Intelligent analysis method of dam material gradation for asphalt-core rock-fill dam based on enhanced Cascade Mask R-CNN and GCNet

Reasonable dam materials’ gradation design for asphalt-core rock-fill dams is one of the main ways to control permeability. It is a challenge to test whether it can meet the requirements of dam construction. The computer vision method provides a new idea for asphalt-core rock-fill dam material gradation testing. However, due to the characteristics of densely overlapping and multi-scale sizes of dam material particles, the traditional image segmentation methods and algorithms cannot achieve accurate segmentation of dam materials’ images, and it is hard to apply the segmentation result to quantify the gradation curve. In this research, the enhanced Cascade Mask R-CNN with ResNet and PAFPN (Path Aggregation Feature Pyramid Networks) is proposed. Multi-scale features extracted by ResNet and feature ensemble can be realized using PAFPN. Data augmentation (DA) and online hard example mining (OHEM) are also applied in segmentation model training. Moreover, the GCNet is proposed to calibrate the gradation curve. The nonlinear relationship between the real gradation and the one based on the segmentation results can be revealed and the model of dam materials’ gradation analysis can be established. In the research, the enhanced Cascade Mask R-CNN can achieve 84.2 mAP, which is higher than that of Cascade Mask R-CNN with 74.9 mAP. The effectiveness of the proposed module and training strategies is proved using ablation experiments. The average error of each level for the gradation calibration using GCNet is 0.55%, 1.87%, 2.22%, 1.18%, and 2.42% respectively. The accuracy can meet the requirements of hydraulic engineering construction, which verifies the effectiveness of the GCNet network for gradation calibration, and the research provides a new method and technology for intelligent gradation testing of the asphalt-core rock-fill dam.     

城市污水污泥干化-焚烧系统热力分析

目前,污水处理厂污泥安全高效处理和处置问题在我国尚未彻底解决。干化-焚烧可实现 污泥的无害化和减量化,针对典型污泥独立干化-焚烧工艺建立计算模型,探讨了热值、一次风温度等参数对污泥燃烧温度和辅助燃料需要量等的影响。结果显示:随着污泥热值升高,污泥燃烧温度升高,临界含水率上升,热值为10、12、14 MJ/kg的临界含水率约为45%、51%和54%;通过提高一次风温度,可以大幅度提高污泥燃烧温度,但是对于热值为12~14 MJ/kg污泥,在一次风温超过200 ℃情况下,燃烧温度超过950 ℃,需采取降温措施;污泥自身提供的热量无法满足污泥干化-焚烧系统整体能耗,干化-焚烧系统的辅助燃料需要量高于仅考虑焚烧系统的需要量;干化-焚烧系统的辅助燃料需要量随着入炉含水率的减少增加。     

3D LIDAR based on FPCB mirror

This paper presents the first 3D LIDAR (light detection and ranging) constructed from two 1D FPCB (flexible printed circuit board) oscillation mirrors and one single-point LIDAR with a very low total cost of ∼$150 (assuming no additional angle sensor used). One FPCB mirror is for vertical scanning and the other is for horizontal scanning. The low cost is realized because of the low cost 1D FPCB mirror (a few dollars), as well as the widely available and relatively easy to make single-point LIDAR (<$100 cost for mass production). The 3D LIDAR can be used to obtain 3D map for navigation and obstacle avoidance of AGVs (automated guidance vehicles) subject to low speed and low acceleration. The FPCB mirror in this paper evolves from FPCB micromirrors previously developed but has a large aperture (20 × 20 mm). The achieved performance is: horizontal and vertical FOV (field of view) of 38° and 24°, respectively, 12.5 or 25 horizontal scanning lines, refreshing rate of 2, 4 or 8 fps (frames per second), 0.2∼20 m detection distance for low reflectivity object, and 1, 250∼5,000 points/frame when using the standard single-point LIDAR (TF03). If using a customized single-point LIDAR, the distance would be increased to 50∼80 m with 10 times more points/frame. The 3D LIDAR is suitable for AGV's navigation and obstacle avoidance. Modeling, prototyping and testing are presented.     

基于堆叠降噪自编码器的神经–符号模型及在晶圆表面缺陷识别

深度神经网络是具有复杂结构和多个非线性处理单元的模型, 通过模块化的方式分层从数据提取代表性特征, 已经在晶圆缺陷识别领域得到了较为广泛的应用. 但是, 深度神经网络在应用过程中本身存在“黑箱”和过度依赖数据的问题, 显著地影响深度神经网络在晶圆缺陷识别的工业可应用性. 提出一种基于堆叠降噪自编码器的神经–符号模型. 首先, 根据堆叠降噪自编码器的网络特点采用了一套符号规则系统, 规则形式和组成结构使其可与深度神经网络有效融合. 其次, 根据 网络和符号规则之间的关联性提出完整的知识抽取与插入算法, 实现了深度网络和规则之间的知识转换. 在实际工业晶圆表面图像数据集WM-811K上的试验结果表明, 基于堆叠降噪自编码器的神经–符号模型不仅取得了较好的缺陷探测与识别性能, 而且可有效提取规则并通过规则有效描述深度神经网络内部计算逻辑, 综合性能优于目前经典的深度神经网络.     

<Emphasis Type="Italic">In situ</Emphasis> synthesis of graphene oxide/gold nanorods theranostic hybrids for efficient tumor computed tomography imaging and photothermal therapy

Graphene oxide/gold nanorod (GO/GNR) nanohybrids were synthesized with a GO- and gold-seed-mediated in situ growth method at room temperature by mixing polystyrene sulfonate (PSS) functionalized GO, secondary growth solution, and gold seeds. Compared with ex situ preparation methods of GO/GNRs or graphene (G)/GNRs, the in situ synthesis of GO/GNRs addressed the issue of the aggregation of the GNRs before their attachment onto the GO. The method is straightforward and environment-friendly. The GO/GNRs showed a remarkable photothermal effect in vitro. The temperature of the GO/GNR nanohybrids increased from 25 to 49.9 °C at a concentration of 50 μg/mL after irradiation with an 808-nm laser (0.4 W/cm²) for 6 min. Additionally, the GO/GNRs exhibited good optical and morphological stability and photothermal properties after six cycles of laser irradiation. Upon injection of the GO/GNRs into xenograft tumors, excellent computed tomography (CT) imaging properties and photothermal effect were obtained. The preclinical CT agent iohexol was combined with the GO/GNRs and further enhanced CT imaging. Therefore, the GO/GNR nanohybrids have great potential for precise CT-image-guided tumor photothermal treatment.

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A rear-end collision risk assessment model based on drivers’ collision avoidance process under influences of cell phone use and gender—A driving simulator based study

Driver’s collision avoidance performance has a direct link to the collision risk and crash severity. Previous studies demonstrated that the distracted driving, such as using a cell phone while driving, disrupted the driver’s performance on road. This study aimed to investigate the manner and extent to which cell phone use and driver’s gender affected driving performance and collision risk in a rear-end collision avoidance process. Forty-two licensed drivers completed the driving simulation experiment in three phone use conditions: no phone use, hands-free, and hand-held, in which the drivers drove in a car-following situation with potential rear-end collision risks caused by the leading vehicle’s sudden deceleration. Based on the experiment data, a rear-end collision risk assessment model was developed to assess the influence of cell phone use and driver’s gender. The cell phone use and driver’s gender were found to be significant factors that affected the braking performances in the rear-end collision avoidance process, including the brake reaction time, the deceleration adjusting time and the maximum deceleration rate. The minimum headway distance between the leading vehicle and the simulator during the rear-end collision avoidance process was the final output variable, which could be used to measure the rear-end collision risk and judge whether a collision occurred. The results showed that although cell phone use drivers took some compensatory behaviors in the collision avoidance process to reduce the mental workload, the collision risk in cell phone use conditions was still higher than that without the phone use. More importantly, the results proved that the hands-free condition did not eliminate the safety problem associated with distracted driving because it impaired the driving performance in the same way as much as the use of hand-held phones. In addition, the gender effect indicated that although female drivers had longer reaction time than male drivers in critical situation, they were more quickly in braking with larger maximum deceleration rate, and they tended to keep a larger safety margin with the leading vehicle compared to male drivers. The findings shed some light on the further development of advanced collision avoidance technologies and the targeted intervention strategies about cell phone use while driving.     

剪切夹具设计及铝合金循环剪切变形行为

目的 研究金属薄板在剪切变形条件下的随动硬化行为。方法 设计一款金属薄板循环剪切变形试验夹具,对夹具的强度进行数值仿真校核。采用该夹具进行5052铝合金板的循环剪切试验,通过数字图像相关测量系统对剪切应变进行跟踪测量,对变形区剪切变形的均匀性进行分析,对5052铝合金的循环剪切应力应变曲线所表现出的包辛格效应进行讨论。结果 该夹具满足强度要求,剪切变形区的剪切应变与等效应变比值非常稳定,5052铝合金板的正向剪切强度与反向剪切强度不同,在3.97%和7.1%剪切应变时,包辛格效应系数分别为0.328和0.51。结论 所设计的夹具可以有效实现剪切变形,剪切应变分布均匀;试验所用的5052铝合金具有显著的包辛格效应。     

环保型石膏-水泥-火山灰胶凝体系的早期水化过程研究

应用X射线衍射(X-ray diffraction,XRD)及热流仪研究了组分、水化环境对环保型石膏-水泥-火山灰胶凝体系(Gypsum-cement-pozzolan binder system,GCP)早期水化过程的影响。结果表明,胶凝体系水化后产物主要由钙矾石、生石膏、羟钙石、方解石以及非晶态CSH凝胶组成。随着水化龄期的延长,钙矾石的含量增加,而生石膏的含量减少。高效减水剂的掺入延缓了GCP胶凝体系的初期水化(0~70h)。在原料中加入偏高岭土可以促进钙矾石的生成;而加入硅微粉则会抑制钙矾石的生成。羟钙石仅可在水化开始后的第一周内测得,之后会由于火山灰反应而被消耗。水中养护促进钙矾石的生成,阻碍试样与二氧化碳的接触,使得方解石的含量大幅下降。     

常温养护型超高性能混凝土的圆环约束收缩性能

研究了HCSA膨胀剂3种掺量(0%、3%、6%)下常温养护型超高性能混凝土(Ultra high performance concrete,UHPC)的圆环约束收缩性能,包括:(1)UHPC轴拉应力应变曲线测试;(2)根据GB/T50082的UHPC自由收缩实验;(3)根据ASTM C1581的UHPC圆环约束实验。结果表明,3种UHPC的极限拉伸应变均高于3 000με,28d总收缩值分别为1 005.6με、600.0με、462.2με,并且在圆环约束作用下转化为残余应变、弹性拉应变和塑性拉应变,其中塑性拉应变分别为700.4με、437.9με、389.9με。3种UHPC在拉伸应变达到1 000με时及圆环约束实验中均未发现0.01mm以上的可检测裂缝。基于拉伸实验和声发射损伤分析方法对UHPC进行应变分析,可知具有应变强化段的3种UHPC在圆环约束实验中的塑性变形以小于0.01mm的多点分布微裂纹形式存在。通过添加HCSA膨胀剂对常温养护型UHPC进行收缩补偿,可有效地降低UHPC自身的拉应力以及对原有结构的影响。