Neural network approach for estimation of hole-diameter in thin plates perforated by spherical projectiles

Despite the availability of large number of empirical and semi-empirical models, the problem of hole-diameter prediction for thin metallic plates has remained inconclusive partly due to the complexity of the phenomenon involved and partly because of the limitations of the statistical regression employed. Conventional statistical analysis is now being replaced in many fields by the alternative approach of neural networks. Neural networks have advantages over statistical models like their data-driven nature, model-free form of predictions, and tolerance to data errors. The objective of this study is to reanalyze the data for the prediction of hole-diameter by employing the technique of neural networks with a view towards seeing if better predictions are possible. The data used in the analysis pertains to the strike of spherical projectile on thin metallic targets and the neural network models result in very low errors and high correlation coefficients as compared to the regression based models.     

High velocity impact of metal sphere on thin metallic plate using smooth particle hydrodynamics (SPH) method

The modeling of high velocity impact is an important topic in impact engineering. Due to various constraints, experimental data are extremely limited. Therefore, detailed numerical simulation can be considered as a desirable alternative. However, the physical processes involved in the impact are very sophisticated; hence a practical and complete reproduction of the phenomena involves complicated numerical models. In this paper, we present a smoothed particle hydrodynamics (SPH) method to model two-dimensional impact of metal sphere on thin metallic plate. The simulations are applied to different materials (Aluminum, Lead and Steel); however the target and projectile are formed of similar metals. A wide range of velocities (300, 1000, 2000, and 3100 m/s) are considered in this study. The goal is to study the most sensitive input parameters (impact velocity and plate thickness) on the longitudinal extension of the projectile, penetration depth and damage crater.     

弹丸对混凝土薄板的冲击破坏效应

介绍高速弹丸冲击混凝土薄板后所产生的贯穿破坏效应,通过模型试验、数值模拟和量纲理论分析,取得了三者吻合较好的结果,并导出了计算弹丸穿透混凝土薄板后残余速度的经验公式。通过弹丸撞击有限厚度钢筋混凝土靶板的模型试验,获得了有关靶板冲击破坏的宏观图象及弹丸贯穿靶板后的残余速度。介绍了非线性三维动力有限元程序和混凝土材料的脆性损伤模型,对弹丸冲击效应试验中的靶板破坏过程进行了数值模拟,通过数值模拟计算,形象地再现了弹丸高速冲击作用下,钢筋混凝土靶板发生贯穿破坏的物理过程,数值模拟结果与试验中靶板的实际破坏图象十分吻合。通过量纲分析,得出了描述钢筋混凝土板冲击破坏效果各参数之间的无量纲关系,利用现场试验数据进行回归,导出了贯穿条件下的弹丸余速计算公式。     

BLU-109B模型弹在岩石介质中成坑效应试验研究

国外防护工程设计规范中基本上采用经验法评估各种弹体对岩石介质的毁伤问题,而在我国现行规范中尚未涉及该方面的问题。根据相似准则建立弹坑比例半径同弹体侵彻深度和弹体装药参数的函数关系。通过试验和数据回归分析给出BLU–109B钻地模型弹在岩石介质中爆炸成坑的经验公式,并根据试验结果总结出了同等介质条件下弹速和装药对弹坑半径、弹坑深度及弹坑体积的影响曲线。试验结果表明：弹坑半径大小主要取决于弹速、装药量和岩石介质力学性能。在靶体相同和同等装药条件下弹速是毁伤岩石的主要因素。当弹速低于450 m/s时,弹坑半径大小主要取决于侵彻弹坑半径;当弹速超过450 m/s时,弹坑半径的大小将取决于装药爆炸后所形成的弹坑半径,弹坑体积将随之迅速增加。     

Model-based moisture sorption stabilization in historical buildings

A novel air humidity control technique is proposed for preventing the moisture sensitive materials from varying their equilibrium moisture content, providing in this way more desirable environment conditions for preventive conservation of cultural heritage. The moisture content in artistic works or historical exhibits deposited in historical buildings is stabilized by means of a specific adjustment of the interior air humidity while the annual temperature variations in the interior are left almost unaffected. The proposed humidity control compensating for the impact of temperature changes on EMC variations is based on the application of sorption phenomena models while both the used models are not applied to estimate EMC but to suggest a prevention of its varying. Namely the Kelvin theory of micro-pore condensation and the Henderson model of moisture sorption are applied to determine the so-called equal-sorption humidity control. For long two implementations of this control – in a castle and archives collections – prove the ability of this control to stabilize the moisture content in the preserved exhibits at constant admissible level.     

弹体侵彻靶体的弹道轨迹预测分析

现代战争对弹体在侵彻靶体过程中运动轨迹的准确性和可预测性提出了较高的要求,以试验为主的传统方法和纯粹的数值模拟方法均不能对预测弹体在深层侵彻过程中的运动与相关设计提供有效的方法。本文详细阐述了基于弹靶分离方法程序的发展现状,进而解释了弹体与靶体介质分离的方法,描述了建立弹体在靶体介质中运动、变形及磨损的理论框架和开发方案。建立了一种包含经验公式、理论方法及数值模拟的分析方法,从而能够对弹体的深层侵彻过程进行快捷、有效及准确的预测,为弹体设计及防护工程设计提供有效的工具,为军事打击效果评估提供实时数据。     

Backflow air and pressure analysis in emptying a pipeline containing an entrapped air pocket

ABSTRACT

The prediction of the pressure inside the air pocket in water pipelines has been the topic for a lot of research works. Several aspects in this field have been discussed, such as the filling and the emptying procedures. The emptying process can affect the safety and the efficiency of water systems. Current research presents an analysis of the emptying process using experimental and computational results. The phenomenon is simulated using the two-dimensional computational fluid dynamics (2D CFD) and the one-dimensional mathematical (1D) models. A backflow air analysis is also provided based on CFD simulations. The developed models show good ability in the prediction of the sub-atmospheric pressure and the flow velocity in the system. In most of the cases, the 1D and 2D CFD models show similar performance in the prediction of the pressure and the velocity results. The backflow air development can be accurately explained using the CFD model.     

Estimating moment capacity of ferrocement members using self-evolving network

In this paper, an empirical model based on self-evolving neural network is proposed for predicting the flexural behavior of ferrocement elements. The model is meant to serve as a simple but reliable tool for estimating the moment capacity of ferrocement members. The proposed model is trained and validated using experimental data obtained from the literature. The data consists of information regarding flexural tests on ferrocement specimens which include moment capacity and cross-sectional dimensions of specimens, concrete cube compressive strength, tensile strength and volume fraction of wire mesh. Comparisons of predictions of the proposed models with experimental data indicated that the models are capable of accurately estimating the moment capacity of ferrocement members. The proposed models also make better predictions compared to methods such as the plastic analysis method and the mechanism approach. Further comparisons with other data mining techniques including the back-propagation network, the adaptive spline, and the Kriging regression models indicated that the proposed models are superior in terms prediction accuracy despite being much simpler models. The performance of the proposed models was also found to be comparable to the GEP-based surrogate model.     

The effect of political unrest on construction time for food grain warehouses in Bangladesh

A range of poorly understood factors affect actual construction time in the context of food sector projects in Bangladesh. One factor of particular interest is political unrest. The data for this study were obtained from a leading design and construction management company in Bangladesh. The sample size consisted of data for 104 food grain warehouse projects scattered all over the country. The effect of political unrest on construction time was analysed in conjunction with other known variables for actual construction time, such as increase in project cost and delay in procurement of construction materials. The effect of local political unrest on construction time was statistically significant even in the presence of project cost and procurement of materials variables. Political unrest could be included in prediction models used for finding out actual construction time of food grain warehouse projects in Bangladesh. Based on these findings, a prediction model for construction time for such projects is developed.     

利用层速度钻前预测安全泥浆密度窗口研究

地震波在地层中的传播速度和岩层的性质，如弹性参数、地层成分、密度、埋藏深度、地质年代、孔隙率、构造运动等因素有关。特定的层速度分布规律包含着丰富的地层信息，能不同程度地反映地层力学特性。通过相似构造分析找出与预测井所在构造相似的构造，作相似构造测井速度与层速度误差补偿分析，在深刻地认识相似构造的井壁稳定性基础上，建立了基于趋势面分析理论的钻前预测井壁稳定模型，并对塔里木油田YN4井的安全泥浆密度窗口进行了钻前预测，现场应用表明，本文研究的预测模型是较为成功的。     

锚固岩体抗侵彻分析模型

目前对岩体介质抗侵彻方面研究文献资料较多,但尚无弹丸侵彻锚固岩体的理论计算公式或经验公式,本文在球形空腔膨胀模型的基础上,利用球形空腔膨胀模型计算岩石介质对弹丸的侵彻阻力,计入了弹丸直接与锚固岩体中锚杆发生碰撞的侵彻阻力,并将弹丸侵彻过程中岩石介质和锚杆侵彻阻力进行叠加,建立了弹丸垂直侵彻锚固岩体的工程分析模型。与单一空腔膨胀模型和试验数据进行对比后,模型计算结果与模拟试验结果基本一致,表明了研究具有一定的理论意义和工程适用价值。从而为洞库等地下防护工程设计及其加固改造提供理论研究方法和技术支持。     

Analytical model for the torsional behaviour of reinforced concrete beams retrofitted with FRP materials

An analytical approach for the prediction of the torsional response of reinforced concrete (RC) beams strengthened with fibre-reinforced-polymer (FRP) materials is described. The analysis method employs the combination of two different theoretical models: a smeared crack model for plain concrete in torsion for the elastic till the first cracking response and a properly modified truss model for the post-cracking response. The proposed method addresses the contribution of the externally bonded FRP materials to the torsional capacity of RC beams using specially developed equations in the well-known truss theory and utilizes softened and FRP-confined concrete stress–strain relationships. Detailed verification of this methodology is achieved through extensive comparisons between analytically predicted behaviour curves and experimentally obtained ones. The experimental data comprise a series of 12 tests in pure torsion and an additional database of experimental information for 24 specimens compiled from works around the world. These comparisons demonstrated that the proposed model is capable of adequately describing the full torsional response and of predicting with satisfactory accuracy the torsional moment at cracking and the ultimate torque capacity of FRP strengthened RC beams. Applications of the developed method as an assessment tool to strengthened beams with U-shaped FRP configurations and some first design examples that demonstrate the contribution of the FRP materials on the torsional response are also included.     

基于BP神经网络的堆肥物料抗剪强度预测模型

针对目前传统方式采集堆肥物料抗剪强度数据过程中环境恶劣、数据采集困难、试验误差大等问题,提出一种基于BP神经网络的抗剪强度预测模型。通过现场试验得到堆肥物料抗剪强度和堆体高度、温度、含水率、密度等参数共39组有效数据,以其中35组作为训练样本,其余4组用于评价模型的预测性能。结果表明,该模型预测值与实测值的平均误差为11. 35%,基于BP神经网络的抗剪强度预测模型具有较高的预测精度,为抗剪强度的预测提供了一种新方法。     

粒状材料的一个实用弹塑性模型

提出了一个适用于粒状材料的简单而实用的弹塑性模型，该模型通过对修正剑桥模型进行改进，能够反映三维应力状态下的剪胀剪缩性和变形、强度的平均应力依存性。模型参数可由邓肯－张模型参数换算。用建议模型对某土石坝的石渣料进行了预测和比较，结果表明，模型能够合理地预测粒关材料的变形和强度特性。     

超高韧性水泥基复合材料K&C模型参数确定

超高韧性水泥基复合材料 (UHTCC) 具有超高的延性、优异的能量吸收能力以及良好的耐久性,其在防护结构中有着广泛的应用前景。K&C模型被用于研究混凝土类准脆性材料在动态荷载作用下动力特性,但是该模型无法准确地描述UHTCC这种韧性水泥基材料的各项动态力学特性。为得到适用于UHTCC的K&C模型参数,基于现有UHTCC材料单轴压缩/拉伸、霍普金森杆的压缩/劈裂和三轴压缩试验数据,校核K&C模型中的损伤参数、应变率效应参数以及强度面参数,并采用改进后的K&C模型参数模拟UHTCC靶体在接触爆炸荷载下的动态响应。模拟结果表明：采用改进后的K&C模型参数对爆炸荷载下UHTCC靶板迎爆面的开坑尺寸预测结果与相应文献中的试验结果基本一致,相差在6%以内。同时,改进的K&C模型参数相较于其他K&C模型参数可以更为准确地预测UHTCC靶板在爆炸荷载作用下的损伤分布和破坏形态。为了进一步验证改进的K&C模型参数的准确性,利用LS-DYNA软件预测了弹体高速冲击UHTCC靶体时弹体的侵彻深度和靶体的迎弹面开坑直径,发现模拟结果与文献中的试验结果较为吻合。     

强冲击荷载下RC板失效仿真研究

为了更有效地模拟强冲击荷载作用下混凝土材料的失效行为,采用LS-DYNA软件,基于HJC模型,建立弹体冲击钢筋混凝土(RC)板有限元模型,研究失效类型、主应变、剪应变和应力等参数对弹体侵彻混凝土并贯穿RC板的影响规律。结果表明:当失效控制参数FS值取0或1.0～1.5时,部分模型的弹体未能贯穿RC板,与试验现象不符; 当FS值为0.1～0.9时,弹体侵彻贯穿RC板后的残余速度随FS值的增大而减小,其中FS值为0.3～0.8时,模拟得到的残余速度与试验值吻合较好; 在模型中添加失效准则,当主应变取0.225～0.275或剪应变取0.4～0.5时,弹体以606、746、1 058 m·s^-1的速度冲击贯穿RC板的残余速度计算值与试验值更接近; 在考虑主应变失效、剪应变失效或二者共同作用时,FS值为0.8时的模拟结果与试验结果的吻合程度较好; 拉伸应力失效准则不适用于较薄RC板遭受强冲击荷载作用的情况。     

准脆性材料弹性损伤分析中的概率体元建模

确定材料细观单元的材料物理力学性能的概率分布，以形成细观概率体元，是对岩石、混凝土等准脆性材料进行弹性损伤模拟分析的基础，也是基于弹性损伤模型的有限元岩石破裂过程分析系统为材料非均匀赋值的依据。通过对岩石类材料破坏过程分析中采用的Weibull分布、正态分布、类Weibull分布所作的讨论和剖析，建议采用对数正态分布作为改进方法，并从理论上对所建议的概率体元模型予以说明。通过基于各种概率分布的材料本构关系的相互对比，证明所建议的概率分布适于构造弹性损伤分析中细观概率体元，可被纳入有限元岩石破裂过程分析系统的分布类型库中，同时间接证明了采用Weibull分布是合适的，也证明了正态分布和类Weibull分布在弹性损伤概率模型中则是应当排除的。     

Prediction of rockhead using a hybrid N-XGBoost machine learning framework

The spatial information of rockhead is crucial for the design and construction of tunneling or underground excavation. Although the conventional site investigation methods (i.e. borehole drilling) could provide local engineering geological information, the accurate prediction of the rockhead position with limited borehole data is still challenging due to its spatial variation and great uncertainties involved. With the development of computer science, machine learning (ML) has been proved to be a promising way to avoid subjective judgments by human beings and to establish complex relationships with mega data automatically. However, few studies have been reported on the adoption of ML models for the prediction of the rockhead position. In this paper, we proposed a robust probabilistic ML model for predicting the rockhead distribution using the spatial geographic information. The framework of the natural gradient boosting (NGBoost) algorithm combined with the extreme gradient boosting (XGBoost) is used as the basic learner. The XGBoost model was also compared with some other ML models such as the gradient boosting regression tree (GBRT), the light gradient boosting machine (LightGBM), the multivariate linear regression (MLR), the artificial neural network (ANN), and the support vector machine (SVM). The results demonstrate that the XGBoost algorithm, the core algorithm of the probabilistic N-XGBoost model, outperformed the other conventional ML models with a coefficient of determination (R²) of 0.89 and a root mean squared error (RMSE) of 5.8 m for the prediction of rockhead position based on limited borehole data. The probabilistic N-XGBoost model not only achieved a higher prediction accuracy, but also provided a predictive estimation of the uncertainty. Thus, the proposed N-XGBoost probabilistic model has the potential to be used as a reliable and effective ML algorithm for the prediction of rockhead position in rock and geotechnical engineering.     

高速侵彻弹弹头结构设计探索

高速弹体侵彻过程中,弹体的分段设计以及弹体头部的自锐化效应有利于提高弹体的侵彻性能。本文探讨了弹头分层结构设计,其间接反映了分段设计和自锐化效应的影响;同时,采用二维拉格朗日弹塑性流体力学有限元程序LTZ-2D数值模拟了弹体的高速侵彻过程。计算结果显示,弹体头部采用分层结构设计有利于提高弹体的侵彻性能。     

材料应变局部化分析中不同内尺度律参数间相互作用问题的讨论

梯度塑性和与速率相关的本构模型在动力学应变分析中会起到引入材料内尺度律的作用。利用这两种模型进行动力学软化与应变局部化分析均会使有限元计算的数值结果不再具有网格依赖性。讨论了这两种模型各自所具有的内尺度律效应，研究了两种模型综合使用条件下的内尺度律结果，给出了参数相互作用条件下内尺度律的计算方法。该方法具有一般性。利用该方法，进一步揭示了率相关与梯度塑性模型各自所具有的内尺度律的数学本质，并以数值算例说明了理论预测的正确性。