Hasil untuk "Bridge engineering"

Junwei Yu, Mufeng Yang, Yepeng Ding et al.

The proliferation of AI-powered search engines has shifted information discovery from traditional link-based retrieval to direct answer generation with selective source citation, creating new challenges for content visibility. While existing Generative Engine Optimization (GEO) approaches focus primarily on semantic content modification, the role of structural features in influencing citation behavior remains underexplored. In this paper, we propose GEO-SFE, a systematic framework for structural feature engineering in generative engine optimization. Our approach decomposes content structure into three hierarchical levels: macro-structure (document architecture), meso-structure (information chunking), and micro-structure (visual emphasis), and models their impact on citation probability across different generative engine architectures. We develop architecture-aware optimization strategies and predictive models that preserve semantic integrity while improving structural effectiveness. Experimental evaluation across six mainstream generative engines demonstrates consistent improvements in citation rate (17.3 percent) and subjective quality (18.5 percent), validating the effectiveness and generalizability of the proposed framework. This work establishes structural optimization as a foundational component of GEO, providing a data-driven methodology for enhancing content visibility in LLM-powered information ecosystems.

Long Lu, Taishuai Huang, Guangwu Tang

Abstract Compared with the two-tower suspension bridge, the seismic response of the middle tower is crucial for the seismic design of triple-tower suspension bridges. A finite element model was developed for a suspension bridge. The seismic responses of a triple-tower suspension bridge with an elastic cable (EC) or a fluid viscous damper (FVD) installed between the tower and the deck were analyzed, and the application of an energy dissipation central buckle (EDCB) which was composed of multiple buckling-restrained braces (BRBs) installed at the mid-span in the triple-tower suspension bridge was discussed. Several novel seismic mitigation systems, such as the combination of EDCB and FVD, and the combination of EDCB and EC, were implemented to control the seismic responses of triple-tower suspension bridges. The effects of different seismic mitigation systems on the seismic responses of suspension bridges were studied. Additionally, the seismic performance of triple-tower suspension bridges was evaluated using the analytic hierarchy process (AHP) method, and the selection of parameters for seismic mitigation systems in suspension bridges was discussed. The results show that the longitudinal displacement (LD) of suspension bridges can be effectively controlled by using EC or FVD; however, the internal forces of the middle tower significantly increase due to the use of EC. Applying an energy dissipation central buckle (EDCB) is an effective measure to reduce the internal forces of the middle tower in triple-tower suspension bridges. The combination of EDCB and traditional seismic mitigation devices is highly beneficial for improving the seismic performance of triple-tower suspension bridges. The analytic hierarchy process (AHP) method can be used to select the optimal parameters for seismic mitigation systems. The results indicate that Case 23 is the optimal solution for controlling the seismic responses of the triple-tower suspension bridge.

Cheng Hui, Yong Ouyang, Zhifeng Duan et al.

ABSTRACT Deep coal and rock gas, as an important component of unconventional natural gas, has attracted much attention due to its abundant reserves. However, in the current process of coal and rock gas development, underground accidents of burying drilling tools due to sand bridge stuck drill accidents often occur, which is one of the important difficulties faced by coal and rock gas wells at present. This paper systematically studies the mechanism of stuck drill caused by sand Bridges in deep coal‐rock‐gas horizontal Wells for the problem of stuck drill in sand Bridges. Studies show that collapse and block shedding caused by wellbore instability a key factors in the formation of sand bridges. Traditional models have limited applicability in deep coal‐rock gas reservoirs because they ignore this factor. Based on the drilling conditions, considering the “bulldozer effect” and the influence of coal seam collapse and block drop, the calculation models of the stuck pipe resistance of permeable and impermeable sand bridges were established, respectively. The calculation methods of the sand bridge volume and the additional axial force and torque were derived. Through sensitivity analysis, the results show that the length of the sand bridge, the annular clearance, and the internal and external pressure difference significantly affect the stuck pipe resistance. Among them, the resistance effect of the impermeable sand bridge is particularly prominent. The engineering applicability of the model was verified through the example of the horizontal well for coal and rock gas in Changqing. The research proposes control measures such as optimizing the performance of drilling fluid, staged drilling, and controlling the drilling speed, providing theoretical support and technical reference for the drilling operation of deep coal, rock, and gas horizontal Wells.

Alif Al Arefin Prodhan, Mahmuda Mutahara, Sara Nowreen et al.

Coastal communities in Bangladesh face recurring cyclones that repeatedly undermine their livelihoods. The arrival of COVID-19 in 2020 coincided with Cyclone Amphan, creating a compound disaster that generated cascading impacts across livelihood capitals. This study examined how different livelihood groups were affected by these overlapping crises in two coastal sub-districts namely Shyamnagar and Dacope. Participatory Rural Appraisal (PRA) tools, including 16 focus group discussions, were complemented by 24 key informant interviews to capture both community experiences and institutional perspectives. Matrix ranking exercises were used to identify and prioritize risks under livelihood capitals. Findings show that impacts were not uniform. Land-owning farmers and aquaculture-based fishers retained some productive assets, while landless farmers, day labourers, artisanal fishers, small business owners, and women experienced severe and prolonged income losses. A common coping strategy was diversification into mixed livelihood activities, though these options were constrained during the pandemic. The paper recommends short-term coping mechanisms including interest free loans, livestock support, and embankment protection, while longer-term adaptation initiatives should focus on livelihood diversification, vocational training, and stronger coordination among stakeholders. These findings highlight how compound disasters amplify pre-existing vulnerabilities and erode coping capacity, underscoring the need for integrated, livelihood-sensitive disaster governance in coastal Bangladesh.

Mia Mohammad Imran, Tarannum Shaila Zaman

Large Language Models (LLMs) are increasingly used in empirical software engineering (ESE) to automate or assist annotation tasks such as labeling commits, issues, and qualitative artifacts. Yet the reliability and reproducibility of such annotations remain underexplored. Existing studies often lack standardized measures for reliability, calibration, and drift, and frequently omit essential configuration details. We argue that LLM-based annotation should be treated as a measurement process rather than a purely automated activity. In this position paper, we outline the \textbf{Operationalization for LLM-based Annotation Framework (OLAF)}, a conceptual framework that organizes key constructs: \textit{reliability, calibration, drift, consensus, aggregation}, and \textit{transparency}. The paper aims to motivate methodological discussion and future empirical work toward more transparent and reproducible LLM-based annotation in software engineering research.

Hashini Gunatilake, John Grundy, Rashina Hoda et al.

Empathy plays a crucial role in software engineering (SE), influencing collaboration, communication, and decision-making. While prior research has highlighted the importance of empathy in SE, there is limited understanding of how empathy manifests in SE practice, what motivates SE practitioners to demonstrate empathy, and the factors that influence empathy in SE work. Our study explores these aspects through 22 interviews and a large scale survey with 116 software practitioners. Our findings provide insights into the expression of empathy in SE, the drivers behind empathetic practices, SE activities where empathy is perceived as useful or not, and the other factors that influence empathy. In addition, we offer practical implications for SE practitioners and researchers, offering a deeper understanding of how to effectively integrate empathy into SE processes.

Theresita Herni Setiawan, Andreas Roy, Liyanto Eddy et al.

Abstrak   Jembatan adalah infrastruktur penghubung dua bagian daerah terputus karena adanya rintangan. Berdasarkan bentangnya, jembatan diklasifikasikan menjadi jembatan pendek dengan panjang L‰¤ 30 m, jembatan sedang dengan panjang 30 < L < 100 m, dan jembatan panjang dengan panjang L ‰¥ 100 m. Tahun 2019 Bina Teknik Jalan dan Jembatan telah mendata 18.648 jembatan di Indonesia yang sebagian besar belum diketahui tahun konstruksinya. Tahun konstruksi jembatan dibutuhkan sebagai proses identifikasi usia jembatan berkaitan dengan usia pakai, rencana sistem operasi dan manajemen pemeliharaan jembatan. Penelitian ini melakukan studi perbandingan tahun konstruksi data Bintek JalJem dengan estimasi tahun konstruksi jembatan menggunakan metodologi data satelit remote sensing NDVI dan NDWI. Hasil pembahasan mendapatkan estimasi tahun konstruksi jembatan dengan remote sensing kasus jembatan panjang, persentase sebaran NDWI mencapai 63,7%, NDVI mencapai 63,05%. Untuk kasus jembatan sedang, persentase sebaran NDWI mencapai 58,61%, NDVI mencapai 52,96%. Untuk kasus jembatan pendek, persentase sebaran NDWI mencapai 55,78%, NDVI mencapai 43,7%. Simpulan penelitian mengianjurkan menggunakan metode NDWI untuk mendapatkan hasil perkiraan tahun konstruksi lebih tepat tanpa kunjungan fisik ke lokasi. Untuk mendapatkan ketepatan estimasi tahun konstruksi disarankan menggunakan index lain yang memiliki keakuratan dengan lingkup tinjauan, dengan harapan dapat mengidentifikasi jenis material obyek tinjauan. Hal ini bertujuan membuat prediksi (forecasting) sistem operasi dan manajemen pemeliharaan konstruksi tinjauan.   Kata kunci: estimasi tahun konstruksi, jembatan, remote sensing, NDWI, NDVI     Abstract   A bridge is infrastructure that connect two parts of an area that separated by an obstacle. Based on its span, a bridge is classified into short bridges with a length of L‰¤ 30 m, medium bridges with a length of 30 < L < 100 m, and long bridges with a length of L ‰¥ 100 m. In 2019, Road and Bridge Engineering Development recorded 18,648 bridges in Indonesia, most of which the year of construction is unknown. The year of bridge construction is needed for identifying the age of the bridge in relation to its service life, operation system plan, and bridge maintenance management. This study conducts a comparison of the construction year data from Road and Bridge Engineering Development with estimated construction years using satellite remote sensing methodologies, specifically NDVI and NDWI. The results show that the estimated construction year for long-bridge cases using remote sensing, with an NDWI distribution percentage of 63.7% and an NDVI of 63.05%. For medium-bridge cases, the NDWI distribution percentage reaches 58.61%, while NDVI reaches 52.96%. For short-bridge cases, the NDWI distribution percentage is 55.78%, and the NDVI is 43.7%. The study concludes by recommending the use of the NDWI method to obtain more accurate estimates of the construction year without the need for physical visits to the to obtain accurate construction year estimates, it is also recommended to use other indices that are accurate with the scope of the review. It is hoped that this index can identify the type of material of the object being reviewed. This aims to make forecasting of the operation system and maintenance management for the surveyed construction.   Keywords: estimated year of construction, bridge, remote sensing, NDWI, NDVI

YANG Zaiqing, JIN Shengji, ZHANG Xiaogang et al.

Steel slag and iron tailings are typical industrial solid waste. Their large-scale stockpiling occupies a significant amount of land and has a negative impact on the environment. To respond to the Guiding Opinions on the Comprehensive Utilization of Bulk Solid Waste in the 14th Five Year Plan and expand the use of steel slag powder and iron tailings sand as concrete admixtures and aggregates, this study prepared steel slag powder-cement-based self-compacting iron tailings mortar. The workability index of mortar was determined through two tests: the flow expansion test and the V-shaped funnel test. Additionally, the compressive strength of the mortar was measured using a servo press. The results show that as the replacement rate (Rs) of steel slag powder increases, the flow expansion (e) of the mortar increases, the V-shaped funnel time (Tv) decreases, and the compressive strength (fcu) decreases. Steel slag powders of 300 mesh and 100 mesh show an increase in e by 13.5% and 18.7% and a decrease in Tv by 24.3% and 29.7%, respectively, at Rs=40% compared to Rs=0. The fcu of the three age groups (3 d, 28 d, and 90 d) of the two kinds of steel slag powders decreases by 33.0%, 34.3%, and 20.0% and 43.0%, 40.2%, and 29.3%, respectively. As the replacement rate (Ri) of iron tailings sand increases, e decreases, Tv increases, and fcu first increases and then decreases. Graded iron tailings sand and natural iron tailings sand show a decrease of 14.5% and 31.0% in e and an increase of 31.9% and 52.2% in Tv, respectively, at Ri=40% compared to Ri=0. The Ri corresponding to the peak fcu is 30% and 10%, respectively. Finally, the prediction formulas for compressive strength at the three ages were provided. Validation shows that the predicted compressive strengths agree well with the experimental results, demonstrating the feasibility of the proposed formulas.

Claudio Di Sipio, Riccardo Rubei, Juri Di Rocco et al.

Software engineering (SE) activities have been revolutionized by the advent of pre-trained models (PTMs), defined as large machine learning (ML) models that can be fine-tuned to perform specific SE tasks. However, users with limited expertise may need help to select the appropriate model for their current task. To tackle the issue, the Hugging Face (HF) platform simplifies the use of PTMs by collecting, storing, and curating several models. Nevertheless, the platform currently lacks a comprehensive categorization of PTMs designed specifically for SE, i.e., the existing tags are more suited to generic ML categories. This paper introduces an approach to address this gap by enabling the automatic classification of PTMs for SE tasks. First, we utilize a public dump of HF to extract PTMs information, including model documentation and associated tags. Then, we employ a semi-automated method to identify SE tasks and their corresponding PTMs from existing literature. The approach involves creating an initial mapping between HF tags and specific SE tasks, using a similarity-based strategy to identify PTMs with relevant tags. The evaluation shows that model cards are informative enough to classify PTMs considering the pipeline tag. Moreover, we provide a mapping between SE tasks and stored PTMs by relying on model names.

Johannes Schleiss, Aditya Johri

In this practice paper, we propose a framework for integrating AI into disciplinary engineering courses and curricula. The use of AI within engineering is an emerging but growing area and the knowledge, skills, and abilities (KSAs) associated with it are novel and dynamic. This makes it challenging for faculty who are looking to incorporate AI within their courses to create a mental map of how to tackle this challenge. In this paper, we advance a role-based conception of competencies to assist disciplinary faculty with identifying and implementing AI competencies within engineering curricula. We draw on prior work related to AI literacy and competencies and on emerging research on the use of AI in engineering. To illustrate the use of the framework, we provide two exemplary cases. We discuss the challenges in implementing the framework and emphasize the need for an embedded approach where AI concerns are integrated across multiple courses throughout the degree program, especially for teaching responsible and ethical AI development and use.

Bohui Zhang, Valentina Anita Carriero, Katrin Schreiberhuber et al.

Ontology engineering (OE) in large projects poses a number of challenges arising from the heterogeneous backgrounds of the various stakeholders, domain experts, and their complex interactions with ontology designers. This multi-party interaction often creates systematic ambiguities and biases from the elicitation of ontology requirements, which directly affect the design, evaluation and may jeopardise the target reuse. Meanwhile, current OE methodologies strongly rely on manual activities (e.g., interviews, discussion pages). After collecting evidence on the most crucial OE activities, we introduce \textbf{OntoChat}, a framework for conversational ontology engineering that supports requirement elicitation, analysis, and testing. By interacting with a conversational agent, users can steer the creation of user stories and the extraction of competency questions, while receiving computational support to analyse the overall requirements and test early versions of the resulting ontologies. We evaluate OntoChat by replicating the engineering of the Music Meta Ontology, and collecting preliminary metrics on the effectiveness of each component from users. We release all code at https://github.com/King-s-Knowledge-Graph-Lab/OntoChat.

Lukai Xiang

In mechanics, common energy principles are based on fixed boundary conditions. However, in bridge engineering structures, it is usually necessary to adjust the boundary conditions to make the structure's internal force reasonable and save materials. However, there is currently little theoretical research in this area. To solve this problem, this paper proposes the principle of minimum virtual work for movable boundaries in mechanics through theoretical derivation such as variation method and tensor analysis. It reveals that the exact solution of the mechanical system minimizes the total virtual work of the system among all possible displacements, and the conclusion that the principle of minimum potential energy is a special case of this principle is obtained. At the same time, proposed virtual work boundaries and control conditions, which added to the fundamental equations of mechanics. The general formula of multidimensional variation method for movable boundaries is also proposed, which can be used to easily derive the basic control equations of the mechanical system. The incremental method is used to prove the theory of minimum value in multidimensional space, which extends the Pontryagin's minimum value principle. Multiple bridge examples were listed to demonstrate the extensive practical value of the theory presented in this article. The theory proposed in this article enriches the energy principle and variation method, establishes fundamental equations of mechanics for the structural optimization of movable boundary, and provides a path for active control of mechanical structures, which has important theoretical and engineering practical significance.

Isaiah Lahr, Saghir Alfasly, Peyman Nejat et al.

Searching for similar images in archives of histology and histopathology images is a crucial task that may aid in patient matching for various purposes, ranging from triaging and diagnosis to prognosis and prediction. Whole slide images (WSIs) are highly detailed digital representations of tissue specimens mounted on glass slides. Matching WSI to WSI can serve as the critical method for patient matching. In this paper, we report extensive analysis and validation of four search methods bag of visual words (BoVW), Yottixel, SISH, RetCCL, and some of their potential variants. We analyze their algorithms and structures and assess their performance. For this evaluation, we utilized four internal datasets ($1269$ patients) and three public datasets ($1207$ patients), totaling more than $200,000$ patches from $38$ different classes/subtypes across five primary sites. Certain search engines, for example, BoVW, exhibit notable efficiency and speed but suffer from low accuracy. Conversely, search engines like Yottixel demonstrate efficiency and speed, providing moderately accurate results. Recent proposals, including SISH, display inefficiency and yield inconsistent outcomes, while alternatives like RetCCL prove inadequate in both accuracy and efficiency. Further research is imperative to address the dual aspects of accuracy and minimal storage requirements in histopathological image search.

Zhen Li, Dejian Li, Jincheng Li et al.

In this study, multiple tuned mass dampers (MTMDs) were studied to understand their impact on the human-induced vibration response and comfort level of a pedestrian cable-supported suspension bridge. A spatial finite element model based on a specific engineering case was established. The dynamic characteristics of the bridge under human-induced loads were investigated, and its comfort level under human-induced vibrations was analyzed using the time-history method. Then, this study adjusted the design parameters of the dampers based on various optimal damper parameter expressions. Furthermore, the damping effectiveness of MTMD under different mass ratios (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>μ</mi></mrow></semantics></math></inline-formula>) was evaluated, and it was found that increasing the mass ratio significantly impacts damping performance. Finally, determinant-TMD (TMDD) was introduced, and a comparison between the damping effect, robustness, and performance of TMDD and MTMD was conducted. The results indicate that while increasing the mass ratio does not linearly affect maximum vibration acceleration, the damping effect increases initially and then stabilizes, with a damping rate converging at approximately 55%. However, with the TMDD approach, the maximum damping rate can reach approximately 70%, enhancing comfort levels from the “minimum CL3” achieved with MTMD to the “medium CL2” level. Additionally, while TMDD’s robustness is slightly inferior to MTMD at lower mass ratios, it demonstrates superior robustness at higher mass ratios.

Chongsheng Cheng, Dequan Chen, Shuai Shao et al.

Infrared thermography (IRT) is an effective nondestructive testing method for detecting delamination in concrete structures. However, erroneous data interpretation often diminishes its practical utility due to surface irregularities (e.g., color variations) during inspection. These “noisy conditions” alter the temperature distribution of the structure under solar heating cycles, making it challenging to quantify delamination based on the developed thermal contrast (ΔT). This study experimentally investigates the impact of different surface conditions (bare concrete vs. painted surfaces) on ΔT. Artificial delamination at varying depths was simulated and tested under natural environmental conditions, where the maximum ΔT values for shallow delamination were 9.40 °C (bare concrete), 7.35 °C (yellow paint), and 5.15 °C (white paint), respectively. This study measured and analyzed the absorptivity (bare concrete: 0.652, yellow paint: 0.538, and white paint: 0.369), emissivity, and the temperature difference (δT) between non-delaminated areas and air, revealing their correlation with ΔT variation. Based on the results, three typical scenarios are proposed to correlate δT with delamination detection. These findings contribute to a better understanding of the optimal detection window and present a new approach to quantifying delamination at different time windows. The conclusion also discusses the limitations of this study and future research directions.

Mikhail Lukin, Svetlana Roshchina, Anastasiya Lukina et al.

High air permeability and the presence of thermal bridges at the junctions of wooden frame wall panels have a significant impact on the thermal balance of the building and its operational characteristics. The importance of improving the energy efficiency of nodal interfaces of panels with a wooden frame is undeniable. To date, there is no single generally accepted method for calculating heat losses through nodal interfaces of panels with a wooden frame. Based on the analysis carried out, it is necessary to carry out calculations and measurements that allow creating this calculation methodology. To carry out numerical studies, a list of characteristics and parameters affecting their conduct is formulated: the influence of the thickness of a li-ear-discrete inclusion on the heat-protective properties of the panel docking unit; the thermal conductivity characteristics of the material used to fill linear-discrete inclusions affecting the heat flux density of the node interface; consideration of the influence of the outdoor temperature of air depending on different climatic zones on the density of heat flow. The dependences of the heat flux density on the "inner" surface of the experimental samples on the thermal conductivity coefficient of the material of the insulating insert, the width of the insulating insert and the outside air temperature were revealed and the nature of the temperature distribution on the "inner" surface of the prototypes was established. By calculating two-dimensional temperature fields in the cross section of the node, isofields of temperature distribution inside the structure, isofields of heat flux density and its direction, lines of temperature distribution and heat flux density along the inner and outer surfaces are obtained. It was found that the heat flux density in the ribs with heat-insulating inclusions is lower in comparison with solid wood parts by an amount from 13% to 52%.

Mohammad Abdul Aziz, Sakib Muhammad Mohtasim, Rubel Ahammed

Large MR (MR) dampers are popular due to their higher damping force capabilities which makes them suitable in the field of civil engineering, structural engineering, suspension bridge structure, mining engineering, and agricultural engineering applications. This paper presents a comprehensive review of large MR dampers. The classifications and applications of large MR dampers, the principle of operation, different fluid models, their structural design and control systems are classified and reviewed in this paper. The large MR dampers have higher damping force controllability than conventional MR dampers. The review indicates that the large MR dampers have enough vibration mitigation ability and higher damping performances.

S. Mitoulis, S. Argyroudis, M. Loli et al.

Abstract Bridges are the most vulnerable assets of our transport networks. They are disproportionately exposed to and hit by multiple natural hazards, with flooding being the leading cause of bridge failures in the world. Their performance is constantly challenged by the combined effects of natural hazard stressors, e.g. flash floods, exacerbated by climate change, ageing, increasing traffic volumes and loads. Bridges are vulnerable to scour and other flood-related impacts, such as hydraulic forces and debris accumulation. In order to assess and quantify the resilience of flood-critical bridges and subsequently deploy bridge resilience models aiming at building resilience into transport networks, it is essential to use reliable fragility, capacity restoration and traffic reinstatement metrics and models. It is surprising that, despite the importance of bridges and their high vulnerability to hydraulic actions, there are no available recovery models. The latter can help quantify the pace of post-flood capacity and functionality gain for facilitating well-informed decision making for reliable prioritisation and efficient allocation of resources in transport networks. The main barrier is the nature and complexity of recovery actions, which encompass engineering, operational, owner resources and organisational challenges, among others. This paper, for the first time in the international literature, aims at filling this gap by generating a set of reliable recovery models that include both bridge reinstatement (traffic capacity) and restoration (structural capacity) models based on a detailed questionnaire that elicits knowledge from experts. Recovery models are then presented and validated for spread and deep foundations for a typical reinforced concrete bridge, including restoration task prioritisation and scheduling, inter-task dependencies, idle times, durations and cost ratios for different damage levels, as well as the evolution of traffic capacity after floods.

Larissa Chazette, Wasja Brunotte, Timo Speith

The growing complexity of software systems and the influence of software-supported decisions in our society awoke the need for software that is transparent, accountable, and trust-worthy. Explainability has been identified as a means to achieve these qualities. It is recognized as an emerging non-functional requirement (NFR) that has a significant impact on system quality. However, in order to incorporate this NFR into systems, we need to understand what explainability means from a software engineering perspective and how it impacts other quality aspects in a system. This allows for an early analysis of the benefits and possible design issues that arise from interrelationships between different quality aspects. Nevertheless, explainability is currently under-researched in the domain of requirements engineering and there is a lack of conceptual models and knowledge catalogues that support the requirements engineering process and system design. In this work, we bridge this gap by proposing a definition, a model, and a catalogue for explainability. They illustrate how explainability interacts with other quality aspects and how it may impact various quality dimensions of a system. To this end, we conducted an interdisciplinary Systematic Literature Review and validated our findings with experts in workshops.

Marek Stolarski

Abstract: In order to effectively warn wild animals of the danger posed by a fast-moving train, knowledge of ethology—that is, the natural behavior of animals—is necessary. Understanding how animals’ senses function and the instincts that guide their behavior allows for the selection of stimuli that will be interpreted as a warning of impending danger and will prompt the animals to move away from the tracks. This is how the acoustic system for protecting animals on railway tracks, developed in Poland, works. Keywords: Railway lines; Wild animals; Prevention of train–wild animal collisions; Acoustic animal protection devices