Hasil untuk "Architectural engineering. Structural engineering of buildings"

S. Pessoa, A. S. Guimarães, S. Lucas et al.

Abstract Building Information Modelling (BIM) paved the way to better information management in the construction sector, simplifying and encouraging the advent of digital technologies and tools. The application of large-scale additive manufacturing (AM) is growing and therefore subject to intensive research – on account of its disruptive potential to revolutionise the Architecture, Engineering and Construction (AEC) industry. With this systematic literature review, the authors aim to identify the major advances made so far on AM's applicability to the construction sector, with particular attention being given to the thermal efficiency of 3D printed buildings. The article begins by presenting the review methodology applied and offering an outline of the current situation in the construction industry, followed by a discussion on different AM processes. Applications in the construction industry are presented and the development of extrudable materials is addressed. The influence of the thermal insulation of the building's envelope on its energy consumption is explained and experimental applications presented. The state-of-the-art shows that 3D printing (3DP) is still in an early stage and the research remains focused on the printability and structural capacity. There is a noticeable gap on physical aspects such as thermal and acoustic behaviour, which are of major importance to the indoor environment quality. By discussing the difference in performance between commercial thermal insulation materials and the existing 3D printed materials, this research outlines new ways of improving the thermal performance of 3D printed structures, by using additives in the printed mix or by acting on the wall's structure.

Shuai Cheng, Chenjun Guo, Shan Liu et al.

Moisture damage severely compromises the material properties, structural integrity, and decorative layer integrity of historic buildings, presenting a critical technical challenge in architectural heritage conservation. Electromagnetic wave dehumidification technology has garnered attention for its minimal intervention, low cost, and high efficiency, yet its practical engineering applications remain limited. This paper categorizes electromagnetic wave dehumidification devices into two main types based on their active moisture removal capability: “water-blocking type” and “dewatering type”. Research indicates that electromagnetic wave dehumidification devices utilizing electroosmosis principles require precise control of electric field strength (≥40 V/m) and Joule effect, making them more suitable for historic buildings where the material surface carries a net negative charge and low salt content. Among moisture-blocking devices, those neutralizing water molecules perform best during humidity maintenance phases. Devices that primarily alter the structure of water molecules struggle to meet heritage dehumidification requirements. Experimental analysis indicates that external factors like moisture sources and seasonal environments significantly influence technical evaluations. This paper recommends that future research should optimize experimental design, strengthen comparative studies, and explore composite mechanisms to enhance the systematic reliability of electromagnetic wave dehumidification technology in architectural heritage conservation. This research helps to clarify some of the conceptual uncertainties associated with the use of electromagnetic wave dehumidification technology. Furthermore, it proposes a principle-based experimental framework that can be used to guide future experimental designs and the application of this technology in the field of cultural heritage preservation.

Anna Burgstaller, Sara Madureira, Oskar Staufer

Tissue functions rely on complex structural, biochemical, and biomechanical cues that guide cellular behavior and organization. Synthetic cells, a promising new class of biomaterials, hold significant potential for mimicking these tissue properties using simplified, nonliving building blocks. Advanced synthetic cell models have already shown utility in biotechnology and immunology, including applications in cancer targeting and antigen presentation. Recent bottom-up approaches have also enabled synthetic cells to assemble into 3D structures with controlled intercellular interactions, creating tissue-like architectures. Despite these advancements, challenges remain in replicating multicellular behaviors and dynamic mechanical environments. Here, we review recent advancements in synthetic cell-based tissue formation and introduce a three-pillar framework to streamline the development of synthetic tissues. This approach, focusing on synthetic extracellular matrix integration, synthetic cell self-organization, and adaptive biomechanics, could enable scalable synthetic tissues engineering for regenerative medicine and drug development.

Ali Arkan Alwan, Zena Kadhem, Hussain Al-Kayiem et al.

Double-pipe heat exchangers are widely used in thermal systems, and enhancing their performance is critical for energy efficiency. This study examines the impact of fin installation on heat transfer and entropy generation in a counterflow double-pipe heat exchanger using CFD simulation. The inner pipe is made of copper with an inner diameter of , outer diameter of  and 1000 mm in length. The outer pipe is made of PVC with an inner diameter of  and an outer diameter of  sharing the same length as the inner pipe. Numerical simulations were conducted to compare smooth and finned tubes under identical thermal and flow conditions. Entropy generation due to heat transfer and fluid friction was analyzed. The results showed that finned tubes improved heat transfer (Q) watts by up to 22%, particularly at higher hot water temperatures of 70 oC and 0.1 kg/s flow rate. However, this enhancement was accompanied by increased entropy generation up to 40%, indicating higher thermodynamic irreversibility. The study highlights the trade-off between thermal performance and entropy generation, providing valuable insight for optimizing heat exchanger design. The finned tube also showed good enhancement of Nusselt number by 46% and effectiveness by 20% compared to the smooth tube.

Ahmed Jasim Obaid, Hassan K. Al-Musawi, Majid Valizadeh

Within the last ten years, several modern technologies were invented, and different types of services were subscribed to and used in daily life. All these are in need of high data rate and wide coverage in respect to mobile communication, and it thus needs an advanced generation to meet these performances as dictated by the end users. This paper is intended to advocate radio-over-fiber technique in 5G systems, improving standards of techniques for ensuring effective wireless communications coverage. But the problem was an issue of nonlinear effect causing some failure in the system performance, especially at a distance of 400km in transmission and data rate impact at fifth generation-the data downloaded is up to 100 GBps. It uses a major concept from signal processing within NG5 RoF for transmission and reception. The defects take place starting off with the use of the transmitted signal at first instance within modulated 16QAM while it reaches receiving through the power account until the filtering to BER, which is taken up to distance transmission, initially starting from the 100 n right up to a distance of 400 km, hence. Worth remarking is that all the models presented in this report were simulated using Optisystem 18.

Mia Mohammad Imran, Tarannum Shaila Zaman

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

Marios Impraimakis

The response-only model class selection capability of a novel deep convolutional neural network method is examined herein in a simple, yet effective, manner. Specifically, the responses from a unique degree of freedom along with their class information train and validate a one-dimensional convolutional neural network. In doing so, the network selects the model class of new and unlabeled signals without the need of the system input information, or full system identification. An optional physics-based algorithm enhancement is also examined using the Kalman filter to fuse the system response signals using the kinematics constraints of the acceleration and displacement data. Importantly, the method is shown to select the model class in slight signal variations attributed to the damping behavior or hysteresis behavior on both linear and nonlinear dynamic systems, as well as on a 3D building finite element model, providing a powerful tool for structural health monitoring applications.

Dinesh Eswararaj, Ajay Babu Nellipudi, Vandana Kollati

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.

Hashini Gunatilake, John Grundy, Rashina Hoda et al.

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

Yibin Ao, P. Peng, Mingyang Li et al.

PurposeBuilding Information Modeling (BIM) competitions are a beneficial approach to enhance BIM education, offering students practical experience in BIM application, including mastering workflows and technical tools. However, research exploring the individual perceptions influencing participation intentions and behaviors in BIM competitions is limited. Therefore, this study aims to investigate the factors affecting university students' behavioral intention and behavior in BIM competitions, providing theoretical support for BIM competitions and educational reform.Design/methodology/approachThis study employs the Structural Equation Modeling (SEM) based on the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to analyze the factors influencing BIM competition participation among 970 Architecture, Engineering, and Construction (AEC) university students.FindingsThe results of the study show that social influence, attitude, and self-efficacy play critical roles in shaping students' intentions to participate in BIM competitions. Furthermore, self-efficacy, facilitating conditions, and behavioral intention significantly influence students' actual engagement in such competitions. Surprisingly, effort expectancy negatively influences intentions, as less challenging tasks can lead students to perceive their participation as less impactful on their skills and learning, reducing their behavioral intention to participate.Originality/valueThis research provides valuable insights into the effectiveness of BIM competitions in enhancing BIM education for AEC students. Extending the UTAUT model to include self-efficacy and attitude, provides a novel perspective for understanding students' intentions and behaviors regarding BIM competitions. The study’s theoretical support proposes incorporating BIM competitions to augment BIM teaching methods and offers suggestions for advancing the efficacy of students' involvement in BIM competitions within higher education, thus contributing to educational reform in the AEC sector.

Rumia Z. Kiseleva, Natalia A. Kirsanova, Anatoliy P. Nikolaev et al.

For describing elastoplastic deformation, three versions of constitutive equations are used. The first version employs the governing equations of the flow theory. In the second version, elastic strain increments are defined the same way as in the flow theory, and the plastic strain increments are expressed in terms of stress increments using the condition of their proportionality to the components of the incremental stress deviator tensor. In the third version, the constitutive equations for a load step were obtained without using the hypothesis of separating strains into the elastic and plastic parts. To obtain them, the condition of proportionality of the components of the incremental strain deviator tensor to the components of the incremental stress deviator tensor was applied. The equations are implemented using a hybrid prismatic finite element with a triangular base. A sample calculation shows the advantage of the third version of the constitutive equations.

Mikhail N. Voskresenskiy, Alena A. Kurdanova

Studying the nature of the occurrence and propagation of microseismic tremors has not lost its relevance over the past few decades. Currently, the analysis of microseisms is the basis of some engineering and geological studies, including those aimed at the inspection of structures of various purposes. The procedure for preparing and conducting surveys is governed by a system of regulatory documents. However, the current codes and specifications represent a general guide for assessing the operational properties of building structures. Therefore, specific survey methods need to be clarified and detailed. Describes the experiment of examining the building regarding the dynamics of frequency characteristics within 24 hours. The observation system was implemented in the form of 16 points, evenly distributed over the volume of the building. Spectral analysis based on FFT was carried out to identify the time intervals within the 24-hour period with a pronounced maximum and minimum level of man-induced impact on the studied subject. During the hours of maximum exposure, the spectra were correlated according to records of different duration in terms of the correspondence of frequency components. The necessary and sufficient duration of registration of microseismic vibrations was derived to determine the frequency of natural vibration of a building when the observation points are located on the lower and upper floors.

Mohamed Hatem, Nader Mohamed, Khaled Samy et al.

The current study aims to study the structural behavior of ferrocement beams using seawater to produce concrete beams that can be used as an alternative to conventional reinforced concrete beams. The formulated beams would have a high resistance to loads and cracking, and would be more economical and environmentally friendly than traditional concrete beams. This research also aims to conserve freshwater by using seawater as a substitute in the concrete mix and curing process. The experimental work include three groups of beams ,The water-cement ratio and seawater content were varied in the concrete mix. Six concrete specimens with dimensions of 1600 mm * 300 mm * 150 mm were cast. All specimens were reinforced with fiber glass bars and fiberglass mesh. The fresh water in concrete mixing was varied and replaced with seawater. The curing water for the beams was also replaced with seawater. The reinforcement ratios were also varied in the specimens. In the first group, a ferrocement beam was cast as a reference using potable water for casting. In the second group, three beams were cast with different seawater contents in the concrete mix. In the third group, two ferrocement beams were cast with different seawater contents in the concrete mix and curing water. The cracking load, load-deflection curves, energy absorption capacity and cracking patterns have been investigated. The results showed that increasing the seawater content increased the concrete strength by 5% to 15% and the ultimate load increased by 5% to 47%.

Zaurbek K. Abaev, Faiz Sulthan

The methodology for seismic performance evaluation of a residential building in Indonesia with the use of seismic isolation is considered. An 8-storey reinforced concrete frame residential building with shear wall structural system was selected as a case study. Nonlinear methods of seismic response analysis were used to calculate the response of the structure: nonlinear static (Pushover) and Nonlinear-Time History Analysis, NLTHA. The analysis is performed in STERA 3D freeware. The nonlinear time history analysis was performed for seven pairs of horizontal components of earthquake ground motions, selected according to the parameters of possible earthquakes for the considered site (Bandung city). The selected earthquake records were modified using the spectral matching procedure for design spectrum. Friction-pendulum bearings developed by Nippon Steel Corporation of Japan were used as seismic isolation. The results of nonlinear time history analysis show that shallow earthquakes result in greater damage compared to megathrust earthquakes, with both scenarios providing a life safety (LS) performance level. The use of seismic isolation can reduce seismic loads, as evidenced by the reduction in top-level accelerations and shear forces at the base.

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

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

Johannes Schleiss, Aditya Johri

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

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

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

N. Alaboud, Adnan Alshahrani

The Saudi Vision 2030 is a program of change management on a national level driven mostly by the use of digital technology. The implementation of building information modelling (BIM) is part of this change, and there is general agreement that its use improves the productivity and quality of the architecture, engineering, and construction (AEC) industries. Despite its extensive construction projects, Saudi Arabia has only recently planned for BIM. Several conditions must apply before it is successfully implemented. While the literature has identified the factors critical to its success and the barriers to its adoption, few studies have rated these factors in terms of their importance and their contingent impact. Furthermore, the interactional relationship between the factors has rarely been investigated. As a result, an interpretative structural model (ISM) was conducted to establish a hierarchy of variables, while accounting for the dynamic interaction between each. For factor selection, the matrix-based multiplication applied to a classification (MICMAC) method was utilized. Therefore, awareness of BIM and sustainability benefits are expected to be the most important variables in acceptance. Furthermore, the dynamic method is gradually shifting from bottom-down to a combined effect of top-down and bottom-up leadership.

Georgina Esi Takyi-Annan, Hong Zhang

Over the past 20 years, the phrase “Building Information Modelling” (BIM) has spread throughout the Architecture, Engineering and Construction (AEC) industries. BIM usage in the construction industry is vital in the revolution towards Industry 4.0 in the AEC Industry. BIM contributes to this change due to its automatization and sustainability features. However, there are growing concerns about its implementation in the developing world context. The BIM Implementation Barriers (BIMIBs) in individual countries and on a global scale have been examined in a variety of studies and works of literature, but two research questions are still open; (1) what specific BIMIBs are the AEC industries in the developing world encountering the most, and (2) what is the interrelationship between these barriers? Through a combination of expert interviews and a bibliometric analysis of published relevant empirical studies on the subject, the aim of this study is to identify these frequently occurring BIMIBs in the developing world and to determine the interrelationships between these barriers using an Interpretive Structural Modelling (ISM) approach and MICMAC analysis. The study identified the 14 BIMIBs with ‘high associated cost’ as the most fundamental of all. A comparison of the study's findings and a proposed 3-level barrier mitigation strategy with other studies identified the lack of governmental support for BIM implementation and research as a root cause of majority of the BIMIBs identified in the developing world. This study lays forth the knowledge base for future studies in the area of BIM implementation in the developing world.

Jiuzhou Han, Wray Buntine, Ehsan Shareghi

Semi-structured explanation depicts the implicit process of a reasoner with an explicit representation. This explanation highlights how available information in a specific query is utilised and supplemented with information a reasoner produces from its internal weights towards generating an answer. Despite the recent improvements in generative capabilities of language models, producing structured explanations to verify a model's true reasoning capabilities remains a challenge. This issue is particularly pronounced for not-so-large LMs (e.g., FLAN-T5-XXL). In this work, we first underscore the limitations of supervised fine-tuning (SFT) in tackling this challenge, and then introduce a carefully crafted reward engineering method in reinforcement learning (RL) to better address this problem. We investigate multiple reward aggregation methods and provide a detailed discussion which sheds light on the promising potential of RL for future research. Our proposed method on two semi-structured explanation generation benchmarks (ExplaGraph and COPA-SSE) achieves new state-of-the-art results.