Hasil untuk "Bridge engineering"

Chuqiao Song, Zhaohua Wang, Zhouhong Ren et al.

ABSTRACT Photothermal CO2 methanation offers a route to store renewable energy as synthetic methane, yet conventional Ni catalysts typically require intense light or auxiliary heating and show poor tolerance to intermittency. Here, we report a CeZrOx/NiO‐Ni inverse catalyst via a heterostructure engineering strategy, featuring a protective NiO interlayer. This tailored architecture achieves 83% single‐pass CO2 conversion with >99% CH4 selectivity under 0.71 W cm−2 irradiation in a continuous‐flow system, without external heating. Notably, it delivers a CH4 space‐time yield of 464 mmol·gcat−1·h−1 under natural concentrated sunlight and maintains robust performance over repeated light‐dark cycles, extended air storage, and 100‐g scaled synthesis, demonstrating its potential compatibility with intermittent renewable energy. Mechanistic studies reveal that the sub‐nanometer NiO layer on Ni domains enhances LSPR‐induced heating and hot‐carrier injection while establishing a favorable CeZrOx/NiO‐Ni band alignment for charge separation. This heterointerface further promotes CO2 activation via *COOH intermediates and electron‐mediated pathways, thereby amplifying photothermal synergy under low‐intensity illumination. This work highlights the critical role of interfacial engineering in advancing solar‐driven energy conversion and provides a catalyst‐level design strategy that could help bridge lab‐scale innovation and future practical applications.

Kaicheng Huang, Fanyu Wang, Yutan Huang et al.

Advancements in large language models (LLMs) have led to a surge of prompt engineering (PE) techniques that can enhance various requirements engineering (RE) tasks. However, current LLMs are often characterized by significant uncertainty and a lack of controllability. This absence of clear guidance on how to effectively prompt LLMs acts as a barrier to their trustworthy implementation in the RE field. We present the first roadmap-oriented systematic literature review of Prompt Engineering for RE (PE4RE). Following Kitchenham's and Petersen's secondary-study protocol, we searched six digital libraries, screened 867 records, and analyzed 35 primary studies. To bring order to a fragmented landscape, we propose a hybrid taxonomy that links technique-oriented patterns (e.g., few-shot, Chain-of-Thought) to task-oriented RE roles (elicitation, validation, traceability). Two research questions, with five sub-questions, map the tasks addressed, LLM families used, and prompt types adopted, and expose current limitations and research gaps. Finally, we outline a step-by-step roadmap showing how today's ad-hoc PE prototypes can evolve into reproducible, practitioner-friendly workflows.

Lazlo Bleker, Mustafa Cem Güneş, Pierluigi D'Acunto

Machine learning (ML) is increasingly used in structural engineering and design, yet its broader adoption is hampered by the lack of openly accessible datasets of structural systems. We introduce BridgeNet, a publicly available graph-based dataset of 20,000 form-found bridge structures aimed at enabling Graph ML and multi-modal learning in the context of conceptual structural design. Each datapoint consists of (i) a pin-jointed equilibrium wireframe model generated with the Combinatorial Equilibrium Modeling (CEM) form-finding method, (ii) a volumetric 3D mesh obtained through force-informed materialization, and (iii) rendered images from two canonical camera angles. The resulting dataset is modality-rich and application-agnostic, supporting tasks such as CEM-specific edge classification and parameter inference, surrogate modeling of form-finding, cross-modal reconstruction between graphs, meshes and images, and generative structural design. BridgeNet addresses a key bottleneck in data-driven applications for structural engineering and design by providing a dataset that facilitates the development of new ML-based approaches for equilibrium bridge structures.

YU Nan, SONG Yang, BEI Bei et al.

Construction solid waste is often used as subgrade filler, and its mechanical properties are greatly affected by moisture content and compaction degree. To explore the influence of these factors on the mechanical and particle crushing performance of construction solid waste, laboratory large-scale direct shear tests and particle screening tests were conducted. This study analyzed samples with varying moisture content and compaction degrees under a certain maximum dry density. The large-scale shear tests were carried out under three normal stress conditions: 50 kPa, 100 kPa, and 150 kPa, and the particle crushing characteristics of construction solid waste before and after shearing were analyzed. The results reveal notable changes in particle crushing form of the section before and after shearing of construction solid waste, which can be categorized into three types: rupture, abrasion, and grinding. The shear stress‑shear displacement curve shows a “jumping” phenomenon. The cohesion of construction solid waste increases with the decrease in moisture content or the increase in compaction degree. Similarly, the internal friction angle rises with decreased moisture content or a higher degree of compaction. The overall screening statistics of construction solid waste show that the particle gradation curve moves upward, and the relative crushing rate of particles increases as moisture content decreases, or compaction degree increases.

Buyun Zhang, Shipeng Dai, Yunshun Zhang et al.

With the rapid development of transportation infrastructure, bridges increasingly face prominent issues of dynamic response and fatigue damage induced by vehicle–bridge interaction (VBI). To effectively suppress the coupled vibrations and enhance both vehicle ride comfort and bridge service life, this paper proposes an active inerter-spring-damper (ISD) suspension system based on Particle Swarm Optimization (PSO) algorithm and Linear Quadratic Regulator (LQR) control. By establishing a VBI model considering general boundary conditions and employing the modal superposition method to solve the system response, an LQR controller is designed for multi-objective optimization targeting the vehicle body acceleration, suspension dynamic travel, and tire dynamic load. To further improve control performance, the PSO algorithm is utilized to globally optimize the LQR weighting matrices. Numerical simulation results demonstrate that, compared to passive suspension and unoptimized LQR active suspension, the PSO-LQR control strategy significantly reduces vertical body acceleration and tire dynamic load, while also improving the convergence and stability of the suspension dynamic travel. This research provides a new insight into the control method for VBI systems, possessing both theoretical and practical engineering application value.

LI Tao, ZHANG Xiu’ang

To study the long-term salt release characteristics of self-melting ice asphalt mixture and the impact of the complete salt release on pavement durability, an accelerated salt release method was developed using a Los Angeles abrasion tester. The salt release mechanism under varying asphalt types, deicing agent contents, and gradation types was revealed. The impact of the complete salt release on road performance was analyzed. Results show that the Los Angeles abrasion tester-based salt release method achieves 91 times and 114 times higher salt release efficiency than the magnetic stirrer and natural immersion methods, respectively. SBS-modified asphalt mixture exhibits a longer salt release duration. The salt release duration is proportional to the deicing agent content. The SMA-13 self-melting ice asphalt mixture shows relatively poor salt release uniformity. After complete salt release, the high-temperature stability of the self-melting ice asphalt mixture decreases by 31.6%, low-temperature performance by 15.4%, and water stability by 26.7%.

Zbigniew Szafrański

Abstract: In recent months, the abbreviation CPK has likely been the most frequently used acronym in public discourse. Debates, and often highly emotional disputes, have centred around whether the central airport and its associated railway network are necessary at all, whether they are oversized or not, and similar issues. However, less attention has been given to the impact of such a large investment project on the economic and social development of the regions that will fall within CPK’s sphere of influence. The Łódź Voivodeship, following the completion of infrastructure projects currently being implemented by PKP Polskie Linie Kolejowe S.A., as well as those being prepared by Centralny Port Komunikacyjny Sp. z o.o., could be one of the biggest beneficiaries of this landmark initiative. Keywords: CPK; Lodz Region

Guoqing Wang, Zeyu Sun, Zhihao Gong et al.

Large Language Models (LLMs) have significantly advanced software engineering (SE) tasks, with prompt engineering techniques enhancing their performance in code-related areas. However, the rapid development of foundational LLMs such as the non-reasoning model GPT-4o and the reasoning model o1 raises questions about the continued effectiveness of these prompt engineering techniques. This paper presents an extensive empirical study that reevaluates various prompt engineering techniques within the context of these advanced LLMs. Focusing on three representative SE tasks, i.e., code generation, code translation, and code summarization, we assess whether prompt engineering techniques still yield improvements with advanced models, the actual effectiveness of reasoning models compared to non-reasoning models, and whether the benefits of using these advanced models justify their increased costs. Our findings reveal that prompt engineering techniques developed for earlier LLMs may provide diminished benefits or even hinder performance when applied to advanced models. In reasoning LLMs, the ability of sophisticated built-in reasoning reduces the impact of complex prompts, sometimes making simple zero-shot prompting more effective. Furthermore, while reasoning models outperform non-reasoning models in tasks requiring complex reasoning, they offer minimal advantages in tasks that do not need reasoning and may incur unnecessary costs. Based on our study, we provide practical guidance for practitioners on selecting appropriate prompt engineering techniques and foundational LLMs, considering factors such as task requirements, operational costs, and environmental impact. Our work contributes to a deeper understanding of effectively harnessing advanced LLMs in SE tasks, informing future research and application development.

Jonathan Álvarez Ariza

Active Learning (AL) is a well-known teaching method in engineering because it allows to foster learning and critical thinking of the students by employing debate, hands-on activities, and experimentation. However, most educational results of this instructional method have been achieved in face-to-face educational settings and less has been said about how to promote AL and experimentation for online engineering education. Then, the main aim of this study was to create an AL methodology to learn electronics, physical computing (PhyC), programming, and basic robotics in engineering through hands-on activities and active experimentation in online environments. N=56 students of two engineering programs (Technology in Electronics and Industrial Engineering) participated in the methodology that was conceived using the guidelines of the Integrated Course Design Model (ICDM) and in some courses combining mobile and online learning with an Android app. The methodology gathered three main components: (1) In-home laboratories performed through low-cost hardware devices, (2) Student-created videos and blogs to evidence the development of skills, and (3) Teacher support and feedback. Data in the courses were collected through surveys, evaluation rubrics, semi-structured interviews, and students grades and were analyzed through a mixed approach. The outcomes indicate a good perception of the PhyC and programming activities by the students and suggest that these influence motivation, self-efficacy, reduction of anxiety, and improvement of academic performance in the courses. The methodology and previous results can be useful for researchers and practitioners interested in developing AL methodologies or strategies in engineering with online, mobile, or blended learning modalities.

Qinrui Liu, Haozhe Jiang, Guocheng Tao et al.

To investigate the anchorage loss mechanism of externally prestressed CFRP tendons in concrete beams, this study introduces a novel theoretical calculation system (TCS) developed through both the finite element method (FEM) and experimental validation. Firstly, the FEM and the proposed TCS were employed based on the mechanism of anchorage loss to compute the deformation of each part of the prestressed tendon–main beam connection system, ensuring result accuracy through mutual validation. Subsequently, field tests, designed according to FEM guidelines, measured the anchorage loss in externally prestressed CFRP tendons, with long-term monitoring included. Finally, experimental data were then used to refine the TCS. The results indicate that deformation at the connecting screw and the front end of the steel reaction frame constitutes approximately 95% of the total deformation, with theoretical calculations aligning closely with the FEM results. The field tests revealed that the anchorage loss of a 12 m long CFRP tendon under 950 MPa prestress accounted for about 35% of the total prestress loss. The discrepancy in deformation compared with the theoretical results was due to a gap of approximately 0.4 mm between the two threaded connections, which can be minimized by improving construction techniques. After correction, the calculation error was reduced to about 5%. Control variable studies confirmed that anchorage loss is influenced by the prestress level, the dimensions of the steel reaction frame front end, the connecting screw length, and the number of thread gaps. This study provides a comprehensive approach for accurately predicting and mitigating anchorage loss in externally prestressed CFRP tendons, with significant implications for future engineering applications.

Si-Qi. Li

To explore the vulnerability of a reinforced concrete girder bridge and reinforced concrete building during an earthquake, and to compare the difference in the seismic capacity of the two types of engineering structures, the nonlinear vulnerability numerical and probabilistic model analysis methods were combined. Overall, 1069 reinforced concrete girder bridges and 949 reinforced concrete buildings damaged in the Wenchuan earthquake of May 12, 2008 were selected for vulnerability analysis. The vulnerability grades of damaged samples were evaluated according to the Chinese seismic intensity scale (CSIS-08), and the vulnerability matrix of reinforced concrete girder bridges and reinforced concrete buildings in multiple intensity regions was established. Moreover, the novel vulnerability comparison curve model was developed by considering the failure ratio and exceeding probability. The anomaly characteristics of seismic damage vulnerability between reinforced concrete girder bridges and reinforced concrete buildings under the influence of age, seismic design, the coupling of age and seismic design, and foundation type factors were compared and analysed. By employing the matrix calculation model of the mean damage index, the matrix and curve comparison model of the mean damage index vulnerability parameters of reinforced concrete girder bridges and reinforced concrete buildings in multiple intensity zones were developed.

Zhao Wensheng, Fang Guotao, Qin Xiao et al.

To clarify the effect and mechanism of hindered amine light stabilizer (HALS) on the UV aging behavior of asphalt binder, T622-HALS was selected as the modifier for UV aging resistance of asphalt. The physicochemical properties and microstructure of T622 light stabilizer were comprehensively analyzed. The light stabilizer-modified asphalt was prepared and placed in the UV radiation chamber for UV aging treatment. Scanning electron microscope and atomic force microscope were used to analyze the microscopic morphology evolution of light stabilizer-modified asphalt induced by UV radiation. The thermal properties and functional group composition changes in light stabilizer-modified asphalt during UV aging were studied by using the thermogravimetric and infrared spectroscopy combined testing system. The decay laws of the physical and rheological performances of light stabilizer-modified asphalt were studied during UV aging process, and the effect of light stabilizer on the UV aging behavior of asphalt binder was clarified. The research results indicated that HALSs could alleviate the microcracks and roughness change on the surface of asphalt and reduce the content of functional groups such as carbonyl and sulfoxide in asphalt. Furthermore, HALS could reduce the value difference of physical and rheological properties of asphalt before and after UV aging, significantly improving the UV aging resistance of asphalt binder.

Ting Huang, Zongchao Li, Fangtou Tang et al.

On September 5, 2022, an MS6.8 earthquake occurred in Luding County, Ganzi Prefecture, Sichuan Province, China, causing extensive damage. The scientific expedition team of the Institute of Geophysics of the China Earthquake Administration investigated the damage caused by the earthquake in several terrace hydropower stations on the main stream of the Dadu River and nearby areas. It was determined that the cascade power stations ware less affected by the earthquake and that normal operation was not affected. Using the empirical Green's function method and considering the uncertainty characteristics of the seismic source parameters, the ground motion acceleration time histories were estimated for a reasonable range of three typical locations in the seismic region: the Shimian Caluo area (termed location 1), the Xingkang Expressway bridge area in the Dadu River basin (termed location 2), and the area near the historical seismic ancient landslides (Mogangling, termed location 3). The preliminary results showed that: buildings at locations 1 and 3 may be destroyed by an earthquake of this strength, whereas the bridges in location 2 are less likely to be destroyed. Here, combining the results of the disaster investigation, the seismic network built by the key engineering project, and the results of the rapid estimation of the ground motion at typical locations, we consider the feasibility of applying the Green's function library based on the waveforms of actual small earthquakes in key project areas.

Rose Omari, Mavis Akuffobea-Essilfie, Sylvia Baah-Tuahene et al.

Abstract Engineering is critical for socio-economic development, however only a few women participate in engineering education and careers. This study aimed to identify the types of negative information propagated by the social networks of engineering students that could create barriers to students, and particularly women’s retention in engineering education and careers, and assess whether they influence men and women differently. The study was exploratory hence six focus group discussions were conducted with undergraduate engineering students in their second, third, and fourth years of study in a Ghanaian university. An interview guide was used to, among others, examine the perceptions and misconceptions of students’ social networks about engineering and the negative information that circulates within the networks. Demotivating information from students’ social networks were mainly misconceptions such as (1) engineering is too difficult and strenuous for women, and only meant for strong and well-built people, (2) engineering negatively affects women’s beauty and body image, (3) engineering makes women unfashionable and unattractive, and (4) engineering is a threat to marital and family lives. Both female and male students were negatively affected by misinformation about engineering being difficult and having limited job prospects as well as societal preferences for other programmes such as medicine. The misinformation could serve as a barrier, especially for students lacking ‘faith and the spirit of perseverance’ to pursue and graduate from engineering programmes. While efforts are being made to bridge the gender gap in engineering education and careers, there are misconceptions and misinformation that can hinder progress toward achieving the desired gender parity. Educational policies must integrate gender-responsive strategies including addressing the socio-cultural and stereotypical factors and public misconceptions. There is a need to provide strategic counselling services to engineering students to be able to cope with the effects of negative information from their social networks especially during the early years of their studies in the universities.

Brian S. Mitchell

Cloud compute adoption has been growing since its inception in the early 2000's with estimates that the size of this market in terms of worldwide spend will increase from \$700 billion in 2021 to \$1.3 trillion in 2025. While there is a significant research activity in many areas of cloud computing technologies, we see little attention being paid to advancing software engineering practices needed to support the current and next generation of cloud native applications. By cloud native, we mean software that is designed and built specifically for deployment to a modern cloud platform. This paper frames the landscape of Cloud Native Software Engineering from a practitioners standpoint, and identifies several software engineering research opportunities that should be investigated. We cover specific engineering challenges associated with software architectures commonly used in cloud applications along with incremental challenges that are expected with emerging IoT/Edge computing use cases.

Jocelyn Ahmed Mazari, Antoine Reverberi, Pierre Yser et al.

In this work, we propose a built-in Deep Learning Physics Optimization (DLPO) framework to set up a shape optimization study of the Duisburg Test Case (DTC) container vessel. We present two different applications: (1) sensitivity analysis to detect the most promising generic basis hull shapes, and (2) multi-objective optimization to quantify the trade-off between optimal hull forms. DLPO framework allows for the evaluation of design iterations automatically in an end-to-end manner. We achieved these results by coupling Extrality's Deep Learning Physics (DLP) model to a CAD engine and an optimizer. Our proposed DLP model is trained on full 3D volume data coming from RANS simulations, and it can provide accurate and high-quality 3D flow predictions in real-time, which makes it a good evaluator to perform optimization of new container vessel designs w.r.t the hydrodynamic efficiency. In particular, it is able to recover the forces acting on the vessel by integration on the hull surface with a mean relative error of 3.84\% \pm 2.179\% on the total resistance. Each iteration takes only 20 seconds, thus leading to a drastic saving of time and engineering efforts, while delivering valuable insight into the performance of the vessel, including RANS-like detailed flow information. We conclude that DLPO framework is a promising tool to accelerate the ship design process and lead to more efficient ships with better hydrodynamic performance.

Tao Yue, Shaukat Ali, Paolo Arcaini

Quantum software engineering (QSE) is receiving increasing attention, as evidenced by increasing publications on topics, e.g., quantum software modeling, testing, and debugging. However, in the literature, quantum software requirements engineering (QSRE) is still a software engineering area that is relatively less investigated. To this end, in this paper, we provide an initial set of thoughts about how requirements engineering for quantum software might differ from that for classical software after making an effort to map classical requirements classifications (e.g., functional and extra-functional requirements) into the context of quantum software. Moreover, we provide discussions on various aspects of QSRE that deserve attention from the quantum software engineering community.

Alexander Schied, Zhenyuan Zhang

We introduce a new class of stochastic processes called fractional Wiener-Weierstrass bridges. They arise by applying the convolution from the construction of the classical, fractal Weierstrass functions to an underlying fractional Brownian bridge. By analyzing the $p$-th variation of the fractional Wiener-Weierstrass bridge along the sequence of $b$-adic partitions, we identify two regimes in which the processes exhibit distinct sample path properties. We also analyze the critical case between those two regimes for Wiener-Weierstrass bridges that are based on standard Brownian bridge. We furthermore prove that fractional Wiener-Weierstrass bridges are never semimartingales, and we show that their covariance functions are typically fractal functions. Some of our results are extended to Weierstrass bridges based on bridges derived from a general continuous Gaussian martingale.

Kolodin K. I., Kolodina T. Y.

The article is based on an architectural concept that was developed at the St. Petersburg State University of Architecture and Civil Engineering at the Department of Architectural Design, in the architectural studio “ANESTIKA”. The main objectives of this experiment are related to the issues of a conceptual idea creation, its development and implementation in the developed intellectual architectural concept. A volumetric-spatial model of the fragmentary structure of the Street of the World was completed as a result of the work. The model presented the developed compositional solutions in the form of separate functional blocks and zones. They were united by a common three-dimensional structural frame of the supporting structures in the form of a linear habitable bridge. It is an architectural manifesto in which “Street of the World” represents a great intellectual international infinite linear megapolis formed by an environmental space without borders around the entire globe. It is based on the unification of the world space around a unified unique grandiose architectural object. The endless street is built for all the states of the globe.

Miroslav Vořechovský

The paper presents a new efficient and robust method for rare event probability estimation for computational models of an engineering product or a process returning categorical information only, for example, either success or failure. For such models, most of the methods designed for the estimation of failure probability, which use the numerical value of the outcome to compute gradients or to estimate the proximity to the failure surface, cannot be applied. Even if the performance function provides more than just binary output, the state of the system may be a non-smooth or even a discontinuous function defined in the domain of continuous input variables. In these cases, the classical gradient-based methods usually fail. We propose a simple yet efficient algorithm, which performs a sequential adaptive selection of points from the input domain of random variables to extend and refine a simple distance-based surrogate model. Two different tasks can be accomplished at any stage of sequential sampling: (i) estimation of the failure probability, and (ii) selection of the best possible candidate for the subsequent model evaluation if further improvement is necessary. The proposed criterion for selecting the next point for model evaluation maximizes the expected probability classified by using the candidate. Therefore, the perfect balance between global exploration and local exploitation is maintained automatically. The method can estimate the probabilities of multiple failure types. Moreover, when the numerical value of model evaluation can be used to build a smooth surrogate, the algorithm can accommodate this information to increase the accuracy of the estimated probabilities. Lastly, we define a new simple yet general geometrical measure of the global sensitivity of the rare-event probability to individual variables, which is obtained as a by-product of the proposed algorithm.