基于PLC的船舶空气源热泵供热水控制系统研发

为了极大限度节省船舶热水站能耗,研制出一套空气源热泵热水控制系统及PLC与变频器构成恒压供热水系统,并通过触摸屏对系统进行参数设置和实时监控,可保证昼夜不间断恒压供水,提高了船舶热水站的可靠性和经济性。     

Application of digital image correlation method to in-situ dynamic strain measurement

Application of digital image correlation (DIC) method to determination of in-situ dynamic strain is presented in this study. Firstly, an integrative software is programmed based on the DIC algorithms and point-wise least-squares fitting technique. Then, simulated speckle images are generated to study the computational accuracy of this software. The experimental setup and procedures for measuring in-situ dynamic strain through both DIC and strain gauge are proposed. The DIC results are close to those measured by strain gauge. This fact reveals that DIC is a practical and effective tool for in-situ dynamic strain measurement. Finally, the full-field in-situ dynamic strain of another specimen is measured by DIC, and the overall distribution of the strain in the measurement area is clearly shown.     

地铁供电系统中压开关柜电流分析理论和方法

通过分析地铁供电系统不同电压等级的设备电流特征,确定35 kV电压等级设备电流可构造标准曲线,采用机器智能学习算法分析、测算地铁供电系统中各类开关峰谷时段运行电流,以均值-方差方法确定电流的高度异常偏离点,实现异常点数据周期内统计以及实时提醒功能。应用电流实测值分析电流在工作日、节假日的不同曲线,为负荷预测和非正常运行方式下的负荷叠加风险提供预测和评估依据,保障供电系统的安全运行,提高负荷管控效率。     

铁路预应力路堤加固技术数值研究

研究目的:铁路预应力路堤在国内外尚属一种新型路基加固法,其受力变形特性暂未得到系统化研究,相关加固设计理论仍处于探索性阶段。因此,有必要通过数值手段了解预应力路堤的工作状态,以掌握其加固性能。鉴于此,借助ABAQUS软件平台构建预应力路堤仿真系统,分析差异化预应力加固参数对路堤变形和承载能力的影响以及预应力加固构件的受力特征。研究结论:(1)路堤本体段坡面较优加固位置为距本体顶面以下0.3倍本体高度处;(2)坡率1∶1的预应力路堤在第1、2排侧压板分别施加50 k Pa、100 k Pa预压荷载时,其变形与承载力均可达传统路堤(坡率1∶1.5)水平,并可通过提升加固标准进一步强化路堤承载性能;(3)当对第1、2、3排侧压板分别施加50 k Pa、100 k Pa、100 k Pa预压荷载时,路堤内部附加围压S11>13.5 k Pa区域大致呈"x"形分布并形成横贯路堤的"预压加固区";(4)侧压板锚固区受力集中且复杂,应注意保障锚固区板体强度;(5)力筋在路堤加载前后的应力变化量与坡面侧向变形特征相关;(6)本研究成果可为铁路预应力路堤的加固设计提供技术指导。     

CT reconstruction with priori MRI images through multi-group datasets expansion

Computed tomography (CT) reconstruction with a well-registered priori magnetic resonance imaging (MRI) image can improve reconstruction results with low-dose CT, because well-registered CT and MRI images have similar structures. However, in clinical settings, the CT image of patients does not always match the priori MRI image because of breathing and movement of patients during CT scanning. To improve the image quality in this case, multi-group datasets expansion is proposed in this paper. In our method, multi-group CT-MRI datasets are formed by expanding CT-MRI datasets. These expanded datasets can also be used by most existing CT-MRI algorithms and improve the reconstructed image quality when the CT image of a patient is not registered with the priori MRI image. In the experiments, we evaluate the performance of the algorithm by using multi-group CT-MRI datasets in several unregistered situations. Experiments show that when the CT and priori MRI images are not registered, the reconstruction results of using multi-group dataset expansion are better than those obtained without using the expansion.     

Attitudes,mode switching behavior,and the built environment: A longitudinal study in the Puget Sound Region

Carpooling in the US has a storied history. After experiencing a peak 20% mode share in 1980, the current share of carpooling for work trips is about 10% and the majority of these carpooling trips are made by intra-household members. Casting the choice between SOV and carpool as a social dilemma in which SOV is a noncooperative choice and carpool is a cooperative one, we propose to test two hypotheses. First, the switch from SOV to carpool and the reverse choice are attributed to different factors—structural factors, or those factors altering the objective features of a decision scenario such as travel time and travel cost, play a dominant role in the switch from carpool to SOV while psychosocial factors (attitudes and beliefs) play a critical role in the switch from SOV to carpool. Second, the two choices are underlay by different behavioral mechanisms. In particular, we expect self-justification by carpool-to-SOV switchers—after they switch from carpool to SOV, they adjusted their attitudes toward carpool accordingly to match their behavior. The analysis of the first three waves of the Puget Sound Transportation Panel supports these two hypotheses. Our study results recommend developing programs and policies that aim at influencing people’s subjective assessments of carpooling, in addition to the existing ones that mostly focus on incentivizing carpooling, and differentiating between programs seeking to encourage SOV users to switch to carpool and those aiming to maintain existing carpoolers.     

Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditions北大核心CSCD

［Objective ］ To meet the requirements of remotely controlling ship in curved, narrow and crowded inland waterways, this paper proposes an approach that consists of CNN-based algorithms and knowledge based models under ship-shore cooperation conditions. ［Method］On the basis of analyzing the characteristics of ship-shore cooperation, the proposed approach realizes autonomous perception of the environment with visual simulation at the core and navigation decision-making control based on deep reinforcement learning, and finally constructs an artificial intelligence system composed of image deep learning processing, navigation situation cognition, route steady-state control and other functions. Remote control and short-time autonomous navigation of operating ships are realized under inland waterway conditions, and remote control of container ships and ferries is carried out. ［Results］The proposed approach is capable of replacing manual work by remote orders or independent decision-making, as well as realizing independent obstacle avoidance, with a consistent deviation of less than 20 meters. ［Conclusions］The developed prototype system carries out the remote control operation demonstration of the above ship types in such waterways as the Changhu Canal Shenzhou line and the Yangtze River, proving that a complete set of algorithms with a CNN and reinforcement learning at the core can independently extract key navigation information, construct obstacle avoidance and control awareness, and lay the foundation for inland river intelligent navigation systems. © 2022 Journal of Clinical Hepatology. All rights reserved.     

Personalization method of e-catalog based on user interesting degree

The user interesting degree evaluation index is designed to fulfill the users’ real needs, which includes the user’ attention degree of commodity, hot commodity and preferential commodity. User interesting degree model (UIDM) is constructed to justify the value of user interesting degree; the personalization approach is presented; operations of add and delete nodes (branches) are covered in this paper. The improved e-catalog is more satisfied to users’ needs and wants than the former e-catalog which stands for enterprises, and the improved one can complete the recommendation of related products of enterprises.     

Estimation of delay variability at signalized intersections for urban arterial performance evaluation

Urban arterial performance evaluation has been broadly studied, with the major focus on average travel time estimation. However, in view of the stochastic nature of interrupted flow, the ability to capture the characteristics of travel time variability has become a critical step in determining arterial level of service (LOS). This article first presents a stochastic approach that integrates classic cumulative curves and probability theories in order to investigate delay variability at signalized intersections, as a dominant part of the link travel time variability. This serves as a basis for arterial travel time estimation, which can be obtained through a convolution of individual link travel time distributions. The proposed approach is then applied in the estimation of travel time along one arterial in Shanghai, China, with abundant automatic vehicle identification (AVI) data sources. The travel time variability is evaluated thoroughly at 30-min intervals, with promising results achieved in comparison to the field measurements. In addition, the estimated travel time distributions are utilized to illustrate the probability of multiple LOS ranges, namely, reliability LOS. The results provide insights into how we might achieve a more reliable and informative understanding of arterial performance.