Analysis of Spatial Travel Association Rules for Rail Transit Based on AFC and POI Data

In order to explore the spatial distribution rules and causes of urban rail transit passenger travel, this paper mines the spatial 1-frequent itemset and 2-frequent itemsets of weekdays and weekends metro passenger travel based on Apriori algorithm using the continuous week of Automatic Fare Collection System (AFC) swipe card. At the same time, the K-Means algorithm is used to cluster the subway stations and explore the causes of association rules by combining the Point of Interest (POI) data of the same period within the radiation range of the subway stations. The study shows that the spatial distribution pattern of inbound and outbound passenger flow of Shanghai rail transit is consistent between weekdays and weekends, and the outbound passenger flow is more concentrated than the inbound passenger flow, and the significance of weekends is higher; the spatial distribution of metro stations is "circled"; the analysis of the high-lift association rules show that a large passenger flow group centered on the type 3 station is formed in the spatial location, and the passenger flow within the group is mainly commuter flow with separation of employment and residence. The association rule mining of metro passenger travel data is beneficial to understanding the spatial distribution pattern and causes of metro ridership, which can provide reference for rail network planning and operation management

Research on the Post Occupancy Evaluation of Green Public Building Environmental Performance Combined with Carbon Emissions Accounting

AbstractThe development of green building in China has reached a new stage, needs to turn to the total energy consumption control from the technology control[1]. We should avoid packing technologies in green building projects and regard achieving good environmental performance as the fundamental goal. In this paper, we use the method of post-occupancy evaluation and regard the building environmental performance as the core of the evaluation system, in order to reduce the influence on the accuracy of results from the measures evaluation. We establish the evaluation index system of green public building environmental performance in severe cold and cold regions, including the index of building life-cycle carbon emissions accounting. And we set up the application plan of index and the scoring method, then we put forward a kind of evaluation grade based on environmental performance level, finally proposed the POE System of Green Public Building Environmental Performance in Severe Cold and Cold Regions (POE-GPBEPC)

Effect of Cr3C2 Content on the Microstructure and Wear Resistance of Fe3Al/Cr3C2 Composites

In this paper, an engine piston ring coating comprising composite material of Fe3Al and Cr3C2 mixed powder was prepared by laser cladding onto carbon structural steel. The microstructure and tribological properties of the cladding materials were investigated through X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), transmission electron microscopy (TEM), and wear tests. The influence mechanism of the Cr3C2 content in cladding powder was studied. During the process of wear, the soft Fe3Al/Fe2AlCr matrix is first ground off, and the hard Cr7C3 phase initially supports the abrasive surface before being worn away into hard particles, resulting in abrasive wear. With the increase in Cr3C2 content, the hardness of the cladding layer increases, the proportion of the Cr7C3 phase increases, and the morphology changes from a sparse network to a dense floccule. Of the cladding layers with different Cr3C2 content, the 15 wt.% Cr3C2 cladding layer had the lowest friction coefficient, and the 25 wt.% Cr3C2 cladding layer had the lowest wear rate. The low wear rate of the 25 wt.% Cr3C2 cladding layer can be attributed to the fact that adhesive wear does not easily occur and the fine microstructure of the strengthening phase, which facilitates better separation in the grinding surfaces

OpenLane-V2: A Topology Reasoning Benchmark for Unified 3D HD Mapping

Accurately depicting the complex traffic scene is a vital component for autonomous vehicles to execute correct judgments. However, existing benchmarks tend to oversimplify the scene by solely focusing on lane perception tasks. Observing that human drivers rely on both lanes and traffic signals to operate their vehicles safely, we present OpenLane-V2, the first dataset on topology reasoning for traffic scene structure. The objective of the presented dataset is to advance research in understanding the structure of road scenes by examining the relationship between perceived entities, such as traffic elements and lanes. Leveraging existing datasets, OpenLane-V2 consists of 2,000 annotated road scenes that describe traffic elements and their correlation to the lanes. It comprises three primary sub-tasks, including the 3D lane detection inherited from OpenLane, accompanied by corresponding metrics to evaluate the model's performance. We evaluate various state-of-the-art methods, and present their quantitative and qualitative results on OpenLane-V2 to indicate future avenues for investigating topology reasoning in traffic scenes.Comment: Accepted by NeurIPS 2023 Track on Datasets and Benchmarks | OpenLane-V2 Dataset: https://github.com/OpenDriveLab/OpenLane-V

Topology Reasoning for Driving Scenes

Understanding the road genome is essential to realize autonomous driving. This highly intelligent problem contains two aspects - the connection relationship of lanes, and the assignment relationship between lanes and traffic elements, where a comprehensive topology reasoning method is vacant. On one hand, previous map learning techniques struggle in deriving lane connectivity with segmentation or laneline paradigms; or prior lane topology-oriented approaches focus on centerline detection and neglect the interaction modeling. On the other hand, the traffic element to lane assignment problem is limited in the image domain, leaving how to construct the correspondence from two views an unexplored challenge. To address these issues, we present TopoNet, the first end-to-end framework capable of abstracting traffic knowledge beyond conventional perception tasks. To capture the driving scene topology, we introduce three key designs: (1) an embedding module to incorporate semantic knowledge from 2D elements into a unified feature space; (2) a curated scene graph neural network to model relationships and enable feature interaction inside the network; (3) instead of transmitting messages arbitrarily, a scene knowledge graph is devised to differentiate prior knowledge from various types of the road genome. We evaluate TopoNet on the challenging scene understanding benchmark, OpenLane-V2, where our approach outperforms all previous works by a great margin on all perceptual and topological metrics. The code would be released soon

Treatment of paraffin deposition behavior in gas-condensate wells with chemical inhibitors

Abstract As deep gas-condensate reservoirs are explored, the problem of paraffin deposition is becoming more prominent. Therefore, this paper collects condensate samples from representative paraffin deposition gas-condensate wells and analyzes basic physical properties. The cold plate deposition device is employed to study paraffin deposition behavior under well conditions and to divide the critical regions for paraffin deposition in gas-condensate wells. The experimental apparatus, such as the crude oil dynamic paraffin deposition rate tester, is utilized to investigate the preventive effect of paraffin dispersants and paraffin crystal modifier. The results show that there is significant phase change behavior in gas-condensate wells and gas phase is dominant form, but there is also phase evolution. It can be identified from the experiments that paraffin deposition is mainly located in the 1000 ~ 1500 m region, and a paraffin deposition identification chart has been established. The maximum deposition rate could reach 15.50 mm/year, which matched the temperature and pressure conditions of 45 ℃ and 70 MPa. The preventive effect of paraffin crystal modifiers greatly exceeds that of paraffin dispersants, with paraffin prevention rates of 85–95% at the optimal concentrations of 0.25–0.50 wt.%. The dissolving paraffin rate can reach 0.0169 g/min. It decreases the paraffin appearance temperature approximately 40% and significantly changes the paraffin crystal morphology. Increased deposition surface area of the cold plate structural design describes the paraffin deposition. This diagram facilitates the reliable identification of paraffin deposition areas and the deposition rates in the wellbore during production. The optimum amounts of BZ and PI paraffin inhibitors are quantified. This study provides a comprehensive understanding of the paraffin deposition behavior, and scientific basis and guidance for the selection of paraffin inhibitors in gas-condensate wells