厂房下开采力学预计

传统法预计的危险变形区不一定是力学预计的主应变危险区。如文中原法预计的主加固房却位于力学预计的微应变区，可不必加固，其邻接小房采动过程中安然无恙就是明证。

一种基于静力学预计算的开关磁阻电机模态仿真方法

针对开关磁阻电机模态仿真结果低阶模态计算误差较大的问题,提出了一种基于静力学预计算的开关磁阻电机模态仿真方法.该方法建立了开关磁阻电机的3维有限元模型,并采用现有的模态仿真方法和改进的模态仿真方法分别对模型进行了模态仿真计算,通过电机实验验证了模态仿真结果的准确性.模态结果对比分析表明:现有的模态仿真方法在低阶模态计算中存在不足,而基于静力学预计算的模态仿真方法通过考虑电机装配应力和自重应力的影响,能够把低阶模态仿真结果的相对误差控制在5%以内.

Effect of thermodynamic parameters on prediction of phase behavior and process design of extractive distillation

Extractive distillation was investigated for separation of the minimum azeotrope of n-propanol/water, via the Aspen Plus simulation platform. Experimental data of n-propanol/water, which could pass the thermodynamic consistency test, were regressed to get suitable binary interaction parameters(BIPs) by the UNIQUAC thermodynamic model. The azeotrope system was heterogeneous in the simulation with built-in BIPs, which was contrary to the experimental data. The study focused on the effect of thermodynamic parameters on the prediction of phase behavior, and process design of extractive distillation. N-methyl-2-pyrrolidone(NMP) and ethylene glycol were used as solvents to implement the separation. Processes with built-in and regressed BIPs were explored,based on the minimum total annual cost(TAC). There were significant differences in the phase behavior simulation using different thermodynamic parameters, which showed the importance of BIPs in the design and optimization of extractive distillation.

Mechanical properties of porous titanium with different distributions of pore size

To satisfy the mechanical and biological requirement of porous bone substitutes, porous Ti with two different pore sizes designed in advance was fabricated by the space-holder sintering process. Mechanical properties of the porous Ti were explored via room temperature compressive tests. The pore sizes and shapes are uniform throughout the specimens with porosities ranging from 36% to 63%. The compression strength and the elastic modulus are in the range from 94.05 to 468.57 MPa and 2.662 to 18 GPa, respectively. It is worth noting that the relationship between the compressive strength and the porosities is completely linear relation beyond the effect of pore size distributions on the mechanical properties. The value of the constant C achieved from the Gibson-Ashby model suggests that the pore sizes affect the yield strength of the porous Ti and the values of density exponent （n） for porous Ti with two different pore sizes are higher than 2, which suggests that the deformation mode of the porous Ti with a porosity ranging from 36% to 63% is mainly buckling of the cell struts.

Statistical Downscaling Prediction of Summer Precipitation in Southeastern China

A statistical downscaling approach based on multiple-linear-regression(MLR) for the prediction of summer precipitation anomaly in southeastern China was established,which was based on the outputs of seven operational dynamical models of Development of a European Multi-model Ensemble System for Seasonal to Interannual Prediction(DEMETER) and observed data.It was found that the anomaly correlation coefficients(ACCs) spatial pattern of June-July-August(JJA) precipitation over southeastern China between the seven models and the observation were increased significantly;especially in the central and the northeastern areas,the ACCs were all larger than 0.42(above 95% level) and 0.53(above 99% level).Meanwhile,the root-mean-square errors(RMSE) were reduced in each model along with the multi-model ensemble(MME) for some of the stations in the northeastern area;additionally,the value of RMSE difference between before and after downscaling at some stations were larger than 1 mm d-1.Regionally averaged JJA rainfall anomaly temporal series of the downscaling scheme can capture the main characteristics of observation,while the correlation coefficients(CCs) between the temporal variations of the observation and downscaling results varied from 0.52 to 0.69 with corresponding variations from-0.27 to 0.22 for CCs between the observation and outputs of the models.

Semi-empirical modeling of volumetric efficiency in engines equipped with variable valve timing system

Volumetric efficiency and air charge estimation is one of the most demanding tasks in control of today's internal combustion engines.Specifically,using three-way catalytic converter involves strict control of the air/fuel ratio around the stoichiometric point and hence requires an accurate model for air charge estimation.However,high degrees of complexity and nonlinearity of the gas flow in the internal combustion engine make air charge estimation a challenging task.This is more obvious in engines with variable valve timing systems in which gas flow is more complex and depends on more functional variables.This results in models that are either quite empirical(such as look-up tables),not having interpretability and extrapolation capability,or physically based models which are not appropriate for onboard applications.Solving these problems,a novel semi-empirical model was proposed in this work which only needed engine speed,load,and valves timings for volumetric efficiency prediction.The accuracy and generalizability of the model is shown by its test on numerical and experimental data from three distinct engines.Normalized test errors are 0.0316,0.0152 and 0.24 for the three engines,respectively.Also the performance and complexity of the model were compared with neural networks as typical black box models.While the complexity of the model is less than half of the complexity of neural networks,and its computational cost is approximately 0.12 of that of neural networks and its prediction capability in the considered case studies is usually more.These results show the superiority of the proposed model over conventional black box models such as neural networks in terms of accuracy,generalizability and computational cost.

CFD prediction of local scour hole around bridge piers

In order to predict the local scour hole and its evaluation around a cylindrical bridge pier, the computational fluid dynamics （CFD） and theories of sediment movement and transport were employed to carry out numerical simulations. In the numerical method, the time-averaged Reynolds Navier-Stokes equations and the standard k-e model were first used to simulate the three-dimensional flow field around a bridge pier fixed on river bed. The transient shear stress on river bed was treated as a crucial hydrodynamic mechanism when handling sediment incipience and transport. Then, river-bed volumetric sediment transport was calculated, followed by the modification of the river bed altitude and configuration. Boundary adaptive mesh technique was employed to modify the grid system with changed river-bed boundary. The evolution of local scour around a cylindrical bridge pier was presented. The numerical results represent the flow pattern and mechanism during the pier scouring, with a good prediction of the maximum scour hole depth compared with test results.

A CFD model for predicting the heat transfer in the industrial scale packed bed

Compared to the traditional lumped-parameter model, computational fluid dynamics （CFD） attracted more attentions due to facilitating more accurate reactor design and optimization methods when analyzing the heat transfer in the industrial packed bed. Here, a model was developed based on the CFD theory, in which the heterogeneous fluid flow was resolved by considering the oscillatory behavior of voidage and the effective fluid viscosity. The energy transports in packed bed were calculated by the convection and diffusion incorporated with gaseous dispersion in fluid and the contacting thermal conductivity of packed particles in solids. The heat transfer coefficient between fluid and wall was evaluated by considering the turbulence due to the packed particles adjacent to the wall. Thus, the heat transfer in padded bed can be predicted without using any adjustable semi-empirical effective thermal conductivity coefficient. The experimental results from the literature were employed to validate this model.

A TREND DISPLACEMENT ANALYSIS FOR SPACE AND TIME ON XINTAN LANDSLIDE

This paper, having made systematic trend analysis on the front and rear segments of Xintan landslide for space and time respectively by using matbematical statistical principles,discovered that there is obvious trend displacement Of the monitoring points in the rear margin area of the slope and the rates of trend displacement gradually increase with time whereas there is no trend displacement of the monitoring points in the front margin area. This result suggests that the rear margin area of segment is an area of overall sliding and is transforming towards destabilization whereas the front margin area is an area of relative stability. This analytical result well coincides with the conclusion of evaluation on dynamic stability. The analytical result mentioned above shows that the medium to short term forecast and prediction of slope stability can be made by using trend displacement analysis technique in order to achieve the goal of timely evaluation and prevention.

Seeing permeability from images： fast prediction with convolutional neural networks

Fast prediction of permeability directly from images enabled by image recognition neural networks is a novel pore-scale modeling method that has a great potential. This article presents a framework that includes (1) generation of porous media samples,(2) computation of permeability via fluid dynamics simulations,(3) training of convolutional neural networks (CNN) with simulated data, and (4) validations against simulations. Comparison of machine learning results and the ground truths suggests excellent predictive performance across a wide range of porosities and pore geometries, especially for those with dilated pores. Owning to such heterogeneity, the permeability cannot be estimated using the conventional Kozeny–Carman approach. Computational time was reduced by several orders of magnitude compared to fluid dynamic simulations. We found that, by including physical parameters that are known to affect permeability into the neural network, the physics-informed CNN generated better results than regular CNN. However, improvements vary with implemented heterogeneity.

Wear analysis of revolute joints with clearance in multibody systems

In this work, the prediction of wear for revolute joint with clearance in multibody systems is investigated using a computational methodology. The contact model in clearance joint is established using a new hybrid nonlinear contact force model and the friction effect is considered by using a modified Coulomb friction model. The dynamics model of multibody system with clearance is established using dynamic segmentation modeling method and the computational process for wear analysis of clearance joint in multibody systems is presented. The main computational process for wear analysis of clearance joint includes two steps, which are dynamics analysis and wear analysis. The dynamics simulation of multibody system with revolute clearance joint is carried out and the contact forces are drawn and used to calculate the wear amount of revolute clearance joint based on the Archard's wear model. Finally, a four-bar multibody mechanical system with revolute clearance joint is used as numerical example application to perform the simulation and show the dynamics responses and wear characteristics of multibody systems with revolute clearance joint. The main results of this work indicate that the contact between the joint elements is wider and more frequent in some specific regions and the wear phenomenon is not regular around the joint surface, which causes the clearance size increase non-regularly after clearance joint wear. This work presents an effective method to predict wear of revolute joint with clearance in multibody systems.

Investigations on Several Mechanical Problems in Windblown Sand Movement

It is very necessary for investigation on mechanism of windblown sand movement to understand and find out effective measures of preventing and reducing windblown sand, This also deals with some general features and hot spots in the scientific forelands. such as multi-scale problems. interactions among. multi-physical-fields, randomness and nonlinearity as well as complex systems. In recent years, a series of experiments in wind tunnels and theoretical modeling as well as computer simulation have been taken by our research group （the Laboratory of Environmental Mechanics on Windblown Sand Movement in Lanzhou University ）in a cross-disciplinary （mechanics and geography） viewpoint. Several original and essential studies were explored such as the main regularities of charges on sand particles, the mechanisms of electric field in windblown sand flux, the effects induced by the electric field on the flux, the microwave propagations, the evolution process of windblown and flux under mutual couple interations among several physical fields, and the simulation of the main features of Aeolian sand ripples.

Prediction of Aerodynamic Noise in a Ring Fan Based on Wake Characteristics

A ring fan is a propeller fan that applies an axial-flow impeller with a ring-shaped shroud on the blade tip side. In this study, the entire flow field of the ring fan is simulated using computational fluid dynamics (CFD); the accuracy of the CFD is verified through a comparison with the aerodynamic characteristics of a propeller fan of current model. Moreover, the aerodynamic noise generated by the fan is predicted on the basis of the wake characteristics. The aerodynamic characteristic of the ring fan based on CFD can represent qualitatively the variation in the measured value. The main flow domain of the ring fan is formed at the tip side of the blade because blade tip vortex is not formed at that location. Therefore, the relative velocity of the ring fan is increased by the circumferential velocity. The sound pressure levels of the ring fan within the frequency band of less than 200 Hz are larger than that of the propeller fan. In the analysis of the wake characteristics, it revealed that Karman vortex shedding occurred in the main flow domain in the frequency domain lower than 200 Hz ; the aerodynamic noise of the ring fan in the vortex shedding frequency enlarges due to increase in the relative velocity and the velocity fluctuation.

Influences of cavity leakage on the design of low flow coefficient centrifugal impeller

The low flow coefficient centrifugal impeller(LFCCI)gives a relatively low efficiency and a special treatment is required for the design of this kind of impeller.This paper investigates the influences of cavity leakage on the performance prediction and design of LFCCI based on Computational Fluid Dynamics(CFD)techniques.The results show that,the reduction in the effi-ciency of impeller due to the introduction of cavity leakage varies with the blade shape of impeller in a wide range since there is a strong and complex interaction of main flow and leakage flow in the LFCCI.To get a credible optimization result,the backside and foreside cavities should be considered in the CFD-based design of LFCCI.

On Using Physico-Chemical Properties of Amino Acids in String Kernels for Protein Classification via Support Vector Machines

String kernels are popular tools for analyzing protein sequence data and they have been successfully applied to many computational biology problems. The traditional string kernels assume that different substrings are independent. However, substrings can be highly correlated due to their substructure relationship or common physico-chemical properties. This paper proposes two kinds of weighted spectrum kernels： The correlation spectrum kernel and the AA spectrum kernel. We evMuate their performances by predicting glycan-binding proteins of 12 glycans. The results show that the correlation spectrum kernel and the AA spectrum kernel perform significantly better than the spectrum kernel for nearly all the 12 glycans. By comparing the predictive power of AA spectrum kernels constructed by different physico-chemical properties, the authors can also identify the physico- chemical properties which contributes the most to the glycan-protein binding. The results indicate that physico-chemical properties of amino acids in proteins play an important role in the mechanism of glycamprotein binding.