Search Results (777)

Corrosion can accelerate the deterioration of the mechanical properties of steel structures. However, few studies have systematically evaluated its impact on seismic performance, particularly with respect to seismic economic losses. In this paper, the seismic fragility and loss assessment of a multi-story steel frame with viscous dampers (SFVD) building are investigated through experimental and numerical analysis. Based on corrosion and tensile test results, OpenSees software 3.3.0 was used to model the SFVD, and the effect of corrosion on the seismic fragility was evaluated via incremental dynamic analysis (IDA). Then, the economic losses of the SFVD during different seismic intensities were assessed at various corrosion times based on fragility analysis. The results show that as the corrosion time increases, the mass and cross-section loss rate of steel increase, causing a decrease in mechanical property indices, and theprobability of exceedance of the SFVD in the limit state increases gradually with increasing corrosion time, with an especially significant impact on the collapse prevention (CP) state. Furthermore, the economic loss assessment based on fragility curves indicates that the economic loss increases with corrosion time. Thus, the aim of this paper is to provide guidance for the seismic design and risk management of steel frame buildings in coastal regions throughout their life cycle. Full article

Numerous rural residential buildings exhibit inadequate seismic performance when subjected to blast-induced vibrations, which poses potential threats to their overall stability and structural integrity when in proximity to blasting project sites. The investigation conducted in conjunction with the Qianshi Mountain blasting operations along the Wenzhou segment of the Hangzhou–Wenzhou High-Speed Railway integrates household field surveys and empirical measurements to perform modal analysis of rural residential buildings through finite element simulation. Adhering to the principle of stratified arrangement and composite measurement point configuration, an effective and reasonable experimental observation framework was established. In this investigation, the seven-story rural residential building in adjacent villages was selected as the research object. Strong-motion seismographs were strategically positioned adjacent to frame columns on critical stories (ground, fourth, seventh, and top floors) within the observational system to acquire test data. Methodical signal processing techniques, including effective signal extraction, baseline correction, and schedule conversion, were employed to derive temporal dynamic characteristics for each story. Combined with the Fourier transform, the frequency–domain distribution patterns of different floors are subsequently obtained. Leveraging the structural dynamic theory, time–domain records were mathematically converted to establish the structure’s maximum response spectra under blast-induced loading conditions. Through the analysis of characteristic curves, including floor acceleration response spectra, dynamic amplification coefficients, and spectral ratios, the dynamic response patterns of rural residential buildings subjected to blast-induced vibrations have been elucidated. Following the normalization of peak acceleration and velocity parameters, the mechanisms underlying differential floor-specific dynamic responses were examined, and the layout principles of measurement points were subsequently formulated and summarized. These findings offer valuable insights for enhancing the seismic resilience and structural safety of rural residential buildings exposed to blast-induced vibrations, with implications for both theoretical advancements and practical engineering applications. Full article

A wave of energy efficiency-focused activity has spread across Europe in recent years, with ambitious goals for improving the energy performance of existing buildings through various directives. Among these existing buildings, there are older structures with heritage-protected facades. Some of the protected facades consist of timber plank frame walls, which were common in Norway in the 19th and early 20th centuries. Internal insulation is an option for increasing the energy efficiency of such walls while preserving their protected facades. However, this approach alters the moisture performance of the wall and introduces a potential risk for mould growth, which must be assessed. To better understand the performance of these walls, the $s_d$ values of traditional types of building paper have been tested, as timber plank frame walls comprise vertical planks covered in building paper. In addition, the risk of mould growth in timber plank frame walls has been evaluated using the one-dimensional simulation tool WUFI^® Pro by modelling the wall with internal retrofitting and varying input parameters. The types of building paper used have a wide range of vapour resistance values (diffusion-equivalent air layer thicknesses, $s_d$ values), which range from 0.008 m to 5.293 m. Adding 50 mm of interior insulation generally resulted in a low risk of mould growth, except in cases involving the use of a moisture-adaptive vapour barrier (MAVB). The MAVB did not result in an acceptable mould growth risk in any of the tested scenarios. Full article

Translation initiation site (TIS) prediction in mRNA sequences constitutes an essential component of transcriptome annotation, playing a crucial role in deciphering gene expression and regulation mechanisms. Numerous computational methods have been proposed and achieved acceptable prediction accuracy. In our previous work, we developed NeuroTIS, a novel method for TIS prediction based on a hybrid dependency network combined with a deep learning framework that explicitly models label dependencies both within coding sequences (CDSs) and between CDSs and TISs. However, this method has limitations in fully exploiting the primary structural information within mRNA sequences. First, it only captures label dependency within three neighboring codon labels. Second, it neglects the heterogeneity of negative TISs originating from different reading frames, which exhibit distinct coding features in their vicinity. In this paper, under the framework of NeuroTIS, we propose its enhanced version, NeuroTIS+, which allows for more sophisticated codon label dependency modeling via temporal convolution and homogenous feature building through an adaptive grouping strategy. Tests on transcriptome-wide human and mouse datasets demonstrate that the proposed method yields excellent prediction performance, significantly surpassing the existing state-of-the-art methods. Full article

The accurate identification of modal parameters is essential for structural health monitoring (SHM), as it provides critical insights into the presence of damage or degradation within the structure. A promising technique, stochastic subspace identification (SSI) has numerous advantages in operational modal analysis (OMA), particularly in implementing automated OMA. Hence, an improved procedure is proposed in this study, addressing the size of the SSI matrix, the estimation of system order, and the removal of spurious modes for automated modal analysis. A general instruction for user-defined parameters is first reviewed and summarized. Subsequently, a proposed procedure is then introduced and framed into three steps. Key advances include the preliminary identification of fundamental frequency, which helps the overall automated work, adequately assigning the size of the SSI matrix, which can improve decomposition, and a decay function, which provides a good estimation of system order. To demonstrate and verify the procedure, a numerical simulation of a ten-story shear-type building structure and two field datasets, collected from reinforced concrete (RC) frames in Taiwan, are utilized. Consequently, the results suggest that the proposed three-step procedure based on SSI can facilitate automated OMA for continuous and long-term SHM, in terms of autonomously adjusting user-defined parameters. Full article

Construction costs have increased significantly since the COVID-19 pandemic due to supply chain disruption, labour shortages, and construction material price hikes. The market is increasingly demanding innovative construction methods that can save construction costs, reduce construction time, and minimise waste and carbon emission. The prefabrication system has been used for years in industrial construction, resulting in better performance in regard to structure stability, the control of wastage, and the optimisation of construction time and cost. In addition, prefabrication has had a positive contribution on resource utilisation in the construction industry. There are various types of prefabricated wall systems. However, the majority of comparative studies have focused on comparing each prefabrication wall system against the conventional construction system, while limited research has been conducted to compare different prefabrication structures. This study examined four prominent prefabricated wall systems, i.e., precast walls, tilt-up walls, prefabricated steel-frame walls, and on-site-cut steel-frame walls, to determine which one is more suitable for the construction of industrial buildings to minimise cost, time delay, and labourer utilisation on construction sites, as well as to enhance structure durability, construction efficiency, and sustainability. One primary case project and five additional projects were included in this study. For the primary case project, data were collected and analysed; for example, a subcontractor cost comparison for supply and installation was conducted, and shop drawings, construction procedures, timelines, and site photos were collected. For the additional five projects, the overall cost data were compared. The main research finding of this study is that factory-made precast walls and tilt-up wall panels require similar construction time. However, on average, tilt-up prefabrication construction can reduce the cost by around 23.55%. It was also found that prefabricated frame walls provide cost and time savings of around 39% and 10.5%, respectively. These findings can provide architects, developers, builders, suppliers, regulators, and other stakeholders with a comprehensive insight into selecting a method of wall construction that can achieve greater efficiency, cost savings, and environmental sustainability in the construction of industrial and commercial buildings. Full article

This study presents a computational approach to optimize the stiffness distribution of large deformable elastic braces (LDEBs), which possess a high elastic deformation capacity and are designed to enhance the seismic performance of building structures. An optimization problem was formulated to minimize the seismic response of two-story buildings modeled as multi-degree-of-freedom systems, in which both the building frame and the LDEBs were represented by spring elements. Seismic responses under earthquake excitations were evaluated through time-history analyses. Particle swarm optimization (PSO) was employed to determine the optimal stiffness ratios of LDEBs that minimize the maximum story drift. Extensive round-robin analyses were conducted to verify the validity of the PSO results, generating response surfaces that mapped the maximum story drift against the LDEBs’ stiffness under three different earthquake records. The analysis revealed that the optimal solutions obtained from the PSO coincided with the global minimum identified in the round-robin response surfaces. These results confirm the effectiveness of the proposed optimization framework and demonstrate the potential of LDEBs for enhancing seismic resilience in structural designs. Full article

Masonry industrial buildings, common in the 19th and 20th centuries, represent a significant architectural typology. These structures are crucial to the study of industrial archeology, which focuses on preserving and revitalizing historical industrial heritage. Often left neglected and deteriorating, they hold great potential for adaptive reuse, transforming into vibrant cultural, commercial, or residential spaces through well-planned restoration and consolidation efforts. This paper explores a case study of such industrial architecture: a decommissioned factory near Naples. The complex consists of multiple structures with vertical supports made of yellow tuff stone and roofs framed by wooden trusses. To improve the building’s seismic resilience, a comprehensive analysis was conducted, encompassing its historical, geometric, and structural characteristics. Using advanced computer software, the factory was modelled with a macro-element approach, allowing for a detailed assessment of its seismic vulnerability. This approach facilitated both a global analysis of the building’s overall behaviour and the identification of potential local collapse mechanisms. Non-linear analyses revealed a critical lack of seismic safety, particularly in the Y direction, with significant out-of-plane collapse risk due to weak connections among walls. Based on these findings, a restoration and consolidation plan was developed to enhance the structural integrity of the building and to ensure its long-term safety and functionality. This plan incorporated metal tie rods, masonry strengthening through injections, and roof reconstruction. The proposed interventions not only address immediate seismic risks but also contribute to the broader goal of preserving this industrial architectural heritage. This study introduces a novel multidisciplinary methodology—integrating seismic analysis, traditional retrofit techniques, and sustainable reuse—specifically tailored to the rarely addressed typology of masonry industrial structures. By transforming the factory into a functional urban space, the project presents a replicable model for preserving industrial heritage within contemporary cityscapes. Full article

This paper explores the concept of evolutionary urban resilience by framing cities as complex, open, and adaptive Social-Ecological-Technological Systems (SETS), shaped by multi-scalar dynamics, systemic uncertainty, and interdependent crises. It challenges the reductionist view of resilience as a fixed capacity or linear sequence of risk management phases, and instead proposes a process-based paradigm rooted in learning, creativity, and the ability to navigate disequilibrium. The framework defines urban resilience as a continuous and iterative transformation process, supported by: (i) a combination of tangible and intangible qualities activated according to problem typology; (ii) cross-domain processes involving infrastructures, flows, governance, networks, and community dynamics; and (iii) the engagement of diverse agents in shared decision-making and coordinated action. These dimensions unfold across three incremental and interdependent scenarios—baseline, critical, and chronic crisis—forming a ladder of resilience that guides communities through escalating challenges. Special emphasis is placed on the role of Information and Communication Technologies (ICTs) as relational and adaptive tools enabling distributed intelligence and inclusive governance. The framework also outlines concrete operational and policy implications for cities aiming to build anticipatory and transformative resilience capacities. Applied to the case of Taranto, the approach offers insights into how structurally fragile communities facing conflicting adaptive trajectories can unlock transformative potential. Ultimately, the paper calls for a shift from government to governance, from control to co-creation, and from reactive adaptation to chaos generativity, recasting urban resilience as an evolving project of collective agency, systemic reconfiguration, and co-production of emergent urban futures. Full article

Pile–raft foundations are widely used in soft soil engineering due to their good integrity and high stiffness. However, traditional design methods independently design pile–raft foundations and superstructures, ignoring their interaction. This leads to significant deviations from actual conditions when the superstructure height increases, resulting in excessive costs and adverse effects on building stability. This study experimentally investigates the interaction characteristics of pile–raft foundations and superstructures in soft soil under different working conditions using a 1:10 geometric similarity model. The superstructure is a cast-in-place frame structure (beams, columns, and slabs) with bamboo skeletons with the same cross-sectional area as the piles and rafts, cast with concrete. The piles in the foundation use rectangular bamboo strips (side length ~0.2 cm) instead of steel bars, with M1.5 mortar replacing C30 concrete. The raft is also made of similar materials. The results show that the soil settlement significantly increases under the combined action of the pile–raft and superstructure with increasing load. The superstructure stiffness constrains foundation deformation, enhances bearing capacity, and controls differential settlement. The pile top reaction force exhibits a logarithmic relationship with the number of floors, coordinating the pile bearing performance. Designers should consider the superstructure’s constraint of the foundation deformation and strengthen the flexural capacity of inner pile tops and bottom columns for safety and economy. Full article

Background: The provision of education, health, and social care for children with special educational needs and disabilities (SEND) in England has long been criticised for its inequities and chronic underfunding. These systemic issues were further exacerbated by the onset of the COVID-19 pandemic and the accompanying restrictions, which disrupted essential services and resulted in widespread unmet needs and infringements on the rights of many children with SEND. This study aimed to use a three-phase consensus-building approach with 1353 participants across five stakeholder groups to collaboratively develop evidence-informed priorities for policy and practice. The priorities sought to help address the longstanding disparities and respond to the intensified challenges brought about by the pandemic. Methods: A total of 55 children with SEND (aged 5–16), 893 parents/carers, and 307 professionals working in SEND-related services participated in the first phase through online surveys. This was followed by semi-structured interviews with four children and young people, ten parents/carers, and 15 professionals, allowing for deeper exploration of lived experiences and priorities. The data were analysed, synthesised, and structured into five overarching areas of priority. These were subsequently discussed and refined in a series of activity-based group workshops involving 20 children with SEND, 11 parents/carers, and 38 professionals. Results and Conclusions: The consensus-building process led to the identification of key priorities for both pandemic response and longer-term recovery, highlighting the responsibilities of central Government and statutory services to consider and meet the needs of children with SEND. These priorities are framed within a children’s rights context and considered against the rights and duties set out in the United Nations Convention on the Rights of the Child (1989). Priorities include protecting and promoting children with SEND’s rights to (1) play, socialise, and be part of a community, (2) receive support for their social and emotional wellbeing and mental health, (3) feel safe, belong, and learn in school, (4) “access health and social care services and therapies”, and (5) receive support for their parents/carers and families. Together, they highlight the urgent need for structural reform to ensure that children with SEND receive the support they are entitled to—not only in times of crisis but as a matter of routine practice and policy. Full article

In this article, we revisit the core concepts of nature and of landscape assessment and sustainability, based on which we propose an approach to natural resource management and diversity preservation from the perspective of cultural landscapes. We build on past and contemporary debates on the notion of nature and its relation to “Non-Nature”, attempting to systematize the main variables of the study of past societies as a methodological framework for the analysis of contemporary contexts; this is based on bibliographic references and case studies using such methodological approaches. Landscapes are structured through human activity, which relates to the technological and logistic drivers of historical studies, and are the domain of humans (anthropic nature), as opposed to non-anthropic nature (or wilderness). Sustainable resource management, focused on the preservation of biodiversity and cultural diversity as part of it, needs to overcome the divide between nature and culture, framing debates and conflicts as part of a cultural landscape of discussions served by an established methodological framework, in which education is the main driver and museum-related structures (libraries, etc.) form the flexible institutional backbone. The introduction sets the context for the argument, revisiting some of the theoretical approaches to the notions of nature and landscapes from the late 19th century in Europe, while also referring to reflections in antiquity and traditional and indigenous understandings. A section on materials and methods explains the methodological framework and data used by the author, situating it within a systematization of the humanities’ assessment of the past. A third section explores the interplay between materialities and perceptions, including the relevance of time- and space-driven approaches that shape different perceived landscapes; it proposes a definition of cultural landscape structured through these interplays. The fourth section discusses the dimension of perceived nature as a cultural landscape and characterizes its main drivers, offering two contemporary case studies as examples. A final section of conclusions discusses the role of humanities and of structures like museums, pointing to the new UNESCO program BRIDGES as a useful tool for pursuing landscape transformations. Full article

In order to solve the problems of low tracking accuracy of in-orbit satellites by ground stations and slow processing speed of satellite target tracking images, this paper proposes an orbital satellite regional tracking and prediction model based on graph convolutional networks (GCNs). By performing superpixel segmentation on the satellite tracking image information, we constructed an intra-frame superpixel seed graph node network, enabling the conversion of spatial optical image information into artificial-intelligence-based graph feature data. On this basis, we propose and build an in-orbit satellite region of interest prediction model, which effectively enhances the perception of in-orbit satellite feature information and can be used for in-orbit target prediction. This model, for the first time, combines intra-frame and inter-frame graph structures to improve the sensitivity of GCNs to the spatial feature information of in-orbit satellites. Finally, the model is trained and validated using real satellite target tracking image datasets, demonstrating the effectiveness of the proposed model. Full article

In structural health monitoring, visual inspection remains vital for detecting damage, especially in concealed elements such as columns and beams. To improve damage localization, many studies have investigated and implemented deep learning into damage detection frameworks. However, the practicality of such models is often limited by their computational demands, and the relative accuracy may suffer if input features lack sensitivity to localized damage. This study introduces an efficient method for estimating damage locations and severity in buildings using a neural network array. A synthetic dataset is first generated from a simplified building model that includes floor flexural behavior and reflects the target dynamics of the structures. A dense, single-layer neural network array is initially trained with full floor accelerations, then pruned iteratively via the Lottery Ticket Hypothesis to retain only the most effective sub-networks. Subsequently, critical event measurements are input into the pruned array to estimate story-wise stiffness reductions. The approach is validated through numerical simulation of a six-story model and further verified via shake table tests on a scaled twin-tower steel-frame building. Results show that the pruned neural network array based on the Lottery Ticket Hypothesis achieves high accuracy in identifying stiffness reductions while significantly reducing computational load and outperforming full-input models in both efficiency and precision. Full article

Engineered laminated bamboo frame structures have seen notable advancements in China, driven by their potential in sustainable construction. However, accurately predicting their seismic performance remains a pivotal challenge. Structural and non-structural damage caused by earthquakes can severely compromise building operability, lead to substantial economic losses, and disrupt safe evacuation processes, collectively exacerbating disaster impacts. To address this, three laminated bamboo frame models (3-, 4-, and 5-story) were developed, integrating energy-dissipating T-shaped steel plate beam–column connections. Two engineering demand parameters—peak inter-story drift ratio (PIDR) and peak floor acceleration (PFA)—were selected to quantify seismic responses under near-field and far-field ground motions. The study systematically evaluates suitable intensity measures for these parameters, emphasizing efficiency and sufficiency criteria. Regarding efficiency, the applicable intensity measures for PFA differ from those for PIDR. The measures for PFA tend to focus more on acceleration amplitude-related measures such as peak ground accelerations (PGA), sustained maximum acceleration (SMA), effective design acceleration (EDA), and A₉₅ (the acceleration at 95% Arias intensity), while the measures for PIDR are primarily based on spectral acceleration-related measures such as S_a(T₁) (spectral acceleration at fundamental period), etc. Concerning sufficiency, significant differences exist in the applicable measures for PFA and PIDR, and they are greatly influenced by ground motion characteristics. Full article