Topic Editors

Prof. Dr. Tomasz Nowakowski
Department of Technical Systems Operation and Maintenance, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland
Department of Technical Systems Operation and Maintenance, Wroclaw University of Science and Technology, 27 Wyb. Wyspianskiego Str., 50-370 Wroclaw, Poland
Faculty of Mechanical Engineering, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland
Dr. Franciszek Restel
Department of Technical Systems Operation and Maintenance, Wroclaw University of Science and Technology, 27 Wyb. Wyspianskiego Str., 50-370 Wroclaw, Poland
Department of Technical Systems Operation and Maintenance, Wroclaw University of Science and Technology, 27 Wyb. Wyspianskiego Str., 50-370 Wroclaw, Poland
Dr. Anna Jodejko-Pietruczuk
Department of Technical Systems Operation and Maintenance, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland
Department of Technical Systems Operation, Wrocław University of Science and Technology, Wroclaw, Poland

New Technological Solutions, Research Methods, Simulation and Analytical Models That Support the Development of Modern Transport Systems

Abstract submission deadline
closed (31 May 2024)
Manuscript submission deadline
closed (30 August 2024)
Viewed by
72653

Topic Information

Dear Colleagues,

The sustainable development of transport systems (including eco-mobility) and information technology have generated an increasing demand for scientific research to support managerial and engineering decisions linked to improving current transport systems and processes. For this reason, research studies with results that can be implemented in real transport systems are becoming increasingly valuable. The development of cyber-physical systems provides an increasing amount of data which require complex models and methods, developed by the scientific community, to be analyzed and correctly interpreted. On the other hand, technology supports science, in terms of the analytical tools used and the methods of improving professional competencies.

The issue aims to present new technological solutions, research methods, and analytical models that support the development of modern transport systems (considering the requirements of passengers, freight, and urban transport). All modes of transport are undergoing fundamental technological, organizational, and infrastructural changes. For this reason, this issue is also focused on presenting new approaches to the ongoing changes and solutions regarding the functioning of transport systems. The key aspect here is the development of methods for building the resistance of transport systems to withstand emerging disturbances and threats. All methods and approaches are welcome, including reliability and risk assessment, as well as analytical and simulation modeling.

Prof. Dr. Tomasz Nowakowski
Prof. Dr. Artur Kierzkowski
Dr. Agnieszka A. Tubis
Dr. Franciszek Restel
Dr. Tomasz Kisiel
Dr. Anna Jodejko-Pietruczuk
Dr. Mateusz Zając
Topic Editors

Keywords

  • critical infrastructure
  • transportation system analysis, modeling, and simulation
  • resilience of transport systems
  • resilience and risk assessment
  • monitoring of transport infrastructure
  • transportation system risk and protection
  • energy efficient transport solutions
  • sustainable development of transport
  • digitization and its use in the operation of transport systems
  • transport in a smart city
  • development of urban transport
  • virtual and augmented reality in improving the competencies of employees employed in transport systems

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Sciences
applsci
2.5 5.3 2011 17.8 Days CHF 2400
Drones
drones
4.4 5.6 2017 21.7 Days CHF 2600
Energies
energies
3.0 6.2 2008 17.5 Days CHF 2600
Infrastructures
infrastructures
2.7 5.2 2016 16.8 Days CHF 1800
Logistics
logistics
3.6 6.6 2017 29.7 Days CHF 1400
Modelling
modelling
1.3 2.7 2020 21.2 Days CHF 1000

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Published Papers (36 papers)

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23 pages, 9098 KiB  
Article
An Interdisciplinary Double-Diamond Design Thinking Model for Urban Transport Product Innovation: A Design Framework for Innovation Combining Mixed Methods for Developing the Electric Microvehicle “Leonardo Project”
by Sara Viviani, Michelangelo-Santo Gulino, Alessandra Rinaldi and Dario Vangi
Energies 2024, 17(23), 5918; https://doi.org/10.3390/en17235918 - 25 Nov 2024
Viewed by 371
Abstract
The increase in greenhouse gas emissions prompts the transport sector towards new technological perspectives on personal mobility. Addressing sustainable mobility through electric micromobility requires interdisciplinary design research methods and approaches. In the context of the LEONARDO project, funded under the Horizon 2020 framework, [...] Read more.
The increase in greenhouse gas emissions prompts the transport sector towards new technological perspectives on personal mobility. Addressing sustainable mobility through electric micromobility requires interdisciplinary design research methods and approaches. In the context of the LEONARDO project, funded under the Horizon 2020 framework, this paper addresses a critical literature review on the design thinking, design research models, tools, and mixed methods to be undertaken for driving product mobility innovation in a cross-disciplinary context. Following the “research through design” research strategy, the authors applied the Double-Diamond design thinking model to frame the design research process in four phases, aligning with three overarching objectives, four specific research objectives, and 24 research tasks, supported by a total of 71 mixed methods and tools. As a result, the transdisciplinary process provides a co-designed energy-efficient stand-alone microvehicle and a scalable interdisciplinary design model for urban transport product innovation. In conclusion, this case study suggests the value of the Double-Diamond design thinking model as a design research instrument capable of addressing sustainable mobility and guiding interdisciplinary design research, design practice, and education in the industrial engineering and design disciplinary sectors. Full article
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25 pages, 4062 KiB  
Article
Formalizing Sustainable Urban Mobility Management: An Innovative Approach with Digital Twin and Integrated Modeling
by Andrea Grotto, Pau Fonseca i Casas, Alyona Zubaryeva and Wolfram Sparber
Logistics 2024, 8(4), 117; https://doi.org/10.3390/logistics8040117 - 11 Nov 2024
Viewed by 633
Abstract
Background: Urban mobility management faces growing challenges that require the analysis and optimization of sustainable solutions. Digital twins (DTs) have emerged as innovative tools for this assessment, but their implementation requires standardized procedures and languages; Methods: As part of a broader [...] Read more.
Background: Urban mobility management faces growing challenges that require the analysis and optimization of sustainable solutions. Digital twins (DTs) have emerged as innovative tools for this assessment, but their implementation requires standardized procedures and languages; Methods: As part of a broader methodology for continuous DT validation, this study focuses on the conceptual validation phase, presenting a conceptualization approach through formalization using Specification and Description Language (SDL), agnostic to simulation tools. The conceptual validation was achieved through stakeholder engagement in the Bolzano context, producing 41 SDL diagrams that define both elements common to different urban realities and specific local data collection procedures; Results: The feasibility of implementing this stakeholder-validated conceptualization was demonstrated using Simulation of Urban MObility (SUMO) for traffic simulation and optimization criteria calculation, and its framework SUMO Activity GenerAtion (SAGA) for generating an Activity-Based Modeling (ABM) mobility demand that can be improved through real sensor data; Conclusions: The SDL approach, through its graphical representation (SDL/GR), enables conceptual validation by enhancing stakeholder communication while defining a framework that, while adapting to the monitoring specificities of different urban realities, maintains a common and rigorous structure, independent of the chosen implementation tools and programming languages. Full article
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20 pages, 1686 KiB  
Article
Analysing the Influence of Augmented Reality on Organization Performance via Supply and Logistics Value Chain Functions: A Hybrid ANN-PLS Model Assessment in the Gulf Cooperation Council Region
by Ahmad Aburayya
Logistics 2024, 8(4), 110; https://doi.org/10.3390/logistics8040110 - 5 Nov 2024
Viewed by 466
Abstract
Background: Despite the resurgence of interest in augmented reality (AR) due to Industry 4.0 and its ability to resolve several challenges faced by current business models, comprehensive research examining the capabilities of AR in supply chain management (SCM) and logistics remains limited. [...] Read more.
Background: Despite the resurgence of interest in augmented reality (AR) due to Industry 4.0 and its ability to resolve several challenges faced by current business models, comprehensive research examining the capabilities of AR in supply chain management (SCM) and logistics remains limited. This article aims to investigate the potential effects of AR technology on organizational performance through the mediation role of SCM and logistics value chain functions to address the existing knowledge gap. Methods: This research employed a cross-sectional design and an explanatory survey as a deductive approach for hypothesis development. The primary data collection method involved the self-administration of a questionnaire to furniture suppliers located in the Gulf Cooperation Council (GCC), including six countries. Of the 656 questionnaires submitted to suppliers, 483 were considered usable, yielding a response rate of 73.6%. The research utilized partial least squares structural equation modelling (PLS-SEM) and artificial neural network (ANN) techniques to evaluate the gathered data. Results: The current paper’s statistical evidence demonstrates that AR implementation has a positive impact on the supply and logistics value chain activities and organizational performance of furniture suppliers in the GCC region. Moreover, it illustrates that the design and planning variable of supply chain value dominates as the primary predictor of organization performance. The results indicated that the ANN strategy provided a more comprehensive explanation of internally generated constructs compared to the PLS-SEM technique. Conclusions: This study demonstrates its usefulness by advising furniture industry decision-makers on what to avoid and what aspects to consider when creating plans and regulations. The report also suggests operations managers apply machine learning (ANN) for prediction and decision-making in supply and operations value chains. This essay looks at how the AR and resource-based supply value chain view may affect company performance across countries, firm sizes, and ages. Full article
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17 pages, 3747 KiB  
Article
A Large Bridge Traffic Operation Status Impact Assessment Model Based on AHP–Delphi–SVD Method
by Jianxing Guo, Yunrui Zhang, Guanhu Yuan, Yanbo Li, Longfei Wang and Zhi Dong
Appl. Sci. 2024, 14(20), 9327; https://doi.org/10.3390/app14209327 - 13 Oct 2024
Viewed by 570
Abstract
As an important component of road traffic facilities, bridges play a crucial role in daily traffic operations, and changes in their status can have an impact on traffic operation. The existing research mainly focuses on monitoring the status of bridges themselves or analyzing [...] Read more.
As an important component of road traffic facilities, bridges play a crucial role in daily traffic operations, and changes in their status can have an impact on traffic operation. The existing research mainly focuses on monitoring the status of bridges themselves or analyzing the operation status of road traffic, and rarely considers the changes in traffic operation status caused by changes in bridge status. Therefore, in order to evaluate the impact relationship between the two, this article designs an algorithm that combines the Analytic Hierarchy Process (AHP), the Delphi method, and Singular Value Decomposition (SVD) based on the traditional evaluation of bridges and road traffic operation status, and establishes a bridge traffic operation status impact assessment model. Then, simulation analysis and actual data verification will be conducted based on the specific situation of Ma’anshi Bridge on the Chongqing Wuhan Expressway. The experimental results show that the evaluation model established in this paper conforms to the characteristics of traffic operation, can reflect the impact of bridge state changes on traffic operation status well, effectively promote the automation level of bridge traffic impact management, and has high reliability and accuracy. Full article
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19 pages, 4032 KiB  
Article
An Algorithm for Predicting Vehicle Behavior in High-Speed Scenes Using Visual and Dynamic Graphical Neural Network Inference
by Menghao Li, Miao Liu, Weiwei Zhang, Wenfeng Guo, Enqing Chen, Chunguang Hu and Maomao Zhang
Appl. Sci. 2024, 14(19), 8873; https://doi.org/10.3390/app14198873 - 2 Oct 2024
Viewed by 624
Abstract
Accidents caused by vehicles changing lanes occur frequently on highways. Moreover, frequent lane changes can severely impact traffic flow during peak commuting hours and on busy roads. A novel framework based on a multi-relational graph convolutional network (MR-GCN) is herein proposed to address [...] Read more.
Accidents caused by vehicles changing lanes occur frequently on highways. Moreover, frequent lane changes can severely impact traffic flow during peak commuting hours and on busy roads. A novel framework based on a multi-relational graph convolutional network (MR-GCN) is herein proposed to address these challenges. First, a dynamic multilevel relational graph was designed to describe interactions between vehicles and road objects at different spatio-temporal granularities, with real-time updates to edge weights to enhance understanding of complex traffic scenarios. Second, an improved spatio-temporal interaction graph generation method was introduced, focusing on spatio-temporal variations and capturing complex interaction patterns to enhance prediction accuracy and adaptability. Finally, by integrating a dynamic multi-relational graph convolutional network (DMR-GCN) with dynamic scene sensing and interaction learning mechanisms, the framework enables real-time updates of complex vehicle relationships, thereby improving behavior prediction’s accuracy and real-time performance. Experimental validation on multiple benchmark datasets, including KITTI, Apollo, and Indian, showed that our algorithmic framework achieves significant performance improvements in vehicle behavior prediction tasks, with Map, Recall, and F1 scores reaching 90%, 88%, and 89%, respectively, outperforming existing algorithms. Additionally, the model achieved a Map of 91%, a Recall of 89%, and an F1 score of 90% under congested road conditions in a self-collected high-speed traffic scenario dataset, further demonstrating its robustness and adaptability in high-speed traffic conditions. These results show that the proposed model is highly practical and stable in real-world applications such as traffic control systems and self-driving vehicles, providing strong support for efficient vehicle behavior prediction. Full article
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22 pages, 3904 KiB  
Article
Integrating Null Controllability and Model-Based Safety Assessment for Enhanced Reliability in Drone Design
by Zahra Motahari Rad and Jonathan Liscouët
Modelling 2024, 5(3), 1009-1030; https://doi.org/10.3390/modelling5030053 - 23 Aug 2024
Viewed by 768
Abstract
The increasing use of drones for safety-critical applications, particularly beyond visual lines of sight and over densely populated areas, necessitates safer and more reliable designs. To address this need, this paper introduces a novel methodology integrating Null Controllability with the Model-Based Safety Assessment [...] Read more.
The increasing use of drones for safety-critical applications, particularly beyond visual lines of sight and over densely populated areas, necessitates safer and more reliable designs. To address this need, this paper introduces a novel methodology integrating Null Controllability with the Model-Based Safety Assessment (MBSA) framework AltaRica 3.0 to optimize propulsor configurations and system architectures. The main advancement of this method lies in the automation of reliability modeling and the integration of controllability assessment, eliminating restrictions on the types of propulsor configurations and system architectures that can be evaluated and significantly reducing the effort required for each design iteration. Through a hexarotor drone case study, the proposed method enabled a high number of design iterations, efficiently exploring various aspects of the design problem simultaneously, such as configuration, system architecture, and controllability hypothesis, which is not possible with state-of-the-art techniques. This approach demonstrated significant reliability improvements by implementing and optimizing redundancies, reducing the probability of loss of control by up to 99%. The case study also highlighted the increasing difficulty of enhancing reliability with each iteration and confirmed that it is unnecessary to consider more than two simultaneous failures for design optimization. A comparison of reliability figures with previous studies highlights the crucial role of system architecture in effectively enhancing drone design reliability. This work advances the field by providing an effective multidisciplinary modeling framework for drone design, enhancing reliability in safety-critical applications. Full article
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18 pages, 5534 KiB  
Article
Enhancing Highway Driving: High Automated Vehicle Decision Making in a Complex Multi-Body Simulation Environment
by Ali Rizehvandi, Shahram Azadi and Arno Eichberger
Modelling 2024, 5(3), 951-968; https://doi.org/10.3390/modelling5030050 - 15 Aug 2024
Viewed by 892
Abstract
Automated driving is a promising development in reducing driving accidents and improving the efficiency of driving. This study focuses on developing a decision-making strategy for autonomous vehicles, specifically addressing maneuvers such as lane change, double lane change, and lane keeping on highways, using [...] Read more.
Automated driving is a promising development in reducing driving accidents and improving the efficiency of driving. This study focuses on developing a decision-making strategy for autonomous vehicles, specifically addressing maneuvers such as lane change, double lane change, and lane keeping on highways, using deep reinforcement learning (DRL). To achieve this, a highway driving environment in the commercial multi-body simulation software IPG Carmaker 11 version is established, wherein the ego vehicle navigates through surrounding vehicles safely and efficiently. A hierarchical control framework is introduced to manage these vehicles, with upper-level control handling driving decisions. The DDPG (deep deterministic policy gradient) algorithm, a specific DRL method, is employed to formulate the highway decision-making strategy, simulated in MATLAB software. Also, the computational procedures of both DDPG and deep Q-network algorithms are outlined and compared. A set of simulation tests is carried out to evaluate the effectiveness of the suggested decision-making policy. The research underscores the advantages of the proposed framework concerning its convergence rate and control performance. The results demonstrate that the DDPG-based overtaking strategy enables efficient and safe completion of highway driving tasks. Full article
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23 pages, 1491 KiB  
Article
Examining the Intention to Adopt an Online Platform for Freight Forwarding Services in Thailand: A Modified Unified Theory for Acceptance and Use of Technology (UTAUT) Model Approach
by Nattakorn Pinyanitikorn, Walailak Atthirawong and Wirachchaya Chanpuypetch
Logistics 2024, 8(3), 76; https://doi.org/10.3390/logistics8030076 - 31 Jul 2024
Viewed by 1298
Abstract
Background: The freight forwarding industry is undergoing digital transformation through the implementation of online platforms designed to enhance operational efficiency and transparency. Despite these benefits, the adoption of these platforms has been slower than anticipated due to customer concerns and industry-specific challenges. [...] Read more.
Background: The freight forwarding industry is undergoing digital transformation through the implementation of online platforms designed to enhance operational efficiency and transparency. Despite these benefits, the adoption of these platforms has been slower than anticipated due to customer concerns and industry-specific challenges. Methods: This study investigates the factors influencing the intention to adopt and the actual use of online platforms for freight forwarding services among business customers in Thailand. A modified Unified Theory for Acceptance and Use of Technology (UTAUT) model, incorporating perceived risk, serves as the theoretical framework. Survey data were collected from 400 respondents in managerial or higher-level positions involved in freight shipping within Thai firms and analyzed using a structural equation model (SEM). Results: The analysis reveals that performance expectancy, effort expectancy, social influence, and facilitating conditions positively influence adoption intention, while perceived risk negatively impacts it. Firm size moderates the effect of social influence, with a stronger impact observed in larger enterprises. Conclusions: The findings offer practical insights for Thai freight forwarders, suggesting strategies to improve customer acceptance and encourage the adoption of online platforms. Addressing the identified factors could lead to improved efficiency and greater integration of digital technologies in the logistics industry. Full article
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20 pages, 7748 KiB  
Article
Commuter Experience: An Assessment of Metro-Train Comfort Amidst Operational Vibroacoustic Conditions
by Krzysztof Kowalczyk and Michał Opala
Appl. Sci. 2024, 14(14), 6137; https://doi.org/10.3390/app14146137 - 15 Jul 2024
Cited by 1 | Viewed by 912
Abstract
This study investigates the impact of different passenger rolling stock structures and train configurations on vibrations and noise generated during operation. Vibroacoustic measurements were performed during acceleration, constant speed, and braking phases to analyze the effects using statistical analysis according to the relevant [...] Read more.
This study investigates the impact of different passenger rolling stock structures and train configurations on vibrations and noise generated during operation. Vibroacoustic measurements were performed during acceleration, constant speed, and braking phases to analyze the effects using statistical analysis according to the relevant standards, revealing a statistically significant relationship between the equivalent noise level and vibration dose. In the context of the expanding Warsaw metro network, which is adding new lines and modern rolling stock, trends in the development of metro rolling stock were analyzed using five different types of metro vehicles, from the oldest to the newest designs. Vehicle performance was ranked in the context of ride comfort using standards and combined vibration and noise measures. The research results allowed for a collective comparative assessment of the construction of individual types of passenger rolling stock in terms of vibroacoustic phenomena, thanks to which it is possible to assess the impact of modern solutions and the justification for investing in modern rolling stock. Newer trains generally record significantly lower vibration and noise levels. The difference between the oldest and the most modern vehicle types is 57% for the vibration acceleration level (0.08 ms−2 RMS) and 66% for the noise level (2.2 dB LAeq). Full article
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24 pages, 2013 KiB  
Review
Comprehensive Review of Robotized Freight Packing
by German Pantoja-Benavides, Daniel Giraldo, Ana Montes, Andrea García, Carlos Rodríguez, César Marín and David Álvarez-Martínez
Logistics 2024, 8(3), 69; https://doi.org/10.3390/logistics8030069 - 8 Jul 2024
Cited by 1 | Viewed by 1251
Abstract
Background: This review addresses the emerging field of automated packing cells, which lies at the intersection of robotics and packing problems. Integrating these two fields is critical for optimizing logistics and e-commerce operations. The current literature focuses on packing problems or specific [...] Read more.
Background: This review addresses the emerging field of automated packing cells, which lies at the intersection of robotics and packing problems. Integrating these two fields is critical for optimizing logistics and e-commerce operations. The current literature focuses on packing problems or specific robotic applications without addressing their integration. Methods: To bridge this gap, we conducted a comprehensive review of 46 relevant studies, analyzing various dimensions, including the components of robotic packing cells, the types of packing problems, the solution approaches, and performance comparisons. Results: Our review reveals a significant trend towards addressing online packing problems, which reflects the dynamic nature of logistics operations where item information is often incomplete. We also identify several research gaps, such as the need for standardized terminologies, comprehensive methodologies, and the consideration of real-world constraints in robotic algorithms. Conclusions: This review uniquely integrates insights from robotics and packing problems, providing a structured framework for future research. It highlights the importance of considering practical robotic constraints. It proposes a research structure that enhances the reproducibility and comparability of results in real-world scenarios. By doing so, we aim to guide future research efforts and facilitate the development of more robust and practical automated packing systems. Full article
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18 pages, 2099 KiB  
Article
Optimization Models for the Maintenance Management of Tropical Paved and Unpaved Roads
by Taciano Oliveira da Silva, Heraldo Nunes Pitanga, Emerson Cordeiro Lopes, Laura Carine Pereira Ribeiro, Gustavo Henrique Nalon, Klaus Henrique de Paula Rodrigues, José Carlos Lopes Ribeiro and Khaled Ksaibati
Infrastructures 2024, 9(7), 100; https://doi.org/10.3390/infrastructures9070100 - 27 Jun 2024
Viewed by 1022
Abstract
The degradation of paved and unpaved roads stands as a critical concern in contemporary infrastructure management. When faced with limited budgets, it is important to identify the optimal combination of road preservation strategies to minimize the lifecycle cost of the road network. Specific [...] Read more.
The degradation of paved and unpaved roads stands as a critical concern in contemporary infrastructure management. When faced with limited budgets, it is important to identify the optimal combination of road preservation strategies to minimize the lifecycle cost of the road network. Specific studies are necessary to improve the maintenance management systems and analyze the behavior of road surface deformation. To narrow these knowledge gaps, this study investigates a management system that focuses on the application of optimization techniques for managing both paved and unpaved tropical roads. Probabilistic deterioration models were constructed using the Markovian process, resulting in precise degradation curves in the context of 18 unpaved road segments in the Zona da Mata County of Minas Gerais (Brazil), along with 88 paved roads located in Minas Gerais. An optimization algorithm was proposed for the prediction of maintenance resources for unpaved and paved roads, emphasizing the cost-effectiveness of preventive and minor rehabilitation treatments over reconstruction. Comparisons between the maintenance costs of unpaved and paved roads indicated that the full rehabilitation costs of paved roads were approximately 10 times higher per kilometer compared to those of unpaved roads. The models effectively captured the trend wherein a major treatment leads to minor additional treatments being necessary for the subsequent several years in both scenarios. The findings of this study provide future directions for the optimized allocation of resources in the management of transportation infrastructures. Full article
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17 pages, 12405 KiB  
Article
Analysis of Stray Current Leakage in Subway Traction Power Supply System Based on Field-Circuit Coupling
by Shan Lin, Zhixi Tang, Xia Chen, Xuehua Liu and Yunsheng Liu
Energies 2024, 17(13), 3121; https://doi.org/10.3390/en17133121 - 25 Jun 2024
Viewed by 1010
Abstract
In a rail transit system, there is a constant leakage of current from the subway rails to the earth, and these stray currents have complex propagation paths and a wide range of influence. Since no stray current collection devices are installed at subway [...] Read more.
In a rail transit system, there is a constant leakage of current from the subway rails to the earth, and these stray currents have complex propagation paths and a wide range of influence. Since no stray current collection devices are installed at subway depots, some of the stray current leaking from the mainline will converge at the depot, seriously corroding the structural reinforcement and buried metal of the station, thereby jeopardizing the normal operation of subway trains and passenger safety. In this paper, a field-circuit coupling method is proposed to analyze the current leakage and distribution law of the subway mainline and depot. It is found that the failure of the gauge block at the mainline will trigger the maximum leakage of rail current. Additionally, it is observed that the stray current distribution at the depot is mainly influenced by the operating status of the one-way conduction device (OWCD) and the change of rail potential. These results validate the applicability and effectiveness of the field-circuit coupling method proposed in this paper and provide new technical support for the study of stray current leakage distribution in subways. Full article
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19 pages, 3378 KiB  
Article
Innovative, Three-Dimensional Model for Time-Dependent, Mechanical Battery Module Behaviour Due to Cell Volume Change
by Tolga Bozalp, Shraddha Suhas Kulkarni, Holger Opfer and Thomas Vietor
Energies 2024, 17(12), 2941; https://doi.org/10.3390/en17122941 - 14 Jun 2024
Viewed by 761
Abstract
Battery cells experience volume changes due to intercalation and ageing processes, which may pose a challenge when integrating cells into a battery module. This study presents an innovative, numerical model, which spatially resolved predicts the time-dependent, overall mechanical behaviour of battery modules caused [...] Read more.
Battery cells experience volume changes due to intercalation and ageing processes, which may pose a challenge when integrating cells into a battery module. This study presents an innovative, numerical model, which spatially resolved predicts the time-dependent, overall mechanical behaviour of battery modules caused by volume changes in built-in cells. An already self-developed battery module model, which statically describes the three-dimensional (3D), mechanical behaviour in a 0D simulation environment, is extended by the time dimension for dynamic modelling. The existing model abilities and features are maintained, such as the inclusion of multiple size scales from the cell to module level as well as the automatized model building process for the investigation of different module designs in regard to the number and arrangement of foam pads and multiple other design parameters. The validation of the predication abilities against those of complex, commercial software solutions, which use Finite Element Analysis (FEA) in a 3D model environment, have shown good agreement regarding sensitivity, robustness and numerical stability, revealing the impact and interdependencies of model parameters as well as the numerical limits of the model. In this study, the potential of the novel model regarding computational time and resources is underlined, making it a useful and effective tool for fast optimization studies. Full article
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13 pages, 2705 KiB  
Article
How Does the Built Environment Affect Mechanical Parking Space Planning: A Case Study in Xi’an City
by Yuejiao Wang and Weijia Li
Appl. Sci. 2024, 14(11), 4666; https://doi.org/10.3390/app14114666 - 29 May 2024
Cited by 1 | Viewed by 904
Abstract
Mechanical parking lots and spaces are known as the “energy saver” of urban space because of their small footprint, high efficiency, and environmental protection. However, the location and number of mechanical parking lots and space planning have become an important part of effectively [...] Read more.
Mechanical parking lots and spaces are known as the “energy saver” of urban space because of their small footprint, high efficiency, and environmental protection. However, the location and number of mechanical parking lots and space planning have become an important part of effectively exerting the function of mechanical parking lots. In order to explore the planning problem of mechanical parking lots, this study used the gradient boosting decision tree–Shapley additive explanations (GBDT-SHAPs) to measure the non-linear impact of the urban built environment on the mechanical parking spaces ratio and extract the optimal threshold of key variables. The results show that land use mix and distance to Bell Tower (CBD) are two key variables affecting mechanical parking space planning, and both have a non-linear relationship with the built environment. The threshold values are 0.83 and 7 km. The results will provide urban and transport planners with strategies for planning mechanical parking lots and spaces. Full article
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22 pages, 19427 KiB  
Article
Digital Battle: A Three-Layer Distributed Simulation Architecture for Heterogeneous Robot System Collaboration
by Jialong Gao, Quan Liu, Hao Chen, Hanqiang Deng, Lun Zhang, Lei Sun and Jian Huang
Drones 2024, 8(4), 156; https://doi.org/10.3390/drones8040156 - 18 Apr 2024
Viewed by 1883
Abstract
In this paper, we propose a three-layer distributed simulation network architecture, which consists of a distributed virtual simulation network, a perception and control subnetwork, and a cooperative communication service network. The simulation architecture runs on a distributed platform, which can provide unique virtual [...] Read more.
In this paper, we propose a three-layer distributed simulation network architecture, which consists of a distributed virtual simulation network, a perception and control subnetwork, and a cooperative communication service network. The simulation architecture runs on a distributed platform, which can provide unique virtual scenarios and multiple simulation services for the verification of basic perception, control, and planning algorithms of a single-robot system and can verify the distributed collaboration algorithms of heterogeneous multirobot systems. Further, we design simulation experimental scenarios for classic heterogeneous robotic systems such as unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). Through the analysis of experimental measurement data, we draw several important conclusions: firstly, the replication time characteristics and update frequency characteristics of entity synchronization in our system indicate that the replication time of entity synchronization in our system is relatively short, and the update frequency can meet the needs of multirobot collaboration and ensure the real-time use and accuracy of the system; secondly, we analyze the bandwidth usage of data frames in the whole session and observe that the server side occupies almost half of the data throughput during the whole session, which indicates that the allocation and utilization of data transmission in our system is reasonable; and finally, we construct a bandwidth estimation surface model to estimate the bandwidth requirements of the current model when scaling the server-side scale and synchronization-state scale, which provides an important reference for better planning and optimizing of the resource allocation and performance of the system. Based on this distributed simulation framework, future research will improve the key technical details, including further refining the coupling object dynamic model update method to support the simulation theory of the coupling relationship between system objects, studying the impact of spatiotemporal consistency of distributed systems on multirobot control and decision making, and in-depth research on the impact of collaborative frameworks combined with multirobot systems for specific tasks. Full article
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30 pages, 22960 KiB  
Article
Multi-Context Point Cloud Dataset and Machine Learning for Railway Semantic Segmentation
by Abderrazzaq Kharroubi, Zouhair Ballouch, Rafika Hajji, Anass Yarroudh and Roland Billen
Infrastructures 2024, 9(4), 71; https://doi.org/10.3390/infrastructures9040071 - 9 Apr 2024
Cited by 2 | Viewed by 2849
Abstract
Railway scene understanding is crucial for various applications, including autonomous trains, digital twining, and infrastructure change monitoring. However, the development of the latter is constrained by the lack of annotated datasets and limitations of existing algorithms. To address this challenge, we present Rail3D, [...] Read more.
Railway scene understanding is crucial for various applications, including autonomous trains, digital twining, and infrastructure change monitoring. However, the development of the latter is constrained by the lack of annotated datasets and limitations of existing algorithms. To address this challenge, we present Rail3D, the first comprehensive dataset for semantic segmentation in railway environments with a comparative analysis. Rail3D encompasses three distinct railway contexts from Hungary, France, and Belgium, capturing a wide range of railway assets and conditions. With over 288 million annotated points, Rail3D surpasses existing datasets in size and diversity, enabling the training of generalizable machine learning models. We conducted a generic classification with nine universal classes (Ground, Vegetation, Rail, Poles, Wires, Signals, Fence, Installation, and Building) and evaluated the performance of three state-of-the-art models: KPConv (Kernel Point Convolution), LightGBM, and Random Forest. The best performing model, a fine-tuned KPConv, achieved a mean Intersection over Union (mIoU) of 86%. While the LightGBM-based method achieved a mIoU of 71%, outperforming Random Forest. This study will benefit infrastructure experts and railway researchers by providing a comprehensive dataset and benchmarks for 3D semantic segmentation. The data and code are publicly available for France and Hungary, with continuous updates based on user feedback. Full article
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23 pages, 7915 KiB  
Article
Operational Analysis of an Axial and Solid Double-Pole Configuration in a Permanent Magnet Flux-Switching Generator
by Manuel Garcia Neto, Francisco Ferreira da Silva and Paulo José da Costa Branco
Energies 2024, 17(7), 1698; https://doi.org/10.3390/en17071698 - 2 Apr 2024
Cited by 3 | Viewed by 1269
Abstract
There are two main beneficial characteristics that doubly salient permanent magnet (PM) electrical machines present for aircraft applications: armature windings and PMs excitation sources placed on the stator side (maintenance and thermal management), and having a clear-cut rotor without PMs or excitation windings [...] Read more.
There are two main beneficial characteristics that doubly salient permanent magnet (PM) electrical machines present for aircraft applications: armature windings and PMs excitation sources placed on the stator side (maintenance and thermal management), and having a clear-cut rotor without PMs or excitation windings (vulnerable at high speeds due to associated centripetal mechanical stresses). Within this framework, a doubly salient permanent magnet (DSPM) generator was conceived by optimizing the stator size and rotor structure to minimize the torque ripple and maximize the root-mean-square (RMS) voltage value per turn of each generator phase. Firstly, a comparison between the 2D and 3D finite element method (FEM) models is made considering the results of 3D finite element analysis (FEA) as our benchmark in order to understand the accuracy of the 2D results against our benchmark model, the 3D one. A multi-objective design strategy based on a 2D FEA is made, it is set to have characteristics closest to optimal for a Boeing 767 turbine, that is, the necessary electromotive force for a required power of 90 kW at 3000 rpm, feeding a simplified Boeing 767 electrical power distribution system. The results show that the machine could not deliver the required power at 3000 rpm since the 2D FEA demonstrates that the 2D model gives optimistic results when compared with the 3D FEM model. However, with a 3D FEA of the machine feeding the aircraft load, it was seen that the machine’s efficiency is 92%, suggesting that this machine can be a plausible solution. Full article
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22 pages, 2695 KiB  
Article
Investigating the Crash Protection Performance of a Medical Carrier Bag for Drone Transport
by Fraser McLeod, Tom Cherrett, Andy Oakey, Katherine Theobald, Tim Waters, Matt Grote, John Armstrong, Jack Denny and Alex Murray
Logistics 2024, 8(1), 31; https://doi.org/10.3390/logistics8010031 - 15 Mar 2024
Viewed by 2196
Abstract
Background: Drone transport regulations in Europe require a crash-protected container (CPC) to be used for the carriage of dangerous goods. With increasing interest in the use of drones for medical logistics, the motivation behind this research was to investigate whether the existing approved [...] Read more.
Background: Drone transport regulations in Europe require a crash-protected container (CPC) to be used for the carriage of dangerous goods. With increasing interest in the use of drones for medical logistics, the motivation behind this research was to investigate whether the existing approved medical carriers could also pass as CPCs. To date, there has been little practical experimentation on or theoretical research into the crash protection performance of medical containers. Methods: Addressing this gap, this paper reports findings from a series of drop test experiments to investigate the crashworthiness of a standard medical carrier bag used by the National Health Service (NHS) in the UK. Th drop tests were performed from heights of up to 122 m using standard medical carriers containing bags of dyed saline to examine the robustness of the carrier and whether it could contain any leakages, a key requirement for transporting dangerous goods. Results: The tests found that the medical carrier failed on some drops, with the zipped lid being identified as the main weakness. Conclusions: A new understanding of the carrier’s terminal velocity, impact acceleration, and failure mechanisms were gained and subsequent strengthening and waterproofing remedial measures recommended. New insights and practical recommendations are provided relating to performing formal drop tests and how to conduct these using a drone. Full article
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18 pages, 1234 KiB  
Article
Cooperative Application of Onboard Energy Storage and Stationary Energy Storage in Rail Transit Based on Genetic Algorithm
by Deshi Kong and Masafumi Miyatake
Energies 2024, 17(6), 1426; https://doi.org/10.3390/en17061426 - 15 Mar 2024
Cited by 3 | Viewed by 1306
Abstract
The transition towards environmentally friendly transportation solutions has prompted a focused exploration of energy-saving technologies within railway transit systems. Energy Storage Systems (ESS) in railway transit for Regenerative Braking Energy (RBE) recovery has gained prominence in pursuing sustainable transportation solutions. To achieve the [...] Read more.
The transition towards environmentally friendly transportation solutions has prompted a focused exploration of energy-saving technologies within railway transit systems. Energy Storage Systems (ESS) in railway transit for Regenerative Braking Energy (RBE) recovery has gained prominence in pursuing sustainable transportation solutions. To achieve the dual-objective optimization of energy saving and investment, this paper proposes the collaborative operation of Onboard Energy-Storage Systems (OESS) and Stationary Energy-Storage Systems (SESS). In the meantime, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied to optimize the ESS capacity and reduce its redundancy. The simulation is programmed in MATLAB. The results show that the corporation of OESS and SESS offers superior benefits (70 kWh energy saving within 30 min operation) compared to using SESS alone. Moreover, the OESS plays a significant role, emphasizing its significance in saving energy and investment, therefore presenting a win–win scenario. It is recommended that the capacity of OESS be designed to be two to three times that of SESS. The findings contribute to the ongoing efforts in developing more sustainable and energy-efficient transportation solutions, with implications for the railway industry’s investment and broader initiatives in energy saving for sustainable urban mobility. Full article
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26 pages, 4283 KiB  
Article
A Bayesian Optimization Approach for Tuning a Grouping Genetic Algorithm for Solving Practically Oriented Pickup and Delivery Problems
by Cornelius Rüther and Julia Rieck
Logistics 2024, 8(1), 14; https://doi.org/10.3390/logistics8010014 - 4 Feb 2024
Cited by 3 | Viewed by 2041
Abstract
Background: The Multi Depot Pickup and Delivery Problem with Time Windows and Heterogeneous Vehicle Fleets (MDPDPTWHV) is a strongly practically oriented routing problem with many real-world constraints. Due to its complexity, solution approaches with sufficiently good quality ideally contain several operators with [...] Read more.
Background: The Multi Depot Pickup and Delivery Problem with Time Windows and Heterogeneous Vehicle Fleets (MDPDPTWHV) is a strongly practically oriented routing problem with many real-world constraints. Due to its complexity, solution approaches with sufficiently good quality ideally contain several operators with certain probabilities.Thus, automatically selecting the best parameter configurations enhances the overall solution quality. Methods: To solve the MDPDPTWHV, we present a Grouping Genetic Algorithm (GGA) framework with several operators and population management variants. A Bayesian Optimization (BO) approach is introduced to optimize the GGA’s parameter configuration. The parameter tuning is evaluated on five data sets which differ in several structural characteristics and contain 1200 problem instances. The outcomes of the parameter-tuned GGA are compared to both the initial GGA parameter configuration and a state-of-the-art Adaptive Large Neighborhood Search (ALNS). Results: The presented GGA framework achieves a better solution quality than the ALNS, even for the initial parameter configuration used. The mean value of the relative error is less than 0.9% and its standard deviation is less than 1.31% for every problem class. For the ALNS, these values are up to three times higher and the GGA is up to 38% faster than the ALNS. Conclusions: It is shown that the BO, as a parameter tuning approach, is a good choice in improving the performance of the considered meta-heuristic over all instances in each data set. In addition, the best parameter configuration per problem class with the same characteristics is able to improve both the frequency of finding the best solution, as well as the relative error to this solution, significantly. Full article
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25 pages, 2883 KiB  
Article
Comparative Analysis of Deterministic Fundamental Diagrams Representative of Continuous and Interrupted Traffic Flow on Selected Regional Road in Croatia
by Bojan Jovanović, Marko Ševrović and Grgo Luburić
Appl. Sci. 2024, 14(2), 533; https://doi.org/10.3390/app14020533 - 8 Jan 2024
Viewed by 1342
Abstract
Since the inception of the traffic flow theory, numerous traffic flow models have been formulated by scholars in an effort to more accurately delineate the relationships between various traffic flow parameters. However, only a limited number of studies have explored the distinctions between [...] Read more.
Since the inception of the traffic flow theory, numerous traffic flow models have been formulated by scholars in an effort to more accurately delineate the relationships between various traffic flow parameters. However, only a limited number of studies have explored the distinctions between fundamental traffic diagrams, which characterize continuous and interrupted traffic flow conditions. Addressing this research lacuna, we compared twelve “speed–density” and “flow–density” models fitted to empirical data collected under continuous and interrupted traffic flow conditions on a selected regional road in Croatia. The empirical data used to develop these models were extracted from video footage captured by an unmanned aerial vehicle on two representative road segments during characteristic peak and off-peak hours on workdays. Our analysis reveals that, depending on the selected traffic flow model and prevailing traffic flow conditions, the practical capacity of the observed regional road is estimated to be in the range from 799 to 2333 veh/h/lane. It was also discovered that the considered models reach practical capacity at a significantly different density under continuous and interrupted traffic stream conditions, i.e., between 37 and 129 veh/km/lane. The conducted t-tests underscore the need to employ distinct “speed–density” and “flow–density” regression functions for modeling continuous and interrupted traffic stream conditions. Full article
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22 pages, 14409 KiB  
Article
Study on the Susceptibility of Drifting Snow in Ya’an–Qamdo Section of the Railway in Southwest China
by Xue Zhou, Zhen Zhang, Weidong Yang and Qingkuan Liu
Appl. Sci. 2024, 14(2), 475; https://doi.org/10.3390/app14020475 - 5 Jan 2024
Cited by 2 | Viewed by 901
Abstract
To investigate the susceptibility of drifting snow along the Ya’an–Qamdo section of the railway, which is located in a high-altitude and cold plateau in Southwest China with scarce meteorological information, the Weather Research and Forecasting Model (WRF) is used in this paper to [...] Read more.
To investigate the susceptibility of drifting snow along the Ya’an–Qamdo section of the railway, which is located in a high-altitude and cold plateau in Southwest China with scarce meteorological information, the Weather Research and Forecasting Model (WRF) is used in this paper to simulate the spatio-temporal distribution of meteorological data. According to the varying terrain, the railway section from Ya’an to Qamdo is divided into two regions along 100.8° E for double-layer nested simulation. The original land use data of the WRF model are used in region 1. Due to the increased number of mountains in region 2, the original data are replaced by the MCD12Q1v006 land use data, and the vertical direction layers are densified near the ground to increase simulation accuracy. The simulated results are compared with the observation data. It is found that after densification, the results have been significantly improved. The results obtained by the WRF model can accurately simulate the change trends of temperature, rainfall, and wind speed, and the correlation coefficients are relatively high, which verifies the accuracy of WRF for simulating complex terrain regions. The simulation results further indicate that approximately 300 km of the Ya’an–Qamdo railway may experience drifting snow. Among them, no drifting snow events occur in Ya’an County, and the areas with higher probability are located at the border between Luding County and Tianquan County, followed by Kangding area. The remaining areas have a probability of less than 10%. The WRF model demonstrates its capability in the drifting snow protection of railways with limited meteorological data. Full article
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20 pages, 1281 KiB  
Article
Examination of Logistics Simulation Demand Related to Enterprises: Focusing on a Hungarian County
by Károly Szabó, László Szabó and Richárd Kása
Logistics 2024, 8(1), 7; https://doi.org/10.3390/logistics8010007 - 4 Jan 2024
Cited by 1 | Viewed by 2123
Abstract
Background: Despite the fact that some results can be found for the logistics simulation in the literature, there is a lack of an experiment based on inner company data. Therefore, the study aimed to determine the potential need for this kind of solution [...] Read more.
Background: Despite the fact that some results can be found for the logistics simulation in the literature, there is a lack of an experiment based on inner company data. Therefore, the study aimed to determine the potential need for this kind of solution by Zala County enterprises. Methods: As a first step, the paper presents the existing literature with the help of a literature review. Afterwards, questionnaire sampling was conducted among local enterprises. The paper applies several statistical methods (e.g., descriptive statistics, SPSS, exploratory factor analysis, and structural equation modeling) to the sample for the validation of the reorganization demand. Results: The study obtained a total of 147 complete responses from the 1022 invitations. An overwhelming majority of the respondents indicated regular and significant delays in their logistics processes, as well as the need for a new simulation method. Based on the SEM model, it has been observed that IT solutions are being utilized in an inefficient manner, resulting in logistical system issues and operational damages. Conclusion: The paper successfully identified a research gap, the research of which can have not only theoretical but also many practical benefits. Hopefully, the results will generate other academic research in this field. Full article
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36 pages, 3833 KiB  
Article
Controller Design for Air Conditioner of a Vehicle with Three Control Inputs Using Model Predictive Control
by Trevor Parent, Jeffrey J. Defoe and Afshin Rahimi
Modelling 2024, 5(1), 117-152; https://doi.org/10.3390/modelling5010008 - 3 Jan 2024
Cited by 1 | Viewed by 1694
Abstract
Fuel consumption optimization is a critical field of research within the automotive industry to meet consumer expectations and regulatory requirements. A reduction in fuel consumption can be achieved by reducing the energy consumed by the vehicle. Several subsystems contribute to the overall energy [...] Read more.
Fuel consumption optimization is a critical field of research within the automotive industry to meet consumer expectations and regulatory requirements. A reduction in fuel consumption can be achieved by reducing the energy consumed by the vehicle. Several subsystems contribute to the overall energy consumption of the vehicle, including the air conditioning (A/C) system. The loads within the A/C system are mainly contributed by the compressor, condenser fan, and underhood aerodynamic drag, which are the components targeted for overall vehicle energy use reduction in this paper. This paper explores a new avenue for A/C system control by considering the power consumption due to vehicle drag (regulated by the condenser fan and active grille shutters (AGS)) to reduce the energy consumption of the A/C system and improve the overall vehicle fuel economy. The control approach used in this paper is model predictive control (MPC). The controller is designed in Simulink, where the compressor clutch signal, condenser fan speed, and AGS open-fraction are inputs. The controller is connected to a high-fidelity vehicle model in Gamma Technologies (GT)-Suite (which is treated as the real physical vehicle) to form a software-in-the-loop simulation environment, where the controller sends actuator inputs to GT-Suite and the vehicle response is sent back to the controller in Simulink. Quadratic programming is used to solve the MPC optimization problem and determine the optimal input trajectory at each time step. The results indicate that using MPC to control the compressor clutch, condenser fan, and AGS can provide a 37.6% reduction in the overall A/C system energy consumption and a 32.7% reduction in the error for the air temperature reference tracking compared to the conventional baseline proportional integral derivative control present in the GT-Suite model. Full article
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30 pages, 6207 KiB  
Review
A Review of Icing Research and Development of Icing Mitigation Techniques for Fixed-Wing UAVs
by Liang Zhou, Xian Yi and Qinglin Liu
Drones 2023, 7(12), 709; https://doi.org/10.3390/drones7120709 - 18 Dec 2023
Cited by 1 | Viewed by 3815
Abstract
With the continuous expansion of Unmanned Aerial Vehicle (UAV) applications, the threat of icing on UAV flights has garnered increased attention. Understanding the icing principles and developing anti-icing technologies for unmanned aircraft is a crucial step in mitigating the icing threat. However, existing [...] Read more.
With the continuous expansion of Unmanned Aerial Vehicle (UAV) applications, the threat of icing on UAV flights has garnered increased attention. Understanding the icing principles and developing anti-icing technologies for unmanned aircraft is a crucial step in mitigating the icing threat. However, existing research indicates that changes in Reynolds numbers have a significant impact on the physics of ice accretion. Icing studies on aircraft operating at high Reynolds numbers cannot be directly applied to unmanned aircraft, and mature anti-icing/deicing techniques for manned aircraft cannot be directly utilized for UAVs. This paper firstly provides a comprehensive overview of research on icing for fixed-wing UAVs, including various methods to study unmanned aircraft icing and the identified characteristics of icing on unmanned aircraft. Secondly, this paper focuses on discussing UAV anti-icing/deicing techniques, including those currently applied and under development, and examines the advantages and disadvantages of these techniques. Finally, the paper presents some recommendations regarding UAV icing research and the development of anti-icing/deicing techniques. Full article
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24 pages, 3334 KiB  
Article
A Novel Approach to Identify Industrial Logistics Decarbonization Opportunities: Method Development and Preliminary Validation
by Philipp Miklautsch-Breznik, Mario Hoffelner and Manuel Woschank
Appl. Sci. 2023, 13(22), 12277; https://doi.org/10.3390/app132212277 - 13 Nov 2023
Viewed by 1380
Abstract
This article explores how different types of inventories affect the costs of decarbonizing transportation in manufacturing companies. For these companies, it is difficult to find affordable ways to reduce emissions from transportation given their resource scarcity. Additionally, they handle numerous inventory items that [...] Read more.
This article explores how different types of inventories affect the costs of decarbonizing transportation in manufacturing companies. For these companies, it is difficult to find affordable ways to reduce emissions from transportation given their resource scarcity. Additionally, they handle numerous inventory items that have varying transportation needs based on their order frequency and value, which necessitates the development of tailored inventory management strategies. One tool to do so efficiently is the ABC/XYZ analysis, which classifies items into nine different inventory categories. These groups have different economic importance and predictability, which impacts total logistics costs. Our literature analysis contends that lower-carbon transportation alternatives yield varying abatement costs contingent upon the specific inventory categories. Subsequently, we empirically validate this proposition through discrete-event simulations in two case studies involving Austrian manufacturing enterprises, employing combined road-rail transportation as an illustrative decarbonization measure. Statistical tests substantiate the significance of the XYZ dimension in influencing carbon emission abatement costs during the transition from road to rail transportation. In conclusion, our study offers a novel perspective on decarbonization efforts, underscoring the importance of leveraging established management tools to inform strategic decarbonization decisions. This research holds promise for catalyzing progress in overcoming entrenched challenges associated with decarbonization initiatives within industrial logistics. Full article
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14 pages, 3763 KiB  
Article
Supply-Driven Analysis for a Continuous Water Supply Network Based on a Pressure-Based Outflow at the House Outlets under Peak Withdrawal Scenarios
by Conety Ravi Suribabu, Neelakantan Renganathan Thurvas and Perumal Sivakumar
Modelling 2023, 4(4), 515-528; https://doi.org/10.3390/modelling4040029 - 8 Nov 2023
Viewed by 1003
Abstract
This research brings a new analysis method for a continuous water supply distribution network. The number of house service connections in different story buildings, rather than the nodal peak demand, shall be accounted for in the analysis. This work aims to consider the [...] Read more.
This research brings a new analysis method for a continuous water supply distribution network. The number of house service connections in different story buildings, rather than the nodal peak demand, shall be accounted for in the analysis. This work aims to consider the flow when pipes are opened in the house plumbing systems. The approach deviates from a traditional peak demand-based analysis of the water distribution network. The analysis gives the flow rate at each nodal point that could be observed in the different story buildings. The methodology is applied to a hypothetical network and shows how much flow and nodal pressure can occur when different percentages of consumers are in an active state. This study indicates that the peak demand-based sizing of the supply pipes could have a deficient capacity under real scenarios. The proposed analysis method will help to understand the actual behavior of the network. Full article
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20 pages, 1701 KiB  
Article
Receding Horizon Optimization for Cooperation of Connected Vehicles at Signal-Free Intersections under Mixed-Automated Traffic
by Jian Gong, Weijie Chen and Ziyi Zhou
Appl. Sci. 2023, 13(20), 11576; https://doi.org/10.3390/app132011576 - 23 Oct 2023
Viewed by 1454
Abstract
This paper proposes a distributed coordination scheme for connected vehicles, including automated vehicles (AVs) and manual vehicles (MVs), at signal-free intersections. The cooperation issue of vehicles at an intersection is formulated into a multi-objective optimization problem that aims to eliminate conflicts and improve [...] Read more.
This paper proposes a distributed coordination scheme for connected vehicles, including automated vehicles (AVs) and manual vehicles (MVs), at signal-free intersections. The cooperation issue of vehicles at an intersection is formulated into a multi-objective optimization problem that aims to eliminate conflicts and improve traffic mobility and fuel economy. For this purpose, the future trajectories of AVs and MVs are predicted by the respective car-following models, and are shared with neighboring vehicles in conflict relationships. The proposed scheme optimizes the sum of the performance of AVs within the cooperative zone in a prediction horizon. A distributed optimization algorithm in the receding horizon is presented to obtain the local optimal solutions, and is tested in simulations with different demand levels and penetration rates of AVs. The results show that the proposed scheme reduces travel time by 29.7–45.5% and 34.5–49.2%, and decreases fuel consumption by 27.6–35.3% and 21.6–29.9% under 70–100% penetration rates of AVs, compared to the no-control operation and fixed-time signal control strategy. In addition, a comparison simulation with the strategy of jointly optimizing the vehicle trajectory and signal timing is conducted to evaluate the relative merits of the proposed scheme. Full article
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19 pages, 8203 KiB  
Article
Development of a Virtual Reality Tool for Train Crew Training
by Agnieszka A. Tubis, Franciszek Restel and Anna Jodejko-Pietruczuk
Appl. Sci. 2023, 13(20), 11415; https://doi.org/10.3390/app132011415 - 18 Oct 2023
Cited by 4 | Viewed by 1661
Abstract
(1) Background: The article presents the results of research carried out as part of one of the project’s tasks, aiming to develop training scenarios for selected workstations related to the operation of passenger rail transport. The article aims to present the results of [...] Read more.
(1) Background: The article presents the results of research carried out as part of one of the project’s tasks, aiming to develop training scenarios for selected workstations related to the operation of passenger rail transport. The article aims to present the results of a training experiment to verify the effectiveness of the developed training scenario for conductors regarding lift operations for people with disabilities. (2) Methods: The study used an analysis of the execution times of individual training tasks, accompanying observation, face-to-face interviews, and a comparative analysis of the effectiveness of various training strategies. The research was carried out following the developed five-stage research procedure. (3) Results: The obtained research results confirm the benefits of using virtual reality in training conductors and allow for determining the most effective training strategy. The measurements of the execution times of individual training operations made it possible to identify the tasks in the training program that were the most time-consuming or characterized by highly diversified execution times. (4) Conclusions: Based on the research, it was possible to develop recommendations regarding the changes that should be introduced in the training tool to better adapt to the real conditions of service operations. The effectiveness of using this form of training in relation to the improvement of a selected group of employees was confirmed. Full article
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21 pages, 4976 KiB  
Article
The Impact of the Level of Training of Airport Security Control Operators on the Energy Consumption of the Baggage Control Process
by Jacek Ryczyński and Artur Kierzkowski
Energies 2023, 16(19), 6957; https://doi.org/10.3390/en16196957 - 5 Oct 2023
Cited by 2 | Viewed by 1378
Abstract
The article focuses on the study of the impact of the level of training of security control operators (SCOs) at airports on the energy consumption of the passenger baggage control process. With the constant growing emphasis on security at airports, the intensification of [...] Read more.
The article focuses on the study of the impact of the level of training of security control operators (SCOs) at airports on the energy consumption of the passenger baggage control process. With the constant growing emphasis on security at airports, the intensification of training processes for security personnel, especially those dealing with baggage control, has become very dynamic. An essential aspect in times of sustainable development is optimizing all kinds of processes (including training processes) to reduce energy consumption. The analysis of the demand for energy used to conduct this type of training and the impact of the operator’s training level on the energy consumption of the control process are entirely ignored and have not been the subject of research by scientists so far. Therefore, this is a research gap that the authors are trying to fill in this article. The impact of safety system operator training levels on ensuring optimal energy efficiency was critically analyzed. The added value of the article is the authors’ model assessing the influence of the level of training of the SCO on the energy consumption of the control process. The effects of the frequency, duration and level of operator training on energy consumption rates were investigated. The authors’ activities aimed to identify the most energy-efficient approaches to training without compromising its quality and, thus, the safety of passengers. The article discusses potential strategies for minimizing energy use and draws conclusions that can help airport administrations and training providers adopt sustainable and energy-efficient training practices. Full article
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40 pages, 1091 KiB  
Systematic Review
Transformative Procurement Trends: Integrating Industry 4.0 Technologies for Enhanced Procurement Processes
by Areej Althabatah, Mohammed Yaqot, Brenno Menezes and Laoucine Kerbache
Logistics 2023, 7(3), 63; https://doi.org/10.3390/logistics7030063 - 13 Sep 2023
Cited by 25 | Viewed by 18271
Abstract
Background: the advent of Industry 4.0 (I4.0) innovations has revolutionized supply chain management through technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) integrated into procurement processes. Methods: this study addresses a critical knowledge gap by conducting a comprehensive [...] Read more.
Background: the advent of Industry 4.0 (I4.0) innovations has revolutionized supply chain management through technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) integrated into procurement processes. Methods: this study addresses a critical knowledge gap by conducting a comprehensive review of 111 papers sourced from the Scopus database. These papers are classified into seven sub-themes encompassing I4.0 or procurement 4.0 (P4.0), big data, IoT, additive manufacturing, blockchain, e-procurement, and AI. Results: the investigation reveals that I4.0 technologies, particularly e-procurement and blockchain, have garnered substantial attention. Such technologies offer diverse value propositions, encompassing streamlined supplier evaluation, lead time reduction, cost optimization, and enhanced data security. Conclusion: the paper underscores pivotal trends and insights for the evolution of Procurement 4.0, illuminating a path toward more efficient supply chain management. Full article
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18 pages, 325 KiB  
Article
Order Picking Problem: A Model for the Joint Optimisation of Order Batching, Batch Assignment Sequencing, and Picking Routing
by Antonio Maria Coruzzolo, Francesco Lolli, Elia Balugani, Elisa Magnani and Miguel Afonso Sellitto
Logistics 2023, 7(3), 61; https://doi.org/10.3390/logistics7030061 - 11 Sep 2023
Cited by 3 | Viewed by 3215
Abstract
Background: Order picking is a critical activity in end-product warehouses, particularly using the picker-to-part system, entail substantial manual labor, representing approximately 60% of warehouse work. Methods: This study develops a new linear model to perform batching, which allows for defining, assigning, and sequencing [...] Read more.
Background: Order picking is a critical activity in end-product warehouses, particularly using the picker-to-part system, entail substantial manual labor, representing approximately 60% of warehouse work. Methods: This study develops a new linear model to perform batching, which allows for defining, assigning, and sequencing batches and determining the best routing strategy. Its goal is to minimise the completion time and the weighted sum of tardiness and earliness of orders. We developed a second linear model without the constraints related to the picking routing to reduce complexity. This model searches for the best routing using the closest neighbour approach. As both models were too complex to test, the earliest due date constructive heuristic algorithm was developed. To improve the solution, we implemented various algorithms, from multi-start with random ordering to more complex like iterated local search. Results: The proposed models were tested on a real case study where the picking time was reduced by 57% compared to single-order strategy. Conclusions: The results showed that the iterated local search multiple perturbation algorithms could successfully identify the minimum solution and significantly improve the solution initially obtained with the heuristic earliest due date algorithm. Full article
12 pages, 1933 KiB  
Article
An Indirect Identification Method for Train Basic Resistance Parameters
by Fei Xia, Tianxiang Li and Pengfei Sun
Appl. Sci. 2023, 13(15), 8843; https://doi.org/10.3390/app13158843 - 31 Jul 2023
Viewed by 1137
Abstract
The train basic resistance characteristic is crucial for ATO performance. However, this characteristic is slow time-varying with wheel rail wear and fast time-varying with weather conditions. The parameters of train basic resistance are difficult to measure directly, usually only a set of empirical [...] Read more.
The train basic resistance characteristic is crucial for ATO performance. However, this characteristic is slow time-varying with wheel rail wear and fast time-varying with weather conditions. The parameters of train basic resistance are difficult to measure directly, usually only a set of empirical parameters can be obtained through repeated experiments. These factors result in an inconsistency between the model parameters in the ATO controller and the actual train basic resistance parameters (TBRP), leading to a decrease in the effectiveness of the model-based controller. Therefore, this paper proposes an indirect TBRP identification method based on speed trajectory fitting to improve the effectiveness of the TBRP for model-based ATO controllers. Firstly, the original TBRP identification problem is transformed into an optimization problem, which is to minimize the deviation between the actual speed trajectory and the model-calculated one. Then, the Newton’s method is used to accelerate the search for the best set of TBRPs with minimum deviation. Finally, case studies are used to verify the effectiveness of the proposed method. Full article
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12 pages, 740 KiB  
Article
Transport Task Models with Variable Supplier Availabilities
by Julian Vasilev, Rosen Nikolaev and Tanka Milkova
Logistics 2023, 7(3), 45; https://doi.org/10.3390/logistics7030045 - 27 Jul 2023
Cited by 1 | Viewed by 1625
Abstract
Background: With regard to the definition of an optimal transport plan for some material flow in the logistics system in literature and practice, the classical transport task model is developed. The minimization of total transport costs is usually considered for optimality. Some [...] Read more.
Background: With regard to the definition of an optimal transport plan for some material flow in the logistics system in literature and practice, the classical transport task model is developed. The minimization of total transport costs is usually considered for optimality. Some modifications to the classical transport task have also been developed. Methods: The article uses the methods of linear optimization. Based on these methods, two modified transport task models have been constructed, which consider the possibility of planning in advance the quantities available from the suppliers of the transported cargo. These models are applicable in SCM for pharmaceuticals with a national logistics hub. Furthermore, a solver in MS Excel is used to determine the optimal solution of optimization models. Results: Two new (modified, extended) models of the transport task have been constructed, in which a preliminary planning of the available quantities of the transported cargo at the suppliers is made. These quantities shall be planned in such a way as to ensure a minimum total transport cost. Conclusions: By applying the proposed new transport task models, lower total transport costs for carrying out imported pharmaceuticals can be ensured compared to an application of the classical transport task model. Full article
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19 pages, 1551 KiB  
Article
Retrieving Relevant EU Drone Legislation with Citation Analysis
by Gijs van Dijck, Alexandru-Daniel On, Jasper Snel and Rohan Nanda
Drones 2023, 7(8), 490; https://doi.org/10.3390/drones7080490 - 26 Jul 2023
Cited by 2 | Viewed by 1909
Abstract
Can the retrieval of relevant unmanned aircraft systems (UAS) legislation be automated? In this article, references from and to EU legislation are used to create an overview that is subsequently compared to legislation considered relevant by subject-matter experts. The overlap between the results [...] Read more.
Can the retrieval of relevant unmanned aircraft systems (UAS) legislation be automated? In this article, references from and to EU legislation are used to create an overview that is subsequently compared to legislation considered relevant by subject-matter experts. The overlap between the results of the citation analysis and the expert overview is promising. Additionally, an approach was proposed and tested where, first, a relatively large number of laws were identified and, second, the laws that were considered relevant were selected. The findings reveal that this approach was successful at retrieving the majority of relevant laws. The results are relevant to researchers, policymakers, practitioners, and laypeople searching for relevant EU legislation on UAS. Full article
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20 pages, 5696 KiB  
Article
Determining the Efficiency of Small-Scale Propellers via Slipstream Monitoring
by Jaan Susi, Karl-Eerik Unt and Siim Heering
Drones 2023, 7(6), 381; https://doi.org/10.3390/drones7060381 - 6 Jun 2023
Cited by 2 | Viewed by 3341
Abstract
A large part of small-sized UAVs that are used for surface scanning, video- and photography, or other similar applications are of the multirotor type. These small aircraft perform mainly in hovering or nearly hovering flight mode, and the endurance of these vehicles depends [...] Read more.
A large part of small-sized UAVs that are used for surface scanning, video- and photography, or other similar applications are of the multirotor type. These small aircraft perform mainly in hovering or nearly hovering flight mode, and the endurance of these vehicles depends greatly on the efficiency of their motors and the aerodynamic efficiency of their thrust-generating systems, including propellers, ducted fans, etc. Propellers may therefore work in different regimes: in a regime where the propeller performs work to move the vehicle through the air, and the static or hovering regime, in which standing air is accelerated. In both cases, the concept of efficiency can be used to describe the propeller’s performance. There have been several previous studies on static and advancing propellers’ performances. In these studies, when determining the efficiency of a static propeller, the thrust and power coefficients are most commonly compared to evaluate the propeller’s performance. Sometimes, the inducted velocities are calculated via the momentum theory. As small-scale propellers work on very low Reynolds (Re) numbers below 500,000, the flow type transition and boundary layer separation make it very hard to predict the actual efficiency of the propellers in static mode. Therefore, the aim of this paper is to introduce a method to determine the static efficiency of small-scale propellers directly and empirically via a comparison between the output and input power, wherein the output power is determined via the measured thrust and mean induced velocity. The used method combines thrust, torque, and angular velocity measurements with slipstream monitoring. The performed tests showed a decrease in efficiency, with the Re number rising in spite of the rising values of the thrust coefficient. This study led to two main conclusions: thrust and power coefficients are not always the key parameters to determine the efficiency of a propeller; the role of the Re number in the propeller’s efficiency is not yet clear and requires further investigation. The presence of Re number effects has been proven in numerous works, but the impact of those effects seems to not be as trivial as the claim that the lower the Re number, the weaker the propeller’s performance. Full article
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