Hasil untuk "Railroad engineering and operation"

Mayuranath SureshKumar, Hanumanthrao Kannan

Classic problem-space theory models problem solving as a navigation through a structured space of states, operators, goals, and constraints. Systems Engineering (SE) employs analogous constructs (functional analysis, operational analysis, scenarios, trade studies), yet still lacks a rigorous systems-theoretic representation of the problem space itself. In current practice, reasoning often proceeds directly from stakeholder goals to prescriptive artifacts. This makes foundational assumptions about the operational environment, admissible interactions, and contextual conditions implicit or prematurely embedded in architectures or requirements. This paper addresses that gap by formalizing the problem space as an explicit semantic world model containing theoretical constructs that are defined prior to requirements and solution commitments. These constructs along with the developed axioms, theorems and corollary establish a rigorous criterion for unambiguous boundary semantics, context-dependent interaction traceability to successful stakeholder goal satisfaction, and sufficiency of problem-space specification over which disciplined reasoning can occur independent of solution design. It offers a clear distinction between what is true of the problem domain and what is chosen as a solution. The paper concludes by discussing the significance of the theory on practitioners and provides a dialogue-based hypothetical case study between a stakeholder and an engineer, demonstrating how the theory guides problem framing before designing any prescriptive artifacts.

Daniel Rodriguez-Cardenas, Xiaochang Li, Marcos Macedo et al.

Large language models for code are advancing fast, yet our ability to evaluate them lags behind. Current benchmarks focus on narrow tasks and single metrics, which hide critical gaps in robustness, interpretability, fairness, efficiency, and real-world usability. They also suffer from inconsistent data engineering practices, limited software engineering context, and widespread contamination issues. To understand these problems and chart a path forward, we combined an in-depth survey of existing benchmarks with insights gathered from a dedicated community workshop. We identified three core barriers to reliable evaluation: the absence of software-engineering-rich datasets, overreliance on ML-centric metrics, and the lack of standardized, reproducible data pipelines. Building on these findings, we introduce BEHELM, a holistic benchmarking infrastructure that unifies software-scenario specification with multi-metric evaluation. BEHELM provides a structured way to assess models across tasks, languages, input and output granularities, and key quality dimensions. Our goal is to reduce the overhead currently required to construct benchmarks while enabling a fair, realistic, and future-proof assessment of LLMs in software engineering.

Paloma Guenes, Rafael Tomaz, Maria Teresa Baldassarre et al.

The Impostor Phenomenon (IP) impacts a significant portion of the Software Engineering workforce, yet it is often viewed primarily through an internal individual lens. In this position paper, we propose framing the prevalence of IP as a form of Human Debt and discuss the relation with the ICSE2026 Pre Survey on the Future of Software Engineering results. Similar to technical debt, which arises when short-term goals are prioritized over long-term structural integrity, Human Debt accumulates due to gaps in psychological safety and inclusive support within socio-technical ecosystems. We observe that this debt is not distributed equally, it weighs heavier on underrepresented engineers and researchers, who face compounded challenges within traditional hierarchical structures and academic environments. We propose cultural refactoring, transparency and active maintenance through allyship, suggesting that leaders and institutions must address the environmental factors that exacerbate these feelings, ensuring a sustainable ecosystem for all professionals.

Zhen Wang, Huajian Li, Zhiqiang Yang et al.

PurposeSevere scarcity of natural river sand (RS), exacerbated by environmental protection policies and extraction constraints, has significantly impacted aggregate supply for railway concrete. While manufactured sand (MS) offers a substitute for RS in railway applications, its widespread adoption in high-strength railway prestressed structures is challenged by lack of drying shrinkage and creep research data on concrete.Design/methodology/approachHigh-strength manufactured sand concrete (MSC) was prepared using MS with varying lithologies and stone powder contents. Its drying shrinkage and creep behaviors were evaluated in accordance with the Chinese standard GB/T 50082. The deformation mechanism was analyzed by combining nano-scratch testing.FindingsCompared to RS concrete, MSC from all tested lithologies showed higher drying shrinkage but lower creep deformation. The drying shrinkage rose steadily with increased stone powder content, while the creep strain displayed a distinct non-linear trend, decreasing first before rising. To prepare low-deformation MSC, select high-strength MS and limit stone powder content not greater 10%. Nano-scratch tests indicated that harder MS particles suppress microcracking at the interfacial transition zone (ITZ), improving the creep resistance. The predictive models for drying shrinkage and creep were also developed by incorporating coefficients for stone powder and lithology effects.Originality/valueThese findings serve as a foundation for the application of MSC in railway prestressed structures, offering both theoretical and practical guidance.

PU Quanwei, LIAO Congjian, ZHONG Xiaobo et al.

To facilitate through operation on railway lines with different gauges, this paper presents the design of a gauge-changeable locomotive bogie along with wheelsets that are adaptable to gauge changes between 1 000 mm and 1 435 mm. Based on a wheel-locking mode that was selected after analyzing various locking and unlocking methods, the overall bogie solution and main technical parameters were established. The design focused on the wheelsets and the gauge-changing process, including the internal structure of the locking and unlocking device, the principles of locking and unlocking, and the design of the pin spring and axial positioning spring. Subsequent motion simulation analysis identified the friction coefficient between the pin and the wedge sliding block. The gauge-changing process was described in five stages: entry, unlocking, gauge changing, locking, and exit. Meanwhile, the principle of a ground transformation facility working in conjunction with the gauge-changeable wheelsets was explained. The new gauge-changeable locomotive bogie solution, alongside the locking-unlocking principle of the wheelsets and gauge-changing process proposed in this paper serve as a reference for further research and engineering application of gauge-changeable locomotive bogies.

Max Neuwinger, Dirk Riehle

The design of effective programming languages, libraries, frameworks, tools, and platforms for data engineering strongly depends on their ease and correctness of use. Anyone who ignores that it is humans who use these tools risks building tools that are useless, or worse, harmful. To ensure our data engineering tools are based on solid foundations, we performed a systematic review of common programming mistakes in data engineering. We focus on programming beginners (students) by analyzing both the limited literature specific to data engineering mistakes and general programming mistakes in languages commonly used in data engineering (Python, SQL, Java). Through analysis of 21 publications spanning from 2003 to 2024, we synthesized these complementary sources into a comprehensive classification that captures both general programming challenges and domain-specific data engineering mistakes. This classification provides an empirical foundation for future tool development and educational strategies. We believe our systematic categorization will help researchers, practitioners, and educators better understand and address the challenges faced by novice data engineers.

Marvin Wyrich, Lloyd Montgomery

A well-rounded software engineer is often defined by technical prowess and the ability to deliver on complex projects. However, the narrative around the ideal Software Engineering (SE) candidate is evolving, suggesting that there is more to the story. This article explores the non-technical aspects emphasized in SE job postings, revealing the sociotechnical and organizational expectations of employers. Our Thematic Analysis of 100 job postings shows that employers seek candidates who align with their sense of purpose, fit within company culture, pursue personal and career growth, and excel in interpersonal interactions. This study contributes to ongoing discussions in the SE community about the evolving role and workplace context of software engineers beyond technical skills. By highlighting these expectations, we provide relevant insights for researchers, educators, practitioners, and recruiters. Additionally, our analysis offers a valuable snapshot of SE job postings in 2023, providing a scientific record of prevailing trends and expectations.

O. A. Suslow, I. V. Khromov

Introduction. Currently, contact-fatigue defects prevail on rails with increased intensity of lateral and vertical rail wear. The authors consider it essential to develop rational repair profiles for sections with different track plan, as current repair profile regulations are insufficient, while taking into account the wheel and rail interaction in curves of different radii and straight lines.Materials and methods. Optimal rail head repair profiles were determined for different operating conditions by calculating the effect of wheel and rail profiles on the force impact on the track using the Universal Mechanism software. The rational parameters of the rail head tread surface were selected by mathematical analysis. The authors modeled variants of a conical wheel with two-point contact: a new wheel and a moderately worn profile. R65 type rail profiles were modeled: new profiles, R65 medium-grid, R65K.Results. The calculation and analysis data formed the basis for the recommended tread surface parameters to minimise the intensity of defect formation and rail wear. The authors developed rail head repair profiles for various operating conditions to be applied in grinding programmes.Discussion and conclusion. Grinding assignment criteria should include the basic parameters of the tread surface: central rolling radius R1 and arc length of the central radius d. The resulting repair profiles could be used to update the rail track grinding regulations.

Juan M. Murillo, Jose Garcia-Alonso, Enrique Moguel et al.

As quantum computers advance, the complexity of the software they can execute increases as well. To ensure this software is efficient, maintainable, reusable, and cost-effective -key qualities of any industry-grade software-mature software engineering practices must be applied throughout its design, development, and operation. However, the significant differences between classical and quantum software make it challenging to directly apply classical software engineering methods to quantum systems. This challenge has led to the emergence of Quantum Software Engineering as a distinct field within the broader software engineering landscape. In this work, a group of active researchers analyse in depth the current state of quantum software engineering research. From this analysis, the key areas of quantum software engineering are identified and explored in order to determine the most relevant open challenges that should be addressed in the next years. These challenges help identify necessary breakthroughs and future research directions for advancing Quantum Software Engineering.

Johan Cederbladh, Antonio Cicchetti

In this paper we discuss the growing need for system behaviour to be validated and verified (V&V'ed) early in model-based systems engineering. Several aspects push companies towards integration of techniques, methods, and processes that promote specific and general V&V activities earlier to support more effective decision-making. As a result, there are incentives to introduce new technologies to remain competitive with the recently drastic changes in system complexity and heterogeneity. Performing V&V early on in development is a means of reducing risk for later error detection while moving key activities earlier in a process. We present a summary of the literature on early V&V and position existing challenges regarding potential solutions and future investigations. In particular, we reason that the software engineering community can act as a source for inspiration as many emerging technologies in the software domain are showing promise in the wider systems domain, and there already exist well formed methods for early V&V of software behaviour in the software modelling community. We conclude the paper with a road-map for future research and development for both researchers and practitioners to further develop the concepts discussed in the paper.

Oleksandr Kosenkov, Michael Unterkalmsteiner, Jannik Fischbach et al.

Context: Regulatory acts are a challenging source when eliciting, interpreting, and analyzing requirements. Requirements engineers often need to involve legal experts who, however, may often not be available. This raises the need for approaches to regulatory Requirements Engineering (RE) covering and integrating both legal and engineering perspectives. Problem: Regulatory RE approaches need to capture and reflect both the elementary concepts and relationships from a legal perspective and their seamless transition to concepts used to specify software requirements. No existing approach considers explicating and managing legal domain knowledge and engineering-legal coordination. Method: We conducted focus group sessions with legal researchers to identify the core challenges to establishing a regulatory RE approach. Based on our findings, we developed a candidate solution and conducted a first conceptual validation to assess its feasibility. Results: We introduce the first version of our Artifact Model for Regulatory Requirements Engineering (AM4RRE) and its conceptual foundation. It provides a blueprint for applying legal (modelling) concepts and well-established RE concepts. Our initial results suggest that artifact-centric RE can be applied to managing legal domain knowledge and engineering-legal coordination. Conclusions: The focus groups that served as a basis for building our model and the results from the expert validation both strengthen our confidence that we already provide a valuable basis for systematically integrating legal concepts into RE. This overcomes contemporary challenges to regulatory RE and serves as a basis for exposure to critical discussions in the community before continuing with the development of tool-supported extensions and large-scale empirical evaluations in practice.

MA Qun, SHENG Longjiang, YAO Yuan et al.

The secondary suspension parameters of locomotives have a significant influence on the stability of heavy-haul couplers under compression. This paper aimed to explore the reasonable matching between 102-type couplers and the secondary suspension parameters of heavy-haul locomotives. A detailed two-locomotive dynamics model was established by using SIMPACK software, incorporating a 102-type coupler and HXD1 eight-axle heavy-haul locomotives. The mechanical characteristics of the coupler and the safety performance of the heavy-haul locomotives were analyzed under different calculation conditions. Moreover, the influence of secondary suspension parameters on locomotive safety was compared at different coupler free angles and under varying longitudinal forces. The results indicate that at low longitudinal pressure, the coupler angle stabilizes at a free angle, and the lateral force on the locomotive's wheel axles increases with an increasing free angle of the coupler and a higher lateral stiffness of the secondary suspension. This relationship was independent of the longitudinal force of the coupler. As the longitudinal coupler pressure increases, resulting in deflection to overcome the pre-compression load of the restoration block, the coupler angle further increases. At this stage, an appropriate increase in the lateral stiffness of the secondary suspension helped to maintain coupler stability along with just a minimal impact. In order to secure safe train operation in braking conditions, it is recommended to control coupler free angles within 6°, and set the lateral stiffness of the secondary system on a single side of bogies within the range of 0.45-0.60 kN/mm. Additionally, the recommended secondary lateral stop clearance includes a 35 mm free clearance plus a 5 mm elastic clearance.

Raphael Pfaff

Abstract The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive (e.g. in the case of depot operations) or highly inefficient (e.g. in industrial railways). These parts are typically managed on-sight, i.e. with no signalling and train protection systems ensuring the freedom of movement. This is possible due to the rather short braking distances of individual vehicles and shunting consists. The present article analyses the braking behaviour of such shunting units. For this purpose, a dedicated model is developed. It is calibrated on published results of brake tests and validated against a high-definition model for low-speed applications. Based on this model, multiple simulations are executed to obtain a Monte Carlo simulation of the resulting braking distances. Based on the distribution properties and established safety levels, the risk of exceeding certain braking distances is evaluated and maximum braking distances are derived. Together with certain parameters of the system, these can serve in the design and safety assessment of driver assistance systems and automation of these processes.

HAN Guopeng, YANG Yuze, ZHAO Lili et al.

To meet the power requirements of DC-powered rail vehicles equipped with hydrogen fuel cell power systems operating at high busbar voltage conditions, the application of two-stage DC/DC converters in series can be adopted for voltage boosting. In order to explore the dynamic operational characteristics in this application, a system control strategy by building a hydrogen-powered system for rail vehicles was proposed, which was composed of 100 kW fuel cells in series with two-stage DC/DC converters, with the power cells directly connected to the busbar. Revealed in the dynamic operational test carried out with the circuit system of trams on a test bench specially established. The results show that the state of charge (SOC) of the power battery consistently approaches 45% when the initial value is preset within 40%~60% of its allowable working range, and the maximum busbar voltage fluctuations during traction and braking range between -4.5% and 3.4%. Moreover, the hybrid power system demonstrates a quick response to the varying power demands in different vehicle operating modes while the power of fuel cells varies gently. Additionally, the energy control strategy allows for preset system troubleshooting actions in response to different fault types. Despite the presence of large low-frequency current ripples between the two-stage DC/DC converters, the voltage ripple observed during testing is less than 1.86%. As a result, the hybrid power system operates smoothly throughout the whole test.

Michał Żochowski

Abstract: The author presented the legal status in relation to the use of balustrades on bridges. The analysis presented regulations on technical conditions on bridges and regulations on occupational health and safety. The article attempts to carry out the analysis in such a way that the conclusions are universal and can be applied to all types of objects. It has been shown that the balustrades are an element which protects against falling from a height. This type of collective protection elements should be used when there is a risk of falling from a height. Keywords: Balustrade, Bridge, Safety

Bishal Lakha, Kalyan Bhetwal, Nasir U. Eisty

Context: On top of the inherent challenges startup software companies face applying proper software engineering practices, the non-deterministic nature of machine learning techniques makes it even more difficult for machine learning (ML) startups. Objective: Therefore, the objective of our study is to understand the whole picture of software engineering practices followed by ML startups and identify additional needs. Method: To achieve our goal, we conducted a systematic literature review study on 37 papers published in the last 21 years. We selected papers on both general software startups and ML startups. We collected data to understand software engineering (SE) practices in five phases of the software development life-cycle: requirement engineering, design, development, quality assurance, and deployment. Results: We find some interesting differences in software engineering practices in ML startups and general software startups. The data management and model learning phases are the most prominent among them. Conclusion: While ML startups face many similar challenges to general software startups, the additional difficulties of using stochastic ML models require different strategies in using software engineering practices to produce high-quality products.

ZHANG Qingsong, ZHANG Bing, QIN Yi

Aiming at the problem that the fault information of high-speed train wheel bearing is weak and difficult to extract, a fault feature extraction and recognition model for vibration signal of high-speed train bearing based on variational mode decomposition and adaptive particle swarm optimization-support vector machine was proposed. To avoid the under-decomposition or over-decomposition of VMD, the selection principle of <italic>k</italic> was suggested from the perspective of energy entropy change rate. The fault features obtained by VMD were input into SVM for different bearing fault identification. The experimental results show that traditional SVM has better effect on the diagnosis of rolling element fault and composite type fault, but the diagnosis effect on cage fault is relatively poor. Therefore, APSO algorithm was used to optimize the core parameters of the SVM, which further improved the recognition accuracy of cage fault and realized the effective identification for the fault bearings of high-speed train.

LIN Jun, YUAN Hao, LIU Yue et al.

As an important component to carry running train, the working state of the track has an important impact on the safety of the subway operation. Traditional manual detection or rail inspection vehicles can not operate until subway operation ends, leading to low work efficiency. Aiming at this problem, an track line status detection system based on subway passenger trains was proposed. A high frequency line-scanning camera was used to collect real-time images and a lightweight backbone RegNet was used to extract the deep features of track line images. Then, a BiFPN was added to fuse multi-layer features. Finally, the features were send to a object detection head for track line status real-time detection. Combined with the hard sample mining based on cloud-edge collaboration and model acceleration technologies, the algorithm can meet the detection performance of high accuracy and real-time. The experiments show that the mean average precision of detection for 11 types of rail failure and fastener status reaches 0.951, and the inference speed is greater than 20 f/s, which proves that the system can realize real-time track line status detection during the subway passenger operation.

Toufique Ahmed, Premkumar Devanbu

Well-trained machine-learning models, which leverage large amounts of open-source software data, have now become an interesting approach to automating many software engineering tasks. Several SE tasks have all been subject to this approach, with performance gradually improving over the past several years with better models and training methods. More, and more diverse, clean, labeled data is better for training; but constructing good-quality datasets is time-consuming and challenging. Ways of augmenting the volume and diversity of clean, labeled data generally have wide applicability. For some languages (e.g., Ruby) labeled data is less abundant; in others (e.g., JavaScript) the available data maybe more focused on some application domains, and thus less diverse. As a way around such data bottlenecks, we present evidence suggesting that human-written code in different languages (which performs the same function), is rather similar, and particularly preserving of identifier naming patterns; we further present evidence suggesting that identifiers are a very important element of training data for software engineering tasks. We leverage this rather fortuitous phenomenon to find evidence that available multilingual training data (across different languages) can be used to amplify performance. We study this for 3 different tasks: code summarization, code retrieval, and function naming. We note that this data-augmenting approach is broadly compatible with different tasks, languages, and machine-learning models.

Rodrigo Henrique Barbosa Monteiro, Maurício Ronny de Almeida Souza, Sandro Ronaldo Bezerra Oliveira et al.

Gamification has been used to motivate and engage participants in software engineering education and practice activities. There is a significant demand for empirical studies for the understanding of the impacts and efficacy of gamification. However, the lack of standard procedures and models for the evaluation of gamification is a challenge for the design, comparison, and report of results related to the assessment of gamification approaches and its effects. The goal of this study is to identify models and strategies for the evaluation of gamification reported in the literature. To achieve this goal, we conducted a systematic mapping study to investigate strategies for the evaluation of gamification in the context of software engineering. We selected 100 primary studies on gamification in software engineering (from 2011 to 2020). We categorized the studies regarding the presence of evaluation procedures or models for the evaluation of gamification, the purpose of the evaluation, the criteria used, the type of data, instruments, and procedures for data analysis. Our results show that 64 studies report procedures for the evaluation of gamification. However, only three studies actually propose evaluation models for gamification. We observed that the evaluation of gamification focuses on two aspects: the evaluation of the gamification strategy itself, related to the user experience and perceptions; and the evaluation of the outcomes and effects of gamification on its users and context. The most recurring criteria for the evaluation are 'engagement', 'motivation', 'satisfaction', and 'performance'. Finally, the evaluation of gamification requires a mix of subjective and objective inputs, and qualitative and quantitative data analysis approaches. Depending of the focus of the evaluation (the strategy or the outcomes), there is a predominance of a type of data and analysis.