Merging Point Research Articles

Evaluation of Airspace Operation Safety Level based on PMS

The point merge (PM) flight procedure is a new type of flight procedure of performance -based navigation (PBN). The capacity of the point merge procedure is evaluated through the parameters of the point merge flight procedure. Through the parameters of the point merge flight procedure and the parameters of the aircraft flying in the point merge flight procedure, the collision risk between two aircraft in the merge area and the overall collision risk of the aircraft in the point merge procedure are calculated. The evaluation methods and calculation formulas of these three parameters are summarized, and a reasonable method of airspace operation safety level evaluation based on point merge system (PMS) is sought. The inferred method of airspace operation safety level evaluation based on PMS is to compare the operation capacity with the calculated theoretical capacity, and compare the collision risk between two aircraft in the fusion area calculated according to track data and radar data and the overall collision risk of aircraft in PMS with the target safety level specified by China’s air transportation industry.

Comparison of performance between PMS and trombone arrival route topologies in terminal maneuvering area

The contradiction between air traffic capacity and demand exerts congestion and delay, resulting in airspace operating at or above its capacity. This paper proposes a performance comparison of two arrival route topologies in Terminal Maneuvering Area (TMA) with a tailored optimization algorithm, including Point Merge System (PMS) and trombone paradigms. We aim at enhancing the capacity of arrival topologies and efficiently landing more aircraft through identifying which topological route is better suitable for current traffic demands. The problem involves integrating and sequencing arrival operations into the TMA. A mathematical model is developed for which entry times, entry speeds and flight routes are regarded as decision variables. The operation constraints of this optimization modelling correspond to detection of potential conflicts between consecutive aircraft at merging waypoints and on the same link segments, based on the safety separation standards. The objective function is set to minimize the delay and speed deviation for all flights in the optimized system. Because of the highly combinatorial nature of this problem and the non-deterministic polynomial hard (NP-hard), a tailored selective simulated annealing algorithm is proposed to optimally make decisions for the arrival traffic flow. Finally, the validation of our approach has been performed for Ataturk Airport in Turkey, by using 11 different operation scenarios of arrival demands. For lower demands, all aircraft can be positively scheduled, while for more than 80% extra scenarios based on the regular traffic demand, there exist some remaining conflicts for the situations. The results illustrate that, compared with the trombone procedure, PMS paradigm could enhance the arrival capacity and has better performance throughout the arrival procedure. Additionally, more flexible sequence position shift is possible in PMS, and it has the ability to accommodate high-density flight operating environment.

Quasi-stochastic optimization model for time-based arrival scheduling considering Standard Terminal Arrival (STAR) track time and a new delay-conflict relationship

This paper presents a quasi-stochastic mixed integer programming model to determine the optimal arrival schedule of flights in the Terminal Area (TMA). The proposed formulation addresses two key aspects of TMA operations: (i) the variability induced due to the Standard Terminal Arrival (STAR) descent procedure and (ii) the risk of merging conflicts due to scheduling delays. The variability arising from the STAR procedure is captured through a non-deterministic parameter defined as the track time. The risk of conflicts at merging points is quantified using the expected number of conflicts, estimated based on a new delay-conflict relationship. The optimization model is also extended for a multiple-runway structure. The Chennai International Airport TMA is taken as an experimental setup to validate the model. Performance assessment reveals that the observed throughput aligns with the throughput based on the optimal scheduling. Moreover, the number of conflicts is reduced by 100% after implementing the scheduling model. Research outcomes exhibit the potential to obtain practical arrival schedules with limiting controller workload. Implications of this work hint towards better stability and performance of the TMA and the overall Air Traffic Management (ATM) system.

Fredholm separating maps on continuous function spaces

For locally compact Hausdorff spaces X and Y, we initiate a study of Fredholm separating maps T from C(X) into C(Y). Our key aim is to completely recognize the structures of the kernel space and the range space of T in terms of merging points to show that X and Y are homeomorphic after removing related finite subsets; as the main result, we describe the interaction between continuity of T and closedness of its range; in particular, under certain condition, we conclude that T can be represented as a weighted composition operator.

THREE-DIMENSIONAL MODELING OF SHRUBS BASED ON LIDAR POINT CLOUDS

Abstract. This paper proposes a method for constructing 3D models of shrubs with high accuracy from 3D point clouds acquired by terrestrial laser scanning (TLS). Since the shrub point cloud obtained by LiDAR scanning contains a large amount of redundant data, the focus of this method is to segment the branches and leaves of the shrub point cloud first, which can remove the noise and make the branch skeleton of the shrub stand out. Secondly, a triangulation network is constructed for the segmented branch points, and a minimum spanning tree (MST) is established from the triangulation network as the initial shrub skeleton of the input point cloud. Then, the redundant branches are removed by merging adjacent points and edges to simplify the initial skeleton. Finally, the 3D model of a shrub is constructed by a cylindrical fitting algorithm based on robust principal component analysis (RPCA). Experiments on different types of shrubs from different data sources demonstrate the effectiveness and robustness of the proposed method. The 3D models of shrubs can be further applied to the accurate estimation of shrub attributes and urban landscape visualization.

Overcrowding and separation estimates for the Coulomb gas

AbstractWe prove several results for the Coulomb gas in any dimension that follow from isotropic averaging, a transport method based on Newton's theorem. First, we prove a high‐density Jancovici–Lebowitz–Manificat law, extending the microscopic density bounds of Armstrong and Serfaty and establishing strictly sub‐Gaussian tails for charge excess in dimension 2. The existence of microscopic limiting point processes is proved at the edge of the droplet. Next, we prove optimal upper bounds on the ‐point correlation function for merging points, including a Wegner estimate for the Coulomb gas for . We prove the tightness of the properly rescaled th minimal particle gap, identifying the correct order in and a three term expansion in , as well as upper and lower tail estimates. In particular, we extend the two‐dimensional “perfect‐freezing regime” identified by Ameur and Romero to higher dimensions. Finally, we give positive charge discrepancy bounds which are state of the art near the droplet boundary and prove incompressibility of Laughlin states in the fractional quantum Hall effect, starting at large microscopic scales. Using rigidity for fluctuations of smooth linear statistics, we show how to upgrade positive discrepancy bounds to estimates on the absolute discrepancy in certain regions.

Numerical Study of Mixed Convection of Buoyant Twin Jet

Abstract The effect of mixed convection of twin vertical jets is investigated numerically in this paper. The results are presented specifically for flows affected by buoyancy for two parallel jets of same velocities ranging between 0.25 m/s and 5.0 m/s and temperatures between 295 K and 320 K. Both jets generate a slow flow with a temperature difference (with the ambient flow) less or equal to 32 °C (305 K). Predictions of dynamical and thermal parameters are obtained for the merging and combining regions. This study reveals that the trajectory of the two jets is strongly influenced by the ratio of buoyancy to inertial forces. Results indicate that, relative to isotherm jets, the location along the vertical symmetry plane at which the two jets merge (merging point) decreases with increasing jet inlet temperature. It was also found that the location of the merging point is shifted toward the confining wall as the velocity of the jets increases. The behavior law (linear regression), relating to the expansion of the jet, is not verified in the developed region for each value of the inlet velocity and temperature. This is explained by the fact that natural convection is more predominant than forced convection. The results show that the self-similarity of the cross profiles of the mean velocity and the behavior law relating to the expansion of the jet are obtained throughout the developed region.

Investigation of Point Merge Utilization Worldwide Using Opensky Network Data

Point Merge (PM) arrival procedure is implemented at multiple airports around the World. There are different PM design variants: with overlapping, partially overlapping or separated sequencing legs, a position of the sequencing legs inside or outside the TMA, different geometry of the flows to PM or merging to a point; each coming with a different impact on the trade-offs associated with the structure. In this work, we investigate the usage of PM procedure in several airports around the globe using open-access ADS-B-based data provided by the Opensky Network. We analyse arrival flows at the airports with PM, and propose a catchment algorithm to see which flights from the blend are actually adherent to the procedure. Then quantify the PM utilization applying the performance indicators specifically designed for this purpose.

Cooperative Merging Strategy in Mixed Traffic Based on Optimal Final-State Phase Diagram With Flexible Highway Merging Points

The cooperation between connected and automated vehicles (CAVs) has emerged as a promising way to improve traffic efficiency and safety for ramp merging on highways. Existing research mostly focused on the collaboration of individual CAVs, while the cooperative merging strategy in mixed traffic considering vehicle platoons has been less explored. To address the above problem, this study aims to build connections between sequence scheduling and motion planning in mixed traffic, where individual CAVs, CAVs platoons, and mixed platoons coexist. First, optimal control strategies are presented for vehicles with flexible merging points based on Pontryagin’s minimum principle (PMP), and the final vehicle states in variable conditions are summarized in a phase diagram. Subsequently, the optimal final-state phase diagram is introduced into the passing sequence tree search process, which is designed for different vehicle groups in mixed traffic. Heuristic pruning rules are added to the depth-first search strategy to facilitate finding the optimal solution. Finally, an event-triggered receding horizon optimization algorithm is developed for continuous implementation. The numerical simulations are conducted in multiple traffic volumes, and the simulation results reveal that our proposed algorithm significantly improves the overall traffic efficiency and reduces vehicle-passing delays compared with the traditional FIFO-based cooperation method.

Based on point merge for paired approach sequencing on closely spaced parallel runways

Based on point merge for paired approach sequencing on closely spaced parallel runways

Research on airflow convergence patterns and air distribution characteristics under multi-column attachment ventilation

Multi-column attachment ventilation (M-CAV) is usually delivered to the occupied zone by floor-attached airflows in large spaces. However, after the floor-attached airflow converges, the original air distribution will change, which will have an important impact on the traditional air distribution design. In this paper, airflow convergence patterns and air distribution characteristics in the most common double-column and tri-column layouts are studied by experiments and computational fluid dynamics (CFD) simulations. A 1:3 scaled-down model was established for velocity experiments and flow field visualization, and the results were used to verify and optimize the CFD model. The results indicated a seagull-like convergence flow pattern under the symmetric double-column layout. Under the axisymmetric layout with different column spacings, the floor-attached airflow in the half-open air outlet mode exhibited full convergence with the merging point (point MP) and combined point (point CP), partial convergence with point MP, and non-convergence without point MP and point CP. Under the centrosymmetric layout, an M-shaped velocity distribution was formed, and no airflow converged. For equal-velocity conditions, the dimensionless convergence axial velocity distributions for different air supply velocities was approximately consistent. In the fully-open air outlet mode, the floor-attached airflow could be divided into the collision-dominated region, the combined collision and convergence-dominated region, and the convergence-dominated region based on the forms of airflow interaction. For unequal-velocity conditions, the high-velocity airflow restricted the diffusion of the low-velocity airflow.

Study on heat transfer characteristics of ultra-thin flat heat pipes at different liquid filling rates and heat loads

The boiling characteristics of flat heat pipes greatly affect their heat transfer performance, but the research on micro-scale ultra-thin steam chamber is still unclear. The heat transfer performance of ultra-thin plate heat pipe (UTFHP) was investigated by analyzing the boiling heat transfer characteristics under various operating conditions through both theoretical analysis and visualization experiments. The findings demonstrate that the heat transfer process of UTFHP can be classified into three stages based on changes in bubble behavior and heat transfer characteristics. Additionally, we conducted a comprehensive examination of the heat transfer mechanism. The study identifies key factors that affect bubble heat transfer in UTFHP, including temperature, pressure, working fluid properties, and gas–liquid interface area. The impact of heating power on the merging point and turning point of the UTFHP is discussed, while the liquid filling rate is found to have an insignificant effect. The start-up time of the UTFHP is delayed by the liquid bridge, which can be improved by introducing multiple air bubbles and liquid bridges. The study also investigates factors affecting the heat transfer capacity of UTFHP during stable operation, revealing that as heating power increases, the temperature of the evaporator and condenser increases linearly, while the thermal resistance initially increases, decreases, and then increases.

Real-Time Adjustment and Spatial Data Integration Algorithms Combining Total Station and GNSS Surveys with an Earth Gravity Model

During the dynamic development of modern technologies based on advanced algorithmic and instrumental solutions, it is essential to integrate geospatial data efficiently. Such an approach is applied in all geo-information services, especially mobile ones, and is helpful in, for example, precise navigation or effective risk management. One leading application is deformation monitoring (structural monitoring) and displacement control surveying. In addition, spatial data integration methods are used in modern accessibility analysis, Smart City ideas, tracing utility networks, and building information modelling (BIM). The last aforementioned technology plays a crucial role in architectural design and construction. In this context, it is crucial to develop efficient and accurate algorithms supporting data fusion, which do not strain the computing resources and operate efficiently online. This paper proposes an algorithm for real-time adjustment of integrated satellite GNSS (global navigation satellite system), total station, and Earth Gravitational Model (EGM) vertical direction data in a geocentric coordinate system based on a statistical general linear mixed model. A numerical example shows that the proposed algorithm of the online adjustment works correctly. The results of the online adjustment are the same as those of the offline adjustment. It is also shown that the GNSS measurements are necessary only at the total station points in the spatial total station traverse. There is no need to add additional merging points of the total station positions because the differences between the results of the online adjustment, including and excluding the merging points, are very small (around 1–2 mm in standard deviation).

Unmanned aircraft path planning for construction safety inspections

With its flexible and convenient features, the Unmanned Aircraft System (UAS) provides an efficient platform for safety inspections in hazardous areas. Yet sparse studies have explored path planning for construction safety inspections. This research developed a multi-precision unmanned aircraft path planning system (MP-UAS) by using MATLAB for safety inspections on partially known 3D exterior construction environments. Firstly, a detailed house-building checklist and monitoring levels are formulated. Subsequently, based on the principle of merging pixel points in four neighborhoods, the Four-neighborhood Growing algorithm extracts information from the point cloud grid model to divide inspection areas. Finally, the Ant Colony Optimization (ACO) combined with four-element optimization achieves a full coverage optimal design of UAS path in two-dimensional planes above the inspection area. The system greatly reduces the path length and minimizes energy consumption while meeting requirements of coverage accuracy in the validation case, and is expected to facilitate safety inspection and decision-making.

Limited exposure to preserve stability and achieve complete excision of limited dorsal myeloschisis - the "Skip-Hop Laminectomy" technique: a technical note.

The fibroneural stalk of an LDM has variable thickness, complexity, and length, which can span 5 to 6 vertebral segments from its skin attachment to its "merge point" with the dorsal spinal cord. Therefore, complete resection may require extensive multi-level laminotomies. In this technical note, a modification of the procedure is presented that avoids long segment laminectomies while ensuring complete excision of long LDM stalks. An illustrative case of resection of LDM is presented using skip laminectomies. The technique ensures complete removal of the stalk, thus reducing the risk of future intradural dermoid development, while at the same time minimizes the risk for delayed kyphotic deformity. A technique of "skip-hop" proximal and distal short segment laminectomies in cases of LDM optimizes the objectives of complete stalk resection with preservation of spinal integrity.

Beyond RMSE: Do Machine-Learned Models of Road User Interaction Produce Human-Like Behavior?

Autonomous vehicles use a variety of sensors and machine-learned models to predict the behavior of surrounding road users. Most of the machine-learned models in the literature focus on quantitative error metrics like the root mean square error (RMSE) to learn and report their models' capabilities. This focus on quantitative error metrics tends to ignore the more important behavioral aspect of the models, raising the question of whether these models really predict human-like behavior. Thus, we propose to analyze the output of machine-learned models much like we would analyze human data in conventional behavioral research. We introduce quantitative metrics to demonstrate presence of three different behavioral phenomena in a naturalistic highway driving dataset: 1) The kinematics-dependence of who passes a merging point first 2) Lane change by an on-highway vehicle to accommodate an on-ramp vehicle 3) Lane changes by vehicles on the highway to avoid lead vehicle conflicts. Then, we analyze the behavior of three machine-learned models using the same metrics. Even though the models' RMSE value differed, all the models captured the kinematic-dependent merging behavior but struggled at varying degrees to capture the more nuanced courtesy lane change and highway lane change behavior. Additionally, the collision aversion analysis during lane changes showed that the models struggled to capture the physical aspect of human driving: leaving adequate gap between the vehicles. Thus, our analysis highlighted the inadequacy of simple quantitative metrics and the need to take a broader behavioral perspective when analyzing machine-learned models of human driving predictions.

Environmental inefficiencies for arrival flights at European airports.

In this paper, we analyze two months of trajectory data for aircraft landing in five major European airports. Based on open ADS-B data from the OpenSky Network and open performance models, we enrich all trajectories with automatically detected procedure information, fuel consumption, and emissions for supported aircraft types. To assess the inefficiencies associated with holding patterns, point merges, and continuous descent operations across different airports, we propose methodologies to quantify and compare these environmental inefficiencies. Holding patterns are found to have a higher negative impact on the environment than point merge and continuous descent operations. Furthermore, the paper provides recommendations for procedure evaluations of future airports, which could help policymakers and relevant stakeholders to evaluate the environmental performances of arrival procedures based on open data and open models.

Robust optimization integrating aircraft trajectory and sequence under weather forecast uncertainty

Integration of trajectory optimization into sequence optimization is required for next-generation Arrival Managers (AMANs) to support Collaborative Decision-Making (CDM) and implementation of user-preferred 4D trajectories. In addition, considering uncertainty in the optimization is also necessary for making more robust decisions. To achieve these aims, this study proposes a method to integrate the trajectory and sequence of approach aircraft in a single optimization framework and calculate optimal robust solutions against weather forecast uncertainty. This uncertainty is quantified utilizing the ensemble weather forecast and the robust optimizations for trajectory and sequence are formulated in an ensemble approach. To connect the two optimizations, we introduce the so-called performance surfaces, which represent the characteristics of the optimal trajectory. The resulting integrated Trajectory and Sequence (T&S) optimization is a combination of the robust Optimal Control (OC) and Mixed-Integer Nonlinear Programming (MINLP). The MINLP problem is relaxed to the corresponding Nonlinear Programming (NLP) problem to reduce computational costs. In the case study, the trajectory and sequence are simultaneously optimized for two different objectives: the maximum throughput at the merging point and the minimum fuel burn while maintaining the inter-aircraft separation.

Analysis of Stochasticity and Heterogeneity of Car-Following Behavior Based on Data-Driven Modeling

Traffic dynamics on freeways are stochastic in nature because of errors in perception and operation of drivers as well as the heterogeneity between and within drivers. This stochasticity is often represented in car-following models by a stochastic term, which is assumed to follow a normal distribution for the convenience of mathematical processing. However, the validity of this assumption has not been studied yet. In this study, we focused on the shape of the distribution of a stochastic term in the car-following model that predicts an acceleration after a time step. Based on vehicle trajectory data on a freeway in Japan, a car-following model is first developed by using data-driven methodology in which long short-term memory (LSTM) network is applied. In this LSTM network, the acceleration value is discretized and the model parameters are trained with the focal loss function. The relationship between the predicted distributions’ modality, standard deviation (SD), and [Formula: see text] with respect to traffic states is then examined. The findings demonstrate that: 1) the developed model can accurately predict the accelerations; 2) a probabilistic distribution tends to have a large SD and multimodality around a merging point and at the beginning of and along stop-and-go waves; and 3) driving behavior can be classed in one of four clusters based on the variation of the percentile value that a driver takes within the probability distribution. The proposed model and the insights are helpful for improving microscopic simulation models when considering new traffic management measures.

Optimization research regarding the jet nozzle combination mode for marine hydrate solid fluidized mining tools based on dual nozzles

Natural gas hydrate solid fluidization mining technology is a new hydrate mining technology, but due to the lack of combined nozzle design theory and basis, the crushing efficiency of mining tools is low. To solve this problem, the characteristics of the combined jet flow fields of nozzles with diameters from 1 mm to 4 mm and combination angles from 10° to 20° were studied in this paper by means of experiments and simulations. The results show that the maximum velocity at the merging point increases negatively linearly with increases in the combination angle and positively linearly with increase in the nozzle diameter. The position of the merging point changes little with the nozzle diameter and increases exponentially with increases in the combination angle. The effective crushing lengths of nozzles with different diameters all turn (increase first and then decrease) when the combination angle is 12.5°. The optimal combination angle for nozzles with diameter less than 4.5 mm is 12.5°, and 15° is for nozzles with diameter more than 4.5 mm. This study reveals the flow field variation mechanism for the combined nozzle and provides guidance for the design of the combined nozzles of gas hydrate combined nozzles.