Search Results (643)

Bridges are critical infrastructures that support our economic activities and daily lives. Aging bridges have been a major issue for decades, prompting researchers to improve resilience and performance through structural health monitoring. While most research focuses on superstructure damage, the majority of bridge failures are associated with support or joint damages, indicating the importance of bridge support. Indeed, bridge support affects the performance of both the substructure and superstructure by maintaining the load path and allowing certain movements to mitigate thermal and other stresses. The support deterioration leads to a change in fixity in the superstructure, compromising the bridge’s integrity and safety. Hence, a reliable method to determine support fixity level is essential to detecting bearing health and enhancing the accuracy of the bridge health monitoring system. However, such research is lacking because of its complexity. In this study, we developed a support fixity quantification method based on thermal responses using an Artificial Neural Network (ANN) model. A finite element (FE) model of a representative highway bridge is used to derive thermal displacement data under different bearing stiffnesses, superstructure damage, and thermal loading. The thermal displacement behavior of the bridge under different support fixity conditions is presented, and the model is trained on the simulated response. The performance of the developed FE model and ANN was validated with field monitoring data collected from two in-service bridges in Connecticut using a real-time Wireless Sensor Network (WSN). Finally, the support stiffnesses of both bridges were predicted using the ANN model for validation. Full article

This study aims to comprehensively investigate the dynamic characteristics of the tower of a scaled wind turbine model through wind tunnel tests. A model was scaled from the NREL 5 MW prototype wind turbine with a geometric scale ratio of 1/75, based on the similarity rules in thrust coefficient and dynamic characteristics. A series of wind tunnel tests were carried out on the scaled wind turbine model under different operating conditions and parked conditions with different yaw angles, and the modal parameters of the scaled model were identified by the stochastic subspace identification method and rotor stop tests. It was found that the vibration response of the tower in the fore–aft direction achieved its maximum value when the yaw angle was 90° with feathered blades, while the tower vibration response in the side–side direction was relatively severe with the yaw angle ranging from 10° to 50°. These observations are found to be well aligned with the aerodynamic characteristics of the airfoil. Moreover, the experimental results indicate that the scaled wind turbine model can reflect the vibration responses of its full-scale counterpart in the fore–aft direction. The natural frequencies and mode shapes of the scaled model can be accurately identified by different methods, but the identified damping ratios are relatively scattered. Full article

Understanding how faulty hardware affects machine learning models is important to both safety-critical systems and the cloud infrastructure. Since most machine learning models, like Deep Neural Networks (DNNs), are highly computationally intensive, specialized hardware accelerators are developed to improve performance and energy efficiency. Evaluating the fault resilience of these DNN accelerators during early design and implementation stages provides timely feedback, making it less costly to revise designs and address potential reliability concerns. To this end, we introduce Architecture-Level Pre-Register-Transfer-Level Implementation Fault Injection (ALPRI-FI), which is a comprehensive framework for assessing the fault resilience of DNN models deployed on hardware accelerators. Full article

This paper presents a comprehensive and evidence-based cyber-risk assessment approach specifically designed for Medical Cyber Physical Systems (MCPS)- and Internet-of-Medical Devices (IoMT)-based collaborative digital healthcare systems, which leverage Federated Identity Management (FIM) solutions to manage user identities within this complex environment. While these systems offer advantages like easy data collection and improved collaboration, they also introduce new security challenges due to the interconnected nature of devices and data, as well as vulnerabilities within the FIM and the lack of robust security in IoMT devices. To proactively safeguard the digital healthcare system from cyber attacks with potentially life-threatening consequences, a comprehensive and evidence-based cyber-risk assessment is crucial for mitigating these risks. To this end, this paper proposes a novel cyber-risk assessment approach that leverages a three-dimensional attack landscape analysis, encompassing existing IT infrastructure, medical devices, and Federated Identity Management protocols. By considering their interconnected vulnerabilities, the approach recommends tailored security controls to prioritize and mitigate critical risks, ultimately enhancing system resilience. The proposed approach combines established industry standards like Cyber Resilience Review (CRR) asset management and NIST SP 800-30 for a comprehensive assessment. We have validated our approach using threat modeling with attack trees and detailed attack sequence diagrams on a diverse range of IoMT and MCPS devices from various vendors. The resulting evidence-based cyber-risk assessments and corresponding security control recommendations will significantly support healthcare professionals and providers in improving both patient and medical device safety management within the FIM-enabled healthcare ecosystem. Full article

The theory of resilience has undergone three stages: engineering, ecological, and evolutionary. It has been developed in various professional fields, focusing on research scales such as urban resilience and community resilience. As the smallest unit of urban composition, the community serves as the principal carrier of numerous emergencies at the grassroots level. Its resilience construction level is somewhat connected to the city’s safe development. However, there is still a lack of a systematic evaluation framework for assessing community resilience, and studies from the perspective of public health safety also lack scientific quantitative results and dynamic analysis. In order to fully understand the connotation of resilient community in the combination of epidemic prevention and control, this study employs literature crawling and high-frequency vocabulary screening to construct a three-level resilience index. Taking into consideration both physical and social factors, a community resilience evaluation system with 4 core indicators, 14 secondary indicators, and 39 tertiary indicators is established by employing the resilience matrix (RM) framework and Analytic Hierarchy Process (AHP). It set up a collection quantification path based on the properties of multivariate data and weighted the indicators using the Delphi method. Taking the typical community in Xuanwu District, Nanjing, as the research sample, the differentiated performance during the COVID-19 pandemic is analyzed, and a systematic evaluation and scoring are conducted. The resilience composition and improvement directions of each sample are interpreted and analyzed to support the formulation of future sustainability strategies as much as possible. The study developed an evaluation approach combining three time periods and four response dimensions to demonstrate a relationship between complex factors and community resilience. The expandable resilience evaluation system offers a wide range of applications and serves as a scientific reference for strengthening community resilience, which is critical for urban sustainability. Full article

This study investigates the corrosion behavior of 5 mm diameter prestressed wires in concrete beams under chloride attack, a prevalent issue for coastal infrastructure. The study simulated aggressive chloride environments to understand their impact on structural integrity and service life. Utilizing a combination of advanced digital image correlation (DIC) techniques and a novel machine learning-based predictive model, the research provides a nuanced analysis of the interplay between stress levels, corrosion rates, and concrete strength. Empirical findings reveal a significant correlation between increased prestress levels and accelerated corrosion, indicating a crucial consideration for the design and maintenance of prestressed concrete structures. Notably, this study found that beams with a 95% prestress level exhibited a corrosion rate of 0.64 mm/year, significantly higher than the 0.37 mm/year for non-prestressed beams. The predictive model’s accuracy was validated with a mean squared error of 0.517 and an R² value of 0.905, offering a valuable tool for quantifying the impact of corrosion. Therefore, the predictive model is a valuable tool for quantifying the impact of corrosion, enhancing the ability to assess and improve the durability of such infrastructure. This study’s insights highlight the necessity for a balanced approach to design and regular monitoring, especially in chloride-rich environments. By helping to develop more resilient construction practices and contributing to sustainable development goals, this study can significantly impact the safety and service life of coastal bridges and structures, aligning with global efforts to create more sustainable and durable infrastructure. Full article

Conifer forests in Michoacán are facing climate change. Pinus devoniana Lindley, with natural distribution in the state, has shown certain adaptability, and knowing the influence of anatomy in the flow system is essential to delimit how it contributes to safety margins and water efficiency. For this, the pressure gradients in the cell lumens and their ramifications were analyzed by numerical simulations of flow throughout the real microstructure. Xylem were evaluated in radial, tangential and longitudinal directions. With the skeletonization of lumens and their constrictions, a branching system of interconnection between tracheids, ray cells, intercellular chambers, extensions, and blind pits were identified. In the simulation, the branched system bypasses the longitudinal fluid passage through the pores in membranes of pairs of pits to redirect it through the direct path branching, contributing to safety margins and water efficiency. Thus, resilience at low pressures because of the lower pressure drop in the extensions. The interface between the branching system and the cell lumens are sites of higher pressure gradient, more conducive to water-vapor formation or air leakage in the face of the lowest pressure system. The flow lines move along easy paths, regardless of the simulated flow direction. Deposits in the cell extensions were shown to be attached to the S3 layer of the cell wall, leaving the center of the duct free to flow. It is concluded that the spatial architecture of the xylem anatomy of Pinus dvoniana is a factor in the resilience at low pressures due to high water stress of the species. Full article

In the field of CO₂ capture and sequestration, ensuring the safety of pipeline infrastructure is paramount to successful climate change mitigation efforts. This study investigates the dynamics of CO₂ dispersion from pipeline systems, assessing not only the transport process but also the physical properties and associated hazards. Advanced simulation techniques are used to model how different states of CO₂ (gas, liquid, and supercritical) and varying pipeline characteristics—such as perforation sizes, flow rates, and orientations—affect the dispersion patterns in the event of a leak. Simulations cover a range of atmospheric conditions, emphasizing the role of atmospheric stability and wind speed in shaping dispersion and defining potential impact zones. An analysis of historical pipeline accidents is included to inform risk management strategies. The results show that the orientation of the pipeline has a significant effect on dispersion, with downward leaks causing the largest impact zones, particularly under supercritical conditions. The results highlight the need for adaptive safety strategies that take into account real-time CO₂ transport conditions and localized environmental data. By integrating these factors, the study recommends refining safety protocols and emergency response strategies to improve pipeline resilience and public safety against potential leaks. Key findings include the quantification of the relationship between leak parameters and dispersion areas, providing a valuable framework for future safety improvements. Full article

With a focus on sustainability and functionality, this Special Issue looks at various topics, including novel food-packaging solutions, bio-based adhesives, and the integration of nanotechnology to improve performance. It emphasizes the importance of understanding limitations and overcoming them through innovation, highlighting the crucial role of bio-based materials in ensuring food safety and quality, especially in the context of the COVID-19 pandemic. Future research areas emphasize the need for holistic approaches that prioritize circularity and sustainability throughout the packaging lifecycle. By fostering collaboration and innovation, this Special Issue aims to make progress towards a more sustainable and resilient future for food packaging. Full article

Gene-edited crops and livestock have the potential to transform food systems by providing resilience to climate change, pest and disease resistance, and the enhancement of nutrients in feed and food in a time-efficient and precise way. In 2023, the UK Parliament passed the Genetic Technology (Precision Breeding) Bill, paving the way for gene-edited products to be farmed in England and sold, providing they could have theoretically been produced via traditional breeding. In this paper, we describe the possible risks of gene-edited products for consumption using four case studies of gene-edited organisms: increased vitamin D tomatoes, reduced linoleic acid cottonseed oil, porcine reproductive and respiratory virus (PRRSV) resistant pigs and reduced-asparagine wheat. Assuming that the only requirement for an organism to be a Precision-Bred Organism (PBO) is that no transgenic material remains within the organism and that the edit could have, in theory, occurred spontaneously or through traditional breeding methods, then all our case studies would likely be defined as PBOs. We also conclude that the food safety risks of these products appear to be similar to those that society accepts in traditionally bred organisms used for food and feed. However, PBOs that possess markedly altered nutrient profiles may require a dedicated identity-preserved retail chain and/or labelling to avoid unintended over-consumption. Full article

Underground space has always been used as a resilient solution in addressing the need for safety in terms of climate conditions and defense purposes. This research seeks to recognize the potential of the underground space in the city as a significant urban resilience strategy, with the aim of revealing how contemporary underground architecture is integrated with the public spaces on the surface and how this groundscape integration contributes to the quality of the use of the public spaces to achieve urban resilience. Public spaces have a crucial role in the environmental, social, and sustainable context of the city and are considered urban domains for spatial urban intervention that contribute to urban resilience in its broader understanding. Based on the review of underground space research and the comparative analysis of selected contemporary design projects, the research explores the integration of underground space in correlation with its utilization model based on contemporary design projects. The research results in the systematization of underground utilization among underground infrastructure, underground living settlements, and urban development to offer insights into the enhancement of resilience planning through the contemporary multifunctional usage of underground space. The contribution of this research is reflected in the methodology of developing the criteria for a groundscape resilience concept, in terms of perceiving underground space as an integral urban layer, its multifunctional utilization, and in terms of achieving urban resilience. Full article

Horizontal storage tanks are integral to the petrochemical industry but pose significant risks during earthquakes, potentially causing severe secondary disasters. Current seismic designs predominantly assume rigid tank walls, which can lead to an underestimation of seismic responses. This study introduces a novel analysis method for assessing the dynamic response of flexible-walled horizontal storage tanks. By separating the liquid velocity potential into convective and impulsive components and integrating these with beam vibration theory, we developed a simplified mechanical model. A parameter analysis and dynamic response research were conducted using numerical methods. Results indicate that flexible tank walls amplify seismic responses, including liquid dynamic pressure peaks, base shear, and overturning bending moments, compared to rigid walls. Additionally, the impact of flexible walls is more pronounced in tanks with larger radii, aspect ratios, diameter–thickness ratios, and H/R ratios. These findings highlight the necessity for revised seismic design approaches that consider wall flexibility to enhance the safety and resilience of horizontal storage tanks. Full article

Cordyceps militaris is considered to be of great medicinal potential due to its remarkable pharmacological effects, safety, and edible characteristics. With the completion of the genome sequence and the advancement of efficient gene-editing technologies, coupled with the identification of gene functions in Cordyceps militaris, this fungus is poised to emerge as an outstanding strain for medicinal engineering applications. This review focuses on the development and application of genomic editing techniques, including Agrobacterium tumefaciens-mediated transformation (ATMT), PEG-mediated protoplast transformation (PMT), and CRISPR/Cas9. Through the application of these techniques, researchers can engineer the biosynthetic pathways of valuable secondary metabolites to boost yields; such metabolites include cordycepin, polysaccharides, and ergothioneine. Furthermore, by identifying and modifying genes that influence the growth, disease resistance, and tolerance to environmental stress in Cordyceps militaris, it is possible to stimulate growth, enhance desirable traits, and increase resilience to unfavorable conditions. Finally, the green sustainable industrial development of C. militaris using agricultural waste to produce high-value-added products and the future research directions of C. militaris were discussed. This review will provide future directions for the large-scale production of bioactive ingredients, molecular breeding, and sustainable development of C. militaris. Full article

The Auckland Harbour Bridge (AHB) utilises a movable concrete barrier (MCB) to regulate the uneven bidirectional flow of daily traffic. In addition to the risk of human error during regular visual inspections, staff members inspecting the MCB work in diverse weather and light conditions, exerting themselves in ergonomically unhealthy inspection postures with the added weight of protection gear to mitigate risks, e.g., flying debris. To augment visual inspections of an MCB using computer vision technology, this study introduces a hybrid deep learning solution that combines kernel manipulation with custom transfer learning strategies. The video data recordings were captured in diverse light and weather conditions (under the safety supervision of industry experts) involving a high-speed (120 fps) camera system attached to an MCB transfer vehicle. Before identifying a safety hazard, e.g., the unsafe position of a pin connecting two 750 kg concrete segments of the MCB, a multi-stage preprocessing of the spatiotemporal region of interest (ROI) involves a rolling window before identifying the video frames containing diagnostic information. This study utilises the ResNet-50 architecture, enhanced with 3D convolutions, within the STENet framework to capture and analyse spatiotemporal data, facilitating real-time surveillance of the Auckland Harbour Bridge (AHB). Considering the sparse nature of safety anomalies, the initial peer-reviewed binary classification results (82.6%) for safe and unsafe (intervention-required) scenarios were improved to 93.6% by incorporating synthetic data, expert feedback, and retraining the model. This adaptation allowed for the optimised detection of false positives and false negatives. In the future, we aim to extend anomaly detection methods to various infrastructure inspections, enhancing urban resilience, transport efficiency and safety. Full article

Seismic risk assessment in school buildings is critical for ensuring the safety and resilience of educational institutions against seismic events. This paper presents a new seismic risk methodology named MM Risk and comparative study with Adriseismic methodology used for seismic risk assessment. The study aims to provide insights into the effectiveness and reliability of these methods in evaluating the seismic vulnerability of school buildings. Through a comprehensive review of the existing literature and application on a dataset of 213 schools (367 buildings), this paper evaluates the strengths and limitations of each method in terms of accuracy, complexity, and practical applicability. The results show that by integrating the approach of Adriseismic methodology and incorporating extensions related to irregularities, the social risk component (number of users), and the ability to assess different types of structures, a comprehensive and tailored methodology for assessing seismic risk can be developed. This is important since these factors are strongly influencing the seismic risk of schools as connected systems. Furthermore, this paper explores the implications of these findings for improving seismic risk mitigation strategies in school buildings. MM Risk methodology places over 70% of school buildings in the medium seismic risk category and 27% in the high seismic risk category. On the other hand, the Adriseismic methodology is more stringent, classifying 60% of school buildings into high and very-high risk categories. This disparity undoubtedly influences the prioritization list for seismic risk mitigation measures. However, definitely the comparative analysis presented in this paper offers valuable guidance for engineers, policymakers, and stakeholders involved in the seismic retrofitting and design of school buildings, ultimately contributing to the enhancement of seismic resilience in educational infrastructure. Full article