强水敏砂岩油藏水驱油相对渗透率曲线异常分析

以强水敏砂岩油藏实际岩样为例,通过水驱油渗流实验和渗流物理分析,探讨强水敏砂岩油藏水驱油过程相对渗透率曲线异常现象及其对油藏开发的影响。     

双排刚性桩屏障对平面SH波的隔离性状研究

基于Twersky的理论,引入圆柱体对声波和电磁波的多重散射解析解,对用排桩隔离环境振动的问题,提出了一种新的求解任意排列、任意直径刚性桩对平面SH波多重散射的理论方法,解决了传统的假设单重散射的计算方法中不考虑桩列作为整体屏障从而忽略桩间相互干涉关系的不足。随后,在数值计算分析中讨论了散射重数,排间距,桩间距等因素对双排刚性桩隔振效果的影响,对实际工程中利用排桩进行振动污染治理和屏障隔振的设计提出了有意义的结论。     

非纯CO_2对MMP和驱油效率影响的实验研究

提出以油井产出气(烃类与CO2混合气体)为对象,采用细管实验确定混相驱最小混相压力(MMP)及非混相驱过程中的驱油效率.研究了气体组成跨度较大情况下气体组成对MMP和驱油效率的影响,通过大量地实验观察和分析,将驱替过程分为3个阶段,并对相应过程的驱油机理、组成等对采收率的影响进行了分析,得出驱油效率随CO2摩尔分数、压力变化的趋势及数量关系.结果表明:CO2摩尔分数降低则混相压力提高。在非混相状态,CO2摩尔分数每提高10%,驱油效率提高3.0%～5.4%,平均为4.4%;注气压力对驱油效率有较大影响,注气压力每提高1MPa,驱油效率提高1.2%～3.0%,平均为1.8%.     

钢筋混凝土柱-H型钢斜梁结构有限元分析

钢筋混凝土柱-H型钢斜梁结构由混凝土和钢两种性能差异较大的材料构成,其受力性能相对复杂.针对大部分设计人员采用PKPM进行该结构设计的现状,笔者将ANSYS考虑大变形、非线性的计算结果引入.分析表明,因PKPM未考虑非线性等因素,故导致相同条件下水平推力和水平位移的计算结果存在较大偏差.     

倾斜疲劳裂纹在混合型应力下张开及滑移特性

对于存在裂纹的机械零件或者构件,它很有可能会受到来自不同方向的作用力, 因此有必要研究裂纹在混合型应力条件下的传播特性. 该文使用具有不同倾斜角度的裂纹--这些裂纹是在应力比R=0的Ⅰ型循环应力下制作的,通过测量裂纹的开口方向和滑移方向的位移量,计算了裂纹端部Ⅰ型应力强度因子(KⅠ)mes和Ⅱ型应力强度因子(KⅡ)mes.裂纹的倾斜角度是指载荷方向与裂纹间的夹角.结果表明,对于存在压缩残余应力的疲劳裂纹,当倾斜角度较大,即β=60°时,应力强度因子的实验值(KⅠ)mes小于理论计算值(KⅠ),但此时实验值(KⅡ)mes与理论值(KⅡ)基本一致.另一方面,对于倾斜角度较小β=45°的疲劳裂纹,其(KⅠ)mes减少的同时,由于裂纹上下表面相互接触,从而导致(KⅡ)mes同时下降.     

基于SITRANS料位计的监控系统设计

针对吕梁山木瓜煤矿原有料位计老化、测量不准确等问题,设计基于SITRANS LU 10超声波料位计的自动监控系统。系统采用S7-300系列PLC及组态软件作为控制核心,通过WinCC组态管理软件可直观地显示料位数据实时变化,实现煤仓料位的自动检测、超限报警、卸料小车运行与卸料控制等功能。     

Experimental and Numerical Analysis of the Viscous Fingering Instability of Shear‐Thinning Fluids

Miscible flow displacements in a rectilinear Hele‐Shaw cell of Newtonian as well as rheologically well‐characterized shear‐thinning fluids are examined through experimental measurements and numerical modelling. Water is used as a displacing fluid while the displaced fluid consists of either a reference Newtonian glycerol solution or shear‐thinning solutions of Alcoflood? polymers of different molecular weights. The experimental measurements revealed that the shear‐thinning behaviour of the non‐Newtonian solutions resulted in more complex instability patterns and new finger structures not previously observed in the case of Newtonian displacements are identified and characterized. An analysis of the effects of the rheological behaviour of the shear‐thinning fluids on instability characteristics such as the finger width and finger tip velocity is presented. Numerical simulations using a pseudo‐spectral method are conducted and allowed to compare the predictions of the mathematical model based on an effective Darcy's law with the experimental measurements.     

A novel deep learning prediction model for concrete dam displacements using interpretable mixed attention mechanism

Dam displacements can effectively reflect its operational status, and thus establishing a reliable displacement prediction model is important for dam health monitoring. The majority of the existing data-driven models, however, focus on static regression relationships, which cannot capture the long-term temporal dependencies and adaptively select the most relevant influencing factors to perform predictions. Moreover, the emerging modeling tools such as machine learning (ML) and deep learning (DL) are mostly black-box models, which makes their physical interpretation challenging and greatly limits their practical engineering applications. To address these issues, this paper proposes an interpretable mixed attention mechanism long short-term memory (MAM-LSTM) model based on an encoder-decoder architecture, which is formulated in two stages. In the encoder stage, a factor attention mechanism is developed to adaptively select the highly influential factors at each time step by referring to the previous hidden state. In the decoder stage, a temporal attention mechanism is introduced to properly extract the key time segments by identifying the relevant hidden states across all the time steps. For interpretation purpose, our emphasis is placed on the quantification and visualization of factor and temporal attention weights. Finally, the effectiveness of the proposed model is verified using monitoring data collected from a real-world dam, where its accuracy is compared to a classical statistical model, conventional ML models, and homogeneous DL models. The comparison demonstrates that the MAM-LSTM model outperforms the other models in most cases. Furthermore, the interpretation of global attention weights confirms the physical rationality of our attention-based model. This work addresses the research gap in interpretable artificial intelligence for dam displacement prediction and delivers a model with both high-accuracy and interpretability.     

智能电能表质量数据采集与质量监控技术研究

针对智能电能表非常容易发生开关跳闸、断电无法工作等故障问题,研究出了一种完善的解决方法;通过调研智能电能表生产企业的信息化系统和生产过程数据,发现生产企业的信息化系统在不同企业间都存在各个信息系统之间分割严重的问题,导致企业内部的数据分布在各个数据仓库内,数据分散,需要对每个生产企业采集装置的采集功能进行定制化对接,基于边缘计算技术的业务系统能够更加切合采集终端,并进行数据处理;本研究将SVG技术和Ajax技术结合使用,构成智能电能表质量监控系统方案框架;经过实验结果表明,通过SVG技术和Ajax技术对智能电力表各项数据信息处理,得到了很好的效果.     

PIV技术在冰盖下复式断面渠道流速测量中的运用

在测定冰盖下复式断面流场、流速的模型试验中,水体中的运动粒子是重点研究对象。粒子图像测速(Particle Image Velocimetry,PIV)技术已在水力学研究领域得到普遍应用,但该技术在冰盖下复式断面渠道模型试验的应用为国内首次。基于试验特点,设计砖砌混凝土的循环水箱,采用变频器配合水泵、流量计实现对流量的定量控制,对不同流量下不同断面的流场、流速进行测定,采用PIV技术对水体中运动的粒子的位移场进行具体分析。试验结果表明,PIV分析结果能够直观反映流场中的状态,且可以避免测量盲区,其所测的流速与多普勒超声测速仪测得值吻合较好,并给出了横向流速分布图,弥补了传统方法无法获得冰盖下的流场分布的难题。