Numerical Investigations on the Transient Behavior of Sand Waves in Beibu Gulf Under Normal and Extreme Sea Conditions

In this study, a morphodynamic numerical model is established with the Regional Ocean Modeling System(ROMS)to investigate the transient behavior of sand waves under realistic sea conditions. The simulation of sand wave evolution comprises two steps: 1) a regional-scale model is configured first to simulate the ocean hydrodynamics, i.e., tides and tidal currents, and 2) the transient behavior of sand waves is simulated in a small computational domain under the time-variant currents extracted from the large model. The evolution of sand waves on the continental shelf in the Beibu Gulf is specifically investigated. The numerical results of the two-year evolution of sand waves under normal sea conditions compare well with the field survey data. The transient behavior of sand waves in individual months shows that the sand waves are more stable in April and October than that in other months, which can be selected as the windows for seabed operations. The effects of sediment properties, including settling velocity, critical shear stress and surface erosion rate, on sand wave evolution are also analyzed. Then, the typhoon-induced currents are further superimposed on the tidal currents as the extreme weather conditions. Sand waves with the average wavelength generally have more active behavior than smaller or larger sand waves. The characteristics of the evolution of sand waves in an individual typhoon process are quite different for different hydrodynamic combinations. For the storm conditions, i.e., the real combination and maximum combination cases, the sand waves experience a significant migration together with a damping in height due to the dominant suspended sediment transport. For the mild conditions, i.e., the pure tidal current and minimum combination cases, the sand waves migrate less, but the heights continue growing due to the dominant bedload transport.

Monitoring vegetation drought in the nine major river basins of China based on a new developed Vegetation Drought Condition Index

The effect of global climate change on vegetation growth is variable.Timely and effective monitoring of vegetation drought is crucial for understanding its dynamics and mitigation,and even regional protection of ecological environments.In this study,we constructed a new drought index(i.e.,Vegetation Drought Condition Index(VDCI))based on precipitation,potential evapotranspiration,soil moisture and Normalized Difference Vegetation Index(NDVI)data,to monitor vegetation drought in the nine major river basins(including the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin,Yangtze River Basin,Southeast River Basin,Pearl River Basin,Southwest River Basin and Continental River Basin)in China at 1-month–12-month(T1–T12)time scales.We used the Pearson's correlation coefficients to assess the relationships between the drought indices(the developed VDCI and traditional drought indices including the Standardized Precipitation Evapotranspiration Index(SPEI),Standardized Soil Moisture Index(SSMI)and Self-calibrating Palmer Drought Severity Index(scPDSI))and the NDVI at T1–T12 time scales,and to estimate and compare the lag times of vegetation response to drought among different drought indices.The results showed that precipitation and potential evapotranspiration have positive and major influences on vegetation in the nine major river basins at T1–T6 time scales.Soil moisture shows a lower degree of negative influence on vegetation in different river basins at multiple time scales.Potential evapotranspiration shows a higher degree of positive influence on vegetation,and it acts as the primary influencing factor with higher area proportion at multiple time scales in different river basins.The VDCI has a stronger relationship with the NDVI in the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin and Yangtze River Basin at T1–T4 time scales.In general,the VDCI is more sensitive(with shorter lag time of vegetation response to drought)than the traditional drought indices(SPEI,scPDSI and SSMI)in monitoring vegetation drought,and thus it could be applied to monitor short-term vegetation drought.The VDCI developed in the study can reveal the law of unclear mechanisms between vegetation and climate,and can be applied in other fields of vegetation drought monitoring with complex mechanisms.

Some Necessary and Sufficient Condition of Multivariate Random Variable Satisfy Normal Distribution

In this paper,we extended some results of article[1],obtain some sufficient and necessary condition which multivariate random variable satisfy normal distribution.

3D prestack reverse time migration of ground penetrating radar data based on the normalized correlation imaging condition

The reverse time migration(RTM)of ground penetrating radar(GPR)is usually implemented in its two-dimensional(2D)form,due to huge computational cost.However,2D RTM algorithm is difficult to focus the scattering signal and produce a high precision subsurface image when the object is buried in a complicated subsurface environment.To better handle the multi-off set GPR data,we propose a three-dimensional(3D)prestack RTM algorithm.The high-order fi nite diff erence time domian(FDTD)method,with the accuracy of eighth-order in space and second-order in time,is applied to simulate the forward and backward extrapolation electromagnetic fi elds.In addition,we use the normalized correlation imaging condition to obtain pre-stack RTM result and the Laplace fi lter to suppress the low frequency noise generated during the correlation process.The numerical test of 3D simulated GPR data demonstrated that 3D RTM image shows excellent coincidence with the true model.Compared with 2D RTM image,the 3D RTM image can more clearly and accurately refl ect the 3D spatial distribution of the target,and the resolution of the imaging results is far better.Furthermore,the application of observed GPR data further validates the eff ectiveness of the proposed 3D GPR RTM algorithm,and its fi nal image can more reliably guide the subsequent interpretation.

Effect of bolt inclination angle on shear behavior ofbolted joints under CNL and CNS conditions

Rock bolts are widely used in rock engineering projects to improve the shear capacity of the jointed rock mass.The bolt inclination angle with respect to the shear plane has a remarkable influence on the bolting performance.In this study,a new artificial molding method based on 3D scanning and printing technology was first proposed to prepare bolted joints with an inclined bolt.Then,the effects of the bolt inclination angle and boundary conditions on the shear behavior and failure characteristic of bolted joints were addressed by conducting direct shear tests under both CNL and CNS conditions.Results indicated that rock bolt could significantly improve the shear behavior of rock joints,especially in the post-yield deformation region.With the increase of bolt inclination angle,both the maximum shear stress and the maximum friction coefficient increased first and then decreased,while the maximum normal displacement decreased monotonously.Compared with CNL conditions,the maximum shear stress was larger,whereas the maximum normal displacement and friction coefficient were smaller under the CNS conditions.Furthermore,more asperity damage was observed under the CNS conditions due to the increased normal stress on the shear plane.

Withdraw: Improvement on Adhesion Properties of Insert Injection Molding Composites: Effect of Inserted Parts, Adhesive Lengths and Injection Conditions

Short Retraction Notice The paper does not meet the standards of "Open Journal of Composite Materials". This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused. Editor guiding this retraction: Prof. Chengye Fan (EiC of OJCM) The full retraction notice in PDF is preceding the original paper, which is marked "Withdraw".

基于历史天气的区域电网负荷预测

随着社会经济的迅速发展,人们对电能的需要日益增加,但是在电网运行中,常常会出现电力产能过剩或者不足的情况,为保证电力系统安全稳定、经济运行,就必须掌握各种区域电网负荷的变化规律和发展趋势。论文对重庆市区供电分公司供电区域电网中长期负荷进行预测,提出一种预测区域电网中长期负荷的方法,即一种基于前12个月历史天气条件和区域电网负荷关联关系的多元非线性拟合的特征参数因子曲线的中长期负荷预测方法,建立基于不同算法的多种预测模型,通过归一化处理,得到的区域电网中长期负荷预测的精度高,与实际区域电网负荷之间的误差小,对于区域电网中长期负荷预测分析具有重要参考利用价值。

“平急两用”视角下应急避难场所布局优化设计

平急两用的应急避难场所是应对突发事件发生的重要场所,在灾害发生时转化的速度与成效是发挥避难场所作用的重要因素之一。为提高我国避难场所在灾害发生时的转化效率,以体育场馆和公园广场为例进行绘图分析,针对避难场所平疫转化和平灾转化过程中的功能分区及不同流线进行研究,并确保方案的可实施性。研究表明:“平急两用”避难场所通过布局优化设计,在一定的功能和流线转化后即可快速转化为应急避难场所。研究结果为“平急两用”公共基础设施的场所建设提供理论与方法指导,优化应急避难场所布局,提高城市韧性,对推动建设可持续高质量发展的城市公共基础设施系统起到重要指引作用。

基于URP-ANCNN的变转速齿轮箱智能故障诊断方法

由于齿轮箱振动信号在变转速工况下出现的调频、调幅等现象,使得信号征兆与故障模式之间的映射关系变得复杂,导致齿轮箱故障难以精确诊断。鉴于深度神经网络在自动提取数据特征和分类上的优势,提出一种基于无阈值递归图编码(Un-threshold Recurrence Plot,URP)和自适应归一化卷积神经网络(Adaptive Normalized Convolutional Neural Network,ANCNN)的变转速工况齿轮箱故障诊断方法。该方法先使用快速傅里叶变换(Fast Fourier Transform,FFT)将时域信号转化为频域信号,再利用URP编码将得到的频域信号转化为二维递归图,并提取图像特征输入到ANCNN模型。在ANCNN模型中,采用批量归一化算法消除因转速变化引起的特征分布差异,同时处理转速波动下产生的频移和调制特性,并使用遗传算法自动调整该网络模型的超参数,以提高该网络的整体性能。采用转速波动的齿轮箱试验数据对该方法进行验证,实验结果表明,该方法能够克服转速波动的影响,成功实现对不同齿轮故障的准确识别。

基于迭代注意力归一化流的低光图像增强

针对网络层级间特征融合不足并缺乏高频特征的精准定位和获取,以及低光图像和多个正常曝光图像之间的不确定映射问题,提出一种迭代注意力归一化流(Iterative attention normalization flow,IANFlow)网络。迭代注意力模块使用空间和通道注意力对输入特征图的高频特征区域定位后进行特征获取,通过递进式层级定位和融合促使深层特征图包含更多的高频特征;可逆归一化流模块学习低光照图像和正常曝光图像之间复杂的条件分布以及将负对数似然(negative log likelihood,NLL)最小化建立低光图像和参考图像之间一对多的映射。在三个数据集上分别对比LLFlow网络,IANFlow网络的峰值信噪比(peak signal-to-noise ratio,PSNR)分别提高了1.1 dB、1.27 dB、2.14 dB。

颗粒级配和表面纹理对饱和砂-钢界面剪切强度的影响

钢桩和钢制吸力基础广泛应用于海洋工程,土体与基础结构界面力学特性决定着其承载能力。通过饱和砂-钢界面排水剪切试验,揭示了颗粒级配、表面纹理和法向边界条件对界面剪切特性的影响规律。研究表明:由于颗粒剪切方式和孔隙水压力消散方式的不同,常法向应力(CNL)下剪应力-位移曲线出现明显的应变软化现象。变法向应力(VNL)下,界面剪切强度随法向应力的增大不断提高。对于光滑和凸起构造,界面摩擦角随不均匀系数C_(u)的增加基本呈线性增长。对于凹槽构造,界面摩擦角随C_(u)的增加而减小。饱和砂-粗糙度钢板界面剪切效能的发挥受水的影响显著,砂与钢板之间水膜的存在减弱了砂颗粒和钢界面的摩擦,使得界面摩擦性能不能完全发挥。

带有偏正态误差的众数回归模型最大似然估计的EM算法

经典的多元线性回归模型要求残差满足高斯-马尔柯夫假设(G-M),在实际生活中由于数据的随机性往往很难满足这个条件.利用Sahu等在2003年提出的偏正态分布来拓展经典的回归模型,给出了偏正态分布众数的近似表达式,建立了偏正态分布下均值和众数多元线性回归模型.在求解模型的参数估计时使用偏正态分布的分层表示构造EM算法.在M步统一给出两点步长梯度下降算法,同时也对均值模型给出显示迭代表达式.最后通过模拟分析以及实例来讨论两种回归模型的可行性.

通车条件下抗扰动混凝土拼接养护期微观损伤研究

扩建桥梁的拼宽连接需要在通车条件下进行,对于仍在养护期内的抗扰砼拼接带性能可能会产生一定影响。通过现场检测仅能发现拼接带的宏观损伤,行车振动引起的拼接带内部微观损伤难以观测。基于有限元仿真分析、CT扫描技术,对拼宽桥梁拼接带的受力分布情况及实际损伤状况进行了研究。首先,利用ANSYS有限元软件建立拼宽桥梁实桥仿真分析模型,明确不同工况下拼宽桥梁拼接带的受力特点。其次,基于仿真模拟结果选取拼接带关键位置,获取拼接带跨中、四分点截面的接缝中心线及交界面关键位置处的抗扰砼芯样,进行抗扰砼芯样的外观观测。最后,利用CT扫描技术获取芯样断层扫描观察图像,并基于获取的扫描数据对芯样内部结构进行了三维重构,分析拼接带抗扰砼在受扰振动后的集料分布情况、裂缝扩展情况。结果表明:各工况下拼接带抗扰砼横向受力主要以顶部受压、底部受拉为主,仅支点位置附近存在偏压趋势,且均能满足抗扰砼材料强度要求;对于拼接带中心线位置处的芯样,芯样内部无明显裂纹损伤,芯样内部骨料、纤维分布均匀,拼接带顶部钢纤维多水平分布、底部纤维多斜向分布;对于交界面位置处的芯样,在芯样顶部交界面存在一定的微裂隙,裂隙深度小于1 cm,该微裂隙对拼接带界面性能影响较小,近交界面位置处,钢纤维存在一定下沉趋势且纤维多呈斜向分布;在通车条件下拼接桥梁,车桥耦合振动将造成拼接带内钢纤维发生取向、甚至下沉的影响,减小拼接带抗扰砼抗拉性能。

“平疫结合”型中庭式酒店建筑公共空间设计方法研究——以西安为例

“平疫结合”型中庭式酒店建筑空间组织模式的更新是改善城市公共空间环境、满足城市公共卫生防疫体系需求的重要组成部分。当前,“平疫结合”理念的研究多集中在医疗建筑领域,对于酒店建筑平转疫的研究则相对较少。研究基于新冠肺炎疫情对于中庭式酒店设计的反思,选择中庭式酒店建筑为研究对象,通过实地考察与问卷调查分析酒店人流行为及隔离行为,探讨“平疫结合”型中庭式酒店公共空间的功能布局与空间流线优化,归纳梳理了中庭式酒店公共空间组织设计方法及酒店“疫时”分区与流线模式,并将其在唐隆酒店平面布局改造中进行了具体实施。

半拟可微拟凸规划的KKT型最优性条件

最优性条件在优化问题中起着重要的作用,它为优化算法的研究提供了重要的理论依据。众所周知,凸规划方面最优性条件已比较完善。然而,由于拟凸函数性质的特殊性,对于拟凸规划问题解的Karush-Kuhn-Tucker(KKT)类型最优性条件的研究相对较少。本文利用半拟可微刻画了拟凸规划的最优性条件,同时研究了可行集法锥与带半拟可微性质的约束函数之间的关系,并证明了上述两个结果与Greenberg-Pierskalla次微分的关系。

基于条件归一化网络的艺术字体多风格融合技术研究

针对艺术字体风格迁移中风格单一性以及多风格字体融合时出现的风格单一、风格溢出和残余黑点的问题,提出了一种基于条件归一化网络的多风格字体图像融合方法。该方法采用了一个字体多风格融合模型,能根据不同的风格参数调整预训练的VGG19Net网络的输出。通过将内容图与多个风格字体图像分别提取特征,并使用一个新的风格损失函数来度量内容图与风格字体图像之间的差异,将多个风格特征混合,生成新的艺术风格字体图像。该方法的关键在于卷积层和条件归一化层,能够实现多风格的迁移和融合。实验结果表明:与其他两种方法相比,内容相似度平均提高了1.2%,风格相似度平均提高了2.7%。

基于条件扩散模型的结直肠图像染色归一化

由于现有染色归一化方法无法准确提取结直肠病理图像的复杂结构特征,导致丢失部分结直肠病理图像的结构信息,无法生成高质量的染色归一化结直肠病理图像。为解决该问题,提出一种基于条件扩散模型的结直肠病理图像染色归一化方法,该方法包括条件扩散模型和图像特征重建。在条件扩散模型中,首先,使用马尔科夫链前向过程对结直肠病理原图像进行加噪声。然后,将噪声图像和条件图像输入到增强去噪网络中进行去噪,在这过程中利用增强激活模块,学习结直肠病理图像的深层特征,捕获更多的图像上下文信息。在编码器和解码器之间引入跳跃连接空间注意力模块,准确提取结直肠病理图像的位置空间信息。在图像特征重建中,设计金字塔特征提取模块,提取多尺度条件图像与生成图像的特征,并构建重建损失函数,优化整个网络的性能。实验结果表明,与现有方法相比,所提染色归一化方法在公共数据集GlaS和CRAG上的能生成质量更高的染色归一化结直肠病理图像。

非负组稀疏约束优化问题的最优性条件

基于Bouligand意义下的切锥与法锥和Clarke意义下的切锥与法锥,该文研究了非负组稀疏约束优化问题的最优性理论.该文定义了非负组稀疏约束集的Bouligand切锥与法锥和Clarke切锥与法锥,并给出了它们的等价刻画形式.在目标函数连续可微的条件下,借助于非负组稀疏约束集的切锥和法锥,给出了该优化问题的四类稳定点的定义,并讨论了它们之间的关系.最后,建立了非负组稀疏约束优化问题的一阶和二阶最优性条件.

基于置信水平的钢轨焊接接头设备状态评定方法

[目的]为解决我国无缝线路钢轨设备状态评定体系不完善的问题,需要建立基于置信水平的钢轨焊接接头设备状态评定方法。[方法]阐述了目前我国规定的高速铁路钢轨平直度允许偏差、焊接接头平直度允许偏差。以我国某条已开通运营13年的高速铁路为案例,对该线钢轨焊接接头平直度数据进行分析,认为钢轨接头平直度检测数据总体服从正态分布。根据正态分布及置信区间原理,对均值和标准差评定法、置信水平评定法进行对比,提出了基于置信水平的钢轨焊接接头设备状态评定方法,得到高速铁路钢轨设备状态的评定标准。[结果及结论]该方法能够客观、直观地反映出钢轨焊接接头的设备状态,可以准确地掌握钢轨设备状态。该方法可为分析钢轨设备变化规律,以及制定大中修的标准、计划及方案等提供很好的理论依据。

汽车空调系统生产过程检漏能力提升

汽车空调系统运行中,管路的微小泄漏会导致制冷剂缺失,进而影响空调系统的制冷效果。迫切需要提升生产过程的检漏能力,避免此类缺陷车给用户造成损害。分析了实际汽车生产过程中的制冷剂加注过程和空调系统初始化过程的制冷剂压力检测,在不追加生产设备及人力的条件下,在制冷剂加注过程运用正态分布3σ准则对加注真空检漏参数进行标准收严控制。在空调系统初始化过程中,当空调系统管路存在泄漏时,系统的压力值会存在异常,通过对压力最大、最小两参数运用正态分布3σ准则设定出监控值,将制冷剂压力异常的车辆检出。测试结果表明,通过加注真空检漏和管路压力值监控,可识别出空调系统存在微小泄漏的车辆,提升了整车生产过程的空调检漏能力。