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碳酸盐胶结砂岩中的指形反应前锋

世界地质 1993年第2期12卷 73-86页

作者： p.ortoleva 汪筱林

水—岩相互作用前锋的形态可以自组织成非平面形,如指形和扇形。这是由于外界流体驱动下的聚流作用而形成的。对于碳酸盐胶结的砂岩,这种现象用一组反应—运移方程来模拟,设计一套计算机程序解此方程组,并用以预测这种现象的时间演化。... 详细信息

水—岩相互作用前锋的形态可以自组织成非平面形,如指形和扇形。这是由于外界流体驱动下的聚流作用而形成的。对于碳酸盐胶结的砂岩,这种现象用一组反应—运移方程来模拟,设计一套计算机程序解此方程组,并用以预测这种现象的时间演化。该程序含有许多特别的数值算法,以使计算迅速收敛。文中阐明了前锋成指形、扇形、指尖分裂形和帽形的效应。文中研究了流速、流渠宽度、以及围岩中胶结物(方解石或白云石)的变化的影响。本文讨论了这种模拟对于加深认识成岩作用和石油工程的潜在重要性。

关键词：碳酸盐胶结砂岩指形反应前锋

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页岩中甲烷的振荡式释放

世界地质 1993年第2期12卷 106-109页

作者： A.Ghaith p.ortoleva 匡立春

在富含干酪根页岩中,甲烷释放率的瞬时振荡起因于其迁移的非线性。这种非线性是由于渗透率和由于甲烷生成、流体的压实与热膨胀的影响而导致的由超压产生的断裂中的流体压力的偶合作用造成的。破裂的愈合在从滞后中心至振荡的过程中起... 详细信息

在富含干酪根页岩中,甲烷释放率的瞬时振荡起因于其迁移的非线性。这种非线性是由于渗透率和由于甲烷生成、流体的压实与热膨胀的影响而导致的由超压产生的断裂中的流体压力的偶合作用造成的。破裂的愈合在从滞后中心至振荡的过程中起着重要作用。我们模拟的振荡释放是通过反应—迁移方程式来说明干酪根分解释放出甲烷,并说明流体压力引起的破裂作用对渗透率的影响以及通过流动和扩散而导致的液态甲烷迁移。

关键词：页岩甲烷振荡式释放

受应力岩石中由物理—化学反馈引起的分异构造

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世界地质 1993年第2期12卷 110-119页

作者： T.Dewers p.ortoleva 胡志勇

本文回顾了一些我们描述变形岩石与其所含流体之间相互反应的数学模型,特别是,我们主张用自组织作用概念作为一种理解从成岩作用到变质条件范围岩石中所观察到的图案状构造演化的一种方式。由于矿物自由能依赖于围岩的结构,这些结构由... 详细信息

本文回顾了一些我们描述变形岩石与其所含流体之间相互反应的数学模型,特别是,我们主张用自组织作用概念作为一种理解从成岩作用到变质条件范围岩石中所观察到的图案状构造演化的一种方式。由于矿物自由能依赖于围岩的结构,这些结构由导源于物理力与化学反应迁移的耦合作用所形成的反馈。在不同极限或初始条件中,同一公式抓住了许多行为的本质,把相关的变形构造观察成缝合线、粒间压溶、破壁理、变质层状构造与由结晶生长力所产生的矿化分异作用。这些方程可预测变质分异作用任何趋势的可能性,并显示了化学因素是如何对岩石的变形效应施加了强烈的影响。

关键词：岩石物理化学应力分异构造

奥斯特瓦德—李泽冈过饱和—成核—消耗循环的分枝

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世界地质 1993年第2期12卷 63-72页

作者： R.Sultan p.ortoleva F.Depasquale p.Tartaglia 刘洪波张立平

用一个新的奥斯特瓦德过饱和一成核一消耗循环新公式来模拟岩石中的沉淀条带。在特殊的极限情形,系统会维持一种扩散固定沉淀脉动。对于黄铁矿/针铁矿系统的简单模拟类比,存在性的极限由分析确定。利用数字模拟,矿物沉淀的非定态脉动可... 详细信息

用一个新的奥斯特瓦德过饱和一成核一消耗循环新公式来模拟岩石中的沉淀条带。在特殊的极限情形,系统会维持一种扩散固定沉淀脉动。对于黄铁矿/针铁矿系统的简单模拟类比,存在性的极限由分析确定。利用数字模拟,矿物沉淀的非定态脉动可以获得,并且表明,随着系统参数的适当变化,可以产生许多图案。这明显地表明,分析获得的定态脉动是不稳定的。不定态脉动、波动图形及不连续条带存在区都确定了。

关键词：岩石过饱和成核消耗循环

Enhanced entropy generation and heat transfer characteristics of magnetic nano-encapsulated phase change materials in latent heat thermal energy storage systems

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Applied Mathematics and Mechanics(English Edition) 2024年第6期45卷 1051-1070页

作者： p.S.REDDY p.SREEDEVI Department of Mathematics Rajeev Gandhi Memorial College of Engineering and TechnologyNandyal 518501India

The objective of the current study is to investigate the importance of entropy generation and thermal radiation on the patterns of velocity,isentropic lines,and temperature contours within a thermal energy storage device filled with magnetic nanoencapsulated phase change materials(NEpCMs).The versatile finite element method(FEM)is implemented to numerically solve the governing *** effects of various parameters,including the viscosity parameter,ranging from 1 to 3,the thermal conductivity parameter,ranging from 1 to 3,the Rayleigh parameter,ranging from 102 to 3×10^(2),the radiation number,ranging from 0.1 to 0.5,the fusion temperature,ranging from 1.0 to 1.2,the volume fraction of NEpCMs,ranging from 2%to 6%,the Stefan number,ranging from 1 to 5,the magnetic number,ranging from 0.1 to 0.5,and the irreversibility parameter,ranging from 0.1 to 0.5,are examined in detail on the temperature contours,isentropic lines,heat capacity ratio,and velocity ***,the heat transfer rates at both the cold and hot walls are analyzed,and the findings are presented *** results indicate that the time taken by the NEpCMs to transition from solid to liquid is prolonged inside the chamber region as the fusion temperatureθf ***,the contours of the heat capacity ratio Cr decrease with the increase in the Stefan number Ste.

关键词： volume fraction of nano-encapsulated phase change material(NEpCM) radiation Stefan number heat capacity ratio entropy generation

A Hybrid Optimization Approach of Single point Incremental Sheet Forming of AISI 316L Stainless Steel Using Grey Relation Analysis Coupled with principal Component Analysiss

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Journal of Wuhan University of Technology(Materials Science) 2024年第1期39卷 160-166页

作者： A Visagan p Ganesh Department of production Technology Madras Institute of TechnologyChennai-600044India

We investigated the parametric optimization on incremental sheet forming of stainless steel using Grey Relational Analysis(GRA) coupled with principal Component Analysis(pCA). AISI 316L stainless steel sheets were used to develop double wall angle pyramid with aid of tungsten carbide tool. GRA coupled with pCA was used to plan the experiment conditions. Control factors such as Tool Diameter(TD), Step Depth(SD), Bottom Wall Angle(BWA), Feed Rate(FR) and Spindle Speed(SS) on Top Wall Angle(TWA) and Top Wall Angle Surface Roughness(TWASR) have been studied. Wall angle increases with increasing tool diameter due to large contact area between tool and workpiece. As the step depth, feed rate and spindle speed increase,TWASR decreases with increasing tool diameter. As the step depth increasing, the hydrostatic stress is raised causing severe cracks in the deformed surface. Hence it was concluded that the proposed hybrid method was suitable for optimizing the factors and response.

关键词： single point incremental forming AISI 316L taguchi grey relation analysis principal component analysis surface roughness scanning electron microscopy

Cryogenic and conventional milling of AZ91 magnesium alloy

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Journal of Magnesium and Alloys 2024年第6期12卷 2503-2519页

作者： Vikas Marakini Srinivasa pai p Gururaj Bolar Bhaskara p Achar Department of Mechanical Engineering Nitte(Deemed to be University)NMAM Institute of Technology(NMAMIT)Nitte 574110India Department of Mechanical and Industrial Engineering Manipal Institute of TechnologyManipal Academy of Higher EducationManipal 576104India

Use of magnesium is the need of the hour due to its low density as well as its high strength-to-weight and stiffness-to-weight ratio *** study focuses on the effectiveness of liquid nitrogen(LN_(2))assisted cryogenic machining on the surface integrity(SI)characteristics of AZ91 magnesium *** milling using uncoated carbide inserts have been performed under liquid nitrogen(LN_(2))assisted cryogenic condition and compared with conventional(dry)*** are performed using machining parameters in terms of cutting speeds of 325,475,625 m/min,feed rates of 0.05,0.1,0.15 mm/teeth and depth of cuts of 0.5,1,1.5 mm *** significant surface integrity characteristics such as surface roughness,microhardness,microstructure,and residual stresses have been *** of SI characteristics with respect to milling parameters have been identified using statistical technique such as ANOVA and signal-to-noise(S/N)ratio ***,the multi criteria decision making(MCDM)techniques such as additive ratio assessment method(ARAS)and complex proportional assessment(COpRAS)have been utilized to identify the optimal conditions for milling AZ91 magnesium alloy under both dry and cryogenic *** of LN_(2)during machining,resulted in reduction in machining temperature by upto 29%with a temperature drop from 251.2℃under dry condition to 178.5℃in cryogenic *** showed the advantage of performing cryogenic milling in improving the surface integrity to a significant *** machining considerably minimized the roughness by upto 28%and maximised the microhardness by upto 23%,when compared to dry *** speed has caused significant impact on surface roughness(95.33%-dry,92.92%-cryogenic)and surface microhardness(80.33%-dry,82.15%-cryogenic).Due to the reduction in machining temperature,cryogenic condition resulted in compressive residual stresses(maximumσ║=-113 Mpa)on the alloy *** indicate no

关键词： Magnesium alloy Cryogenic machining Roughness Microhardness Microstructure Residual stress Multi criteria decision making

On the functions of astrocyte-mediated neuronal slow inward currents

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Neural Regeneration Research 2024年第12期19卷 2602-2612页

作者： Balázs pál Department of physiology Faculty of MedicineUniversity of DebrecenDebrecenHungary

Slow inward currents are known as neuronal excitatory currents mediated by glutamate release and activation of neuronal extra synaptic N-met hyl-D-aspartate receptors with the contribution of *** events are significantly slower than the excitatory postsynaptic *** of slow inward currents are determined by seve ral factors including the mechanisms of astrocytic activation and glutamate release,as well as the diffusion pathways from the release site towards the extra synaptic recepto *** are stimulated by neuronal network activity,which in turn excite neurons,forming an astrocyte-neuron feedback *** as a consequence of brain edema,astrocytic swelling can also induce slow inward currents under pathological *** is a growing body of evidence on the roles of slow inward currents on a single neuron or local network *** events often occur in synchro ny on neurons located in the same astrocytic *** synchronization of neuronal excitability,slow inward currents also set synaptic strength via eliciting timing-dependent synaptic *** addition,slow inward currents are also subject to non-synaptic plasticity triggered by long-la sting stimulation of the excitatory *** note,there might be important regionspecific differences in the roles and actions triggering slow inward *** greater networks,the pathophysiological roles of slow inward currents can be better understood than physiological *** inward currents are identified in the pathophysiological background of autism,as slow inward currents drive early hypersynchrony of the neural *** inward currents are significant contributors to paroxysmal depolarizational shifts/interictal *** events are related to epilepsy,but also found in Alzheimer's disease,parkinson's disease,and stroke,leading to the decline of cognitive *** with features overlapping with slow inward currents(excitatory,N-methyl-Dasp

关键词： astrocyte cortical spreading depolarization gliotransmission glutamate neural synchronization NMDA receptor paroxysmal depolarizational shift slow inward current

An Efficient Approach to Escalate the Speed of Training Convolution Neural Networks

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China Communications 2024年第2期21卷 258-269页

作者： p pabitha Anusha Jayasimhan Department of Computer Technology Anna UniversityMadras Institute of Technology CampusChennai 600044India

Deep neural networks excel at image identification and computer vision applications such as visual product search, facial recognition, medical image analysis, object detection, semantic segmentation,instance segmentation, and many others. In image and video recognition applications, convolutional neural networks(CNNs) are widely employed. These networks provide better performance but at a higher cost of computation. With the advent of big data, the growing scale of datasets has made processing and model training a time-consuming operation, resulting in longer training times. Moreover, these large scale datasets contain redundant data points that have minimum impact on the final outcome of the model. To address these issues, an accelerated CNN system is proposed for speeding up training by eliminating the noncritical data points during training alongwith a model compression method. Furthermore, the identification of the critical input data is performed by aggregating the data points at two levels of granularity which are used for evaluating the impact on the model *** experiments are conducted using the proposed method on CIFAR-10 dataset on ResNet models giving a 40% reduction in number of FLOps with a degradation of just 0.11% accuracy.

关键词： CNN deep learning image classification model compression