一种热轧带钢力学性能预报模型的适用性分析方法

GLOSP模型是以宝钢2050 mm热轧产线的实际生产数据为基础,历经10年的探索与研究,从实际应用的角度研制出的一个全局通用型热轧带钢力学性能预报模型.提出了一种GLOSP模型的适用性分析方法,该方法通过设置分组变量以剔除一些可见因素造成的干扰,并在各分组内分别对力学性能实测值、预报值与其关键自变量进行线性回归,进而根据相应线性回归系数的相似度进行模型的适用性分析.应用实践表明,该方法不仅有效,还为模型的跨产线应用提供了方便.     

针叶树理论材积式在长白山地区的适用性研究

利用吉林省汪清林业局金沟岭林场的963株解析木资料,对由日本井上昭夫与黑川泰亨利用孔兹干曲线推导的针叶树立木材积的理论二元材积公式与东北针叶树二元材积表进行精度检验.结果表明,理论材积式与实际材积和经验材积式之间均极显著相关;理论材积式在红松(Pinus Roraiensis)、落叶松(Larix gmelinii)与云杉(Picea peratu)的精度验证中均比经验材积式的精度高,而且达到我国材积式适用精度要求,适用于长白山地区针叶树材积的计算.     

4种杂交杨荧光光响应曲线

比较研究伊犁地区杂交杨4个不同品系(P.deltaidscv-64 (P64),P.balsamifera L.(Da),P.euramericana(I-262)和P.euramerieanacv (I-467))的荧光参数与光量子通量密度(D_PF)的响应变化特征.4种杂交杨的光照下最大可变荧光(F'm)大小直接影响光合反应中心最大的开放程度和实际的开放程度(φpsπ)的大小;光照下最小荧光(F'o)更多地参与4种杂交杨的orsn能量捕获效率.光合速率(Pn)作为植物生物行为对于植物叶绿素光捕获的光化学行为存在滞后效应,而真正决定植物转化光能的总量由植物叶片叶绿素捕获光量子量决定.υETR反映植物驱动PS Ⅱ的实际量子流量,υETR达到最大值时,光化学反应转化的光能量PE也同样达到最大值,是植物最大限度转化利用太阳能的点.建议用υETR和DPF的荧光光响应曲线作为计算和估算植物对光能的利用及叶片光能转化为净能量的能力,是比表观量子效率更为理想的指标.     

不同湍流模型在中间包钢液流动数值模拟中的适用性研究

摘要：连铸中间包内部结构复杂,钢液流动状态多样,详尽准确的钢液流场信息是中间包控制和优化的前提。数值模拟方法已广泛应用于中间包内钢液流场研究,钢液流场的精确数值模拟离不开合适的湍流模型及相应的边界条件。基于CFD开源代码包OpenFOAM v8,分别应用标准k-ε模型、RNG k-ε模型、SST k-ω模型3种湍流模型,对称面边界、自由滑移边界2种液面边界条件,对中间包流场进行了数值模拟。通过与文献中实验结果比较,发现采用SST k-ω模型可以成功预测RTD曲线的“双峰”,且响应时间、峰值时间与实验结果较为接近;应用SST k-ω模型时,将液面边界类型由自由滑移改为对称面,获得的示踪剂响应时间的误差由93.89%降低至8.35%以下,峰值时间的误差由100.78%降低至12.32%左右。因此,SST k-ω模型、对称面液面边界可以较好地描述中间包内钢液流动过程。     

水平层状岩体边坡动力响应中的结构面效应研究

根据应力波传播原理分析了水平层状岩体边坡中应力波传播特征,建立了应力波在该类边坡中传播的模型.利用离散元软件UDEC分析了不同频率垂向压缩应力波作用下边坡动力响应规律中的结构面效应.结果表明:边坡中的水平层面对坡顶的动力响应有明显影响.低频应力波作用下,水平层状岩体边坡坡顶的垂向峰值速度较均质坡体相同部位的峰值速度的增加值随坡高增加而增大.较高频率应力波作用时,边坡顶部靠近坡面的垂向峰值速度高于无结构面边坡相同部位的峰值速度,远离坡面时情况相反;坡顶垂向峰值速度大小呈周期性变化,输入应力波频率越大该变化频次越高.研究结果将有助于进一步揭示各种不同岩体结构类型边坡在动力荷载作用下损伤机理及破坏模式.     

一种新的控制模型在中厚板定尺剪切中的应用研究

针对目前中厚板定尺剪在定尺送料过程中存在的精度和效率低下等问题,提出一种新的动态误差参数补偿的控制模型,充分利用夹送辊驱动装置的控制回路作为该控制模型的一部分,重点解决了控制模型工艺设置,实现方法及动态误差参数补偿等问题。实际应用结果表明钢板定尺长度L=6~14mm,厚度h=25~40mm,v=1~2m/s时,送板精度小于3mm。     

2种群体平衡模型在连铸结晶器多尺寸泡状流中的应用

摘要：准确预测连铸结晶器内多尺寸泡状流的流动特性对洁净钢水和提高铸坯质量至关重要。为了考虑气泡聚并、破碎等微观现象对气泡尺寸、数密度、含气率等宏观参量的影响,分别采用2种基于群体平衡方程的数学模型—多气泡组质量传递模型（MUSIG）与平均气泡数密度模型（ABND）,对连铸结晶器内的多尺寸泡状流进行了数值模拟,并与水模型实验结果进行了对比研究。结果发现：2种群体平衡模型均可以较准确地捕捉到结晶器多尺寸泡状流中的液相流型、气泡尺寸以及含气率分布特征,尤其是较好地预测了浸入式水口内部含气率的“中间峰”和“出口峰”分布特征;相比于MUSIG模型,ABND模型对靠近水口处气泡尺寸分布的预测结果更加准确。2种群体平衡模型扩展了传统单一粒径双流体模型的适用范围,为结晶器内多尺寸泡状流研究提供了理论基础和数学框架。     

多层线性模型在碳钢土壤腐蚀规律中的应用研究

针对材料在自然土壤环境中的腐蚀预测问题,提出应用多层线性模型对材料的腐蚀规律进行研究.多层线性模型是分析具有层次结构数据的新型统计技术,对于地区间土壤腐蚀规律的差异性特点和单地区实验观测样本不足的问题,可以为不同的区域分别建立腐蚀率模型,使模型假设与实际更为吻合.以碳钢在土壤中的腐蚀数据为研究对象,建立了腐蚀率的多层线性模型.实验验证了该模型可以准确地拟合和预测碳钢在土壤的腐蚀率变化,优于指数平滑算法和差分自回归移动平均算法.     

高强IF钢应变硬化模型研究及在仿真对标中的应用

针对汽车用高强IF钢CR180IF和CR260IF,将拉伸试验机获得的工程应力-应变曲线转变为真实应力-塑性应变曲线,分别采用Swift和Hockett-Sherby应变硬化方程进行拟合,获得拟合参数.通过设定权重系数α,建立Swift-Hockett-Sherby混合应变硬化模型.通过拉伸试验仿真对标,当α值分别为0...     

基于GIS的新安江模型在潦河流域洪涝灾害评估中的应用研究

针对潦河流域的水文特征,采用1996～2005年潦河流域的实测水文、气象观测资料,并利用GIS处理DEM数据,对新安江分布式水文模型所需的各参数进行了优选,并构建了基于GIS的新安江水文模型,通过多次实际洪涝灾害数据的验证,结果表明该模型较为可靠,为建立潦河流域洪水预报系统和灾害预报、评估业务系统奠定了模型基础.     

Applicability of Quasisteady and Axisymmetric Turbulence Models in Water Hammer

Two of the existing turbulence water hammer models, namely the two-layer and the five-layer eddy viscosity models, are implemented and analyzed and the accuracy of their quasi-steady and axisymmetric assumptions evaluated. In addition, a dimensionless parameter P (ratio of the time scale of radial diffusion of shear to the time scale of wave propagation) for assessing the accuracy of quasi-steady turbulence modeling in water hammer problems is developed and applied. It is found that the results of both models are in reasonable agreement, confirming that the turbulence modeling of water hammer flows is insensitive to the magnitude and distribution of the eddy viscosity within the pipe core. Comparison of model results with available data shows that the quasi-steady assumption becomes more accurate as the dimensionless parameter P increases. Furthermore, the analysis shows that the quasi-steady assumption is highly accurate as long as the simulation time is below the diffusion time scale and that this assumption causes an almost linear increase in the difference between model results and data with time. The accuracy of the flow axisymmetry assumption is evaluated by applying both models to a water hammer problem where flow asymmetry has been observed experimentally. It is found that the difference between models and data grows exponentially and reaches 100% after six wave periods.     

A Comparison of Four Precipitation Distribution Models Used in Daily Stochastic Models

Stochastic weather generators are statistical models that produce random numbers that resemble the observed weather data on which they have been fitted; they are widely used in meteorological and hydrological simulations.For modeling daily precipitation in weather generators,first-order Markov chain-dependent exponential,gamma,mixed-exponential,and lognormal distributions can be used.To examine the performance of these four distributions for precipitation simulation,they were fitted to observed data collected at 10 stations in the watershed of Yishu River.The parameters of these models were estimated using a maximum-likelihood technique performed using genetic algorithms.Parameters for each calendar month and the Fourier series describing parameters for the whole year were estimated separately.Bayesian information criterion,simulated monthly mean,maximum daily value,and variance were tested and compared to evaluate the fitness and performance of these models.The results indicate that the lognormal and mixed-exponential distributions give smaller BICs,but their stochastic simulations have overestimation and underestimation respectively,while the gamma and exponential distributions give larger BICs,but their stochastic simulations produced monthly mean precipitation very well.When these distributions were fitted using Fourier series,they all underestimated the above statistics for the months of June,July and August.     

Validation and Application of Empirical Liquefaction Models

Empirical liquefaction models (ELMs) are the standard approach for predicting the occurrence of soil liquefaction. These models are typically based on in situ index tests, such as the standard penetration test (SPT) and cone penetration test (CPT), and are broadly classified as deterministic and probabilistic models. No objective and quantitative comparison of these models have been published. Similarly, no rigorous procedure has been published for choosing the threshold required for probabilistic models. This paper provides (1) a quantitative comparison of the predictive performance of ELMs; (2) a reproducible method for choosing the threshold that is needed to apply the probabilistic ELMs; and (3) an alternative deterministic and probabilistic ELM based on the machine learning algorithm, known as support vector machine (SVM). Deterministic and probabilistic ELMs have been developed for SPT and CPT data. For deterministic ELMs, we compare the “simplified procedure,” the Bayesian updating method, and the SVM models for both SPT and CPT data. For probabilistic ELMs, we compare the Bayesian updating method with the SVM models. We compare these different approaches within a quantitative validation framework. This framework includes validation metrics developed within the statistics and artificial intelligence fields that are not common in the geotechnical literature. We incorporate estimated costs associated with risk as well as with risk mitigation. We conclude that (1) the best performing ELM depends on the associated costs; (2) the unique costs associated with an individual project directly determine the optimal threshold for the probabilistic ELMs; and (3) the more recent ELMs only marginally improve prediction accuracy; thus, efforts should focus on improving data collection.     

Empirical Predictive Models for Earthquake-Induced Sliding Displacements of Slopes

Earthquake-induced sliding displacement is the parameter most often used to assess the seismic stability of slopes. The expected displacement can be predicted as a function of the characteristics of the slope (yield acceleration) and the ground motion (e.g., peak ground acceleration), yet there is significant aleatory variability associated with the displacement prediction. Using multiple ground motion parameters to characterize the earthquake shaking can significantly reduce the variability in the prediction. Empirical predictive models for rigid block sliding displacements are developed using displacements calculated from over 2,000 acceleration–time histories and four values of yield acceleration. These empirical models consider various single ground motion parameters and vectors of ground motion parameters to predict the sliding displacement, with the goal of minimizing the standard deviation of the displacement prediction. The combination of peak ground acceleration and peak ground velocity is the two parameter vector that results in the smallest standard deviation in the displacement prediction, whereas the three parameter combination of peak ground acceleration, peak ground velocity, and Arias intensity further reduces the standard deviation. The developed displacement predictive models can be used in probabilistic seismic hazard analysis for sliding displacement or used as predictive tools for deterministic earthquake scenarios.     

Hardening Models and Their Predictions of Material Response

Several hardening models are investigated in this paper to examine how they predict material behavior under closed-loop loading paths. The linear Prager's kinematic hardening rule and a new kinematic hardening model proposed in a previous paper are first used to solve a thin-walled tube problem subjected to combined internal pressure and axial loads. Closed-form transient and steady-state solutions are achieved for closed-loop loading paths, and the corresponding yield center loci and plastic strain trajectories are illustrated. This paper then shows that Phillips's kinematic hardening rule and the two-surface plasticity theory all predict an unreasonable material response. A conclusion is finally reached that the newly proposed kinematic hardening model has more potential than the other models, and further theoretical and experimental investigations are suggested to probe the optimum form of the plastic modulus to make this new model qualitatively, and also quantitatively, describe well material behavior.     

层流冷却过程低碳钢相变模型的适用性分析

选取了现有典型的C-Mn钢相变过程的物理冶金模型,包括5组孕育期模型、7组相变动力学方程模型、5组相变后铁素体晶粒尺寸模型.利用自行开发的组织性能预报系统软件模拟计算了在3组实际冷却工艺条件下各模型的奥氏体转变过程,并对各模型进行了评价.结果表明,对于所设定的成分和工艺条件,适用性较好的孕育期模型是Kwon所提出的模型...     

New Light on Response of Linear Systems Subjected to Random Nonstationary Filtered Inputs

It is shown here that the response of any linear system subjected to the action of filtered nonstationary or stationary stochastic processes can exactly be replaced by a linear combination of the responses of linear systems subjected to white noise processes. These linear systems have the same dimensions as the structural and filtered ones. In this way the simplifications related to the analysis of linear systems subjected to white noise inputs can be used as they happen, using classical approaches and without increasing the dimensions of the stochastic problem. Only knowledge of the filter equations is required to obtain this property.     

Applicability of Kinematic, Noninertia, and Quasi-Steady Dynamic Wave Models to Unsteady Flow Routing

Propagation of flood waves in an open channel can be mathematically approximated by the Saint-Venant equations (dynamic wave) or by their simplifications including the kinematic wave, noninertia wave, gravity wave, and quasi-steady dynamic wave models. All of these wave approximations differ not only in the physical propagation mechanism, but also in the degree of complexity involved in computation. In order to efficiently implement the approximate wave models for flood routing, their criteria of applicability should be developed. The applicability of the kinematic wave, noninertia wave, and quasi-steady dynamic wave approximations to the full dynamic wave equations for unsteady flow routing is examined by comparing the propagation characteristics of a sinusoidal perturbation to the steady gradually varying flow for different simplified wave models. Development of the applicability criteria provides a guideline for selecting an appropriate wave model for unsteady flow modeling, thus enabling an assessment of the capabilities and limitations of different simplified wave models. By using the linear stability analysis, the derived criteria can be expressed in terms of dimensionless physical parameters that represent the unsteadiness of the wave disturbance, characteristics of the downstream boundary condition (backwater effect), and the location along the channel. The developed criteria are for a specific point and time, thereby providing a more refined indication than the integrated criteria based on the testing for a hydrograph found commonly in the literature. In this study, we have justified whether the simplified wave models such as the kinematic, noninertia, or gravity wave models would be appropriate and reliable approximations to the full Saint-Venant equations with a comparable accuracy for a given flow condition. The downstream backwater effect has been taken into consideration in the developed criteria for broader engineering applications. One hypothetical example is presented for illustration.     

Applicability of Equilibrium Isotherm Models for the Biosorptive Uptakes in Comparison to Activated Carbon-Based Adsorption

The adsorption isotherm models available in the literature have generally developed for sorption onto metallic surfaces or activated carbon-based sorbents. However, biosorptive uptakes involve interactions of biopolymer-based surfaces with different types of pollutants, which are quite different from metal surfaces or activated carbon. So, in the present study, 16 different types of adsorption isotherm models have been studied. For a ready reference both types of sorbents, i.e., a biosorbent and activated carbon have been employed. Results show that in general the accuracy of models to fit experimental data improves with the degree of freedom. The Fritz–Schluender model gives the most accurate fit (R2?0.85–0.99) to all experimental data in comparison to other models used both for activated carbon and the biosorbent. However, most widely used isotherm models, i.e., Langmuir and Freundlich, could be used to describe the sorption equilibrium of biosorptive processes with a fair degree of accuracy, owing to the mathematical ease in the use of these models. Trends of the applicability of various sorption equilibrium models to biosorptive uptakes are similar to those of activated carbon-based sorptions. Comprehensive equilibrium analysis has assisted in understanding the mechanistic aspects associated with different types of sorbents.