Transport Problems Research Articles

Estimating Markov Chain Mixing Times: Convergence Rate Towards Equilibrium of a Stochastic Process Traffic Assignment Model

Network equilibrium models have been extensively used for decades. The rationale for using equilibrium as a predictor is essentially that (i) a unique and globally stable equilibrium point is guaranteed to exist and (ii) the transient period over which a system adapts to a change is sufficiently short in time that it can be neglected. However, we find transport problems without a unique and stable equilibrium in the literature. Even if it exists, it is not certain how long it takes for the system to reach an equilibrium point after an external shock onto the transport system, such as infrastructure improvement and damage by a disaster. The day-to-day adjustment process must be analysed to answer these questions. Among several models, the Markov chain approach has been claimed to be the most general and flexible. It is also advantageous as a unique stationary distribution is guaranteed in mild conditions, even when a unique and stable equilibrium does not exist. In the present paper, we first aim to develop a methodology for estimating the Markov chain mixing time (MCMT), a worst-case assessment of the convergence time of a Markov chain to its stationary distribution. The main tools are coupling and aggregation, which enable us to analyse MCMTs in large-scale transport systems. Our second aim is to conduct a preliminary examination of the relationships between MCMTs and critical properties of the system, such as travellers’ sensitivity to differences in travel cost and the frequency of travellers’ revisions of their choices. Through analytical and numerical analyses, we found key relationships in a few transport problems, including those without a unique and stable equilibrium. We also showed that the proposed method, combined with coupling and aggregation, can be applied to larger transport models. History: This paper has been accepted for the Transportation Science Special Issue on the 25th International Symposium on Transportation and Traffic Theory. Funding: This study was financially supported by the Japan Society for the Promotion of Science [Grant-in-Aid 20H00265]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/trsc.2024.0523 .

ХАРАКТЕРИСТИКА МАРШРУТНОЙ СЕТИ ОБЩЕСТВЕННОГО ТРАНСПОРТА ГОРОДА БАРНАУЛА

The development of a city is closely related to the state of its transport system and the spatial organization of urban public transport. In general, a number of transport problems can be noted for the city related to the waiting time for transport, the provision of various areas with urban public transport routes, etc. These problems have become particularly relevant in the 21st century and have become very actively discussed. The article is devoted to the analysis of the route network of the city of Barnaul, as well as the number of rolling stock on the routes. Particular attention is paid to routes where there is a shortage of rolling stock. The purpose of the work is to analyze the current state of the route network of the city of Barnaul and identify problems. The main methods were literature analysis, as well as monitoring public transport using the 2GIS service. In general, it can be noted that the city’s public transport runs stably and interruptions occur due to weather conditions (in particular freezing) or traffic situations (congestion in the morning and evening); there is also a dependence of preferential traffic to the city center and from the city center to depending on the time of day.

A Corrected Inexact Proximal Augmented Lagrangian Method with a Relative Error Criterion for a Class of Group-Quadratic Regularized Optimal Transport Problems

A Corrected Inexact Proximal Augmented Lagrangian Method with a Relative Error Criterion for a Class of Group-Quadratic Regularized Optimal Transport Problems

Synergistic improvement the Zn storage performance of ZnMn2O4 quantum dots by Ni doping and in-situ electrochemical induction

Manganese-based materials have been widely recognized as the most promising cathode materials for aqueous zinc-ion batteries (ZIBs). However, due to the problems of disproportionation reaction and slow electron transport, the development of manganese-based materials is greatly limited. In this work, a carbon-coated Ni-doped ZnMn2O4 quantum dot (NZMO QD@C) were obtained by a combined strategy of gradient calcination and electrochemical induction process with Mn-MIL-100 as the precursor. The presence of 0D quantum dot structure allows ZnMn2O4 to have shorter Zn2+ diffusion pathways and more active sites. Meanwhile, the doping of Ni can promote electron rearrangement, improve conductivity, and ultimately improve the reaction kinetics and electrochemical performance of cathode materials. Furthermore, Ni doping can effectively enhance the stability of the Mn-O bond in NZMO QD@C by optimizing the Mn ion state and electronic bandgap. Therefore, the synthesized NZMO QD@C provide a higher specific capacity of 392 mAh g-1 (0.1 A g-1) and better (≈80.28 % capacity retention for more than 820 cycles at 1 A g-1) than original MO QD@C cathode. This work brings new ideas to promote the development and design of manganese-based oxide cathode materials for ZIBs.

A comparative study of streamlined flow channels with water drop block configurations and their effects on temperature profiles, mass transport characteristics, and performance in PEM fuel cell

The problems of temperature distribution, mass transport, and drainage performance in flow field channels (FFCs) become the most significant effects on PEMFC performance. In order to solve the above problems, this study proposes five distinct streamlined block architectures of flow channels that consider interface contact resistance (ICR) and gas diffusion layer (GDL) face permeability effect on temperature profiles to enhance mass transport and cell performance of PEMFC. The streamlined block structures of flow channels considering ICR and GDL face permeability were comparatively evaluated. The results show that the temperature profiles exhibit a distinctive "Ʌ" shape with an approximate increase of 0.19ᵒC at CN 2 compared to CN1. Besides, CN6 has current density, power density, and the best removal water saturation of 6.94%, 12.27%, and 7.18%, respectively, are higher than CN1 (conventional model) when the voltage is 0.4 V. Consequently, the streamlined imitated water-drop block (WDB) models applied in the flow channels with considering both suitable ICR and GDL face permeability for PEM fuel cell can improve the mass transport capacity, enhance the speed of the electrochemical reaction, and provide better cell performance.

Study on Flow Pattern Transition of Cuttings Transport in Extended-Reach Drilling

Inadequate hole cleaning is one of the major challenges in extended-reach drilling, especially prominent in large-sized hole sections, such as 121/4-in. section. As the drilling parameters including flow rate, ROP and rotational speed change, the cuttings flow pattern converts between fully suspended flow, two-layer flow, and three-layer flow. However, most existing cuttings transport models only study the problem of cuttings transport under a certain flow pattern and do not consider the dynamic conversion of different cuttings flow patterns. Pipe rotation plays a key role in cuttings transport in rotary drilling, but the existing studies have not fully revealed the effect of pipe rotation on the conversion of cuttings transport patterns. In this paper, a stirring diffusion factor is presented to quantify the effect of pipe rotation on cuttings transport, and the mathematical expression of the stirring diffusion factor is obtained through numerical simulations and the nonlinear regression method. Secondly, the critical conditions for the conversion of cuttings flow patterns are obtained by combining mechanical analysis and numerical simulation results, clarifying the applicable scope of different cuttings flow patterns. According to the comparison with experimental results, the prediction error of the new model considering the conversion of cuttings flow patterns is not higher than 11.1%, and the minimum prediction error is only 3.07%. Thirdly, the flow pattern maps for cuttings transport under different drilling parameters are drawn to provide guidance for the identification of cuttings transport pattern and optimization of drilling parameters. Finally, the flow pattern maps are applied to a case study of an extended-reach drilling. The results show that there is a delay effect in the conversion of cuttings flow patterns due to the nonlinear characteristics of annular geometry. Furthermore, the effects of flow rate, ROP and rotational speed on cuttings transport patterns are not independent, but mutually reinforcing and constraining each other. Inappropriate selection of drilling parameters will result in three-layer flow of cuttings transport, and then pipe sticking is likely to occur. The cuttings transport pattern can be converted from three-layer flow to two-layer flow by optimizing drilling parameters, which can significantly improve the hole cleaning effect.

Ant colony optimization using two-dimensional pheromone for single-objective transport problems

One of the acclaimed algorithms that is used to solve combinatorial graph problems is ant colony optimization (ACO). In this article, we focus on a novel extended model of the pheromone that is responsible for storing collective knowledge. The presented two-dimensional pheromone is able to accommodate more information that is extracted from feasible solutions that can be used to improve the search of a solution space. The idea is positively evaluated on TSP and VRP problems, achieving better results as compared to the original algorithm. Since it is a universal concept, it can be applied to any single-objective problem that is solvable by ACO.

Parallel ensemble Kalman method with total variation regularization for large-scale field inversion

Field inversion is often encountered in data-driven computational modeling to infer latent spatial–varying parameters from available observations. The ensemble Kalman method is emerging as a useful tool for solving field inversion problems due to its derivative-free merits. However, the method is computationally prohibitive for large-scale field inversion with high-dimensional observation data, which necessitates developing a practical efficient implementation strategy. In this work, we propose a parallel implementation of the ensemble Kalman method with total variation regularization for large-scale field inversion problems. It is achieved by partitioning the computational domain into non-overlapping subdomains and performing local ensemble Kalman updates at each subdomain parallelly. In doing so, the computational complexity of the ensemble-based inversion method is significantly reduced to the level of local subdomains. Further, the total variation regularization is employed to smoothen the physical field over the entire domain, which can reduce the inference discrepancy caused by missing covariances near subdomain interfaces. The capability of the proposed method is demonstrated in three field inversion problems with increasing complexity, i.e., the diffusion problem, the scalar transport problem and the Reynolds averaged Navier-Stokes closure problem. The numerical results show that the proposed method can significantly improve computational efficiency with satisfactory inference accuracy.

Optimal Transport Approaches for Cloud Fusion in 3D Reconstruction

Cloud fusion plays a crucial role in achieving accurate 3D models. This paper introduces two optimal transport-based approaches, Gaussian Fusion and Cyclical Fusion, to showcase the effectiveness of optimal transport in establishing dense correspondence among incoming 3D point clouds. These approaches encompass several important components. Firstly, the fusion correspondences are derived from the optimal transport problem. The core principle of Gaussian Fusion and Cyclical Fusion involves manipulating points along geodesic curves to effectively leverage significant local geometric information. Secondly, this paper explores the fundamental concepts underlying Gaussian Fusion (displacement interpolation) and Cyclical Fusion (cyclical monotonicity), which greatly enhance the accuracy and completeness of the reconstruction process. And provides evidence for the uniqueness of displacement interpolation as geodesics on L2-Wasserstein space and the rationality of cyclical monotonicity in this context. Finally, the proposed approaches excel in capturing intricate surface details, particularly on small objects, when compared to the original fusion scheme which often introduces severe artifacts.

Identification of transport and technological problems in the grain product subcomplex

Identification of transport and technological problems in the grain product subcomplex

Uncertainty Benchmarks for Time-Dependent Transport Problems

Verification solutions for uncertainty quantification (UQ) are presented for time-dependent transport problems where , the scattering ratio, is uncertain. The method of polynomial chaos expansions is employed for quick and accurate calculation of the quantities of interest (QoIs), and uncollided solutions are used to treat part of the uncertainty calculation analytically. We find that approximately six moments in the polynomial expansion are required to represent the solutions to these problems accurately. Additionally, the results show that if the uncertainty interval spans c = 1, which means it is uncertain whether the system is multiplying or not, the confidence interval will grow in time. Finally, since the QoI is a strictly increasing function, the percentile values are known and can be used to verify the accuracy of the expansion. These results can be used to test UQ methods for time-dependent transport problems.

Methods and Techniques Supporting Energy and Media Savings in Maintenance of Public Transport Buses—State of the Art and Recommendations

In the article, the authors discussed the topic of energy and media savings in a public transport company. The article is of a review nature, referring to 100 sources, including scientific papers, books, conference proceedings, and websites. In the first part, a detailed literature review on environmental protection problems in road transport and methods of solving them was conducted. Subsequently, the authors reviewed the literature content on maintenance as a pro-environmental activity in transport companies. The great accent was paid to the problem of saving energy and media in the maintenance of public transport buses. Based on the literature and knowledge, the authors proposed the possibilities of conducting a rational method of managing the operation and maintenance of buses from the point of view of environmental protection, based on the strategy of predictive bus maintenance.

Migration of confined micro-swimmers subject to anisotropic diffusion

Shear-induced migration of elongated micro-swimmers exhibiting anisotropic Brownian diffusion at a population scale is investigated analytically in this work. We analyse the steady motion of confined ellipsoidal micro-swimmers subject to coupled diffusion in a general setting within a continuum homogenisation framework, as an extension of existing studies on macro-transport processes, by allowing for the direct coupling of convection and diffusion in local and global spaces. The analytical solutions are validated successfully by comparison with numerical results from Monte Carlo simulations. Subsequently, we demonstrate from the probability perspective that symmetric actuation does not yield net vertical polarisation in a horizontal flow, unless non-spherical shapes, external fields or direct coupling effects are harnessed to generate steady locomotion. Coupled diffusivities modify remarkably the drift velocity and vertical migration of motile micro-swimmers exposed to fluid shear. The interplay between stochastic swimming and preferential alignment could explain the diverse concentration and orientation distributions, including rheological formations of depletion layers, centreline focusing and surface accumulation. Results of the analytical study shed light on unravelling peculiar self-propulsion strategies and dispersion dynamics in active-matter systems, with implications for various transport problems arising from the fluctuating shape, size and other external or inter-particle interactions of swimmers in confined environments.

МАТЕМАТИЧНЕ МОДЕЛЮВАННЯ ПРОСТОРОВИХ КОЛИВАНЬ РУХОМОГО СКЛАДУ ЗАЛІЗНИЦЬ

The development of railway transport is accompanied by the introduction of innovative equipment and modern information technologies. The creation of railway rolling stock and rail machinery requires an assessment of their strength and dynamic qualities even at the stage of design and experimental production, therefore, the development of specialized software for evaluating the main parameters of the rolling stock structures being created is an urgent scientific and applied problem for railway transport and transport engineering. Theoretical studies of spatial fluctuations of certain types of railway rolling stock were performed and recommendations were obtained for the formation of parameters of the structures of freight cars and special rolling stock. When conducting theoretical research, the author's DYNRAIL-PRO software complex was used, which was verified and the reliability of the calculation results was proven.

Upscaling reactive transport models from pore-scale to continuum-scale using deep learning method

Reactive transport modeling of subsurface environments plays an important role in addressing critical problems of geochemical processes, such as dissolution and precipitation of minerals. Current transport models for porous media span various scales, ranging from pore-scale to continuum-scale. In this study, we established an upscaling method connecting pore-scale and continuum-scale models by employing a deep learning methodology of Convolutional Neural Networks (CNNs). We applied Darcy-Brinkmann-Stokes (DBS) method to simulate the fluid flow and reactive transport in pore-scale models, which would act as constituents of a continuum-scale model. The datasets of spatial pore distribution of subvolume samples were used as the input for the deep learning model, and the continuum (Darcy)-scale parameters such as permeability, effective surface area, and effective diffusion coefficient were figured out as outputs (i.e., labels). By applying the trained models of the subvolumes in the entire sample volume, we generated the initial field of porosity, permeability, effective diffusion coefficient, and effective surface area for continuum-scale simulation of a mineral dissolution problem. We took an acid dissolution case as an example to utilize the outcomes of trained deep learning models as input data in the continuum-scale simulation. This work presents a comprehensive upscaling workflow, as bridging the findings of microscale simulations to the continuum-scale simulations of a reactive transport problem.

IOT Based Smart Bus Transportation

The developed IoT-based smart bus health monitor- ing system is expected to bring back the neat service and safety of public transportation at the rate of modern technology that will keep the track of information regarding bus condition. ITS (Intelligent transport systems) are comprised of sensor technolo- gies and communication systems that connect on-board terminal, the vehicular systems, and ’fixed location systems. This modus operandi of ICT (f information and communication technologies ) also encompasses problems of rail, air, and water transport apart from road transport. IoT can be used to support the betterment of public transportation; hence, the transportation systems can become more receptive and more efficient. This entails the live tracking, amount analysis, and user friendly interfaces which helps the commuter to have trustworthy information along with a superior transportation experience. Index Terms—Telemetry, Emergency alarm, mpu6050,GPS sen- sor , Accelerometer, RFID card, Load sensor.

Kinetic cooperativity resolves bidirectional clogging within the nuclear pore complex

As the main gatekeeper of the nucleocytoplasmic transport in eukaryotic cells, the nuclear pore complex (NPC) faces the daunting task of facilitating the bidirectional transport of a high volume of macromolecular cargoes while ensuring the selectivity, speed, and efficiency of this process. The competition between opposing nuclear import and export fluxes passing through the same channel is expected to pose a major challenge to transport efficiency. It has been suggested that phase separation-like radial segregation of import and export fluxes within the assembly of intrinsically disordered proteins that line the NPC pore could be a mechanism for ensuring efficient bidirectional transport. We examine the impact of radial segregation on the efficiency of bidirectional transport through the NPC using a coarse-grained computational model of the NPC. We find little evidence that radial segregation improves transport efficiency. By contrast, surprisingly, we find that NTR crowding may enhance rather than impair the efficiency of bidirectional transport although it decreases the available space in the pore. We identify mechanisms of this novel crowding-induced transport cooperativity through the self-regulation of cargo density and flux in the pore. These findings explain how the functional architecture of the NPC resolves the problem of efficient bidirectional transport, and provide inspiration for the alleviation of clogging in artificial selective nanopores.

Prevalence and factors associated with uptake of pre-exposure prophylaxis amongst women vulnerable to HIV who received HIV antibodies in Antibody Mediated Prevention HVTN703/HPTN081 trial in Harare, Zimbabwe: a cross-sectional study

IntroductionThere is limited evidence on pre-exposure prophylaxis (PrEP) uptake post-trial participation for women vulnerable to HIV. This study investigates the prevalence and factors associated with PrEP uptake post-participation in an...

Large Péclet number forced convection from a circular wire in a uniform stream: hybrid approximations at small Reynolds numbers

Abstract We consider heat or mass transport from a circular cylinder under a uniform crossflow at small Reynolds numbers, $\mathrm{Re}\ll 1$ . This problem has been thwarted in the past by limitations inherent in the classical analyses of the singular flow problem, which have used asymptotic expansions in inverse powers of $\log \mathrm{Re}$ . We here make use of the hybrid approximation of Kropinski, Ward & Keller [(1995) SIAM J. Appl. Math.55, 1484], based upon a robust asymptotic expansion in powers of $\mathrm{Re}$ . In that approximation, the “inner” streamfunction is provided by the product of a pre-factor $S$ , a slowly varying function of $\mathrm{Re}$ , with a $\mathrm{Re}$ -independent “canonical” solution of a simple mathematical form. The pre-factor, in turn, is determined as an implicit function of $\log \mathrm{Re}$ via asymptotic matching with a numerical solution of the nonlinear single-scaled “outer” problem, where the cylinder appears as a point singularity. We exploit the hybrid approximation to analyse the transport problem in the limit of large Péclet number, $\mathrm{Pe}\gg 1$ . In that limit, transport is restricted to a narrow boundary layer about the cylinder surface – a province contained within the inner region of the flow problem. With $S$ appearing as a parameter, a similarity solution is readily constructed for the boundary-layer problem. It provides the Nusselt number as $0.5799(S\,\mathrm{Pe})^{1/3}$ . This asymptotic prediction is in remarkably close agreement with that of the numerical solution of the exact problem [Dennis, Hudson & Smith (1968) Phys. Fluids11, 933] even for moderate $\mathrm{Re}$ -values.

On the convergence of discrete dynamic unbalanced transport models

A generalized unbalanced optimal transport distance WBΛ on matrix-valued measures) was defined in [44] a` la Benamou-Brenier, which extends the Kantorovich-Bures and the Wasserstein-Fisher-Rao distances. In this work, we investigate the convergence properties of the discrete transport problems associated with WBΛ. We first present a convergence framework for abstract discretization. Then, we propose a specific discretization scheme that aligns with this framework, whose convergence relies on the assumption that the initial and final distributions are absolutely continuous with respect to the Lebesgue measure. Further, in the case of the Wasserstein-Fisher-Rao distance, thanks to the static formulation, we show that such an assumption can be removed.