Transport Modeling System Research Articles

Modeling study of dredging induced sediment plume transport in Hamilton Harbour

To assess and predict the direction and range of a dredging induced contaminated sediment plume on the surrounding environment, a three-dimensional hydrodynamic and mud transport modeling system MIKE 3-FM was used in the Randle Reef area of Hamilton Harbour. Simulations were carried out with the typical local and maximum winds under which the dredging operation would proceed. The dredge plume travel pattern and range in both horizontal and vertical planes are examined under various wind conditions and model mesh resolutions. It was found that the simulated plume extents were very sensitive to transport model mesh resolution due to the additional numerical advection induced in the calculations. Detailed discussion of this particular issue has not been observed in other publications. The results of this simulation provide useful information for remediation project managers in planning and guiding the environmental monitoring of dredging operations. In addition, the methodology used in this study can be adapted to other dredging projects.

Lateral Circulation and Associated Sediment Transport in a Convergent Estuary

AbstractThe Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system was used to explore lateral circulation and associated sediment transport in a convergent estuary with existence of channel and shoals. The lateral momentum balance was found to be largely geostrophic with a barotropic pressure gradient balanced by a baroclinic pressure gradient and Coriolis forcing during most time of a tidal cycle, except at the maximum ebb/flood. At the east side (right side looking landward), due to estuarine convergence, barotropic forcing strongly modulates lateral momentum balance and generates eastward residual sediment transport during spring tides. But during neap tides, the enhanced lateral density gradient induces strong lateral baroclinic forcing to cause westward residual sediment flux. At the west side, baroclinic forcing strongly influences the lateral momentum balance and generates westward sediment transport. Together, lateral circulation tends to distribute sediment from the channel to both the side shoals during spring tides but generates westward sediment flux during neap tides. The diagnostic analysis of the lateral gradient of suspended sediment concentration (SSC) demonstrates that lateral sediment trapping is strongly influenced by the lateral circulation and the lateral asymmetry in bed erosion during spring tides, whereas lateral advection becomes the controlling factor during neap tides. Mechanisms for the lateral circulation and sediment transport can be extended to other convergent estuaries.

Operational strategy of customized bus considering customers’ variety seeking behavior and service level

In recent years, customized bus (CB) is becoming an innovative model of the public transport system (PTS) in China. This service provides an advanced, timely, personalized, and flexible responses to the demand of the PTS, especially of commuters. Obviously, it could have an impact on public transport (PT) service. For instance, CB services influence the customers' variety-seeking behavior, which results in changes of customer options in different periods. Therefore, customers could be divided into different groups of preference. In this paper, we construct a two-period Hotelling game model by variety-seeking behavior and service level. The results show that, in the first stage, the departure frequency of CB and PT is influenced by variety-seeking behavior and service level. In the second stage, departure frequency is influenced by service level only. Next, although the departure frequency of bus impacts the changes of passenger ratios in different stages, service level appreciably impacts passenger number. From customer surplus and social welfare, we find that adjustment of service level can increase social welfare, which means that CB and PT will reach an optimum effect. The present work can provide a valuable reference to policymakers, practitioners, and others.

Equations of State in Mathematical Models of Natural Gas Production and Transportation Systems

For the Redlich–Kwong equation of state of real gas, which is widely used for description of behavior of hydrocarbon mixtures, the inversion curve, which determines the change in the throttling coefficient sign, is constructed. The reduced pressure and temperature variation ranges correspond to the characteristic values in natural gas production and transportation systems.

Contributions of traffic and shipping emissions to city-scale NOx and PM2.5 exposure in Hamburg

Abstract We investigated the contribution of road traffic and shipping related emissions of NO2 and PM2.5 to total air quality and annual mean population exposure in Hamburg 2012. For this purpose, we compiled a detailed emission inventory following SNAP categories focusing on the detailed representations of road traffic and shipping emissions. The emission inventory was applied to a global-to-local Chemistry Transport Model (CTM) system to simulate hourly NO2 and PM2.5 concentrations with a horizontal grid resolution of 500 m. To simulate urban-scale pollutant concentrations we used the coupled prognostic meteorological and chemistry transport model TAPM. The comparison of modelled to measured hourly values gives high correlation and small bias at urban and background stations but large underestimations of NO2 and PM2.5 at measurements stations near roads. Simulated contributions of road traffic emissions to annual mean concentrations of NO2 and PM2.5 is highest close to highways with relative contributions of 50% for NO2 and 40% for PM2.5. Nevertheless, the urban domain is widely affected by road traffic, especially in the city centre. Shipping impact focuses on the port and nearby industrial areas with contributions of up to 60% for NO2 and 40% for PM2.5. In residential areas in the north of the port, shipping contributes with up to 20–30% for NO2 and PM2.5. Our simulation resulted in 14% of the population of Hamburg being exposed to hourly NO2 concentration above the hourly limit of 200 μg/m³,

Literature Review on the Rail Transport Schedule Robustness

Abstract The article presents issues concerning rail transport (rail, metro and tramway) and factors influencing the planned implementation of the schedule. At the beginning, the scope of application of the robustness concept was analysed, based on scientific and industry literature. Then the attention was focused on the model of the rail transport system and the schedule, the basic indicator of robustness assessment was discussed, taking into account the methods of analysis used and many variables occurring in rail transport. Finally, a review of the state of knowledge is summarised and the most important observations from the analysis are indicated. In the case of a robust schedule there is no propagation of disruption across the network after an adverse event has occurred.

About passenger travels demand modeling in urban transportation systems

In this paper, the basic concepts of modeling of urban transport systems are analyzed. The known variants of the definition of the concept of the transport system, its main components and the essence of the stages of identification of transport systems (TS) are presented. The example of the Lviv city TS shows the process of modeling the transport network, determining the time characteristics of the modeled transport system and forming a demand matrix for trips of a certain type in a certain segment of users (origin-destination matrix when moving students from their places of compact residence to the nodes of external transport for further implementation of intercity travel). The obtained indicators can be further applied in determining the demand for transportation in transport systems of large cities.

Design and implementation path of intelligent transportation information system based on artificial intelligence technology

By using the concept, guiding ideology and design idea of artificial intelligence (AI) and Internet of Thing, this study puts forward the logistics intelligent transportation system (ITS) model, structure design and function design based on AI, focusing on the time value and information value of the intelligent logistics information system. The results show that the design of ITS model based on AI includes three modules: input, transformation and output of ITS. The ITS supply chain management platform and function design of freight vehicles with AI is feasible and prospective. The application of AI technology in ITS has great value and development prospect.

Seasonal Arctic Sea Ice Prediction Using a Newly Developed Fully Coupled Regional Model With the Assimilation of Satellite Sea Ice Observations

AbstractTo increase our capability to predict Arctic sea ice and climate, we have developed a coupled atmosphere‐sea ice‐ocean model configured for the pan‐Arctic with sufficient flexibility. The Los Alamos Sea Ice Model is coupled with the Weather Research and Forecasting Model and the Regional Ocean Modeling System in the Coupled Ocean‐Atmosphere‐Wave‐Sediment Transport modeling system. It is well known that dynamic models used to predict Arctic sea ice at short‐term periods strongly depend on model initial conditions. Parallel Data Assimilation Framework is implemented into the new modeling system to assimilate sea ice observations and generate skillful model initialization, which aid in the prediction procedures. The Special Sensor Microwave Imager/Sounder sea ice concentration, the CyroSat‐2, and Soil Moisture and Ocean Salinity sea ice thickness are assimilated with the localized error subspace transform ensemble Kalman filter. We conduct Arctic sea ice prediction for the melting seasons of 2017 and 2018. Predictions with improved initial sea ice conditions show reasonable sea ice evolution and small biases in the minimum sea ice extent, although the ice refreezing is delayed. Our prediction experiments suggest that the use of appropriate uncertainty for the observed sea ice thickness can lead to improved spatial distribution of the initial ice thickness and thus the predicted sea ice distribution. Our new modeling system initialized by the output of the National Centers for Environmental Prediction Climate Forecast System seasonal forecasts with data assimilation can significantly increase the sea ice prediction skills in sea ice extent for the entire Arctic as well as in the Northern Sea Route compared with the predictions by the National Centers for Environmental Prediction Climate Forecast System.

Neural model of conveyor type transport system

Neural model of conveyor type transport system

A Collaborative Approach for an Integrated Modeling of Urban Air Transportation Systems

The current push in automation, communication, and electrical energy storage technologies has the potential to lift urban mobility into the sky. As several urban air mobility (UAM) concepts are conceivable, all relevant physical effects as well as mutual interrelations of the UAM system have to be addressed and evaluated at a sufficient level of fidelity before implementation. Therefore, a collaborative system of systems modeling approach for UAM is presented. To quickly identify physical effects and cross-disciplinary influences of UAM, a pool of low-fidelity physical analysis components is developed and integrated into the Remote Component Environment (RCE) workflow engine. This includes, i. a., the disciplines of demand forecast, trajectory, vertiport, and cost modeling as well as air traffic flow and capacity management. The definition and clarification of technical interfaces require intensive cooperation between specialists with different areas of expertise. To reduce this communication effort, the Common Parametric Aircraft Configuration Schema (CPACS) is adapted and used as central data exchange format. The UAM system module is initially applied for a 24-hour simulation of three generic networks in Hamburg City. After understanding the basic system-level behavior, higher level analysis components and feedback loops must be integrated in the UAM system module for evaluation and optimization of explicit operating concepts.

Modeling of Transport and Logistics Systems and the Study of the Structural Stability

The structural stability of the system to external influences is an important parameter of the transport and logistics task. In modern literature, the concept of structural stability is defined as applied to each individual problem, as a result of which there are difficulties in applying the developed methods to new problems. The paper describes assessing the stability of the functioning of transport and logistics systems. The methodological base of the research includes the theory of optimal control and multicriteria optimization; elements of graph theory are used as modeling tools, as well as numerical analysis to evaluate stability coefficients. A list of actions on the system in the form of elementary events over graphs, including their superposition, is proposed. There was proposed the concept of structural destruction of a graph that implies a partition of the graph into disconnected components. The formulation of the combined transport and logistics problem — the search for flows and routes. The authors propose an efficiency coefficient for comparing the obtained solutions, as well as a stability coefficient for assessing the influence of structural changes in the graph on the solution of the problem. A computer simulation of structural destruction on test data sets was carried out. As a result of experiments series, the distribution of a special coefficient for elementary fracture processes was established, as well as an interval of permissible values corresponding to a stable state of the system. The theoretical significance of the study lies in the possibility of using the results obtained at the stage of designing transport and logistics networks. From a practical point of view, the proposed tools can be used to assess the stability of the functioning of existing transport and logistics systems.

Predictive Modeling of Transportation Systems in Jiuzhai Valley World Heritage Site, China

Tourist congestion is a significant issue in Jiuzhai Valley World Heritage Site (JVWH). The “demand-driven” approach of alternative transportation system (ATS) has led to the issues related to visitor crowding, visitor safety, and visitor experience quality. JVWH requires a more efficient approach to achieve a suitable tourist distribution while preserving the quality of visitors’ experiences. Accordingly, this study examines descriptive data, which are collected in 2015 regarding visitor use of the ATS in JVWH to spatially model current and future distribution scenarios. Researchers developed four theoretical scenarios by using the computational model which imitate the current ATS system. Imitation results indicate Scenarios 3 and 4, which adjust spot combination and tourist duration are the two most effective methods for balancing tourist distribution, and are, therefore, the most effectively ways to optimize the current ATS system. This research provides a glimpse into potential management strategies for the tourist distribution of JVWH and possibly other parks in China.

An Integrated Algorithm for Intersection Queue Length Estimation Based on IoT in a Mixed Traffic Scenario

Nowadays, traffic infrastructures and vehicles are connected through the network benefiting from the development of Internet of Things (IoT). Connected automated cars can provide some useful traffic information. An architecture and algorithm of mobile service computing are proposed for traffic state sensing by integration between IoT and transport system models (TSMs). The formation process of queue at this intersection is analyzed based on the state information of connected vehicles and the velocity of shockwave is calculated to predict queue length. The computing results can be delivered to the traffic information edge server. However, not all the vehicles are capable of connecting to the network and will affect the queue length estimation accuracy. At the same time, traffic cameras transmit the traffic image to the edge server and a deep neuron network (DNN) is constructed on the edge server to tackle the traffic image. It can recognize and classify the vehicles in the image but takes several seconds to work with the complex DNN. At last, the final queue length is determined according to the weight of the two computing results. The integrated result is delivered to the traffic light controller and traffic monitoring center cloud. It reveals that the estimation from DNN can compensate the estimation from shockwave when the penetration rate of connected vehicles is low. A testbed is built based on VISSIM, and the evaluation results demonstrate the availability and accuracy of the integrated queue length estimation algorithm.

The Concept of a Sustainable Urban Transport System Model for Developing Countries on the Example of Lagos

Abstract The subject of the article is the concept of a sustainable urban transport system model for developing countries on the example of Lagos in Nigeria. The city of Lagos is the largest and most populated city in Africa. Nowadays, the state of Lagos is facing many challenges, and the problem of urban transport is becoming more and more important due to the increase in the number of inhabitants and the size of the city. Significant problems were identified in the urban transport system in the Lagos state, and conceptual solutions were proposed taking into account the approach of sustainable development.

The role of geothermal resources in sustainable power system planning in Iceland

The aim of this paper was to understand the relevance of accounting for geothermal resource dynamics for sustainable energy system planning in Iceland. This included assessing the implications of transition to electric vehicles as a decarbonisation strategy in Iceland. Therefore, the energy and transport system model (UniSyD_IS) was linked to a geothermal resource dynamics model. This allowed to capture the effects of geothermal resource utilization for electricity production on a national energy systems level. A total of 16 different scenarios that vary in the rate of economic growth, conditions for electric vehicles and consideration of geothermal resource dynamics were analysed in relation to production patterns, cost, resource availability and emissions. Incorporating geothermal resource dynamics allows to provide more holistic insights for sustainable energy system planning in Iceland, especially regarding the availability of geothermal resources and production cost.

Axial Wind Effects on Stratification and Longitudinal Sediment Transport in a Convergent Estuary During Wet Season

AbstractThe Coupled Ocean‐Atmosphere‐Wave‐Sediment Transport (COAWST) modeling system was used to examine axial wind effects on vertical stratification and sediment transport in a convergent estuary. The model demonstrated that stratification dynamics in the upper estuary (Kelvin number <1; ) are dominated by longitudinal wind straining, whereas the dominant mechanism governing estuarine stratification in the lower estuary (Kelvin number ~1) is lateral wind straining. Barotropic advection contributes to seaward sediment transport and peaks during spring tides, whereas estuarine circulation causes landward sediment transport with a maximum during neap tides. Down‐estuary winds impose no obvious effects on longitudinal sediment flux, whereas up‐estuary winds contribute to enhanced seaward sediment flux by increasing the tidal oscillatory flux. The model also demonstrates that bottom friction is significantly influenced by vertical stratification over channel regions, which is indirectly affected by axial winds.

The sustainable future of open-pit trucks operation

Open-pit truck technical operation determines mined bulk transportation effectiveness increasing equipment’s commercial operation duration based on a robust strategy of vehicle’s maintenance, early and high-quality diagnostics, upkeep and recovery. Developed mathematical model of BelAZ open-pit truck operation for various levels of organization of servicing replicates a Markov process in the system of technological automotive transport considering possibilities of vehicle states with time and steady-state condition. The performance of open-pit trucks was consistently evaluated and the model of the technological automotive transport system was synthesized. The validation analysis of the obtained model showed its suitability for optimization of open-pit truck performance. The calculated optimal controlling actions on the open-pit truck allow developing an algorithm and technique for dynamic adjustment of parameters of maintenance, diagnostics and repair of BELAZ open-pit trucks that will become the basis for a sustainable future of industrial transport technical operation.

Optimization of production and transport infrastructure based on cluster analysis methods

In order to solve the problems of optimizing production and transportation systems, a clustering procedure for objects is suggested. The procedure is a universal methodology for dividing a set of objects into subsets with their centers possessing optimal properties. At the same time, the use of point proximity metrics used in cluster analysis models the minimization of distances during transportation. If the volume of produced/extracted containerisable products of a production point is considered as the “weight” of each point, than the problem of minimizing transportation costs can be solved as a problem of optimizing clusters and their centers. A set of analytical models has been developed to describe and optimize the choice of location and number of container terminals (CT) at the first level and container storage and distribution centers (СSDC) at the second level of a two-level terminal model and logistics infrastructure of the container transport system (CTS). New clustering algorithms are suggested to determine the locations of CT and СSDC based on the condition of minimizing transportation costs and creating a terminal and logistics infrastructure, taking into account given or random number of clusters.

Neural model of conveyor type transport system

In this paper, a model of a transport conveyor system using a neural network is demonstrated. The analysis of the main parameters of modern conveyor systems is presented. The main models of the conveyor section, which are used for the design of control systems for flow parameters, are considered. The necessity of using neural networks in the design of conveyor transport control systems is substantiated. A review of conveyor models using a neural network is performed. The conditions of applicability of models using neural networks to describe conveyor systems are determined. A comparative analysis of the analytical model of the conveyor section and the model using the neural network is performed. The technique of forming a set of test data for the process of training a neural network is presented. The foundation for the formation of test data for learning neural network is an analytical model of the conveyor section. Using an analytical model allowed us to form a set of test data for transient dynamic modes of functioning of the transport system. The transport system is presented in the form of a directed graph without cycles. Analysis of the model using a neural network showed a high-quality relationship between the output flow for different conveyor sections of the transport system