Solving Multi-Agent Target Assignment and Path Finding with a Single Constraint Tree

Combined Target-Assignment and Path-Finding problem (TAPF) requires simultaneously assigning targets to agents and planning collision-free paths for agents from their start locations to their assigned targets. As a leading approach to address TAPF, Conflict-Based Search with Target Assignment (CBS-TA) leverages both K-best target assignments to create multiple search trees and Conflict-Based Search (CBS) to resolve collisions in each search tree. While being able to find an optimal solution, CBS-TA suffers from scalability due to the duplicated collision resolution in multiple trees and the expensive computation of K-best assignments. We therefore develop Incremental Target Assignment CBS (ITA-CBS) to bypass these two computational bottlenecks. ITA-CBS generates only a single search tree and avoids computing K-best assignments by incrementally computing new 1-best assignments during the search. We show that, in theory, ITA-CBS is guaranteed to find an optimal solution and, in practice, is computationally efficient

Stratosphere-troposphere coupling during stratospheric extremes in the 2022/23 winter

Using the ERA5 reanalysis, sea surface temperature, sea ice observations, and the real-time multivariate Madden-Julian Oscillation (MJO) index, the evolution of the stratospheric extreme circulation in the winter of 2022/2023 is explored. The stratospheric polar vortex was disturbed three times in the 2022/23 winter, contrasted with only one disturbance during the other three recent winters with an SSW. Possible favorable conditions for the strong stratospheric disturbances and their effects on stratospheric ozone, water vapor distribution, and near-surface temperature were examined. Around 7 December 2022 when a short but strong pulse of planetary wavenumber 2 appeared from the troposphere to stratosphere, a weakened and elongated stratospheric polar vortex formed at 10 hPa. This pulse is related to the intensifying Ural ridge and the deepening East Asian trough. After the first stratospheric disturbance, a large fraction of cold anomalies occurred in the Eurasian continent. A lagged impact after these stratospheric disturbances was observed as strong cold anomalies formed in North America from 13 to 23 December. On 28 January 2023, a minor SSW event occurred due to a displacement of the stratospheric polar vortex. A strong pulse of eddy heat flux contributed alternately by planetary wavenumber 1 and 2 showed a large accumulative effect on the stratospheric disturbance. However, the downward impact of this second disturbance was weak, and cold surges were not noticeable after this minor SSW. The third stratospheric disturbance this winter is a major displace-type SSW that occurred on 16 February 2023, and the total eddy heat flux primarily contributed by planetary wavenumber 1 increased rapidly. Following the major SSW, the North American continent was covered by large patches of strong cold anomalies until the end of March. During the three disturbances, the residual circulation correspondingly strengthened. The water vapor and ozone in the middle and lower layers of the polar stratosphere showed positive anomaly disturbances, especially after the major SSW onset. The unprecedented frequent stratospheric disturbances in winter 2022/23 were accompanied by severe loss of Barents-Laptev Sea ice and anomalously cold tropical Pacific sea surface temperatures (La Niña), which have been reported to be conducive to the enhancement of planetary waves 1 and 2 respectively. Further, two weeks before the major SSW, existing MJO developed into phases 4–6, also contributing to the occurrence of major SSW

Health risk appraisal of urban thermal environment and characteristic analysis on vulnerable populations

Continuous global warming and frequent extreme high temperatures keep the urban climate health risk increasing, seriously threatening residents’ emotional health. Therefore, analysis on spatial distribution of the health risk that the urban heat island (UHI) effect imposes on emotional health as well as basic research on the characteristics of vulnerable populations need to be conducted. This study, with Tianjin city as the case, analyzed data from Landsat remote-sensing images, meteorological stations, and digital maps, explored the influence of summer UHI effect on distress (a typical negative emotion factor) and its spatiotemporal evolution, and conducted difference analysis on the age groups, genders, family state, and distress levels of vulnerable populations. The results show: (1) During the period of 1992–2020, the level and area of UHI influence on residents’ distress drastically increased–influence level elevated from level 2–4 to level 4–7, and highlevel influence areas were concentrated in six districts of central Tianjin. (2) Influence of the UHI effect on distress varied in different age groups–generally dropping with fluctuations as residents got older, especially residents aged 50–59. (3) Men experienced a W-shaped pattern in distress and were more irritable and unsteady emotionally; while women were more sensitive to distress in the beginning, but they became more placid as temperature got higher. (4) Studies on family status show that couples living together showed sound heat resistance in the face of heat stress, while middle-aged and elderly people living alone or with children were relatively weak in adjusting to high ambient temperature

Effects of Wettability and Minerals on Residual Oil Distributions Based on Digital Rock and Machine Learning

AbstractThe wettability of mineral surfaces has significant impacts on transport mechanisms of two-phase flow, distribution characteristics of fluids, and the formation mechanisms of residual oil during water flooding. However, few studies have investigated such effects of mineral type and its surface wettability on rock properties in the literature. To unravel the dependence of hydrodynamics on wettability and minerals distribution, we designed a new experimental procedure that combined the multiphase flow experiments with a CT scan and QEMSCAN to obtain 3D digital models with multiple minerals and fluids. With the aid of QEMSCAN, six mineral components and two fluids in sandstones were segmented from the CT data based on the histogram threshold and watershed methods. Then, a mineral surface analysis algorithm was proposed to extract the mineral surface and classify its mineral categories. The in situ contact angle and pore occupancy were calculated to reveal the wettability variation of mineral surface and distribution characteristics of fluids. According to the shape features of the oil phase, the self-organizing map (SOM) method, one of the machine learning methods, was used to classify the residual oil into five types, namely, network, cluster, film, isolated, and droplet oil. The results indicate that each mineral’s contribution to the mineral surface is not proportional to its relative content. Feldspar, quartz, and clay are the main minerals in the studied sandstones and play a controlling role in the wettability variation. Different wettability samples show various characteristics of pore occupancy. The water flooding front of the weakly water-wet to intermediate-wet sample is uniform, and oil is effectively displaced in all pores with a long oil production period. The water-wet sample demonstrates severe fingering, with a high pore occupancy change rate in large pores and a short oil production period. The residual oil patterns gradually evolve from networks to clusters, isolated, and films due to the effects of snap-off and wettability inversion. This paper reveals the effects of wettability of mineral surface on the distribution characteristics and formation mechanisms of residual oil, which offers us an in-deep understanding of the impacts of wettability and minerals on multiphase flow and helps us make good schemes to improve oil recovery