西安地铁双线隧道地表沉降预测模型研究

针对西安地铁留核心土、上下半洞开挖、超前小导管注浆加固与水平钢撑锁脚的钢拱架和挂网喷层支护的饱和黄土隧道,根据现场地面沉降监测数据,分析了隧道右线、左线掌子面间隔30m开挖过程中洞顶地表沉降变形的历时变化规律,以及左、右线单洞沉降槽和双线沉降槽的分布特征。结果表明,洞顶地表沉降变形可以划分为初期沉降变形、右线开挖主变形、左线开挖主变形及沉降变形稳定4个阶段;左、右线单洞沉降槽和双线沉降槽均可用高斯分布曲线拟合。基于沉降槽Peck公式及O’Reilly和New最大沉降与隧道埋深的关系,得到了饱和黄土隧道单洞与双洞地面沉降槽的宽度和最大沉降,以及右、左线隧道先后开挖单洞的沉降槽宽度比和最大沉降比。考虑双线隧道洞间距、左右洞先后开挖地层松动相互影响以及围岩饱和黄土固结变形的影响,提出了一种饱和黄土隧道双洞开挖施工引起地表沉降的预测模型,验证了该预测模型应用的可靠性。

基于图卷积网络的药物靶标关联预测算法

传统的基于生物学实验的药物-靶标关联预测成本高、效率低,难以满足医药研发的需求。为了解决上述问题,提出一种新的基于图卷积网络的药物靶标关联预测(GCDTI)算法。GCDTI利用半监督学习方法将图卷积和自编码技术相结合,从而分别构建用于整合节点特征的编码层和用于预测全链接交互网络的解码层;同时使用图卷积技术建立潜在因子模型,并有效利用药物和靶标的高维属性信息进行端到端的学习。所提算法不需要对输入的特征信息进行任何预处理便可以将其与已知相互作用网络相结合,证明了该模型的图卷积层能够有效地融合输入数据与节点特征。与其他先进方法相比,GCDTI的预测精度和平均受试者工作特性(ROC)曲线下的面积(AUC)(0.924 6±0.004 8)最高,且具有较强的鲁棒性。实验结果表明:当需要预测大量的药物和靶标数据的关联关系时,利用端到端学习的模型架构的GCDTI有潜力成为一种可靠的预测方法。

机器学习在手术室管理中的研究与应用进展

手术室是医院整体运行中的重要组成部分,其管理质量是影响医院能否高效和安全运行的重要因素。机器学习是人工智能分支之一,是通过计算机模拟人类学习行为并获取智能处理数据能力的一种方法,可通过总结大量数据的内在规律与联系,自主获得新知识与经验,建立相应的计算预测模型,并在学习中不断更新和重组现有的认知方式,最终将获得的新知识应用于精确快速解决新的实际问题中,适用于处理手术室管理所涉及的庞大且复杂的数据。回顾分析相关文献并结合临床工作经验,综述机器学习在手术室管理中的研究进展与应用潜能,使机器学习能够应用于手术室护理管理工作,提高手术室专科护理水平。

砂岩型铀矿勘查中航放、航磁信息开发研究

本文以伊犁盆地南缘5个砂岩型铀矿床为研究对象,通过对已知铀矿床航放、航磁特征的研究,强调航放下测铀宽道Udw、上测铀窄道Uu、上测铀宽道Uuw和下测铀窄道Ud 4种参数异常是砂岩型铀矿的直接指示标志;对航放信息相关性分析进行了探讨,认为航放相关性分析不适合层间氧化带砂岩型铀矿的预测,相关性分析圈定的Th、K元素负相关区带为古河道砂岩型铀矿床产出的有利部位;对弱磁异常进行了研究提取,首次提出用弱磁分布范围来圈定盖层氧化区(带)的观点;建立航放、航磁计算机预测模型,对整个盆地进行了砂岩型铀矿成矿预测,圈定远景区14片,便于进一步开展地面物探工作,继续扩大伊犁盆地的找矿成果。认为航放、航磁在可地浸砂岩型铀矿勘查中仍能发挥重要作用。

地面沉降的研究

系统介绍了地面沉降产生的原因机理、计算预测模型,监测技术手段以及防治措施,并对监测预报以及防治措施进行了较具体的总结,以指导正确预测地面沉降,从而采取合理的预防措施。

Prediction of Distillation Column Performance by Computational Mass Transfer Method

A computational mass transfer model is proposed for predicting the concentration profile and Murphree efficiency of sieve tray distillation column. The proposed model is based on using modified c＇2 -εc＇ two equations formulation for closing the differential turbulent mass transfer equation with improvement by considering the vapor injected from the sieve hole to be three dimensional. The predicted concentration distributions by using proposed model were checked by experimental work conducted on a sieve tray simulator of 1.2 meters in diameter for desorbing the dissolved oxygen in the feed water by blowing air. The model predictions were confirmed by the experimental measurement. The validation of the proposed model was further tested by comparing the simulated result with the performance of an industrial scale sieve tray distillation column reported by Kunesh et al. for the stripping of toluene from its water solution. The predicted outlet concentration of each tray and the Murphree tray efficiencies under different operating conditions were in agreement with the published data. The simulated turbulent mass transfer diffusivity on each tray was within the range of the experimental result in the same sieve column reported by Cai et al. In addition, the prediction of the influence of sieve tray structure on the tray efficiency by using the proposed model was demonstrated.

Comparisons between unsteady sediment-transport modeling

The comparative study between unsteady flow models in alluvial streams shows a chaotic residue as for the choices of a forecasting model. The difficulty resides in the choice of the expressions of friction resistance and sediment transport. Three types of mathematical models were selected. Models of type one and two are fairly general, but require a considerable number of boundary conditions, which related to each size range of sediments. It can be a handicap during rivers studies which are not very well followed in terms of experimental measurements. Also, the use of complex models is not always founded. But then, the model of type three requires a limited number of boundary conditions and solves only a system of three equations at each time step. It allows a considerable saving in calculating times.

Calculation of maximum surface settlement induced by EPB shield tunnelling and introducing most effective parameter

This study aims to predict ground surface settlement due to shallow tunneling and introduce the most affecting parameters on this phenomenon.Based on data collected from Shanghai LRT Line 2 project undertaken by TBM-EPB method,this research has considered the tunnel's geometric,strength,and operational factors as the dependent variables.At first,multiple regression(MR) method was used to propose equations based on various parameters.The results indicated the dependency of surface settlement on many parameters so that the interactions among different parameters make it impossible to use MR method as it leads to equations of poor accuracy.As such,adaptive neuro-fuzzy inference system(ANFIS),was used to evaluate its capabilities in terms of predicting surface settlement.Among generated ANFIS models,the model with all input parameters considered produced the best prediction,so as its associated R^2 in the test phase was obtained to be 0.957.The equations and models in which operational factors were taken into consideration gave better prediction results indicating larger relative effect of such factors.For sensitivity analysis of ANFIS model,cosine amplitude method(CAM) was employed; among other dependent variables,fill factor of grouting(n) and grouting pressure(P) were identified as the most affecting parameters.

Modeling of Soot Formation in Gas Burner Using Reduced Chemical Kinetics Coupled with CFD Code

A computational study of soot formation in ethylene/air coflow jet diffusion flame at atmospheric pres-sure was conducted using a reduced mechanism and soot formation model. A 20-step mechanism was derived from the full mechanism using sensitivity analysis,reaction path analysis and quasi steady state(QSS) approximation. The model in premixed flame was validated and with computing savings in diffusion flame was applied by incor-porating into a CFD code. Simulations were performed to explore the effect of coflow air on flame structure and soot formation. Thermal radiation was calculated by a discrete-ordinates method,and soot formation was predicted by a simple two-equation soot model. Model results are in good agreement with those from experiment data and detailed mechanism at atmospheric conditions. The soot nucleation,growth,and oxidation by OH are all enhanced by decrease in coflow air velocity. The peak soot volume fraction region appears in the lower annular region be-tween the peak flame temperature and peak acetylene concentration locations,and the high soot oxidation rate due to the OH attack occurs in the middle annular region because of high temperature.

Assimilation of High Frequency Radar Data into a Shelf Sea Circulation Model

High Frequency(HF) radar current data is assimilated into a shelf sea circulation model based on optimal interpolation(OI) method. The purpose of this work is to develop a real-time computationally highly efficient assimilation method to improve the forecast of shelf current. Since the true state of the ocean is not known, the specification of background error covariance is arduous. Usually, it is assumed or calculated from an ensemble of model states and is kept in constant. In our method, the spatial covariances of model forecast errors are derived from differences between the adjacent model forecast fields, which serve as the forecast tendencies. The assumption behind this is that forecast errors can resemble forecast tendencies, since variances are large when fields change quickly and small when fields change slowly. The implementation of HF radar data assimilation is found to yield good information for analyses. After assimilation, the root-mean-square error of model decreases significantly. Besides, three assimilation runs with variational observation density are implemented. The comparison of them indicates that the pattern described by observations is much more important than the amount of observations. It is more useful to expand the scope of observations than to increase the spatial interval. From our tests, the spatial interval of observation can be 5 times bigger than that of model grid.

Prediction of Planing Craft Motion Based on Grey System Theory

In order to minimize the harm caused by the instability of a planing craft, a motion prediction model is essential. This paper analyzed the feasibility of using an MGM（1,N） model in grey system theory to predict planing craft motion and carried out the numerical simulation experiment. According to the characteristics of planing craft motion, a recurrence formula was proposed of the parameter matrix of an MGMfl,N） model. Using this formula, data can be updated in real-time without increasing computational complexity significantly. The results of numerical simulation show that using an MGM（1,N） model to predict planing motion is feasible and useful for prediction. So the method proposed in this study can reflect the planing craft motion mechanism successfully, and has rational and effective functions of forecasting and analyzing trends.

Validation of a method to predict hammer speed from cable force

Purpose： The purpose of this study was to develop and validate a method that would facilitate immediate feedback on linear hammer speed during training. Methods： Three-dimensional hammer head positional data were measured and used to calculate linear speed （calculated speed） and cable force. These data were used to develop two linear regression models （shifted and non-shifted） that would allow prediction of hammer speed from measured cable force data （predicted speed）. The accuracy of the two models was assessed by comparing the predicted and calculated speeds. Averages of the coefficient of multiple correlation （CMC） and the root mean square （RMS） of the difference between the predicted and calculated speeds for each throw of each participant were used to assess the level of accuracy of the predicted speeds. Results： Both regression models had high CMC values （0.96 and 0.97） and relatively low RMS values （1.27 m/s and 1.05 m/s） for the non-shifted and shifted models, respectively. In addition, the average percentage differences between the predicted and calculated speeds were 6.6% and 4.7% for the non-shifted and shifted models, respectively. The RMS differences between release speeds attained via the two regression models and those attained via three-dimensional positional data were also computed. The RMS differences between the predicted and calculated release speeds were 0.69 m/s and 0.46 m/s for the non-shifted and shifted models, respectively. Conclusion： This study successfully derived and validated a method that allows prediction of linear hammer speed from directly measured cable force data. Two linear regression models were developed and it was found that either model would be capable of predicting accurate speeds. However, data predicted using the shifted regression model were more accurate.

AN ACCURATE PREDICTION MODEL FOR COMPUTATIONAL OVERHEADS OF SECURITY MECHANISMS IN WIRELESS SENSOR NETWORKS

In Wireless Sensor Networks (WSNs), it is necessary to predict computational overheads of security mechanisms without final implementations to provide guidelines for system design. This paper presents an accurate and flexible model to predict overheads of these mechanisms. This model is based on overheads of basic operations frequently used in cryptography algorithms, which are essential elements of security mechanisms. Several popular cryptography algorithms and security mechanisms are evaluated using this model. According to simulation results, relative prediction errors are less than 7% for most cryptography algorithms and security mechanisms.

A Study on Simple Prediction Method of Heat Load： A Use of Linear Approximation Indicial Response in Basements

This study was conducted to establish a predictable method for a heat load of an underground structure with sufficient accuracy. As the first step, our previous paper reported the measurement results of field experiments on an underground experimental basement under internal heat generation conditions. Also, it presented the results of numerical analyses on the heat and moisture behavior and the influence of internal heat generation of the experimental basement and ground. However, it is practically impossible to utilize the model of simultaneous heat and moisture transfer at the design phase because the prediction by the model of simultaneous heat and moisture transfer requires a long calculation time. In this paper, the authors present the simple load calculation technique, using a linearized approximation indicial response of the inner surface heat flux in a basement to outdoor air temperature change. In addition, the approximation indicial responses for each part of the single-walled concrete drawn using this technique are arranged. The heat load calculation example of application to the basement of the optional size by this technique is shown.

Sensitivity Study of Design Parameters of a Railway Route under Vertical Deformations

Studying the interaction of components is basic for a railroad project, which is also very important for creating maintenance procedures based on predictions from a model that assumes adequate performance. To determine these interactions, which can have a great number of combinations, the use of a computational model is of vital importance, in this case, the program FERROVIA 1.0 （RAILROAD 1.0） was used. A critical study developed the program FERROVIA 1.0, and its variables were characterized based on values observed in the literature. After initial characterization was carried out, a comparative study was performed on the sensitivity between these variables and the indications of significant behavior for a railway deformed by the known load of a wheel. A statistical program was used to correlate the elements. The intention was to launch the program FERROVIA 1.0 and later use it for 2,187 combinations. The data used in these correlations corresponded to the normal values for the elements used in railroad engineering practice. Our main goal is to understand the behavior of the track vertical deflection according to the variation of the scaling of the various elements of the railway,

产量递减规律分析及产量预测

通过对产量递减规律模型的分析,结合油田的产量构成,分析计算油田产量递减指数n及Di值,建立油田老井产量计算模型,编制产量递减规律程序,以此为依据,建立油田各采油厂的新井和老井产量递减模型,并对油田各采油厂的新井产量和老井产量进行实际和预测值的对比分析,为油田下步配产和开发调整提供依据。

Progress in mesoscopic modeling of microstructure evolution in steels

The mesoscopic modeling developed rapidly in the past three decades is a promising tool for predicting and understanding the microstructure evolution at grain scale.In this paper,the recent development of mesoscopic modeling and its application to microstructure evolution in steels is reviewed.Firstly,some representative computational models are briefly introduced,e.g.,the phase field model,the cellular automaton model and the Monte Carlo model.Then,the emphasis is put on the application of mesoscopic modeling of the complex features of microstructure evolution,including solidification,solid-state phase transformation,recrystallization and grain growth.Finally,some issues in the present mesoscopic modeling and its perspective are discussed.

Experimental and computational correlation and prediction on herbicide resistance for acetohydroxyacid synthase mutants to Bispyribac

Bispyribac is a widely used herbicide that targets the acetohydroxyacid synthase （AHAS） enzyme. Mutations in AHAS have caused serious herbicide resistance that threatened the continued use of the herbicide. So far, a unified model to decipher herb- icide resistance in molecular level with good prediction is still lacking. In this paper, we have established a new QSAR method to construct a prediction model for AHAS mutation resistance to herbicide Bispyribac. A series of AHAS mutants concerned with the herbicide resistance were constructed, and the inhibitory properties of Bispyribac against these mutants were meas- ured. The 3D-QSAR method has been transformed to process the AHAS mutants and proposed as mutation-dependent biom- acromolecular QSAR （MB-QSAR）. The excellent correlation between experimental and computational data gave the MB-QSAR/CoMFA model （q2 = 0.615, P = 0.921, F2pred = 0.598） and the MB-QSAR/CoMSIA model （q2 = 0.446, r2 = 0.929, r2pred = 0.612）, which showed good prediction for the inhibition properties of Bispyribac against AHAS mutants. Such MB-QSAR models, containing the three-dimensional molecular interaction diagram, not only disclose to us for the first time the detailed three-dimensional information about the structure-resistance relationships, but may also provide further guidance to resistance mutation evolution. Also, the molecular interaction diagram derived from MB-QSAR models may aid the resistance-evading herbicide design.

Prediction method of impeller performance and analysis of loss mechanism for mixed-flow pump

A loss model for the mixed-flow pump impellers was developed by summarizing a variety of loss calculation formulas systematically.The internal flow field of the impeller was obtained by employing the iterative calculation for S 1 and S 2 stream surfaces to solve the continuity and motion equations of fluid.Based on the calculation method of the flow field and the loss model,it is achieved to predict the impeller performance of the mixed-flow pump and the performance curves of a mixed-flow pump model with adjustable blades.Compared with the test data,the loss model of the mixed-flow pump based on the iterative calculation can predict the impeller performance quickly and accurately,which has a high value on the engineering applications.Based on the test verification,curves of various kinds of losses varied for the flow rate were analyzed under different blade angles.In addition,the mechanisms of various kinds of losses inside the mixed-flow pump impeller were discussed in-depth.

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.