ObjectiveWhen metro station is constructed in combination with a municipal bridge, the station structural stress stage can be divided into pre-bridge and post-bridge parts. At present, there is a lack of systematic summary and analysis of the stress characteristics of the metro station structure in these two stages. Therefore, it is necessary to analyze the deformation and stress characteristics of the metro station structure during the two stages of combined station-bridge construction. MethodBased on the actual engineering project and referring to a certain standard metro station, a load-structure calculation model is established. Focusing on structural components such as the station roof slab, roof longitudinal beam and transfer beam, numerical simulation and calculation are carried out using MIDAS GEN software. The structural stress and deformation characteristics of the metro station constructed in combination with a bridge are comparatively analyzed between the pre-bridge and post-bridge stages, according to the standard section and the end-shaft section respectively. Result & Conclusion The bridge load and transfer beam may alter the stress state of the roof slab and roof longitudinal beams of station structure, with the primary influence range concentrated on the spans adjacent to both sides of the transfer beam, with relatively minor effect on the intermediate spans. For the roof slab of a combined station-bridge structure, except for the side supports of adjacent spans—which should have reinforcement strengthened according to the internal forces during the post-bridge stage—the transverse reinforcement in other areas can be done following the standard station design. During the pre-bridge stage, the roof slab on both sides of the transfer beam experiences larger longitudinal bending moments and shear forces; therefore, it is recommended to set haunches between the transfer beam and the roof slab and to strengthen the longitudinal reinforcement of the roof slab in adjacent spans along the bridge. The spatial stress in the end-shaft section is significant, due to the bridge load, the pier-under columns may undergo large deformations, causing tension on the roof slab at the column support positions and the lower part of the longitudinal beams, which may lead to cracking or damage. Hence, bridge piers should be arranged to avoid the end-shaft area.
Establishing an accurate vehicle fatigue load spectrum is a critical prerequisite for fatigue life analysis and design of highway bridges. However, the time-varying and regional characteristics of vehicle loads pose significant challenges to achieving this goal. This study focuses on vehicle data collected by a weigh-in-motion system installed on a highway bridge in Chongqing, China. The statistical characteristics of vehicle-load-related parameters are analyzed, and the actual vehicle fatigue load spectrum for this section of the road is established. Specifically, vehicles are first categorized based on axle count characteristics. Then, statistical analyses are conducted on key parameters such as vehicle weight, headway time, and axle load for each vehicle type. Finally, the actual vehicle fatigue load spectrum is developed based on Miner’s linear damage rule and the equivalent fatigue damage principle, and the contributions of different vehicle types to fatigue damage are investigated. The results show that the weight distributions of different vehicle types follow a Gaussian mixture distribution, while the headway time distribution for each lane follows a log-normal distribution. A linear approximate relationship was observed between the axle loads of different vehicle types and their respective total weights. Although two-axle trucks exhibited higher frequencies, six-axle trucks contributed the most to structural fatigue damage, accounting for 53.81%. Therefore, six-axle trucks can be regarded as the standard fatigue vehicle model for this section of the road. These findings provide valuable insights for fatigue design and fatigue life assessment of highway bridges under similar vehicle loading conditions.
Bridges play a key and controlling role in transportation systems. Steel bridges are favored for their high strength, good seismic performance, and convenient construction. As important node connectors of steel bridges, high-strength bolts are extremely susceptible to damage such as corrosion and loosening. Therefore, accurate identification of bolt loosening is crucial. First, a new type of adhesive piezoelectric sensor is designed and prepared using PMN-PT piezoelectric single-crystal materials. The PMN-PT sensor and polyvinylidene fluoride (PVDF) sensor are subjected to steel plate fixed frequency load and swept frequency load tests to test the performance of the two sensors. Then, a steel plate component connected by high-strength bolts is designed. By applying exciter square wave load to the structure, the vibration response characteristics of the structure are analyzed to identify the loosening of the bolts. In addition, a piezoelectric smart washer sensor is designed to make up for the shortcomings of the adhesive piezoelectric sensor, and the effectiveness of the piezoelectric smart washer sensor is verified. Finally, a bolt loosening index is proposed to quantitatively evaluate the looseness of the bolt. The results show that the sensitivity of the PMN-PT sensor is 21 times that of the PVDF sensor. Compared with the peak stress change, the natural frequency change is used to identify the bolt loosening more effectively. Piezoelectric smart washer sensor and bolt loosening indicator can be used for bolt loosening identification.
From its early foundations in the 1970s, empirical software engineering (ESE) has evolved into a mature research discipline that embraces a plethora of different topics, methodologies, and industrial practices. Despite its remarkable progress, the ESE research field still needs to keep evolving, as new impediments, shortcoming, and technologies emerge. Research reproducibility, limited external validity, subjectivity of reviews, and porting research results to industrial practices are just some examples of the drivers for improvements to ESE research. Additionally, several facets of ESE research are not documented very explicitly, which makes it difficult for newcomers to pick them up. With this new regular ACM SIGSOFT SEN column (SEN-ESE), we introduce a venue for discussing meta-aspects of ESE research, ranging from general topics such as the nature and best practices for replication packages, to more nuanced themes such as statistical methods, interview transcription tools, and publishing interdisciplinary research. Our aim for the column is to be a place where we can regularly spark conversations on ESE topics that might not often be touched upon or are left implicit. Contributions to this column will be grounded in expert interviews, focus groups, surveys, and position pieces, with the goal of encouraging reflection and improvement in how we conduct, communicate, teach, and ultimately improve ESE research. Finally, we invite feedback from the ESE community on challenging, controversial, or underexplored topics, as well as suggestions for voices you would like to hear from. While we cannot promise to act on every idea, we aim to shape this column around the community interests and are grateful for all contributions.
Hashini Gunatilake, John Grundy, Rashina Hoda
et al.
Empathy plays a critical role in software engineering (SE), influencing collaboration, communication, and user-centred design. Although SE research has increasingly recognised empathy as a key human aspect, there remains no validated instrument specifically designed to measure it within the unique socio-technical contexts of SE. Existing generic empathy scales, while well-established in psychology and healthcare, often rely on language, scenarios, and assumptions that are not meaningful or interpretable for software practitioners. These scales fail to account for the diverse, role-specific, and domain-bound expressions of empathy in SE, such as understanding a non-technical user's frustrations or another practitioner's technical constraints, which differ substantially from empathy in clinical or everyday contexts. To address this gap, we developed and validated two domain-specific empathy scales: EmpathiSEr-P, assessing empathy among practitioners, and EmpathiSEr-U, capturing practitioner empathy towards users. Grounded in a practitioner-informed conceptual framework, the scales encompass three dimensions of empathy: cognitive empathy, affective empathy, and empathic responses. We followed a rigorous, multi-phase methodology, including expert evaluation, cognitive interviews, and two practitioner surveys. The resulting instruments represent the first psychometrically validated empathy scales tailored to SE, offering researchers and practitioners a tool for assessing empathy and designing empathy-enhancing interventions in software teams and user interactions.
The automotive industry generates vast amounts of data from sensors, telemetry, diagnostics, and real-time operations. Efficient data engineering is critical to handle challenges of latency, scalability, and consistency. Modern data lakehouse formats Delta Parquet, Apache Iceberg, and Apache Hudi offer features such as ACID transactions, schema enforcement, and real-time ingestion, combining the strengths of data lakes and warehouses to support complex use cases. This study presents a comparative analysis of Delta Parquet, Iceberg, and Hudi using real-world time-series automotive telemetry data with fields such as vehicle ID, timestamp, location, and event metrics. The evaluation considers modeling strategies, partitioning, CDC support, query performance, scalability, data consistency, and ecosystem maturity. Key findings show Delta Parquet provides strong ML readiness and governance, Iceberg delivers high performance for batch analytics and cloud-native workloads, while Hudi is optimized for real-time ingestion and incremental processing. Each format exhibits tradeoffs in query efficiency, time-travel, and update semantics. The study offers insights for selecting or combining formats to support fleet management, predictive maintenance, and route optimization. Using structured datasets and realistic queries, the results provide practical guidance for scaling data pipelines and integrating machine learning models in automotive applications.
Chaos Engineering (CE) is an engineering technique aimed at improving the resilience of distributed systems. It involves intentionally injecting faults into a system to test its resilience, uncover weaknesses, and address them before they cause failures in production. Recent CE tools automate the execution of predefined CE experiments. However, planning such experiments and improving the system based on the experimental results still remain manual. These processes are labor-intensive and require multi-domain expertise. To address these challenges and enable anyone to build resilient systems at low cost, this paper proposes ChaosEater, a system that automates the entire CE cycle with Large Language Models (LLMs). It predefines an agentic workflow according to a systematic CE cycle and assigns subdivided processes within the workflow to LLMs. ChaosEater targets CE for software systems built on Kubernetes. Therefore, the LLMs in ChaosEater complete CE cycles through software engineering tasks, including requirement definition, code generation, testing, and debugging. We evaluate ChaosEater through case studies on small- and large-scale Kubernetes systems. The results demonstrate that it consistently completes reasonable CE cycles with significantly low time and monetary costs. Its cycles are also qualitatively validated by human engineers and LLMs.
In order to explore the diffusion behavior of chloride ions in cracked cement mortar with high fly ash (FA) content, this study fabricated cement mortar specimens with different FA contents and crack widths by artificially prefabricating cracks. The chloride ion content in cracks was measured after natural soaking for 30 days and 60 days. The results show that the cracks accelerate the diffusion of chloride ions in cement mortar. The increase in the diffusion coefficient caused by 0.05 mm and 0.1 mm cracks is similar, while that caused by a 0.2 mm crack is significantly higher. After 30 days of soaking, the chloride ion content of the FA50 group decreases significantly with increasing depth beyond 10 mm. After 60 days of soaking, the chloride ion content of all specimens decreases significantly with increasing depth. When the fly ash content is not more than 40%, the chloride ion resistance of the mortar improves with increasing FA content. However, at 50% FA content, the chloride ion resistance sharply decreases. The relationship between crack width and the chloride ion diffusion coefficient follows a linear function, while the relationship between fly ash content and chloride ion diffusion coefficient can be described by a cubic function. A diffusion coefficient model considering both fly ash content and crack width has been established, and the validity of the model is verified by comparison between experimental values and fitted values.
Preserving heritage sites is a complex challenge that requires multidisciplinary approaches, combining scientific accuracy with cultural and historical sensitivity. In alignment with UNESCO’s conservation guidelines, this study investigated the airflow dynamics and wind-induced structural effects within ancient architecture using advanced computational fluid dynamics (CFD). The study site was the Na Phra Meru Historical Temple in Ayutthaya, Thailand, where the shear stress transport <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>k</mi><mo>−</mo><mi>ω</mi></mrow></semantics></math></inline-formula> turbulence model was applied to analyze distinctive airflow patterns. A high-precision 3D computational domain was developed using Faro focus laser scanning technology, with the CFD results being validated based on onsite experimental data. The findings provided critical insights into the temple’s ventilation behavior, revealing strong correlations between turbulence characteristics, wind speed, temperature, and relative humidity. Notably, the small slit windows generated complex flow mixing, producing a large internal recirculation zone spanning approximately 70% of the central interior space. In addition to airflow distribution, the study evaluated the aerodynamic forces and rotational moments acting on the structure based on five prevailing wind directions. Based on these results, winds from the east and northeast generated the highest aerodynamic loads and rotational stresses, particularly in the lateral and vertical directions. Overall, the findings highlighted the critical role of airflow and wind-induced forces in the deterioration and long-term stability of heritage buildings. The study demonstrated the value of integrating CFD, environmental data, and structural analysis to bridge the gap between conservation science and engineering practice. Future work will explore further the interactions between wall moisture and the multi-layered pigments in mural paintings to inform preservation practices.
Semi-rigid base offers excellent performance and is widely used as a high-grade highway subgrade in China. Currently, with a large stockpile of waste concrete in the country, using it as aggregate in pavement base materials is of great significance for environmental protection, energy conservation, and emission reduction. In this paper, the basic performance indicators of recycled concrete aggregate (RCA) and the performance of cement-stabilized base materials containing RCA, including strength, shrinkage, fatigue, and erosion resistance were reviewed. It finds that the basic performance indicators of RCA are lower than those of natural aggregate. Therefore, the proportion of RCA in base materials may be limited to 20%‒50%. The shrinkage and erosion resistance of RCA-containing cement-stabilized base materials tend to stabilize after 28 days, necessitating appropriate curing during the early stages. Microscopic testing reveals the reasons for the high water absorption rate and high crushing value of RCA, while finite element analysis explains the characteristics of crack development in such base materials. This paper provides practical recommendations for the application of RCA in cement-stabilized base materials.
The resilience concept is well established in engineering, but the quantitative studies of vessel impact resilience for bridge structures remain limited. This paper presents an integrated framework for assessing vessel impact resilience under combined rebar corrosion and vessel collision effects. First, a corroded reinforced concrete bridge is considered for nonlinear static analysis to quantify initial corrosion damage and for nonlinear dynamic analysis to evaluate post-impact function loss. Then, recovery for each damage state is modeled by using both negative exponential and triangular recovery functions to estimate restoration times and to obtain a vessel impact resilience index. The results show that increasing corrosion severity markedly reduces resilience capacity. Furthermore, resilience indices obtained from the negative exponential function generally exceed those from the triangular function, and this improvement becomes more significant at lower resilience levels. Resilience indices calculated by using negative exponential and triangular recovery functions show negligible differences when the concrete bridge is in the uncorroded initial state and the vessel impact velocity is below 1.5 m/s. However, as reinforcement corrosion increases, the maximum discrepancy between these two recovery functions also increases, reaching a value of 67% at a corrosion level of 15.0%. From the numerical results obtained from a case study, it is important to select an appropriate recovery model when assessing vessel impact resilience. For rapid initial restoration followed by slower long-term recovery, the negative exponential model yields greater resilience gains compared to the triangular model. The proposed method thus provides an effective tool for engineers and decision makers to evaluate and improve the vessel impact resilience of aging bridges under the combined corrosion and impact effects. This proposes a quantitative metric for resilience-based condition assessment and maintenance planning.
Selina Schaum, Stefanie Stenger‐Wolf, Holger Schüttrumpf
et al.
ABSTRACT Temporary structures are important for a rapid recovery phase after extraordinary flood disasters we cannot protect ourselves from. Long‐term temporary structures are particularly relevant when infrastructures are destroyed that require a longer reconstruction phase. In addition, they offer the opportunity of more time to build resilient critical infrastructure (CI). The term “long‐term temporary” is used in the study to emphasize that these temporary solutions are not only used for a short period of time (less than 6 months). On the example of the recovery in the Ahr valley after the 2021 flood, the authors diagnosed the importance of practice examples on long‐term temporaries when ad‐hoc solutions are needed, as well as the long persistence of some of the temporary solutions. A systematic literature analysis was conducted, as limited research in long‐term temporaries exists. We evaluated how many scientific papers on the topic of long‐term temporaries for CI after flood disasters can be identified after a parameter‐oriented literature analysis and which aspects are dealt with. The literature analysis is based on seven search parameter combinations and covers the areas of drinking water supply, power supply, sewage disposal, telecommunications, bridges (transport systems) and gas supply. 138 publications were identified as relevant, with 43 broaching the issue of temporary solutions after flooding. The most common keyword is “critical infrastructure” (CI) with only 3.7%, followed by “flood” with only 3.4%. Most studies on temporary solutions evaluate temporary bridges, followed by drinking water supply. Military engineering plays a key role in providing temporary bridges, which explains the good supply and documentation. The authors analysed temporary structural solutions (long‐term temporaries) based on on‐site observations and the close collaboration with municipalities within the KAHR‐project during the recovery phase of the region. The case study presents some specific long‐term temporary solutions for bridge constructions and flying pipes to temporary drinking water treatment systems and sewage treatment plants. Another key finding is that long‐term temporary structures are very diverse and have varying life spans (shorter for telecommunication and drinking water supply and longer for bridges and sewage disposal) as well as different requirements in technicality and durability (e.g., lower challenges in drinking water supply, higher requirements for bridges). It is therefore important to explore this area in terms of risks and design options, which has a direct impact on flood risk management, as it could make the use of long‐term temporary structures more routine during the emergency management phase.
River protective works. Regulation. Flood control, Disasters and engineering
Corrugated steel–concrete (CSC) composite arches, an innovative structural system with simplified construction and enhanced stiffness, are widely used in bridge and tunnel modular engineering. However, insufficient research on their shear performance limits prefabricated applications. Similarly to beams, their shear behavior is significantly affected by loading location. Specifically, as a parameter significantly affected by the loading location, the shear–compression ratio exerts a notable influence on the shear bearing capacity of CSC arches by altering the development pattern of cracks and the inclination angle of shear cracks. To investigate the influence mechanism of the loading location, this study is the first to systematically link shear–compression ratio variation to load location in CSC arches. In this context, shear performance tests were conducted on two CSC specimens with different loading locations (mid-span and quarter-point) to investigate the influence of loading locations on the shear behavior of CSC arches. To further investigate the impact of key parameters on the shear bearing capacity of CSC arches, a validated finite element model was employed to support the parametric analysis. The parameters involved include the span-to-rise ratio, shear connector spacing, strength and thickness of corrugated steel, as well as strength and thickness of concrete. Theoretical calculations for internal forces under varying rise-to-span ratios and loading methods are conducted, proposing an analytical solution method. Validation using 2 experiments and 96 finite element results show that a modified method is applicable, with a mean value of 1.066, corresponding to a standard deviation of 0.071, and all relative errors within 15%. By introducing the shear–compression ratio, this study extends existing methods to make them applicable under single-point loading, thereby enabling their use for guiding engineering. Similarly, the internal force analysis method proposed herein can serve as a theoretical foundation, providing a valuable reference for future research on shear capacity calculation methods for CSC arches with varying cross-sectional configurations and those where bending moments play a more significant role.
Jinqi Luo, Tianjiao Ding, Kwan Ho Ryan Chan
et al.
Large Language Models (LLMs) are being used for a wide variety of tasks. While they are capable of generating human-like responses, they can also produce undesirable output including potentially harmful information, racist or sexist language, and hallucinations. Alignment methods are designed to reduce such undesirable outputs via techniques such as fine-tuning, prompt engineering, and representation engineering. However, existing methods face several challenges: some require costly fine-tuning for every alignment task; some do not adequately remove undesirable concepts, failing alignment; some remove benign concepts, lowering the linguistic capabilities of LLMs. To address these issues, we propose Parsimonious Concept Engineering (PaCE), a novel activation engineering framework for alignment. First, to sufficiently model the concepts, we construct a large-scale concept dictionary in the activation space, in which each atom corresponds to a semantic concept. Given any alignment task, we instruct a concept partitioner to efficiently annotate the concepts as benign or undesirable. Then, at inference time, we decompose the LLM activations along the concept dictionary via sparse coding, to accurately represent the activations as linear combinations of benign and undesirable components. By removing the latter ones from the activations, we reorient the behavior of the LLM towards the alignment goal. We conduct experiments on tasks such as response detoxification, faithfulness enhancement, and sentiment revising, and show that PaCE achieves state-of-the-art alignment performance while maintaining linguistic capabilities.
Building up competencies in working with data and tools of Artificial Intelligence (AI) is becoming more relevant across disciplinary engineering fields. While the adoption of tools for teaching and learning, such as ChatGPT, is garnering significant attention, integration of AI knowledge, competencies, and skills within engineering education is lacking. Building upon existing curriculum change research, this practice paper introduces a systems perspective on integrating AI education within engineering through the lens of a change model. In particular, it identifies core aspects that shape AI adoption on a program level as well as internal and external influences using existing literature and a practical case study. Overall, the paper provides an analysis frame to enhance the understanding of change initiatives and builds the basis for generalizing insights from different initiatives in the adoption of AI in engineering education.
Horia Mărgărit, Amanda Bowman, Krishnageetha Karuppasamy
et al.
In this work, we present a case study in implementing a variational quantum algorithm for solving the Poisson equation, which is a commonly encountered partial differential equation in science and engineering. We highlight the practical challenges encountered in mapping the algorithm to physical hardware, and the software engineering considerations needed to achieve realistic results on today's non-fault-tolerant systems.
As one of the most critical load-bearing components in suspension bridges, cables require accurate damage assessments. Contemporary research methodologies primarily rely on cross-validation across multiple cables, which can present challenges in identifying damage under certain conditions. To address this limitation, this study proposes an evaluation method utilizing the cable force of individual cables. A damage index is introduced by the ratio of vehicle-induced cable tension (defined as the ratio of vehicle-induced cable force without weight to its baseline value), and the finite element model of a suspension bridge is used to verify this index. Initially, the finite element model of a suspension bridge is established, and a large number of datasets are generated using this model. These datasets include vehicle weight and vehicle-induced cable force. Subsequently, Gaussian Mixture Model (GMM) clustering is employed to categorize the dataset according to lanes, thereby establishing baseline values for each lane. Finally, damage assessments are conducted using data from individual cables and are validated against the outcomes obtained from the upstream–downstream cable force ratio method. The results show that the data trend of the damage index is clearly visible in six lanes, with the most pronounced trend occurring in the lane farthest from the cable (the sixth lane). The robustness of the index is also verified by adding 2% Gaussian white noise data, providing a research basis for related engineering projects.
To address the challenges related to lengthy construction period, complex maintenance requirement, and the elevated risk of shrinkage cracking associated with cast-in-place UHPC reinforcement of orthotropic steel bridge decks. This paper proposes a novel solution that prefabricated ultra-high-performance concrete (UHPC) slab with epoxy bond connection is used as a reinforcement layer for orthotropic steel bridge decks. Four sets of bending tests on composite bridge deck were carried out to compare the flexural performance of composite bridge decks under different joint forms and loading patterns. The results indicate that the precast UHPC decks delaminated from the epoxy bonding layer without failure of the epoxy layer itself in all cases. The positive bending capacity of the jointless composite bridge deck is approximately 27.67 kN, while the negative bending capacity is around 16.58 kN. For the composite bridge deckwith epoxy adhesive joints (EA-J-Ln), the negative bending capacity is 2.54 kN, and the negative bending capacity of the joint area reinforced with carbon fiber cloth (EA-JC-Ln) is increased to 4.17 kN. Therefore, the use of carbon fiber cloth can significantly improve the bending resistance of the joints. Finally, numerical model of the composite deck based on Cohesive Zone Model (CZM) was established, validating the applicability of this simulation method in the novel composite bridge deck.
Prestressed concrete composite girder bridges with corrugated steel webs (PCCGBCSWs) are extensively employed in bridge construction because of their low dead weight, fast construction, and high prestressing efficiency. Moreover, PCCGBCSWs will experience deformation and failure of the corrugated steel webs, including steel fatigue and fracture, during earthquakes. These changes will introduce safety hazards, which can be addressed via bridge disaster prevention and mitigation. Because near-fault pulse-like ground motions (NFPLGMs) have high peak accelerations, these motions can easily cause damage to a bridge. Therefore, in this study, a seismic fragility assessment is performed for long-unit PCCGBCSWs subjected to NFPLGMs considering spatial variability effects, and a sensitivity evaluation of the seismic fragility is conducted considering girder type, bearing type, ground motion type, and apparent wave velocity to offer a point of reference for seismic design. The results show that PCCGBCSWs are less vulnerable than concrete bridges. The shock absorption effect of the friction pendulum bearing is better than that of the viscous damper. The impact of NFPLGMs on bridges is greater than that of near-fault non-pulse-like ground motions (NFNPLMs) and far-fault ground motions (FFGMs). The seismic fragility under nonuniform excitation conditions is greater than that under uniform excitation conditions, showing an increasing trend with decreasing apparent wave velocity.
Double-deck arch bridges are increasingly used to accommodate rising traffic volumes due to their excellent mechanical properties, ease of construction, and economic benefits. However, research on doubledeck steel truss arch bridges is insufficient, particularly regarding the influence of various design parameters on structural performance. This study focuses on a large-span double-deck steel truss arch bridge as the research object. First, the cable force distributions and the effectiveness of the completed bridge state obtained from four different cable force optimization methods, analyzing the differences between these methods and identifying the most suitable approach for achieving an optimal bridge completed state. Next, it further studies the effects on the structure caused by changes in parameters such as the ratio of side span to mid-span, the height of the main beam truss, and the height of the main arch truss, and deeply discusses the mechanical mechanisms. Finally, it summarizes the patterns observed, providing a reference for the design of similar engineering projects.