墙土系统动测模型及土体附加参数识别方法研究

【目的】对墙土系统动测模型进行研究,同时提出了基于模态参数的土体附加参数识别方法,为墙土系统的损伤识别和健康诊断提供一种简单、适用的模型。【方法】建立了墙土系统动测模型,假定附加刚度和附加质量成三角形分布,采用附加刚度和附加质量模拟土体对墙土系统模态特性的影响。基于模态频率构造目标函数,建立模态频率和土体附加参数之间的BP神经网络结构,识别得到不同土体弹性模量对应的土体附加参数。将三维有限元整体模型分析得到的模态频率作为真实值,计算真实值和识别值之间的相对误差,判定识别方法的可行性。【结果】基于模态频率和BP神经网络的土体附加参数识别方法能够满足工程精度要求,模态频率相对误差均在2%以内;随着土体弹性模量的提高,土体的附加刚度呈双指数函数增大,附加质量呈双指数函数减小。【结论】提出的动测模型及基于模态参数和BP神经网络的附加参数识别方法是可行的,为墙土系统的健康诊断提供了一种行之有效的方法。

桥梁大直径灌注桩动测的数值模拟及应用

桥梁大直径灌注桩常用反射波法进行检测 ,测试曲线的正确解释对保证桥梁桩的质量至关重要。建立了低应变反射波法动测模型 ,用差分法进行模拟计算 ,并把研究结果应用于桥梁桩低应变动测资料的解释。

大口径桩检测的三维数值模拟

提出大口径桩动测存在的三维效应现象.通过合理的假设,建立了大口径桩的三维动测模型.较详细地介绍了其动态平衡方程的建立过程,同时对动态平衡方程的解法也作了一般的介绍.通过模拟可对不同几何形状和缺陷的桩设计不同的参数进行正演推算.

大直径桩的三维效应

提出大直径桩动测存在的三维效应现象,通过合理的假设,建立了大直径桩的三维动测模型,探讨了其动态平衡方程的建立过程,并且对缺陷大直径桩三维效应进行了一些研究,从而避免由于在大直径桩中出现的非对称缺陷而导致误判。

Cycle life prediction and match detection in retired electric vehicle batteries

The lifespan models of commercial 18650-type lithium ion batteries （nominal capacity of 1150 mA-h） were presented. The lifespan was extrapolated based on this model. The results indicate that the relationship of capacity retention and cycle number can be expressed by Gaussian function. The selecting function and optimal precision were verified through actual match detection and a range of alternating current impedance testing. The cycle life model with high precision （〉99%） is beneficial to shortening the orediction time and cutting the prediction cost.

Adaptive moving target detection algorithm based on Gaussian mixture model

In order to enhance the reliability of the moving target detection, an adaptive moving target detection algorithm based on the Gaussian mixture model is proposed. This algorithm employs Gaussian mixture distributions in modeling the background of each pixel. As a result, the number of Gaussian distributions is not fixed but adaptively changes with the change of the pixel value frequency. The pixels of the difference image are divided into two parts according to their values. Then the two parts are separately segmented by the adaptive threshold, and finally the foreground image is obtained. The shadow elimination method based on morphological reconstruction is introduced to improve the performance of foreground image＇s segmentation. Experimental results show that the proposed algorithm can quickly and accurately build the background model and it is more robust in different real scenes.

Assessing dynamic modulus properties for typical asphalt mixtures in Jiangsu

To investigate the validity of two dynamic modulus predictive models（ Witczak 1-37 A viscosity-based model and Witczak 1-40 D shear modulus-based model） in the context of Jiangsu, and evaluate the effect of different mixture design variables（ aggregate gradations, binder type, and volumetric properties） on dynamic modulus E＊, asphalt mixtures commonly used in the local surface layer, including Sup-13 and AC-13, are prepared in the laboratory and their dynamic modulus E＊values are predicted based on the above mentioned models. The corresponding asphalt tests, including viscosity and dynamic shear modulus tests, are also carried out to obtain the prediction model parameters. The test results showthat binder type and asphalt content have a significant impact on dynamic modulus.There is a good correlation between the E＊values based on above two predictive models and the measured E＊, while a relatively lower bias can be expected from Witczak 1-37 A model. The test results can be used for the calibration of dynamic modulus with higher accuracy.

Dynamic recrystallization behavior of burn resistant titanium alloy Ti-25V-15Cr-0.2Si

Dynamic recrystallization (DRX) behavior in β phase region for the burn resistant titanium alloy Ti?25V?15Cr?0.2Si was investigated with a compression test in the temperature range of 950?1100 °C and the strain rate of 0.001?1 s?1. The results show that deformation mechanism of this alloy in hot deformation is dominated by DRX, and new grains of DRX are evolved by bulging nucleation mechanism as a predominant mechanism. DRX occurs more easily with the decrease of strain rate and the increase of deformation temperature. Grain refinement is achieved due to DRX during the hot deformation at strain rate range of 0.01?0.1 s?1 and temperature range of 950?1050 °C. DRX grain coarsening is observed for the alloy deformed at the higher temperatures of 1100 °C and the lower strain rates of 0.001 s?1. Finally, in order to determine the recrystallized fraction and DRX grain size under different deformation conditions, the prediction models of recrystallization kinetics and recrystallized grain sizes were established.

Studies on stand dynamic growth model for larch in Jilin in China

The stand growth and yield dynamic models for Larch in Jilin Province were developed based on the forest growth theories with the forest continuous inventory data. The results indicated that the developed models had high precision, and they could be used for the updating data of inventory of planning and designing and optimal decision of forest management.

SIMULATING RHYTHMIC MOVEMENT OF HUMAN ELBOW JOINT USING A NEURAL NETWORK PREDICTIVE MODEL

Human brain is hypothesized to store a geometry and dynamic model of the limb.A multilayer perceptron (or MLP) network is used to stand for the model.In this paper the human elbow joint rhythmic movement is simulated in three cases:1)Parameters of the MLP,the limb geometry and dynamic model match completely,2)Parameters mismatch between them,and 3)Disturbance exists.The results show that parameters mismatch is the main error source,which causes the elbow joint movement to be aberrant.From this we can infer that movement study is a process in which the internal model is updated continuously to match the geometry and dynamic model of limb.

Recent Study of Drag Embedment Plate Anchors in China

Experimental and theoretical studies of drag embedment plate anchors recently carried out in Tianjin University are summarized in this research paper, which involve a series of important topics relevant to the study of drag anchors. The techniques for measuring the trajectory and movement direction of drag anchors in soils, the techniques for measuring the moving embedment point and reverse eatenary shape of the embedded drag line, the penetration mechanism and kinematic behavior of drag anchors, the ultimate embedment depth of drag anchors, the movement direction of the anchor with an arbitrary fluke section, the reverse catenary properties of the embedded drag line, the interaetional properties between drag anchor and installation line, the kinematic model of drag anchors in seabed soils, and the analytical method for predicting the anchor trajectory in soils will all be examined. The present work remarkably reduces the uncertainties in design and analysis of drag embedment plate anchors, and is beneficial to improving the application of this new type of drag anchor in offshore engineering.

Fault Prediction Based on Dynamic Model and Grey Time Series Model in Chemical Processes

This paper combines grey model with time series model and then dynamic model for rapid and in-depth fault prediction in chemical processes. Two combination methods are proposed. In one method, historical data is introduced into the grey time series model to predict future trend of measurement values in chemical process. These predicted measurements are then used in the dynamic model to retrieve the change of fault parameters by model based diagnosis algorithm. In another method, historical data is introduced directly into the dynamic model to retrieve historical fault parameters by model based diagnosis algorithm. These parameters are then predicted by the grey time series model. The two methods are applied to a gravity tank example. The case study demonstrates that the first method is more accurate for fault prediction.

Elastodynamic modeling and joint reaction prediction for 3-PRS PKM

To gain a thorough understanding of the load state of parallel kinematic machines(PKMs), a methodology of elastodynamic modeling and joint reaction prediction is proposed. For this purpose, a Sprint Z3 model is used as a case study to illustrate the process of joint reaction analysis. The substructure synthesis method is applied to deriving an analytical elastodynamic model for the 3-PRS PKM device, in which the compliances of limbs and joints are considered. Each limb assembly is modeled as a spatial beam with non-uniform cross-section supported by lumped virtual springs at the centers of revolute and spherical joints. By introducing the deformation compatibility conditions between the limbs and the platform, the governing equations of motion of the system are obtained. After degenerating the governing equations into quasi-static equations, the effects of the gravity on system deflections and joint reactions are investigated with the purpose of providing useful information for the kinematic calibration and component strength calculations as well as structural optimizations of the 3-PRS PKM module. The simulation results indicate that the elastic deformation of the moving platform in the direction of gravity caused by gravity is quite large and cannot be ignored. Meanwhile, the distributions of joint reactions are axisymmetric and position-dependent. It is worthy to note that the proposed elastodynamic modeling method combines the benefits of accuracy of finite element method and concision of analytical method so that it can be used to predict the stiffness characteristics and joint reactions of a PKM throughout its entire workspace in a quick and accurate manner. Moreover, the present model can also be easily applied to evaluating the overall rigidity performance as well as statics of other PKMs with high efficiency after minor modifications.

A Computationally Efficient Aggregation Optimization Strategy of Model Predictive Control

Model Predictive Control (MPC) is a popular technique and has been successfully used in various industrial applications. However, the big drawback of MPC involved in the formidable on line computational effort limits its applicability to relatively slow and/or small processes with a moderate number of inputs. This paper develops an aggregation optimization strategy for MPC that can improve the computational efficiency of MPC. For the regulation problem, an input decaying aggregation optimization algorithm is presented by aggregating all the original optimized variables on control horizon with the decaying sequence in respect of the current control action.

Verification and Improvement of the Ability of CFSv2 to Predict the Antarctic Oscillation in Boreal Spring

The boreal spring Antarctic Oscillation(AAO)has a significant impact on the spring and summer climate in China.This study evaluates the capability of the NCEP's Climate Forecast System,version 2(CFSv2),in predicting the boreal spring AAO for the period 1983-2015.The results indicate that CFSv2 has poor skill in predicting the spring AAO,failing to predict the zonally symmetric spatial pattern of the AAO,with an insignificant correlation of 0.02 between the predicted and observed AAO Index(AAOI).Considering the interannual increment approach can amplify the prediction signals,we firstly establish a dynamical-statistical model to improve the interannual increment of the AAOI(DY AAOI),with two predictors of CFSv2-forecasted concurrent spring sea surface temperatures and observed preceding autumn sea ice.This dynamical-statistical model demonstrates good capability in predicting DY AAOI,with a significant correlation coeffcient of 0.58 between the observation and prediction during 1983-2015 in the two-year-out cross-validation.Then,we obtain an improved AAOI by adding the improved DY AAOI to the preceding observed AAOI.The improved AAOI shows a significant correlation coeffcient of 0.45 with the observed AAOI during 1983-2015.Moreover,the unrealistic atmospheric response to March-April-May sea ice in CFSv2 may be the possible cause for the failure of CFSv2 to predict the AAO.This study gives new clues regarding AAO prediction and short-term climate prediction.

Simulation logging experiment and interpretation model of array production logging measurements in a horizontal well

The distributions of local velocity and local phase holdup along the radial direction of pipes are complicated because of gravity differentiation,and the distribution of fluid velocity fi eld changes along the gravity direction in horizontal wells.Therefore,measuring the mixture flow and water holdup is difficult,resulting in poor interpretation accuracy of the production logging output profile.In this paper,oil–water two-phase flow dynamic simulation logging experiments in horizontal oil–water two-phase fl ow simulation wells were conducted using the Multiple Array Production Suite,which comprises a capacitance array tool(CAT)and a spinner array tool(SAT),and then the response characteristics of SAT and CAT in diff erent fl ow rates and water cut production conditions were studied.According to the response characteristics of CAT in diff erent water holdup ranges,interpolation imaging along the wellbore section determines the water holdup distribution,and then,the oil–water two-phase velocity fi eld in the fl ow section was reconstructed on the basis of the fl ow section water holdup distribution and the logging value of SAT and combined with the rheological equation of viscous fl uid,and the calculation method of the oil–water partial phase fl ow rate in the fl ow section was proposed.This new approach was applied in the experiment data calculations,and the results are basically consistent with the experimental data.The total fl ow rate and water holdup from the calculation are in agreement with the set values in the experiment,suggesting that the method has high accuracy.

Time series prediction of mining subsidence based on a SVM

In order to study dynamic laws of surface movements over coal mines due to mining activities,a dynamic prediction model of surface movements was established,based on the theory of support vector machines(SVM) and times-series analysis.An engineering application was used to verify the correctness of the model.Measurements from observation stations were analyzed and processed to obtain equal-time interval surface movement data and subjected to tests of stationary,zero means and normality.Then the data were used to train the SVM model.A time series model was established to predict mining subsidence by rational choices of embedding dimensions and SVM parameters.MAPE and WIA were used as indicators to evaluate the accuracy of the model and for generalization performance.In the end,the model was used to predict future surface movements.Data from observation stations in Huaibei coal mining area were used as an example.The results show that the maximum absolute error of subsidence is 9 mm,the maximum relative error 1.5%,the maximum absolute error of displacement 7 mm and the maximum relative error 1.8%.The accuracy and reliability of the model meet the requirements of on-site engineering.The results of the study provide a new approach to investigate the dynamics of surface movements.

Instantaneous and long-term deformation characteristics of deep room-pillar system induced by pillar recovery

The goaf may face a series of deformation and settlement problems when the room-pillar mining method is used to excavate ore and pillars in the deep strata.To this end,a deep room-pillar model with two levels was made,and the pillar recovery was carried out.The instantaneous deformation responses during the pillars recovery and the long-term settlements after the pillar recovery were analyzed.During the pillar recovery,different regions of surrounding rocks suffer from different dynamic disturbances which can be divided into three types,including(I)the combined action of blasting disturbance and unloading disturbance,(II)the sequential action of blasting disturbance and unloading disturbance,and(III)the action of unloading disturbance.After the pillar recovery,the settlement above the first recovering pillar is the largest,which has a traction effect on the settlement in other areas.The settlement process can be divided into two stages,stable displacement stage and unstable displacement stage.When the pillar-room system undergoes the unstable displacement stage,rock spalling and further cascading collapse will occur.

Urinary Profiles of Soy Isoflavone Metabolites in Women,Female Piglets and Female Rats Consuming Soy Diet

Objective: To investigate the urinary soy isoflavone metabolites from women, female piglets and rats fed with diet containing soy protein. Methods: Urinary samples from human and animals were collected after soy diet consumption. Identification for soy isoflavone metabolites in urine samples was processed using an Agilent Bruker LC Esquire ion trap system. Quantification of aglycone and conjugated soy isoflavone metabolites were also analyzed using a method published previously. Results: Identification studies showed that aglycones and conjugates of soy isoflavone metabolites were found in women and porcine samples. Interestingly, glucuronide conjugate of equol, besides glucuronide conjugates of genistein and daidzein, were found in rat urine. Glucuronide conjugate of equol was the major metabolite found in rat urine. A quantitative study showed that conjugated forms of isoflavones were more than 90% in woman urine, were between 80.5% and 84.5% in female porcine urine, and were less than 50% in female rat urine. Conclusion: Equol is the major metabolite found in female rat urine, but it is not found in woman or female porcine urine. Urinary profiles show that porcine model is more appropriate for mimicking human soy diet consuming studies.

Surface roughness prediction model in ultrasonic vibration assisted grinding of BK7 optical glass

Pre-knowledge of machined surface roughness is the key to improve whole machining efficiency and meanwhile reduce the expenditure in machining optical glass components.In order to predict the surface roughness in ultrasonic vibration assisted grinding of brittle materials,the surface morphologies of grinding wheel were obtained firstly in the present work,the grinding wheel model was developed and the abrasive trajectories in ultrasonic vibration assisted grinding were also investigated,the theoretical model for surface roughness was developed based on the above analysis.The prediction model was developed by using Gaussian processing regression(GPR)due to the influence of brittle fracture on machined surface roughness.In order to validate both the proposed theoretical and GPR models,32sets of experiments of ultrasonic vibration assisted grinding of BK7optical glass were carried out.Experimental results show that the average relative errors of the theoretical model and GPR prediction model are13.11%and8.12%,respectively.The GPR prediction results can match well with the experimental results.