Hasil untuk "Architectural engineering. Structural engineering of buildings"

Alexandra González, Xavier Franch, Silverio Martínez-Fernández

Integrating Artificial Intelligence into Software Engineering (SE) requires having a curated collection of models suited to SE tasks. With millions of models hosted on Hugging Face (HF) and new ones continuously being created, it is infeasible to identify SE models without a dedicated catalogue. To address this gap, we present SEMODS: an SE-focused dataset of 3,427 models extracted from HF, combining automated collection with rigorous validation through manual annotation and large language model assistance. Our dataset links models to SE tasks and activities from the software development lifecycle, offering a standardized representation of their evaluation results, and supporting multiple applications such as data analysis, model discovery, benchmarking, and model adaptation.

Mairieli Wessel, Daniel Feitosa, Sangeeth Kochanthara

Rising publication pressure and the routine use of generative AI tools are reshaping how software engineering research is produced, assessed, and taught. While these developments promise efficiency, they also raise concerns about skill degradation, responsibility, and trust in scholarly outputs. This vision paper employs Design Fiction as a methodological lens to examine how such concerns might materialise if current practices persist. Drawing on themes reported in a recent community survey, we construct a speculative artifact situated in a near future research setting. The fiction is used as an analytical device rather than a forecast, enabling reflection on how automated assistance might impede domain knowledge competence, verification, and mentoring practices. By presenting an intentionally unsettling scenario, the paper invites discussion on how the software engineering research community in the future will define proficiency, allocate responsibility, and support learning.

Golnoush Abaei, Mojtaba Shahin, Maria Spichkova

The inclusion of internship courses in Software Engineering (SE) programs is essential for closing knowledge gaps and improving graduates' readiness for the software industry. Our study focuses on year-long internships at RMIT University (Melbourne, Australia), which offers in-depth industry engagement. We analysed how the course evolved over the last 10 years to incorporate students' needs and summarised the lessons learned that can be helpful for other educators supporting internship courses. Our qualitative analysis of internship data based on 91 reports during 2023-2024 identified three challenge themes the students faced, and which courses were found by students to be particularly beneficial during their internships. On this basis, we proposed recommendations for educators and companies to help interns overcome challenges and maximise their learning experience.

Yongqing Jiang, Jianze Wang, Xinyi Shen et al.

A rapid and accurate assessment of structural damage to buildings in the aftermath of earthquakes is critical to emergency responses and engineering retrofit decisions. However, current in situ building damage assessment is primarily conducted through visual inspections by engineering professionals and deep learning techniques using single‐modal information, which are time‐consuming and unable to effectively integrate visual and textual information. In recent years, multimodal learning methods and large language models (LLMs), which could process visual and linguistic information, have emerged as viable alternatives for damage assessment of building constructions. In this study, a vision question–answering model for structural damage assessment (SDA‐Chat) is developed that automatically generates professional textual interpretations of structural damage images via multi‐round visual question–answering (VQA) interactions. A three‐stage training strategy that includes instruction fine‐tuning is designed to improve the model's VQA accuracy. The cross‐modality projector based on dimension reshaping and parallel network architecture is developed to enhance the accuracy and speed of alignment of multimodal features. Comparative experiments are conducted on the self‐constructed dataset containing 8195 pairs of structural damage images and corresponding damage description texts, focusing on various advanced LLMs. The results highlight that the SDA‐Chat can simultaneously process seven different tasks, demonstrating the effectiveness of the proposed method. The highest question–answering accuracy and efficiency of the model reached 83.04% and 435.31 tokens/s, respectively. In addition, high‐precision and lightweight solutions are designed for different application scenarios.

Sergei Yu. Savin

The study addresses the stress-strain state stages of reinforced concrete frames in zones of potential local collapse due to failure of a vertical element, such as a column or pylon. The paper provides initial assumptions about the mechanisms of secondary failure propagation in multi-storey reinforced concrete building frames, depending on the initial local collapse scenario. Based on these assumptions, the paper formulates force and deformation criteria for the stress-strain state stages of reinforced concrete building frames in the zone of potential local collapse. Using energy balance conditions, simplified relations were developed to estimate the ultimate static load for compressive arch and catenary actions of floor slab structures. The calculated force and deformation criteria values were compared with the experimental values. These comparisons demonstrate that the accuracy of the proposed relations is acceptable for engineering calculations.

Aaron Gillich

All UK net zero scenarios call for zero gas use in homes by 2050. Delivering this along with any enabling measures is the largest heating market transformation since the gas conversion in the period 1965–77. Academics have long called for a market transformation approach to retrofit, and past work has outlined pillars of a successful framework: programme design, marketing and outreach, workforce engagement, financial incentives, and data and evaluation. This paper adapts and expands on this framework to study the transformation off the gas network as part of a national net zero retrofit strategy. It uses annual reports from the Gas Council and qualitative interviews with one expert witness to characterise the gas conversion as a market transformation problem. It then carries out a similar mapping for the present-day net zero transformation. The study finds that nearly all the actions taken during the gas conversion have counterpart activities that must be carried out for net zero. In contrast, the transition to net zero is, however, more fragmented, with unclear objectives, an insufficiently articulated value proposition and no process owner. Ideas are proposed for how these gaps can be addressed by both policymakers and researchers. Policy relevance All UK net zero scenarios call for zero gas use in homes by 2050. Delivering this along with any enabling measures is the largest heating market transformation since the gas conversion from ‘town gas’ (i.e. gas manufactured from coal) to natural gas in the period 1965–77. The UK policy approach to retrofit has so far been fragmented and ineffective. Market transformation clarifies long-term objectives and coordinates programmes to meet those objectives. This paper situates the gas conversion process as a market transformation problem and studies the factors that characterised its successful implementation. It then carries out a similar mapping for the present-day net zero transformation. The study finds that net zero has comparatively unclear objectives, fragmented supply chains, an insufficiently articulated value proposition and no process owner. The gas conversion had active policy responses for all these issues, which offer useful lessons and a blueprint for net zero retrofit policies today.

Shraddha Surana, Ashwin Srinivasan, Michael Bain

Engineering information systems for scientific data analysis presents significant challenges: complex workflows requiring exploration of large solution spaces, close collaboration with domain specialists, and the need for maintainable, interpretable implementations. Traditional manual development is time-consuming, while "No Code" approaches using large language models (LLMs) often produce unreliable systems. We present iProg, a tool implementing Interactive Structured Inductive Programming. iProg employs a variant of a '2-way Intelligibility' communication protocol to constrain collaborative system construction by a human and an LLM. Specifically, given a natural-language description of the overall data analysis task, iProg uses an LLM to first identify an appropriate decomposition of the problem into a declarative representation, expressed as a Data Flow Diagram (DFD). In a second phase, iProg then uses an LLM to generate code for each DFD process. In both stages, human feedback, mediated through the constructs provided by the communication protocol, is used to verify LLMs' outputs. We evaluate iProg extensively on two published scientific collaborations (astrophysics and biochemistry), demonstrating that it is possible to identify appropriate system decompositions and construct end-to-end information systems with better performance, higher code quality, and order-of-magnitude faster development compared to Low Code/No Code alternatives. The tool is available at: https://shraddhasurana.github.io/dhaani/

Max Ofsa, Taylan G. Topcu

Systems engineering (SE) is evolving with the availability of generative artificial intelligence (AI) and the demand for a systems-of-systems perspective, formalized under the purview of mission engineering (ME) in the US Department of Defense. Formulating ME problems is challenging because they are open-ended exercises that involve translation of ill-defined problems into well-defined ones that are amenable for engineering development. It remains to be seen to which extent AI could assist problem formulation objectives. To that end, this paper explores the quality and consistency of multi-purpose Large Language Models (LLM) in supporting ME problem formulation tasks, specifically focusing on stakeholder identification. We identify a relevant reference problem, a NASA space mission design challenge, and document ChatGPT-3.5's ability to perform stakeholder identification tasks. We execute multiple parallel attempts and qualitatively evaluate LLM outputs, focusing on both their quality and variability. Our findings portray a nuanced picture. We find that the LLM performs well in identifying human-focused stakeholders but poorly in recognizing external systems and environmental factors, despite explicit efforts to account for these. Additionally, LLMs struggle with preserving the desired level of abstraction and exhibit a tendency to produce solution specific outputs that are inappropriate for problem formulation. More importantly, we document great variability among parallel threads, highlighting that LLM outputs should be used with caution, ideally by adopting a stochastic view of their abilities. Overall, our findings suggest that, while ChatGPT could reduce some expert workload, its lack of consistency and domain understanding may limit its reliability for problem formulation tasks.

Dehai Zhao, Zhenchang Xing, Qinghua Lu et al.

UI automation is a useful technique for UI testing, bug reproduction, and robotic process automation. Recording user actions with an application assists rapid development of UI automation scripts, but existing recording techniques are intrusive, rely on OS or GUI framework accessibility support, or assume specific app implementations. Reverse engineering user actions from screencasts is non-intrusive, but a key reverse-engineering step is currently missing - recognizing human-understandable structured user actions ([command] [widget] [location]) from action screencasts. To fill the gap, we propose a deep learning-based computer vision model that can recognize 11 commands and 11 widgets, and generate location phrases from action screencasts, through joint learning and multi-task learning. We label a large dataset with 7260 video-action pairs, which record user interactions with Word, Zoom, Firefox, Photoshop, and Windows 10 Settings. Through extensive experiments, we confirm the effectiveness and generality of our model, and demonstrate the usefulness of a screencast-to-action-script tool built upon our model for bug reproduction.

Roham Koohestani, Philippe de Bekker, Begüm Koç et al.

Benchmarks are essential for unified evaluation and reproducibility. The rapid rise of Artificial Intelligence for Software Engineering (AI4SE) has produced numerous benchmarks for tasks such as code generation and bug repair. However, this proliferation has led to major challenges: (1) fragmented knowledge across tasks, (2) difficulty in selecting contextually relevant benchmarks, (3) lack of standardization in benchmark creation, and (4) flaws that limit utility. Addressing these requires a dual approach: systematically mapping existing benchmarks for informed selection and defining unified guidelines for robust, adaptable benchmark development. We conduct a review of 247 studies, identifying 273 AI4SE benchmarks since 2014. We categorize them, analyze limitations, and expose gaps in current practices. Building on these insights, we introduce BenchScout, an extensible semantic search tool for locating suitable benchmarks. BenchScout employs automated clustering with contextual embeddings of benchmark-related studies, followed by dimensionality reduction. In a user study with 22 participants, BenchScout achieved usability, effectiveness, and intuitiveness scores of 4.5, 4.0, and 4.1 out of 5. To improve benchmarking standards, we propose BenchFrame, a unified framework for enhancing benchmark quality. Applying BenchFrame to HumanEval yielded HumanEvalNext, featuring corrected errors, improved language conversion, higher test coverage, and greater difficulty. Evaluating 10 state-of-the-art code models on HumanEval, HumanEvalPlus, and HumanEvalNext revealed average pass-at-1 drops of 31.22% and 19.94%, respectively, underscoring the need for continuous benchmark refinement. We further examine BenchFrame's scalability through an agentic pipeline and confirm its generalizability on the MBPP dataset. All review data, user study materials, and enhanced benchmarks are publicly released.

Jake Zappin, Trevor Stalnaker, Oscar Chaparro et al.

This position paper examines the substantial divide between academia and industry within quantum software engineering. For example, while academic research related to debugging and testing predominantly focuses on a limited subset of primarily quantum-specific issues, industry practitioners face a broader range of practical concerns, including software integration, compatibility, and real-world implementation hurdles. This disconnect mainly arises due to academia's limited access to industry practices and the often confidential, competitive nature of quantum development in commercial settings. As a result, academic advancements often fail to translate into actionable tools and methodologies that meet industry needs. By analyzing discussions within quantum developer forums, we identify key gaps in focus and resource availability that hinder progress on both sides. We propose collaborative efforts aimed at developing practical tools, methodologies, and best practices to bridge this divide, enabling academia to address the application-driven needs of industry and fostering a more aligned, sustainable ecosystem for quantum software development.

R. W. Daryono, Nur Hidayat, M. Nurtanto et al.

The discrepancy between competence and real work in engineering graduates can be resolved with cooperation by the construction industry. Therefore, it is necessary to determine the appropriate and required architectural engineering competencies with the current demands and conditions of the construction industry. So this study aims to analyze the determinants of competence and test the competency development model for architectural engineering graduates according to the needs of the construction industry. The research sample method is non-probability sampling using purposive sampling. The research sample consisted of 240 practitioners and trainers from 40 construction industry companies. The PLS-SEM technique was used to test the measurement and structural models (3 dimensions, 8 elements, 47 constructs/indicators, and 9 hypotheses). The competence of architecture graduates is determined by the dominant factor, namely Utilities and Building Construction (UBC1 & UBC2, λ = 89.90%), and Building Estimation and Costing (BEC7, λ = 73.30%) is the lowest factor. The ability of the structural model to explain architectural competency measurements is 36.20% in the moderate category. The predictive relevance value (Q²) explains 47.5% to 56.0% of the phenomena predicted in the field and explains the level of strength of the observed value in the structural model. Furthermore, 9 hypotheses from 8 dimensions have a positive and significant effect. The results of this study can be a recommendation for schools in the competency implementation model, and efforts to improve graduates' abilities and skills so that they can be absorbed by the construction industry and reduce unemployment.

Jun Zhou

This article delves into the synergistic integration of architectural design, structural restoration, and civil engineering, highlighting their pivotal role in fostering sustainable urban development. It explores cutting-edge methodologies and innovative practices that synergize to bolster building efficiency, fortify structural integrity, and advance environmental sustainability within urban landscapes. By delving into the latest trends in architectural design, addressing challenges and breakthroughs in structural restoration, and illuminating the evolving responsibilities of civil engineering in urban planning, this paper provides a comprehensive panorama of the intricate interplay among these disciplines. Furthermore, it ventures into the profound ramifications of technological advancements and sustainable strategies, underscoring their transformative influence on the urban environments of tomorrow. This holistic examination underscores the collective efforts of these fields in shaping resilient and eco-conscious cities poised for a sustainable future.

Gajalakshmi G, Meenakshi S

This paper explores the intricate relationship between man and nature in Ernest Hemingway’s The Old Man and the Sea through the lens of deep ecology. It challenges the traditional anthropocentric interpretation of the novella, proposing that the protagonist Santiago’s struggle is not merely a tale of human triumph over nature but a journey towards understanding and coexisting with the natural world. By applying the principles of deep ecology, the study reveals how Santiago’s evolving relationship with the marlin and other sea elements reflects a broader ecological consciousness. The analysis also draws parallels between Santiago’s experience and the Biblical narrative of Jonah, suggesting that Santiago’s success is not solely due to his physical endurance but also the cosmic forces that aid him. This paper ultimately rethinks the themes of struggle and victory in the novella, emphasising the need for a harmonious relationship between humanity and the environment.

Dejene Tadesse Banjaw, Habtamu Gudisa Megersa

Garlic is a versatile vegetable commonly grown in subtropical and highland agroecosystems, which is utilized for its culinary, medicinal, and spice properties. The use of garlic as a medicinal aid can be traced back to ancient times. The health benefits of garlic production are attributed to its antiviral, antibacterial, and antifungal properties. The use of garlic is prevalent in both traditional and modern healthcare systems, where it is used to treat a wide range of conditions. Numerous studies have reported the therapeutic properties of garlic, and its effectiveness has been demonstrated in clinical trials. The growing global interest in health and wellness, the widespread use of garlic as a spice, and its potential economic, social, and health benefits have contributed to a surge in its demand worldwide. This review aims to provide a comprehensive overview of the scientific literature on the morphological descriptions of garlic and its nutritional and health significance.

Hamed Afsoosbiria, Darja Kubečková, Oskar Kambole Musenda et al.

Post-industrial sites are a part of many cities. The impacts of industrial activities are not only evident in the area where the activity took place, but also affect the buildings within these areas. Buildings that served the industry in the past were built mainly by mass construction methods. From today’s point of view, these buildings are unsatisfactory in terms of typology, operation, and energy. In particular, energy rehabilitation is a way to restore industrial buildings and bring them to a full-fledged state. This issue is documented in a case study of a city affected by underground mining activity and on a selected skeleton construction. Given that industrial buildings have heavy or mass structures where some elements like beams and columns are damaged, it is crucial to consider not only energy solutions, but also the structural and architectural aspects of these buildings. In terms of thermal engineering and energy, including the renovation of structures, a software-supported evaluation of three material variants for the envelope walls of the skeleton construction from the 1970s was conducted. This study evaluates the thermal performance of conventional, proposed, and traditional wall designs by analysing their U-values, thermal resistance, and structural advantages. The results reveal that the conventional wall, featuring a 150 mm EPS 70 NEO insulation layer, achieves the lowest U-value, outperforming the proposed wall by a factor of 1.2 in thermal resistance. Both designs significantly reduce U-values compared to traditional walls, by factors of 6.55 and 5.40, respectively. Despite a 23% reduction in thickness relative to the conventional wall (and 44% compared to traditional walls), the proposed wall demonstrates robust thermal performance. Further benefits include reduced structural dead load, with the conventional and proposed walls being 3.70 times lighter per square meter than traditional walls. This reduction can decrease foundation, column, and beam dimensions, optimizing building design. Thermal bridging analysis highlights superior corner insulation in conventional walls due to higher surface temperatures, while the proposed wall maintains effective insulation with surface temperatures close to indoor conditions. Overall, the findings underscore the importance of advanced materials in achieving efficient thermal performance while balancing architectural and structural demands. The results achieved from the experimental work show that industrial buildings can be effectively energy-renovated in a way that complies with legislative documents, successfully extends the physical life of the frame structures, and contributes to carbon neutrality.

Agatha Czekajlo, Julieta Alva, Jeri Szeto et al.

As urban heatwaves become more severe, frequent and longer, cities seek adaptive building cooling measures. Although passive building design, energy-efficient materials and technologies and mechanical means are proven cooling methods, the potential of nature-based solutions (particularly trees as shading elements) has been understudied despite its significant opportunity. Using a new framework to explore this at the neighbourhood level, three future (2050) potential tree planting strategies are modelled for increasing tree volume and canopy cover and their impacts assessed for summer building-level solar radiation absorption (SRA) and building cooling energy demand (BCED) for a densifying neighbourhood in Vancouver, Canada. The boldest tree planting strategy, with 287% more trees than baseline and 16% canopy cover, reduced neighbourhood-scale total SRA (22%) and BCED (48%) over a no-trees scenario. BCED reductions of up to 64% for retrofitted/redeveloped buildings and 53–79% for low/medium-height buildings (mostly single-family residential) were associated with targeted south-side tree planting. Taller/larger buildings (predominantly mixed use) and buildings along north–south-oriented streets (mainly commercial and mixed use) encountered more tree shading challenges and would require more site-specific interventions. The methodology presented provides a framework to assess current and potential future shading and cooling energy benefits through various tree planting strategies. Practice relevance This research illustrates the tree shading and cooling potential to improve indoor liveability, reduce energy demand and reduce vulnerabilities amidst mounting extreme heat risks. This novel framework and method can be used by planners and urban designers to understand the potential cooling reduction and to develop tree planting and management strategies for effective shading and indoor cooling at the neighbourhood scale. Based on a case study neighbourhood in Vancouver for 2050 climate scenarios, this research shows increased tree volume and canopy cover can significantly reduce building SRA and BCED during the summer. The level of tree shading impact on buildings’ SRA and BCED was associated with the intensity and location of tree planting, but also the relative amount of lower height (and smaller) buildings. The boldest tree planting strategy yielded a 48% reduction in energy demand for cooling.

Samat N. Yakupov, Gabdrauf G. Gumarov, Nukh M. Yakupov

Known methods and approaches are ineffective or not applicable at all in the study of mechanical characteristics and adhesion of coatings of complex structure, initially formed on non-planar surfaces. A device has been developed that includes fragments of spherical substrates with rings for mounting along the contour, a pressure source of the working medium with a pressure gauge, a line with a valve for supplying the working medium, a measuring complex and a line for etching the working medium. In a fragment of a spherical substrate there is a small diameter hole, in the area of which a cover is formed according to a given technology. The working medium is fed through a small hole in the tray. A segment of the coating detached from the substrate forms a dome in the form of an ellipsoid fragment. A numerical model of deformation of a coating fragment in the form of a spherical segment with a complex contour is being developed using well-known software complexes. At each step of loading by the “targeting” method, varying the modulus of elasticity and the Poisson’s ratio, we approach the parameters of the experimental dome and determine the actual mechanical and stiffness properties of the coating under study. We calculate the normal separation forces through the radial forces determined by the current numerical model, and then determine the coupling stresses. The developed experimental-theoretical method is an effective tool for evaluating the mechanical properties and stiffness of coatings of complex structure, as well as the adhesion of the coating to a spherical substrate.

Evgeny A. Lugovtsev, Karim N. Utaliev, Konstantin A. Chutkov

The authors present theoretical basis for creating software for operational (on-site testing) experimental determination of the possibility of safe passage of heavy vehicles on road bridges, taking into account their actual operational condition with experimental confirmations. The features, conditions of use, and benefits of the software under development are expanded upon. The creation of the software is driven, on the one hand, by the need to ensure the safety of the driver and the bridge structure, and on the other hand, the need to assess the load capacity of the superstructures of road bridges according to the parameters of their stress-strain state to ensure guaranteed safe passage of heavy vehicles. The developed software for the operational determination of the possibility of safe passage of heavy vehicles on road bridge structures, with the consideration of their actual operational condition, is implemented using a personal computer. The software provides an assessment of the possibility of heavy vehicle passage through split and non-split systems of any length, considering the actual operational condition of the systems, while allowing to safely use any mobile load as a point of reference. The introduced software will be used as part of an upgraded system for rapid assessment of the load capacity of road bridges, developed on the basis of the SI-PPM measurement system with the addition of technical devices that increase the possibility of operational assessment of the load capacity of road bridges.

Oluwatosin Ogundare, Srinath Madasu, Nathanial Wiggins

Large Language Models (LLMs) have shown great potential in solving complex problems in various fields, including oil and gas engineering and other industrial engineering disciplines like factory automation, PLC programming etc. However, automatic identification of strong and weak solutions to fundamental physics equations governing several industrial processes remain a challenging task. This paper identifies the limitation of current LLM approaches, particularly ChatGPT in selected practical problems native to oil and gas engineering but not exclusively. The performance of ChatGPT in solving complex problems in oil and gas engineering is discussed and the areas where LLMs are most effective are presented.