Hasil untuk "Bridge engineering"

Changqin Ding, Anwei Zhu, Yang Tian

G. Desiraju

Patricia Calero, P. Nikel

The last few years have witnessed an unprecedented increase in the number of novel bacterial species that hold potential to be used for metabolic engineering. Historically, however, only a handful of bacteria have attained the acceptance and widespread use that are needed to fulfil the needs of industrial bioproduction – and only for the synthesis of very few, structurally simple compounds. One of the reasons for this unfortunate circumstance has been the dearth of tools for targeted genome engineering of bacterial chassis, and, nowadays, synthetic biology is significantly helping to bridge such knowledge gap. Against this background, in this review, we discuss the state of the art in the rational design and construction of robust bacterial chassis for metabolic engineering, presenting key examples of bacterial species that have secured a place in industrial bioproduction. The emergence of novel bacterial chassis is also considered at the light of the unique properties of their physiology and metabolism, and the practical applications in which they are expected to outperform other microbial platforms. Emerging opportunities, essential strategies to enable successful development of industrial phenotypes, and major challenges in the field of bacterial chassis development are also discussed, outlining the solutions that contemporary synthetic biology‐guided metabolic engineering offers to tackle these issues.

Guojun Zhang, Zongli Zheng, Hengyue Shi et al.

Temporary support technology is used to support and stabilize the bridge structure, bear the bridge construction load, and ensure the stability and safety of the structure in the construction process. Different demolition sequences have a huge impact on the performance of the structure. In order to study the effect of the temporary support removal sequence on the mechanical performance of a composite beam bridge with corrugated steel webs (CSWs) in the construction stage, this article combined with a case study of a composite beam bridge with CSWs in Gansu Province, adopted finite element software to establish a spatial finite element model reflecting the whole construction process of a curved beam bridge with corrugated webs and selected three working conditions for comparative study. The effects of different removal sequences on the variation of vertical deflection, normal stress and shear stress of the section are analyzed. The results show that the section deformation is dominated by vertical flexural deformation, and the removal sequence of temporary supports has a great influence on the formation of the structural stiffness, in which the structural stiffness increase is the largest under operating Condition 3. When the temporary support is removed after the concrete strength of the bridge panel is formed, the vertical deflection of the beam body is the smallest. In addition, the beam section of the center span appears upward deflection. The normal stress value and stress gradient of the center span midspan section are the largest, while the stress gradient of the other sections is the smallest and the stress value is greatly reduced. The shear distribution ratio of each web plate under different operating conditions is basically the same, and the removal sequence of temporary supports has little influence on it. The study underscores the importance of construction sequence optimization for improving efficiency and sustainability in bridge engineering, contributing to the broader adoption of innovative materials and methods in sustainable infrastructure development.

Hans Martin Kjer, Mariam Andersson, Yi He et al.

We used diffusion MRI and x-ray synchrotron imaging on monkey and mice brains to examine the organisation of fibre pathways in white matter across anatomical scales. We compared the structure in the corpus callosum and crossing fibre regions and investigated the differences in cuprizone-induced demyelination in mouse brains versus healthy controls. Our findings revealed common principles of fibre organisation that apply despite the varying patterns observed across species; small axonal fasciculi and major bundles formed laminar structures with varying angles, according to the characteristics of major pathways. Fasciculi exhibited non-straight paths around obstacles like blood vessels, comparable across the samples of varying fibre complexity and demyelination. Quantifications of fibre orientation distributions were consistent across anatomical length scales and modalities, whereas tissue anisotropy had a more complex relationship, both dependent on the field-of-view. Our study emphasises the need to balance field-of-view and voxel size when characterising white matter features across length scales.

Edi Hartono, Willis Diana, Agus Setyo Muntohar et al.

Clay shale is an easily degraded mudrock when exposed to weathering. The reduced strength due to degradation can be mitigated through soil stabilization. In recent years, soil stabilization using geopolymers has become one of the latest popular methods due to its economic benefits and lower carbon footprint. A widely used cementitious material for this method is fly ash-based geopolymer. The relationship between curing temperatures and the performance of clay shale stabilized with fly ash-based geopolymer has yet to be studied for the purpose of identifying a more effective stabilization method. In this study, clay shale was stabilized using geopolymer. The geopolymer was made of fly ash and an activator. Sodium hydroxide (NaOH) and sodium silicate (Na2SiO3) as activators. The activator is diluted with water to create a 12 M mixture. Before the unconfined compressive strength test, the specimens were subjected to various curing temperatures from 26oC to 60oC. The test result shows that, in general, higher curing temperatures increased the dry density from 1.66 g/cm3 to 1.84 g/cm3. Meanwhile, the unconfined compressive strength multiplies about 3.5 times. Furthermore, the moisture content decreased after the curing process from 19% to 2.5%. This led to the specimen volume experiencing decrement due to the shrinkage during the curing period. The volume reduces from 67.7 cm3 to 63.5 cm3. In general, temperature plays a significant role in enhancing the strength of clay shale stabilized using fly ash-based geopolymer.

HUANG Huanan, CHEN Yong, WANG Yibo et al.

To study the influence of train speed on thermal insulation and anti-thawing measures for surrounding rock of tunnels in cold regions, it is necessary to analyze the temperature field. By using the Kunlun Mountain Tunnel Project in cold regions as a case study, the effects of external atmospheric temperature, piston wind effects caused by varying train speeds, and the driving resistance on the distribution of the tunnel’s internal temperature field were considered. A three-dimensional numerical calculation model including the surrounding rock, concrete lining, and tunnel air was established by utilizing the thermo‑fluid‑structure interaction (TFSI) technique. The thermal environment variations caused by trains at different speeds were predicted. The result shows that during long-term train operation through the tunnel, both the piston wind speed and the pressure difference between the front and rear of the train increase as the train speed rises. This, along with increased driving resistance, significantly raises the surrounding rock temperature. Regardless of operational duration, the radial temperature impact depth of the surrounding rock decreases with greater tunnel depth, and axial temperature variations are reduced. For long-term train operation at speeds of 80 km/h and 160 km/h, it is recommended to set the thermal insulation and anti-thawing lengths at the two tunnel portals of the Kunlun Mountain Tunnel to 420 m and 790 m, respectively, so as to effectively prevent thaw settlement hazards in the surrounding rock of the Kunlun Mountain Tunnel.

Yining Hong, Christopher S. Timperley, Christian Kästner

Machine learning (ML) components are increasingly integrated into software products, yet their complexity and inherent uncertainty often lead to unintended and hazardous consequences, both for individuals and society at large. Despite these risks, practitioners seldom adopt proactive approaches to anticipate and mitigate hazards before they occur. Traditional safety engineering approaches, such as Failure Mode and Effects Analysis (FMEA) and System Theoretic Process Analysis (STPA), offer systematic frameworks for early risk identification but are rarely adopted. This position paper advocates for integrating hazard analysis into the development of any ML-powered software product and calls for greater support to make this process accessible to developers. By using large language models (LLMs) to partially automate a modified STPA process with human oversight at critical steps, we expect to address two key challenges: the heavy dependency on highly experienced safety engineering experts, and the time-consuming, labor-intensive nature of traditional hazard analysis, which often impedes its integration into real-world development workflows. We illustrate our approach with a running example, demonstrating that many seemingly unanticipated issues can, in fact, be anticipated.

Hashini Gunatilake, John Grundy, Rashina Hoda et al.

Empathy, defined as the ability to understand and share others' perspectives and emotions, is essential in software engineering (SE), where developers often collaborate with diverse stakeholders. It is also considered as a vital competency in many professional fields such as medicine, healthcare, nursing, animal science, education, marketing, and project management. Despite its importance, empathy remains under-researched in SE. To further explore this, we conducted a socio-technical grounded theory (STGT) study through in-depth semi-structured interviews with 22 software developers and stakeholders. Our study explored the role of empathy in SE and how SE activities and processes can be improved by considering empathy. Through applying the systematic steps of STGT data analysis and theory development, we developed a theory that explains the role of empathy in SE. Our theory details the contexts in which empathy arises, the conditions that shape it, the causes and consequences of its presence and absence. We also identified contingencies for enhancing empathy or overcoming barriers to its expression. Our findings provide practical implications for SE practitioners and researchers, offering a deeper understanding of how to effectively integrate empathy into SE processes.

Roberto Verdecchia, Justus Bogner

From its first adoption in the late 80s, qualitative research has slowly but steadily made a name for itself in what was, and perhaps still is, the predominantly quantitative software engineering (SE) research landscape. As part of our regular column on empirical software engineering (ACM SIGSOFT SEN-ESE), we reflect on the state of qualitative SE research with a focus group of experts. Among other things, we discuss why qualitative SE research is important, how it evolved over time, common impediments faced while practicing it today, and what the future of qualitative SE research might look like. Joining the conversation are Rashina Hoda (Monash University, Australia), Carolyn Seaman (University of Maryland, United States), and Klaas Stol (University College Cork, Ireland). The content of this paper is a faithful account of our conversation from October 25, 2025, which we moderated and edited for our column.

Dipin Khati, Yijin Liu, David N. Palacio et al.

Applications of Large Language Models (LLMs) are rapidly growing in industry and academia for various software engineering (SE) tasks. As these models become more integral to critical processes, ensuring their reliability and trustworthiness becomes essential. Consequently, the concept of trust in these systems is becoming increasingly critical. Well-calibrated trust is important, as excessive trust can lead to security vulnerabilities, and risks, while insufficient trust can hinder innovation. However, the landscape of trust-related concepts in LLMs in SE is relatively unclear, with concepts such as trust, distrust, and trustworthiness lacking clear conceptualizations in the SE community. To bring clarity to the current research status and identify opportunities for future work, we conducted a comprehensive review of $88$ papers: a systematic literature review of $18$ papers focused on LLMs in SE, complemented by an analysis of 70 papers from broader trust literature. Additionally, we conducted a survey study with 25 domain experts to gain insights into practitioners' understanding of trust and identify gaps between existing literature and developers' perceptions. The result of our analysis serves as a roadmap that covers trust-related concepts in LLMs in SE and highlights areas for future exploration.

Chuheng Zhong, Lijuan Zhang, Weiqi Mao et al.

This study examined the impact of various combinations of metakaolin and 15% fly ash mix (M) on the mechanical properties and durability of recycled fine aggregate concrete (RFAC), aiming to enhance the properties, cost-effectiveness, and sustainability of concrete, while also determining the optimal metakaolin admixture. And the effect of 0%, 30%, 60%, and 90% recycled fine aggregate replaced natural fine aggregate on the compressive strength, splitting tensile strength, flexural strength, and carbonation resistance of RFAC was investigated, and the functional relationship equation of the compressive strength and the model of carbonation depth were established. The results showed that the change rule in mechanical strength and carbonation depth of the recycled concrete with metakaolin were the same as those of the concrete with metakaolin natural aggregate. When metakaolin is mixed in amounts less than 15%, it has a positive effect on the mechanical properties of RFAC, particularly its compressive strength. And the increase in the dosage of metakaolin is obviously advantageous for the improvement of the carbonation resistance of RFAC. Recycled fine aggregates acted negatively on the various properties of concrete and the extent of effect increased with the increase in substitution rate. When 15% fly ash is used as cementitious material, it can be compounded with 15% metakaolin to formulate RFAC with excellent performance, and the recycled fine aggregate can be replaced by 60%.

Yao Shan, Jun Luo, Binglong Wang et al.

Jet grouting piles were widely employed for ground reinforcement in building and infrastructure engineering due to the low cost and construction convenience. However, this foundation treatment method is not allowed to be used in high-speed railway involved constructions in China because of the concerning of the negative effect on the lateral displacement of the existing high-speed railway. To find a reasonable application distance of jet grouting piles away from existing high-speed railway bridge in deep soft soils with medium sensibility, a series of laboratory and in-situ tests on the influence of the jet grouting piling on the deformation of surrounding soils and adjacent high-speed railway bridge are carried out. The geological characteristics of the construction site and the mechanical properties of the soft soil are deeply investigated by utilizing field and laboratory tests. The piling induced lateral displacement of the surrounding soils is monitored as well as the displacement of an adjacent high-speed railway bridge. The monitoring data reveal that the influence area of the jet grouting piling is approximately 1.75 ∼ 1.85 times of the pile length in deep soft soils. The critical distance of the jet grouting piles from the existing high-speed bridge should be larger than 2 times of the pile length.

SHI Linping, LIAO Zhiying, XIE Zhigao et al.

The spillway of Dongchong Reservoir adopts an engineering scheme of spillway step energy dissipation and downstream stilling basin underflow. However, due to the limitations of terrain and geological conditions, the width of the stilling basin is small, and the angle between it and the river is 145°; meanwhile, the current downstream traffic bridge hinders flood discharge, resulting in many unfavorable factors. For the original scheme, the discharge entering the stilling basin makes the water surface fluctuate greatly, and the water flow out of the basin accelerates significantly. The main flow in the river is concentrated, and a large-scale backflow area is formed on the left of the upstream traffic bridge. This paper optimizes the layout scheme of the stilling basin through hydraulic model tests. The results show that through measures such as deepening the stilling basin, installing T-shaped piers in the front section of the basin, shifting the left side wall of the stilling basin to the left, and lowering the tail-weir and creating a reverse slope towards the river, etc., the water flow pattern is significantly improved. After the discharge enters the basin, the fluctuation amplitude of the water surface decreases, and the water flow out of the basin no longer accelerates. The water flow in the river is dispersed and the flow velocity falls. The research results can provide a reference for similar projects.

Hongwei Xiong, Lidong Gu, Jingya Wang et al.

Magnesium matrix composites have garnered significant attention in recent years owing to their exceptional lightweight properties and notable potential in various engineering applications. The interface generally acts as a “bridge” between the matrix and reinforcement, playing crucial roles in critical processes such as load transfer, failure behavior, and carrier transport. A deep understanding of the interfacial structures, properties, and effects holds paramount significance in the study of composites. This paper presents a comprehensive review of prior researches related to the interface of Mg matrix composites. Firstly, the different interfacial structures and interaction mechanisms encompassing mechanical, physical, and chemical bonding are introduced. Subsequently, the interfacial mechanical properties and their influence on the overall properties are discussed. Finally, the paper addresses diverse interface modification methods including matrix alloying and reinforcement surface treatment.

WANG Liang, WEI huanbo, GAO Yajie et al.

To study the degradation patterns of shear resistance of stud connectors under corrosion conditions, an ABAQUS finite element model was established for numerical simulation. Four different corrosion distribution patterns, namely, uniform annulus, compressive zone semi-annulus, tensile zone semi-annulus, and tensile-compressive zone semi-annulus, were considered. Numerical analyses were carried out for different corrosion heights (CH) and depths. The results show that when the corrosion depth (CD) is constant, the shear bearing capacity decreases with the increase of CH, reaching its minimum at a CH of 10 mm. Moreover, the greater the CD, the greater the degree of reduction. When the CH is constant, the shear capacity and stiffness decrease linearly with the increase of CD. Under the conditions of equal CH and CD of the studs, the reduction of shear capacity and stiffness of uniform annulus corrosion is the largest, which is about 60% lower than the other three situations, while the smallest reduction occurs in the studs with compressive zone semi-annulus corrosion. The research results can provide reference for the durability design of stud connectors in steel-concrete composite structures.

Ebube Alor, Ahmad Abdellatif, SayedHassan Khatoonabadi et al.

Software engineering (SE) chatbots are increasingly gaining attention for their role in enhancing development processes. At the core of chatbots are Natural Language Understanding platforms (NLUs), which enable them to comprehend user queries but require labeled data for training. However, acquiring such labeled data for SE chatbots is challenging due to the scarcity of high-quality datasets, as training requires specialized vocabulary and phrases not found in typical language datasets. Consequently, developers often resort to manually annotating user queries -- a time-consuming and resource-intensive process. Previous approaches require human intervention to generate rules, called labeling functions (LFs), that categorize queries based on specific patterns. To address this issue, we propose an approach to automatically generate LFs by extracting patterns from labeled user queries. We evaluate our approach on four SE datasets and measure performance improvement from training NLUs on queries labeled by the generated LFs. The generated LFs effectively label data with AUC scores up to 85.3% and NLU performance improvements up to 27.2%. Furthermore, our results show that the number of LFs affects labeling performance. We believe that our approach can save time and resources in labeling users' queries, allowing practitioners to focus on core chatbot functionalities rather than manually labeling queries.

Yazhou Wang, Meng Zu, Xiaosong Zhou et al.

Abstract Photoelectrocatalysis (PEC) incorporates electrochemical techniques with photocatalysis (PC) to facilitate the separation of the photoelectron-hole produced at semiconductor nanoparticles, leading to enhanced photocatalytic efficiency for various applications. Due to its inherently low cost, non-toxicity and chemical stability, titanium dioxide (TiO2) based PEC devices are considered the most promising system for chemical engineering such as pollution degradation and fuel generation, and PEC sensing. In an attempt to bridge fundamental research and practical applications in chemical engineering and sensing, we herein systematically review recent advances in these PEC systems of different scales. More importantly, we offer a series of rational strategies including cell design, application of electric field photoelectrode morphology manipulation and bandgap engineering to enhance the performance of TiO2-based PEC devices and accelerate the commercialization of the TiO2-based PEC technology in chemical engineering.

Dezhao Wang, Han Wei, Ying Lin et al.

M. Z. Naser, V. Kodur, H. Thai et al.

Abstract Machine learning (ML) continues to rise as an effective and affordable method of tackling engineering problems. Unlike other disciplines, the integration of ML into structural and fire engineering domains remains deficient. This is due in part to the lack of benchmark databases to compare the effectiveness of ML models. In order to bridge this knowledge gap, this paper presents a benchmark examination of common supervised learning ML algorithms that can be easily deployed into structural and fire engineering problems. The selected algorithms include; Decision Trees (DT), Random Forest (RF), Extreme Gradient Boosted Trees (ExGBT), Light Gradient Boosted Trees (LGBT), TensorFlow Deep Learning (TFDL), and Keras Deep Residual Neural Network (KDP), and are used with their default values to establish a proper benchmark against six databases. The compiled datasets have been thoroughly tested and span two domains, structural engineering; 1) elemental response of concrete-filled steel tubular (CFST) circular columns at ambient conditions, 2) shear response of cold-formed steel (CFS) channels with slotted webs, 3) compressive strength of concrete, 4) fatigue life data, 5) shear strength of reinforced concrete (RC) beams and FRP-strengthened RC beams; and fire engineering, 6) fire behavior of RC concrete columns in terms of spalling occurrence and fire resistance. This study also investigates a variety of commonly used performance metrics that are applicable to regression and classification-based ML problems. We invite ML users to apply their models to the presented databases to establish a benchmark by mean of external validation and then extend their models to other problems and databases. Collectively, the presented work establishes the first step towards a unified framework that can be used to accelerate the adoption of ML into structural and fire engineering domains.