Hasil untuk "Railroad engineering and operation"

Henry Paul C Tagle and Jason Andre D Concepcion

Aircraft hangars are critical infrastructure in general aviation, providing secure environments for aircraft storage, ground handling, and basic maintenance. Despite the widespread use of small fixed-wing and rotary-wing aircraft, existing aviation regulations and engineering literature lack validated quantitative guidance for determining minimum and optimal hangar floor area requirements, particularly for mixed-fleet operations. This gap is especially evident in the Philippine context, where national aviation and building regulations address structural integrity, fire safety, and aerodrome standards but do not specify aircraft-specific interior spatial clearances. This study develops a quantitative, engineering-based framework for determining hangar floor area requirements for small fixed-wing and rotary-wing aircraft. Using geometric analysis, aircraft dimensional data, and safety clearance envelopes, mathematical formulas were derived to compute minimum floor areas for single and multiple aircraft configurations. Computer-aided design (CAD) simulations were applied to evaluate side-by-side, nose-to-tail, and staggered layouts while integrating personnel maintenance walk-around zones and National Building Code circulation requirements. Results show that optimized layouts can reduce hangar floor area by 4–7% for fixed-wing aircraft using nose-to-tail arrangements and by 7–10% for rotary-wing aircraft using staggered configurations. Mixed-fleet optimization achieved approximately 10% space savings compared with heuristic designs while maintaining safety compliance. The proposed framework provides validated, adaptable design guidance for general aviation hangars, supporting safer, more efficient, and cost-effective facility planning in the Philippines and similar operational environments..

André Takeshi Endo, Anders Møller

SHEN Zelin, WANG Biao, QIN Yong et al.

Diffusion models enable the generation of virtual fault samples, alleviating issues such as scarcity and imbalance in measured data and showing promising applications in intelligent fault diagnosis of train gearboxes. However, existing methods have two main limitations. First, they ignore correlations between a priori physical information and sample features, hindering use of condition differences to guide the generation process, and resulting in insufficient diversity of generated samples. Second, they neglect the differential contributions of time steps to the diffusion model optimization process, wasting computing resources on low-contribution time steps, and causing low training efficiency and slow convergence rate of the model. To address these limitations, this paper proposes a virtual sample augmentation method for fault diagnosis of train gearboxes based on a dual-condition diffusion model. Within the diffusion-model framework, this method used U-Net as the main architecture for reverse denoising, and integrated an attention mechanism with a dual-condition encoder. This design enables the model to dynamically guide the generation process based on conditions during the denoising stage and to suppress the generation of non-ideal samples by introducing template conditions, thereby enhancing the diversity and distributional completeness of generated data. In addition, a time-step optimization sampling module was introduced to dynamically evaluate and screen time steps in the diffusion process based on their importance, focusing learning on those with greater contributions to denoising to improve training efficiency and convergence rate of the model. By combining a priori information of conditions with adaptive optimization of time steps, the model efficiently generates diverse virtual fault samples. Experimental results demonstrate that the proposed method generates a richer set of fault samples, significantly improves accuracy in fault diagnosis tasks, and achieves superior efficiency of model training to existing methods.

Prof. Dr. Md. Nurul Absar Chowdhury, MD Eusuf Jamil, Tasfiah Tasnim et al.

Globally, railroads are embracing digitalization to improve their operations. The next generation of digital transport systems must incorporate railway data with technological enhancement. Bangladesh Railway industry operates and the network as a whole may come to a complete stop if the central traffic management system fails.Blockchain technology emerges as a disruptive solution, promising greater transparency, trust, and operational efficiency. This abstract examines how blockchain technology may be used to decentralize the railway administration system, emphasizing the main advantages and useful factors from transparency to transformation. The fundamental principles of blockchain, namely distributed ledger technology and immutability, present a novel strategy for decentralizing systems across several industries. This study presents a moderate overview of the literature on the implementation of blockchain technology across several industries, specifically in the context of the railway industry which disclose the application and implementation barriers of block chain in Bangladesh perspective. The blockchain technology's potential benefits and the limitations of usages for the railroad sector have been described. A simple hypothetical analysis of the time required to manually transmit data in the railway

A. Lovska, I. Stanovska, I. Prokopovych et al.

The object of this paper is the processes of perception and redistribution of loads in the roof of a railroad covered wagon with a frame in the form of a triangular arch. To reduce the tare of the covered wagon, it is proposed to improve the structure of its roof. A feature of this improvement is that the roof frame is made in the form of a triangular arch with a reinforcing belt. This contributes to the reduction of the total mass of the roof compared to a typical structure. The selection of execution profiles of the beams forming the arch is carried out according to the maximum values of the moments that act in their cross-section. Taking into account the chosen profile of the arches, the calculation of the strength of the roof when it receives vertical loads was carried out. It was established that the strength of the roof under the considered load schemes is within the permissible stress values. Since the improvement of the roof structure contributes to the reduction of its weight by 1.8 % compared to the prototype, the movement of the covered wagon was evaluated under conditions of moving while empty. To this end, a mathematical modeling of the load of the covered wagon in the vertical plane during its movement along the joint unevenness was carried out. On the basis of the performed calculation, it was established that the movement of the wagon is assessed as "good". Special feature of the results is that the reduction of the tare of the supporting structure of the wagon was achieved by improving its roof, as the least loaded unit. The field of practical application of the results is railroad transport, including other areas of mechanical engineering. The conditions for the practical use of the results are a symmetrical roof load scheme in operation. The results of this research could contribute to advancements related to the design of modern structures of freight wagons with improved technical and economic indicators

S. Bae, Takanori Fujiwara, A. Ynnerman et al.

Interaction is critical for data analysis and sensemaking. However, designing interactive physicalizations is challenging as it requires cross-disciplinary knowledge in visualization, fabrication, and electronics. Interactive physicalizations are typically produced in an unstructured manner, resulting in unique solutions for a specific dataset, problem, or interaction that cannot be easily extended or adapted to new scenarios or future physicalizations. To mitigate these challenges, we introduce a computational design pipeline to 3D print network physicalizations with integrated sensing capabilities. Networks are ubiquitous, yet their complex geometry also requires significant engineering considerations to provide intuitive, effective interactions for exploration. Using our pipeline, designers can readily produce network physicalizations supporting selection—the most critical atomic operation for interaction—by touch through capacitive sensing and computational inference. Our computational design pipeline introduces a new design paradigm by concurrently considering the form and interactivity of a physicalization into one cohesive fabrication workflow. We evaluate our approach using (i) computational evaluations, (ii) three usage scenarios focusing on general visualization tasks, and (iii) expert interviews. The design paradigm introduced by our pipeline can lower barriers to physicalization research, creation, and adoption.

T. Wiese

The Long Island Railroad operates one of the largest commuter rail networks in the U.S.[1]. This study uses data which includes the location and arrival time of trains based on onboard GPS position and other internal sources. This paper analyzes the GPS position of the train to gain insight into potential gaps in on time performance and train operations. This was done by developing a Random Forest Re-gression model [2] and an XGBoost regression model [3[. Both models prove to be useful to make such predictions and should be used to help railroads to prepare and adjust their operations.

Yu Guo, Yi Lingzhi, Wang Yahui et al.

Catenary is a crucial component of an electrified railroad's traction power supply system. There is a considerable incidence of abnormal status and failures due to prolonged outside exposure. Driving safety will be directly impacted if an abnormal status or failure occurs. Currently, catenary detection vehicles are the most often utilized technique for gathering data and identifying faults based on manual experience. However, this technology cannot meet the demands of prompt detection and correction of faults in railways engineering due to its extremely low work efficiency. Based on the above, an abnormal status detection method of catenary based on the improved gray wolf (IGWO) algorithm optimized the least squares support vector machine (LSSVM) with the t-distributed stochastic neighbor embedding (TSNE) is proposed in this paper. In order to improve the accuracy of catenary abnormal status detection and shorten the detection time. Firstly, the TSNE dimensionality reduction technology is used to reduce the original catenary data to three-dimensional space. Then, in order to address the issue that the parameters of the LSSVM detection model are hard to determine, the improved GWO algorithm is used to optimize the penalty factor and kernel parameter in the LSSVM and establish the TSNE-IGWO-LSSVM catenary abnormal status detection model. Finally, contrasting experimental results of different detection models. The T-distributed Stochastic Domain Embedding (TSNE) is an improved nonlinear dimensionality reduction method based on the Stochastic Neighbor Embedding (SNE). TSNE no longer adopts the distance invariance in linear dimensionality reduction methods such as ISOMAP. TSNE is much better than the linear dimensionality reduction method in the reduction degree of the original dimension. The GWO algorithm, which is frequently used in engineering research, has the advantages of a simple model, great generalization capability, and good optimization performance. The premature convergence is one of the remaining flaws. By applying a good point set to initialize the gray wolf population and the nonlinear control parameters, the gray wolf algorithm is improved in this research. The IGWO algorithm effectively makes up for the problem of balancing the local exploitation and global search capabilities of GWO. Additionally, this IGWO algorithm performs the Cauchy variation operation on the current generation optimal solution to improve population diversity, enlarge the search space, and increase the likelihood of the algorithm escaping the local optimal solution in order to prevent the algorithm from failing the local optimum. The Least Squares Support Vector Machine (LSSVM) is an improved version of the Support Vector Machine (SVM), which replaces the original inequality constraint with a linear least squares criterion for the loss function. The kernel parameters of the RBF function and the penalty factor, these two parameters directly determine the detection effect of LSSVM. In this paper, the IGWO is utilized to adjust and determine the LSSVM parameters in order to enhance the detection capacity of the LSSVM model. In this paper, in order to minimize the experiment's bias, the training data and the test data are allocated in a ratio of 4:1, the training data are set to 400 groups, and the test data are set to 100 groups. After training the five models, the test data is used to validate and compare the detection capacity of the models. After each of the five detection models was tested ten times, the TSNE-IGWO-LSSVM model is compared with the IGWO-LSSVM model, the TSNE-FA-LSSVM model, the GWO-LSSVM model, and the GWO-ELM model, the results show that the TSNE-IGWO-LSSVM model has the highest average detection accuracy of 97.1% and the shortest running time of 26.9s. For the root mean squared error (RMSE) and the root mean squared error (RMSE), the TSNE-IGWO-LSSVM model is 0.17320 and 2.51% respectively, which is the best among the five models, indicating that it not only has higher detection accuracy but also better convergence of detection accuracy than the other models. With the thousands of miles of catenary and the complexity of the data, it is crucial to shorten the running time in order to improve the efficiency and ease the burden of the processors. The experiments demonstrate that the TSNE-IGWO-LSSVM detection model can detect the abnormal status of catenary more accurately and quickly, providing a new method for the abnormal status detection of catenary, which has certain application value and engineering significance in the era of fully electrified railways.

Jingxuan Chen, Donglin Jia, E. Johansson et al.

Lead halide perovskite quantum dots (PQDs), also called perovskite nanocrystals, are considered as one of the most promising classes of photovoltaic materials for solar cells due to their prominent optoelectronic properties and simple preparation techniques. Remarkable achievements in PQD solar cells (PQDSCs) have been made. In particular, the power conversion efficiency of PQDSCs has been largely pushed from 10.77% to 17.39% (certified 16.6%) by finely controlling the surface chemistry of PQDs and the device physics of PQDSCs. In this review, we summarize the latest advances of emerging PQDSCs and discuss various strategies applied to improve the device performance of PQDSCs, including the synthesis methods, compositional engineering and surface chemistry of PQDs. Moreover, the device operation of PQDSCs is discussed to highlight the effect of device architecture on the photovoltaic performance of PQDSCs. Facing the practical applications of the PQDSCs under ambient conditions, device stability is also highlighted. Finally, conclusions and perspectives are presented along with the possible challenges and opportunities to promote development steps of PQDSCs with higher photovoltaic performance and robust stability.

YANG Lele, CHEN Yanping, DOU Zechun et al.

The paper presents a new type of gate driver for IGBT, which has the function of acquiring the operation state data in addition to traditional gate drive and short-circuit protection functions. Acquiring data of IGBT in normal operation state and at fault is conducive to understanding the working environment of IGBT, analyzing IGBT failure mechanism, and providing theoretical basis for the improvement and positive design of power electronic devices in power system. The gate driver is based on field programmable gate array, which integrates pulse control, drive and protection, signal acquisition, and serial communication functions. The main functional modules are described in detail in the paper, and the functions and reliability were verified by mathematical model simulation and experiments. The paper provides a technical reserve for the digital and intelligent development of gate drive technology, and data support for the failure analysis and health management research of IGBT modules.

PAN Wenbo, LI Cheng, YUAN Xiwen et al.

Aiming at the problems of difficult real-time construction of train running forward boundary and complex cluster detection of unstructured track and road environment targets, a lidar based on target detection and forward boundary real-time construction system was proposed. Firstly, the strategy of space for time was adopted to improve the efficiency of rail track extraction, and the rail track was extracted steadily by using the local elevation information, global geometric parallel information and multi-frame information of the rail track. Then, the forward limit of train passage was constructed based on the extracted rail track position in real time. Secondly, based on the point cloud depth map and gradient and distance characteristics, the obstacle clustering problem in non-paved road scenarios was solved, and the track information was used for multi-target tracking to improve the stability of target tracking. By real train test on metro scene, it was proved that the proposed method could extract track position accurately and reliably, it also could detect and track targets.

M. I. Mekhedov, E. A. Sotnikov, E. A. Mekhedova

Introduction. The currently applied system of passenger and suburban train traffic in the Russian railway transport does not completely consider the passenger satisfaction of the provided service quality. The authors suggest determining whether supplements of the existing quality assessment method of passenger and suburban traffic are reasonable in terms of the arrival, departure, running schedule and considering the passenger satisfaction of the existing train traffic.Materials and methods. The researches proposed the concept of “passenger dissatisfaction of the provided service quality in terms of passenger and suburban train traffic” (or “rate of passenger dissatisfaction of the train schedule implementation”). The passenger and suburban trains with the schedule deflection should be rated by the weighting coefficient of significance. It is necessary to consider not only train capacity and delay duration, but also the purposes of the trip and technological factors of the train running.Results. The authors determine the numerical value functional of the delayed passenger and suburban trains. Moreover, the authors identify both the initial value of the train capacity and the train delay and the corresponding coefficient of the passenger dissatisfaction growth. The article presents requirements to the studies concerning the rate of passenger psychological sensitivity to the train delays. The developed model allows conducting the necessary research for the quality assessment system of passenger and suburban train traffic.Discussion and conclusion. The solution of the presented problem is important both for the protection of passenger interests and for maintenance and improving of the railway transport image. In addition, the detailed solution will minimize losses in goods traffic while passenger and suburban train commitment to timetable.

Huawei LIU, Yong LIU, Fan JIANG et al.

The operation in the locomotive depot is an important part for freight railway operations. The efficiency and safety of the operation in the locomotive depot directly affect the ef ficiency and effectiveness of railway operating enterprises.In this paper, an intelligent system for locomotive operations was designed to explore and research the application of automatic operation functions such as automatic wake-up and sleep, automatic maintenance, remote automatic setting of operating parameters,automatic shunting in the field of freight railway. The application effect shows that the above functions of the system improve the ef ficiency of operations in the locomotive depot, strengthen the normalization and safety of operations in the depot, and reduce the labor intensity of the operators.

V. Moiseev, T. Komarova, O. Komarova et al.

Guangtai CHEN, Zheng LI, Mengyu LU et al.

The current development status of rail transit vehicle fire prevention and control system technology at home and abroad were introduced, and rail transit vehicle fire prevention and control system technology related standards were summarized. The R & D requirements of fire prevention and control system were analyzed, and the key technologies of rail transit vehicle fire prevention and control system were put forward, which provided some ideas for the R & D of fire prevention and control system for rail vehicles in China.

S. L. Samoshkin, A. O. Meyster, M. A. Yukhnevskiy

The article examines methodical issues of selection of heat insulation materials, their properties affecting energy efficiency, as well as methodical issues of experimental determination of heat insulation properties of the car body. This issue has become recently relevant due to the increased requirements to saving of the fuel and energy resources and to improvement of the passenger travel comfort. Domestic and international regulatory documents are analyzed from this perspective.Contemporary materials used for heat insulation of the car body, methods of determination of the average heat transfer coefficient and requirements to such materials are examined. Review of the test results of the most widely spread passenger cars; the issue is arisen regarding necessity of putting the obtained results of experimental research in compliance with the actual operating conditions with regard to the changes of temperature, air humidity and car movement speed.The article examines in details disadvantages of the currently used standardized method of determination of the average heat transfer coefficient. The issues affecting accuracy of determination of this parameter are underlined, which occur in the experimental research and in processing of the obtained results. Practical use of obtained results for designing of new rolling stock is examined.Ultimately, the authors conclude that the valid domestic standardized method of determination of the average heat transfer coefficient does not take into account the number of important conditions. Examination of effect of these conditions on the results of experimental research allows the authors to make conclusion regarding necessity of review of methodical and regulatory and technical documentation for the test methods.

Guojuan ZHOU, Bingjie XUE, Yongbin LI et al.

This paper introduced the influence of changing the excitation chopper of auxiliary generator to DC input on the circuit of diesel locomotive, and expounded the phenomena of faults, the search for faults, the causes of faults and the solutions of faults. It was determined that the faults were caused by the instantaneous connection of the supporting capacitor in the excitation chopper after the circuit design changes. Pool voltage drops, resulting in digital signal acquisition errors, which led to logical control disorder. Finally, the solution to the problem was put forward, and the correctness of the analysis conclusion and the solution was verified by the test.

Aleksander Pavlyukov, Alexander Buynosov, Aleksander Mironov et al.

The methods that are widely used today to determine the required locomotive fleet, the Corresponding maintenance and repair system consider the locomotive as a whole, without taking into account the technical condition of its individual units, which have a limited life cycle. Furthermore, the methods used today do not take into account the time spent on relocation from an operational locomotive depot to a service depot and back. The purpose of this study is to develop the methods for determining the number of locomotives based on the anticipated workloads for specific operational sections, the necessary accompanying maintenance and repair, the optimized repair cycle structure with due account of the available resources of the limiting units in the railroad operating domain which are capable of taking into account the technical condition of equipment (failures, repair costs, and time spent on relocation from one depot to another). A model for organization of repair of gas turbine locomotives assigned to operational locomotive depots while undergoing repair in service locomotive depots is proposed. Using this model, it is possible to develop a software product for distributing routine locomotive repairs among service providers, thus optimizing the workload of the latter.

A. Klimov, V. Kupriyanovsky, A. Stepanenko et al.

Kristián Čulík, Alica Kalašová, Ján Palúch

This paper is about current state of parking problem in two different housing estates. We have done a traffic survey in housing estate Klokocina situated in city of Nitra and similar survey in housing estate Sekcov in Presov. We have counted cars, which parked on the streets and also parking spaces. City offices in both cities had given us the necessary documentation about numbers of registered cars and flats in these areas. The results from traffic survey are alarming. The car parks have insufficient capacity and many cars stop at forbidden or dangerous areas of the streets. This paper includes results, which were used as a base data for transport planning. We have focused on the most critical areas of housing estates, where the problem with parking was emerged.