Hasil untuk "Architectural engineering. Structural engineering of buildings"

Lishuai Jin, R. Khajehtourian, Jochen Mueller et al.

Significance Mimicking material-level phenomena using macroscopically architected materials has gained popularity and enabled novel engineering applications such as photonic, acoustic, mechanical, and topological metamaterials. An interesting microstructural phenomenon observed in phase-transforming materials is the dissipative motion of topological defects such as phase and domain boundaries. With a few one-dimensional exceptions, structural analogs of dynamic phase-transforming materials are still rare, owing to their complicating strong nonlinearity. Through experiments, models, and simulations, we demonstrate a concept for tailoring propagating transition fronts in periodic structures in arbitrary dimensions. This significantly increases the design space of metamaterial performance and functionality and finds application in programming soft robotic locomotion, in controlling energy absorption (or release), and in mechanical logic devices. Transition fronts, moving through solids and fluids in the form of propagating domain or phase boundaries, have recently been mimicked at the structural level in bistable architectures. What has been limited to simple one-dimensional (1D) examples is here cast into a blueprint for higher dimensions, demonstrated through 2D experiments and described by a continuum mechanical model that draws inspiration from phase transition theory in crystalline solids. Unlike materials, the presented structural analogs admit precise control of the transition wave’s direction, shape, and velocity through spatially tailoring the underlying periodic network architecture (locally varying the shape or stiffness of the fundamental building blocks, and exploiting interactions of transition fronts with lattice defects such as point defects and free surfaces). The outcome is a predictable and programmable strongly nonlinear metamaterial motion with potential for, for example, propulsion in soft robotics, morphing surfaces, reconfigurable devices, mechanical logic, and controlled energy absorption.

Yuvaraj K, Sanam Narayana Reddy

This paper presents a substrate-dependent performance evaluation of a defected ground structure (DGS)-integrated multiband hexagonal microstrip patch antenna operating in the 22–28 GHz millimetre-wave band for 5G FR2 applications. To examine the influence of dielectric properties on electromagnetic behaviour, the same antenna geometry is implemented on three commonly used substrates—Duroid (relative permittivity εr ≈ 2.2, loss tangent tanδ ≈ 0.0009), Rogers (εr ≈ 2.94, tanδ ≈ 0.0012), and FR4 (εr ≈ 4.4, tanδ ≈ 0.02). A controlled substrate-based comparison is conducted with respect to the reflection coefficient, impedance bandwidth, gain, and radiation efficiency. The results indicate that substrate characteristics significantly affect resonance depth, impedance stability, and radiation performance at millimetre-wave frequencies. The Duroid-based configuration achieves S₁₁ below −32 dB, peak gain of 8–8.5 dBi, and high radiation efficiency due to reduced dielectric loss. The Rogers substrate exhibits stable multiband behaviour with moderate gain, whereas the FR4-based design shows reduced resonance depth and lower gain due to increased dielectric dissipation. By maintaining identical geometry across all substrates, the study isolates the direct impact of dielectric constant and loss tangent on modal excitation and efficiency degradation in the 22–28 GHz band. The presented analysis supports informed substrate selection for compact multiband mmWave antenna designs in next-generation wireless systems.

Weixing Zhang, Mario Herb, Martin Armbruster et al.

Despite Domain-Driven Design's proven value in managing complex business logic, a fundamental semantic expressiveness gap persists between generic modeling languages and tactical DDD patterns, causing continuous divergence between design intent and implementation. We envision a constraint-based tactical modeling environment that transforms abstract architectural principles into explicit, tool-enforced engineering constraints. At its core is a DDD-native metamodel where tactical patterns are first-class modeling primitives, coupled with a real-time constraint verification engine that prevents architectural violations during modeling, and bidirectional synchronization mechanisms that maintain model-code consistency through round-trip engineering. This approach aims to democratize tactical DDD by embedding expert-level architectural knowledge directly into modeling constraints, enabling small teams and junior developers to build complex business systems without sacrificing long-term maintainability. By lowering the technical barriers to DDD adoption, we envision transforming tactical DDD from an elite practice requiring continuous expert oversight into an accessible engineering discipline with tool-supported verification.

Ha Vo, Nhut Tran, Khang Vo et al.

In the era of "Software Engineering 2.0" (SE 2.0), where intelligent agents collaborate with human engineers, Generative AI is advancing beyond code generation into Software Architecture (SA). While Large Language Models (LLMs) demonstrate superior capabilities, computational costs and data privacy concerns drive interest in Small Language Models (SLMs) with fewer than 7 billion parameters. However, the reasoning limits of these resource-constrained models remain unexplored. This study benchmarks 10 state-of-the-art SLMs on Architectural Decision Records generation, introducing a multi-dimensional framework evaluating Technical Compliance and Semantic Diversity. Our empirical results reveal a significant reasoning gap: models above the 3B-parameter threshold demonstrate robust zero-shot capabilities, while sub-2B models show the strongest BERTScore gains from Fine-Tuning, though compliance improvements are not guaranteed. Contrary to assumptions regarding context saturation, Few-Shot prompting serves as a highly effective calibration mechanism for select mid-sized models with short context windows. Furthermore, high semantic diversity in off-the-shelf small models often correlates with hallucination rather than productive exploration. These findings establish a rigorous baseline for deploying sustainable, locally hosted architectural assistants.

Sherif Beskhyroun, Seyed Ehsan Aghakouchaki Hosseini

Liqing Hao, Yuexiang Li, Dongfang Zhang

Construction and demolition waste (C&D) and tyre garbage, in particular, are becoming urgent problems on a worldwide scale. One possible solution to this problem is to substitute man-made aggregates like recycled coarse aggregate (RCA) from C&D and crumb rubber (CR) from old tyres in newly-made building materials. The goal of this study is to determine whether machine learning and regression-based methods are best for predicting flexural strength (fs) in FRRAC, or fiber-reinforced rubberized recycled aggregate concrete. The Least Squares Support Vector Regression (LSSVR) was developed for this purpose. Hyperparameters are vital in this simulation, which use the LSSVR in conjunction with the Chimp optimisation algorithm (ChOA) and the Artificial rabbit optimisation algorithm (AROA) processes to identify the optimal set. Regression models were developed and tested to forecast fs's purpose using a portion of the study dataset (102 samples). A quarter (25 samples) were used for evaluation and seventy-five percent (77 samples) for instruction out of the 102 samples included in the database. The estimation process took into account several factors. Based on these metrics outcome numbers which provided in this study, the LSSVR(A) outperformed the LSSVR(C) in order to predicted predicting flexural strength (fs) in FRRAC.

Haoxuan Wang, Yifan Wang, Xu Liang et al.

Dislocations are line defects in crystalline solids and often exert a significant influence on the mechanical properties of metals. Recently, there has been a growing interest in using dislocations in ceramics to enhance materials performance. However, dislocation engineering has frequently been deemed uncommon in ceramics owing to the brittle nature of ceramics. Contradicting this conventional view, various approaches have been used to introduce dislocations into ceramic materials without crack formation, thereby paving the way for controlled ceramics performance. However, the influence of dislocations on functional properties is equally complicated owing to the intricate structure of ceramic materials. Furthermore, despite numerous experiments and simulations investigating dislocation-controlled properties in ceramics, comprehensive reviews summarizing the effects of dislocations on ceramics are still lacking. This review focuses on some representative dislocation-controlled properties of ceramic materials, including mechanical and some key functional properties, such as transport, ferroelectricity, thermal conductivity, and superconducting properties. A brief integration of dislocations in ceramic is anticipated to offer new insights for the advancement of dislocation engineering across various disciplines.

Xiaowen Tao, Yinuo Wang, Jinzhao Zhou

End-to-end reinforcement learning (RL) for motion control trains policies directly from sensor inputs to motor commands, enabling unified controllers for different robots and tasks. However, most existing methods are either blind (proprioception-only) or rely on fusion backbones with unfavorable compute-memory trade-offs. Recurrent controllers struggle with long-horizon credit assignment, and Transformer-based fusion incurs quadratic cost in token length, limiting temporal and spatial context. We present a vision-driven cross-modal RL framework built on SSD-Mamba2, a selective state-space backbone that applies state-space duality (SSD) to enable both recurrent and convolutional scanning with hardware-aware streaming and near-linear scaling. Proprioceptive states and exteroceptive observations (e.g., depth tokens) are encoded into compact tokens and fused by stacked SSD-Mamba2 layers. The selective state-space updates retain long-range dependencies with markedly lower latency and memory use than quadratic self-attention, enabling longer look-ahead, higher token resolution, and stable training under limited compute. Policies are trained end-to-end under curricula that randomize terrain and appearance and progressively increase scene complexity. A compact, state-centric reward balances task progress, energy efficiency, and safety. Across diverse motion-control scenarios, our approach consistently surpasses strong state-of-the-art baselines in return, safety (collisions and falls), and sample efficiency, while converging faster at the same compute budget. These results suggest that SSD-Mamba2 provides a practical fusion backbone for resource-constrained robotic and autonomous systems in engineering informatics applications.

Zhenhong Gu, Ziyi Xiao, Jingjing Yuan et al.

ABSTRACT Adopting carbon-efficient building shapes has significant potential to reduce embodied carbon emissions (ECEs). Early-stage design decisions play a crucial role in this process, yet current methods lack predictive models for ECEs based on building shape parameters. This study addresses this gap by utilizing the Dom-ino system, which includes concrete and steel framing, to develop a method for estimating ECEs. The study analyzes the influence of building shape parameters, such as plan aspect ratio and number of floors, on ECEs and fits equations to the results to establish predictive models. Our findings indicate that these parameters significantly impact ECEs, and the study delves into the mechanisms by which they affect structural components and material usage. The developed method provides architects with a tool to evaluate and optimize building designs for lower carbon impact during the early stages of design. This approach supports a swift and environmentally conscious design process, enhancing the ability to predict and reduce ECEs in architectural projects.

O.I. Bondarenko

Problem statement. The active use of renewable energy sources and the introduction of energy-efficient systems in all spheres of life today is the most important component of future development, which can change the life and comfort of every person. And it is very important to determine the place of architecture in this process. Analyzing the global experience of architectural activity in recent decades, especially in economically developed countries, it can be noted that engineering and technological systems of alternative energy are becoming an integral part of various types of buildings and complexes, both residential (low-rise, high-rise) and public (business, retail, cultural, multifunctional complexes, etc.). Alternative energy is becoming one of the factors influencing the layout and appearance of a building, the choice of materials and decorative finishing, and significantly influencing the formation of objects of new “innovative” architecture. Purpose of the article. To explore the features of the architectural form formation of energy-efficient multi-storey buildings as a result of the interdependence of architecture and energy-efficient technological systems using the example of modern architectural objects in the world. Conclusion. Engineering and technological systems of alternative energy for multi-storey buildings, based on renewable energy sources, provide such characteristics of buildings as: environmental friendliness, autonomy, self-sufficiency, profitability, energy efficiency and a high level of living comfort, architectural individuality and freedom of architectural form formation, unusual volumetric and compositional architectural solutions objects.

P. Ambily, Senthil Kumar Kaliyavaradhan, Neeraja Rajendran

Abstract 3D concrete printing (3DCP) is a recent trend in the construction sector. In 3DCP, the concrete is pumped layer by layer through a nozzle attached to a robotic arm to print structural components or the entire building. The application of 3DCP is not just limited to the earth; it’s also gaining traction in space habitat construction. However, there are constraints associated with using 3DCP in construction projects. This review details the top challenges faced in the 3DCP process related to material, strength, printer and highlights the applications of 3DCP in the construction sector. By choosing the suitable materials and configuring the printing parameters, it is possible to overcome the material and structural strength-related challenges such as workability, hardening time, mechanical and durability properties. The use of 3DCP on construction sites certainly provides cost and waste reductions, faster build rates, safer working environments and the possibility of more intricate architecture. Reinforcing methods and sustainable processes are the most frequently encountered issues with the 3DCP. Lack of technology, material variability, process optimization and many other issues are barriers to advancing 3D printing technology for concrete. It is concluded that 3DCP has potential and opportunity for the construction if the challenges are addressed.

G Priyanka, N Gireesh, S Hemachandra

This paper investigated the performance of Vedic multipliers in a 32-bit Multiplier-Accumulator Unit (MAC) by comparing Urdhva Tiryakbhyam and Nikhilam Sutras with various adder architectures. The goal was to identify the optimal combination of speed and resource efficiency. Urdhva Tiryakbhyam with CLA emerged as the fastest option, achieving a minimal delay of 0.709 ns. However, this came at the cost of higher resource utilization, measured in Logic Look-Up Tables (LUTs). Conversely, Nikhilam implementations generally required fewer LUTs, making them more resource-efficient, but they exhibited slightly slower performance. CLA consistently delivered the best delay for both Vedic multiplier types among the adder architectures. All the explored configurations are viable for practical implementation on Xilinx ISE 14.7. The key takeaway is that the choice between Urdhva Tiryakbhyam and Nikhilam and the specific adder architecture hinges on the application’s priorities.

Ali Naji, Thamer M. Jamel M. Jamel, Hassan F. khazaal

Digital beamforming (DBF) is a crucial technology for large antenna arrays, offering precise control over beam steering. This research introduces a novel method to enhance millimeter wave transmission by incorporating DBF with long-term memory (LSTM) based deep learning Our system utilizes digital signal processing and LSTM networks to optimize beamforming parameters instead of relying on traditional analog beamforming. The objective is to achieve high spectral efficiency. The methodology is executed in the programming language MATLAB and the obtained simulation outcomes validate a substantial enhancement in the metrics that evaluate performance, thereby demonstrating the potential of combining digital beamforming (DBF) with Long Short-Term Memory (LSTM) for forthcoming communication systems. Furthermore, the inclusion of LSTM in the process of digital beamforming presents a comprehensive comprehension of the proposed approach, which imparts valuable insights for advanced communication technologies. To substantiate the efficacy of the technique, several illustrative examples are employed to steer the beam pattern in the desired direction.

Nelly Bencomo, Jordi Cabot, Marsha Chechik et al.

Modern software-based systems operate under rapidly changing conditions and face ever-increasing uncertainty. In response, systems are increasingly adaptive and reliant on artificial-intelligence methods. In addition to the ubiquity of software with respect to users and application areas (e.g., transportation, smart grids, medicine, etc.), these high-impact software systems necessarily draw from many disciplines for foundational principles, domain expertise, and workflows. Recent progress with lowering the barrier to entry for coding has led to a broader community of developers, who are not necessarily software engineers. As such, the field of software engineering needs to adapt accordingly and offer new methods to systematically develop high-quality software systems by a broad range of experts and non-experts. This paper looks at these new challenges and proposes to address them through the lens of Abstraction. Abstraction is already used across many disciplines involved in software development -- from the time-honored classical deductive reasoning and formal modeling to the inductive reasoning employed by modern data science. The software engineering of the future requires Abstraction Engineering -- a systematic approach to abstraction across the inductive and deductive spaces. We discuss the foundations of Abstraction Engineering, identify key challenges, highlight the research questions that help address these challenges, and create a roadmap for future research.

Yiwen Dong, Yuyan Wu, Hae Young Noh

Gait abnormality detection is critical for the early discovery and progressive tracking of musculoskeletal and neurological disorders, such as Parkinson's and Cerebral Palsy. Especially, analyzing the foot-floor contacts during walking provides important insights into gait patterns, such as contact area, contact force, and contact time, enabling gait abnormality detection through these measurements. Existing studies use various sensing devices to capture such information, including cameras, wearables, and force plates. However, the former two lack force-related information, making it difficult to identify the causes of gait health issues, while the latter has limited coverage of the walking path. In this study, we leverage footstep-induced structural vibrations to infer foot-floor contact profiles and detect gait abnormalities. The main challenge lies in modeling the complex force transfer mechanism between the foot and the floor surfaces, leading to difficulty in reconstructing the force and contact profile during foot-floor interaction using structural vibrations. To overcome the challenge, we first characterize the floor vibration for each contact type (e.g., heel, midfoot, and toe contact) to understand how contact forces and areas affect the induced floor vibration. Then, we leverage the time-frequency response spectrum resulting from those contacts to develop features that are representative of each contact type. Finally, gait abnormalities are detected by comparing the predicted foot-floor contact force and motion with the healthy gait. To evaluate our approach, we conducted a real-world walking experiment with 8 subjects. Our approach achieves 91.6% and 96.7% accuracy in predicting contact type and time, respectively, leading to 91.9% accuracy in detecting various types of gait abnormalities, including asymmetry, dragging, and midfoot/toe contacts.

Heitor Vianna Moura

Relevante no debate público nacional desde a sua fundação, o Instituto de Arquitetos do Brasil não limita a sua agenda à institucionalização profissional. Este trabalho se foca em um aspecto pouco explorado nos estudos sobre o tema: a atuação dos departamentos locais do Instituto nas arenas em que as políticas urbanas municipais são discutidas, formuladas e implementadas. Para tanto, investiga-se a relação estabelecida entre o Instituto dos Arquitetos do Brasil – Departamento do Rio de Janeiro e a Prefeitura do Rio de Janeiro sob a gestão Eduardo Paes (2009-2012/2013-2016). Objetiva-se, com isso, compreender como os representantes da entidade atuaram nas disputas em torno de temas que dominaram o debate público da cidade no período, visando a definir e legitimar a prática profissional do grupo e, ao mesmo tempo, a intervir nas propostas elaboradas ou apoiadas pela Prefeitura. A partir desse estudo de caso, pretende-se refletir sobre a atuação desse grupo profissional na disputa pelo monopólio de enunciação dos problemas da cidade, tendo o Estado como instância de legitimação.

Wenchao Wang, Ryozo Ooka, Hideki Kikumoto et al.

Abstract This study serves as a basic study of the indoor dispersion of pollen particles, simulating the flow field and discussing the behavior of particles of different diameters in different rooms. By comparing the vertical velocity components of particles (w¯p) and the mean flow velocity of z‐direction component (wf) plus the terminal settling velocity in a gravitational field (Vg), the differences between w¯p values and wf plus Vg values are found to occur mainly at locations close to the opposite wall of the inlet. The location of the differences between w¯p values and wf plus Vg values is important findings of this study, which facilitates the improvement of the simulation method at a later stage and the rational design of indoor ventilation patterns to easily remove particles from the room.

Fatimah De'nan, Jia Shen Lau, Adham Mohamade Ounahe et al.

The adoption of steel in the construction industry will consistently grow due to rapid urbanisation and the demand of more structures and infrastructures. The main reasons of steel adaptation in construction industry are due to steel attributes that are flexible, sustainable, cost effective and a versatile material. The significant characteristics of steel provide the suitability for the construction of structures such as tall buildings and bridges all around the world. Along with the constant development of technology, the steel industry also aims to increase the sustainability of steel structure construction through constructing low carbon neutral and energy efficient building with steels. Moreover, steels are also considered as one of the most recycled materials in the world which allows the enhancement of the overall environmental performance of a structure’s life cycle. With the increasing utilisation of steel in the design of structures, the stability consideration of the steel structures has become the most crucial concern during the structural designing phase. Stability of structures is vital for every building as the structure instability may lead to catastrophe such as structural collapse that may threatens the safety of occupants inside the building as well as the well -being of the community around the area.

Michael Dorner, Maximilian Capraro, Oliver Treidler et al.

The engineering of complex software systems is often the result of a highly collaborative effort. However, collaboration within a multinational enterprise has an overlooked legal implication when developers collaborate across national borders: It is taxable. In this article, we discuss the unsolved problem of taxing collaborative software engineering across borders. We (1) introduce the reader to the basic principle of international taxation, (2) identify three main challenges for taxing collaborative software engineering making it a software engineering problem, and (3) estimate the industrial significance of cross-border collaboration in modern software engineering by measuring cross-border code reviews at a multinational software company.

Samah Syed, Angel Deborah S

In software development, code comments play a crucial role in enhancing code comprehension and collaboration. This research paper addresses the challenge of objectively classifying code comments as "Useful" or "Not Useful." We propose a novel solution that harnesses contextualized embeddings, particularly BERT, to automate this classification process. We address this task by incorporating generated code and comment pairs. The initial dataset comprised 9048 pairs of code and comments written in C, labeled as either Useful or Not Useful. To augment this dataset, we sourced an additional 739 lines of code-comment pairs and generated labels using a Large Language Model Architecture, specifically BERT. The primary objective was to build classification models that can effectively differentiate between useful and not useful code comments. Various machine learning algorithms were employed, including Logistic Regression, Decision Tree, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Gradient Boosting, Random Forest, and a Neural Network. Each algorithm was evaluated using precision, recall, and F1-score metrics, both with the original seed dataset and the augmented dataset. This study showcases the potential of generative AI for enhancing binary code comment quality classification models, providing valuable insights for software developers and researchers in the field of natural language processing and software engineering.