameters were estimated with the method of L-moments. Based on the marginal distributions, the joint probability distributions, the associated return periods, and the conditional probability distributions were obtained. The GH copula function was found to be optimal according to the ordinary least squares （OLS） test. The results show that wind waves are the prevailing type of wave in the Bohai Bay.

Joint modelling of location and scale parameters of the skew-normal distribution

Joint location and scale models of the skew-normal distribution provide useful ex- tension for joint mean and variance models of the normal distribution when the data set under consideration involves asymmetric outcomes. This paper focuses on the maximum likelihood estimation of joint location and scale models of the skew-normal distribution. The proposed procedure can simultaneously estimate parameters in the location model and the scale model. Simulation studies and a real example are used to illustrate the proposed methodologies.

Finite element analysis of stress and strain distributions in mortise and loose tenon furniture joints

We studied the effect of loose tenon dimensions on stress and strain distributions in T-shaped mortise and loose tenon （M＆amp;LT） furni-ture joints under uniaxial bending loads, and determined the effects of loose tenon length （30, 45, 60, and 90 mm） and loose tenon thickness （6 and 8 mm） on bending moment capacity of M＆amp;LT joints constructed with polyvinyl acetate （PVAc） adhesive. Stress and strain distributions in joint elements were then estimated for each joint using ANSYS finite element （FE） software. The bending moment capacity of joints increased significantly with thickness and length of the tenon. Based on the FE analysis results, under uniaxial bending, the highest shear stress values were obtained in the middle parts of the tenon, while the highest shear elastic strain values were estimated in glue lines between the tenon sur-faces and walls of the mortise. Shear stress and shear elastic strain values in joint elements generally increased with tenon dimensions and corre-sponding bending moment capacities. There was consistency between predicted maximum shear stress values and failure modes of the joints.

Parametric message passing-based relative navigation in joint tactical information distribution system

Relative navigation is a key feature in the joint tactical information distribution system（JTIDS）.A parametric message passing algorithm based on factor graph is proposed to perform relative navigation in JTIDS.First of all,the joint posterior distribution of all the terminals＇ positions is represented by factor graph.Because of the nonlinearity between the positions and time-of-arrival（TOA） measurement,messages cannot be obtained in closed forms by directly using the sum-product algorithm on factor graph.To this end,the Euclidean norm is approximated by Taylor expansion.Then,all the messages on the factor graph can be derived in Gaussian forms,which enables the terminals to transmit means and covariances.Finally,the impact of major error sources on the navigation performance are evaluated by Monte Carlo simulations,e.g.,range measurement noise,priors of position uncertainty and velocity noise.Results show that the proposed algorithm outperforms the extended Kalman filter and cooperative extended Kalman filter in both static and mobile scenarios of the JTIDS.

Bayesian Joint Modelling of Survival Time and Longitudinal CD4 Cell Counts Using Accelerated Failure Time and Generalized Error Distributions

Survival of HIV/AIDS patients is crucially dependent on comprehensive and targeted medical interventions such as supply of antiretroviral therapy and monitoring disease progression with CD4 T-cell counts. Statistical modelling approaches are helpful towards this goal. This study aims at developing Bayesian joint models with assumed generalized error distribution (GED) for the longitudinal CD4 data and two accelerated failure time distributions, Lognormal and loglogistic, for the survival time of HIV/AIDS patients. Data are obtained from patients under antiretroviral therapy follow-up at Shashemene referral hospital during January 2006-January 2012 and at Bale Robe general hospital during January 2008-March 2015. The Bayesian joint models are defined through latent variables and association parameters and with specified non-informative prior distributions for the model parameters. Simulations are conducted using Gibbs sampler algorithm implemented in the WinBUGS software. The results of the analyses of the two different data sets show that distributions of measurement errors of the longitudinal CD4 variable follow the generalized error distribution with fatter tails than the normal distribution. The Bayesian joint GED loglogistic models fit better to the data sets compared to the lognormal cases. Findings reveal that patients’ health can be improved over time. Compared to the males, female patients gain more CD4 counts. Survival time of a patient is negatively affected by TB infection. Moreover, increase in number of opportunistic infection implies decline of CD4 counts. Patients’ age negatively affects the disease marker with no effects on survival time. Improving weight may improve survival time of patients. Bayesian joint models with GED and AFT distributions are found to be useful in modelling the longitudinal and survival processes. Thus we recommend the generalized error distributions for measurement errors of the longitudinal data under the Bayesian joint modelling. Further studies may investigate the models with various types of shared random effects and more covariates with predictions.

Joint and supremum distributions in the compound binomial model with Markovian environment

In this paper, we study the compound binomial model in Markovian environment, which is proposed by Cossette, et al. （2003）. We obtain the recursive formula of the joint distributions of T, X（T - 1） and ｜X（T）｜（i.e., the time of ruin, the surplus before ruin and the deficit at ruin） by the method of mass function of up-crossing zero points, as given by Liu and Zhao （2007）. By using the same method, the recursive formula of supremum distribution is obtained. An example is included to illustrate the results of the model.

Long-Term Joint Distribution of One-Tenth Large (or Significant) Wave Height with Average Period

In this paper, by using the wave data from a few oceanographic observation stations in the coastal zone of the Yellow Sea, the East China Sea and the South China Sea, the long-term joint distribution of the one-tenth large (or significant) wave height with average period is studied. The statistical data demonstrate that the long- term distribution of the one- tenth wave height or average period fits the log-normal distribution, thus the joint distribution also fits the two-dimensional log-normal distribution. Then the conditional probability distribution of the average period is derived, and the range as well as the mode of the average wave period corresponding to a certain return period of wave height can be calculated easily.

Numerical studies on the stress distribution in weldbonded joints with different adhesives

The Effect of elastic modulus and thickness of the adhesives on the stress distribution in weldbonded joints has been studied with three-dimensional elastoplastic finite element method ( FEM). Stress distribution curves have been obtained at the edges of the spot welds and the lap zones in weldbonded joints, which were made with adhesives of different elastic modulus or different thickness. Results show that there exists larger stress concentration at the edge of the spot welds, though the shear stresses in the adhesive layers are smaller for weldbonded joints with low elastic modulus or thick adhesive layers. The stress concentration decreases and the shear stresses in adhesive layers increase with the increase of the elastic modulus or the decrease of the adhesive thickness. It is concluded that the thiner adhesive layers with higher elastic modulius are preferable in weldbonded joints to cut down the stress concentration.

Joint Distribution of Wave Periods and Rate of Change of Wave Surface Elevation

The rate of change of wave surface elevation is of much importance in ocean engineering, especially for the determination of the limitation of wave breaking. This paper gives a kind of joint distribution of wave periods and the rate of change of wave surface elevation by means of calculation of the two-order to four-order moment of the frequency spectrum based on the linear wave theory. For the first time, the distribution density function of wave periods determined by peaks is provided, and the conclusion is drawn that the rate of change of wave surface elevation obeys the Rayleigh distribution.

THE SPATIAL DISTRIBUTION AND MOMENTS OF CIRCULAR FREELY JOINTED CHAIN

The spatial distribution function and second moments of circular freely jointed chain are derived based on an analytical method. The circular Gauss chain, which is simple for long chains, is compared with the circular freely jointed chain, which is exact for short chains. It is shown that the Gauss chain model predicts a more compact configurational distribution than the exact freely jointed chain. The two chain models, however, become closer to each other when the chain length increases. It is found that the difference of the mean square radius of gyration calculated with these two chain models is a constant, independent of the chain length.

Modified Joint Distribution of Wave Heights and Periods

The modified versions of the linear theoretical model of Longuet-Higgins （1983） are derived in this work and also compared with the laboratory experiments carried out in MAR1NTEK. The main feature of modifications is to replace the mean frequency in the formulation with the peak frequency of the wave spectrum. These two alternative forms of joint distributions are checked in three typical random sea states characterized by the initial wave steepness. In order to further explore the properties ＆these models, the associated marginal distributions of wave heights and wave periods are also researched with the observed statistics and some encouraging results are obtained.

On the long-term joint distribution of characteristic wave height and period and its application

By analysing the scatter diagrams of characteristic the wave height H and the period T on the basis of instrumental data from various ocean wave stations, we found that the conditional expectation and standard deviation of wave period for a given wave height can be better predicted by using the equations of normal linear regression rather than by those based on the log- normal law. The latter was implied in Ochi' s bivariate log-normal model(Ochi. 1978) for the long-term joint distribution of H and T. With the expectation and standard deviation predicted by the normal linear regression equations and applying proper types of distribution, we have obtained the conditional distribution of T for given H. Then combining this conditional P(T / H) with long-term marginal distribution of the wave height P(H) we establish a new parameterized model for the long-term joint distribution P(H,T). As an example of the application of the new model we give a method for estimating wave period associated with an extreme wave height.

The joint limiting distribution of maxima with random indexes and sums of normal sequence

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Sand particle lift-off velocity measurements and numerical simulation of mass flux distributions in a wind tunnel

Lift-off velocity of saltating sand particles in wind-blown sand located at 1.0 mm above the sand bed surface was measured using a phase Doppler particle analyzer in a wind tunnel. The results show that the probability distribution of lift-off velocity can be expressed as a lognormal function, while that of lift-off angle follows an exponential function. The probability distribution of lift-off angle conditioned for each lift-off velocity also follows an exponential function, with a slope that becomes steeper with increasing lift-off velocity. This implies that the probability distribution of lift-off velocity is strongly dependent on the lift-off angle. However, these lift-off parameters are generally treated as an independent joint probability distribution in the literature. Numerical simulations were carried out to investigate the effects of conditional versus independent joint probability distributions on the vertical sand mass flux distribution. The simulation results derived from the conditional joint probability distribution agree much better with experimental data than those from the independent ones. Thus, it is better to describe the lift-off velocity of saltating sand particles using the conditional joint probability distribution. These results improve our understanding of saltation processes in wind-blown sand.

Joint resource allocation scheme for target tracking in distributed MIMO radar systems

A joint resource allocation scheme concerned with the sensor subset,power and bandwidth for range-only target tracking in multiple-input multiple-output(MIMO)radar systems is proposed.By selecting an optimal subset of sensors with the predetermined size and implementing the power allocation and bandwidth strategies among them,this algorithm can help achieving a better performance within the same resource constraints.Firstly,the Bayesian Cramer-Rao bound(BCRB)is derived from it.Secondly,a criterion for minimizing the BCRB at the target location among all targets tracking in a certain range is derived.Thirdly,the optimization problem involved with three variable vectors is formulated,which can be simplified by deriving the relationship between the optimal power allocation vector and the bandwidth allocation vector.Then,the simplified optimization problem is solved by the cyclic minimization algorithm incorporated with the sequential parametric convex approximation(SPCA)algorithm.Finally,the validity of the proposed method is demonstrated with simulation results.

Stress distribution in roadbeds of slab tracks with longitudinal discontinuities

Stress concentration occurs in the foundations of railway tracks where discontinuous components are located.The exacerbated stress under the expansion joints in slab tracks may trigger foundation failures such as mud pumping.Although the higher stress due to the discontinuities of track structures has been discussed in past studies,few focused on the stress response of roadbeds in slab tracks and quantitatively characterized the stress pattern.In this paper,we performed a dynamic finite element analysis of a track-formation system,incorporating expansion joints as primary longitudinal discontinuities.The configurations of CRTS Ⅲ slab tracks and the contact conditions between concrete layers were considered.Numerical results show that longitudinal influencing length of induced stress on roadbed under wheel load relates to the contact conditions between concrete layers,increasing nonlinearly at a larger coefficient of friction.Given a measured coefficient of friction of 0.7,the calculated longitudinal influencing length(9.0 m) matches with field data.The longitudinal influencing length is not affected with the increasing velocity.As stress concentration arises with expansion joints,the worstcase scenario emerges when double-axle loads are exerted immediately above the expansion joints between concrete bases.A stress concentration factor Cvon the roadbed is proposed;it increases with the increasing velocity,changing from 1.33 to 1.52 at velocities between 5 and 400 km/h.The stress distribution on roadbeds transforms from a trapezoid pattern at continuous sections to a triangle pattern at points with longitudinal discontinuities.An explicit expression is finally proposed for the stress pattern on roadbed under expansion joints.Although structural discontinuities induce stress raiser,the extent of concentration is mitigated with increasing depth at different velocity levels.

Research on Coordinated Development and Optimization of Distribution Networks at All Levels in Distributed Power Energy Engineering

The uncertainty of distributed generation energy has dramatically challenged the coordinated development of distribution networks at all levels.This paper focuses on the multi-time-scale regulation model of distributed generation energy under normal conditions.The simulation results of the example verify the self-optimization characteristics and the effectiveness of real-time dispatching of the distribution network control technology at all levels under multiple time scales.

Distribution and mechanism of gently dipping fractures subjected to river incision: A case study from Nujiang River, China

Gently dipping fractures subjected to river incision are widely distributed on rock slopes.In this paper,a rock slope on the Nujiang River(China)is investigated to study the role of gently dipping fractures in the rock slopes evolution.Detailed field surveys indicate that gentle fractures are concentrated in four main zones.Moreover,the kinematics of the fracture system suggest that the genesis of these fractures can be synthesized into a progressive evolution model.This model indicates that the joints begin with the formation of an array of en echelon cracks that are subjected to continued crack elongation and shearing before ultimately approaching one another and interacting to form a complex joint system.Geomechanical analysis is performed to reveal the mechanisms of this genesis,and three main fracture patterns are identified based on the slope stress and are classified with respect to the slope evolution.Based on the detail field investigations and the evolutionary history of the river valley,we propose that intermittent incision by the river was the main factor contributing to the concentrated distribution of gently dipping joints.

Research on Direct Yaw Moment Control Strategy of Distributed-Drive Electric Vehicle Based on Joint Observer

Combined with the characteristics of the distributed-drive electric vehicle and direct yaw moment control,a double-layer structure direct yaw moment controller is designed.The upper additional yaw moment controller is constructed based on model predictive control.Aiming at minimizing the utilization rate of tire adhesion and constrained by the working characteristics of motor system and brake system,a quadratic programming active set was designed to optimize the distribution of additional yaw moments.The road surface adhesion coefficient has a great impact on the reliability of direct yaw moment control,for which joint observer of vehicle state parameters and road surface parameters is designed by using unscented Kalman filter algorithm,which correlates vehicle state observer and road surface parameter observer to form closed-loop feedback correction.The results show that compared to the“feedforward+feedback”control,the vehicle’s error of yaw rate and sideslip angle by the model predictive control is smaller,which can improve the vehicle stability effectively.In addition,according to the results of the docking road simulation test,the joint observer of vehicle state and road surface parameters can improve the adaptability of the vehicle stability controller to the road conditions with variable adhesion coefficients.

An Approach of Distributed Joint Optimization for Cluster-based Wireless Sensor Networks

Wireless sensor networks (WSNs) are energyconstrained, so energy saving is one of the most important issues in typical applications. The clustered WSN topology is considered in this paper. To achieve the balance of energy consumption and utility of network resources, we explicitly model and factor the effect of power and rate. A novel joint optimization model is proposed with the protection for cluster head. By the mean of a choice of two appropriate sub-utility functions, the distributed iterative algorithm is obtained. The convergence of the proposed iterative algorithm is proved analytically. We consider general dual decomposition method to realize variable separation and distributed computation, which is practical in large-scale sensor networks. Numerical results show that the proposed joint optimal algorithm converges to the optimal power allocation and rate transmission, and validate the performance in terms of prolonging of network lifetime and improvement of throughput. © 2014 Chinese Association of Automation.