Search Results (32)

This paper reviews emerging dielectric fluids for power transformers, including natural and synthetic esters, silicone oils, gas-to-liquid oils, and nanofluids, driven by environmental regulations, fire safety concerns, and the need for extended asset life. The review synthesizes technical data from standards and field experience, including a case study of an Eskom transformer energized in 2016 with natural ester fluid. Analysis confirms these fluids offer significant benefits in fire safety, biodegradability, and dielectric performance, with the case study demonstrating natural esters’ effectiveness in preserving solid insulation. However, trade-offs involving cost, material compatibility, and operational protocols require careful management. Full article

In the Industry 4.0 era, effective maintenance management is paramount to ensuring production continuity, operational efficiency, and cost-effectiveness. Modern industrial systems operate under inherent uncertainty and limited observability, necessitating the development of sophisticated decision-support frameworks. This study introduces a comprehensive approach to optimizing maintenance control for industrial assets under stochastic degradation and partial observability. The framework integrates stochastic processes for degradation modeling with Overall Equipment Effectiveness (OEE) and Life Cycle Cost (LCC) analysis for multi-dimensional performance assessment. Maintenance interventions are governed by threshold-based strategies, where optimal service limits ($\theta *$) are determined through extensive Monte Carlo simulations. Furthermore, both local and global sensitivity analyses are employed to identify critical drivers of decision-making, such as failure penalties, process volatility, and maintenance efficacy. The model is extended to incorporate Digital Twin concepts, enhancing state estimation under noisy sensor data, and addresses multi-machine scenarios with resource constraints to reflect real-world operational complexities. Results indicate that failure costs and process uncertainty are the primary determinants of maintenance timing. Notably, Digital Twin integration significantly bolsters decision accuracy in the presence of measurement noise, providing a robust and scalable solution for modern manufacturing environments. Full article

Effective asset management is crucial for improving the reliability, resilience, and cost efficiency of distribution networks throughout the asset life cycle. Distribution transformers are among the most critical components, as their failures can cause extensive service interruptions and substantial economic impacts. Therefore, robust and transparent maintenance prioritization strategies are essential, particularly for utilities managing several transformers. Traditional time-based maintenance, while simple to implement, often results in inefficient resource allocation. Condition-based maintenance provides a more effective alternative; however, its performance depends strongly on the reliability of indicator selection and weighting. This study proposes a systematic weighting framework for distribution transformer maintenance prioritization using a multi-criteria decision-making (MCDM) approach. Each transformer is evaluated across two dimensions, including health condition and operational impact, based on indicators identified from the literature and expert judgment. To address uncertainty and judgmental inconsistency, particularly when the consistency ratio (CR) exceeds the conventional threshold of 0.10, the Fuzzy Analytic Hierarchy Process (FAHP) is employed. Seven condition parameters characterize transformer health, while impact is quantified using five indicators reflecting failure consequences. The proposed framework offers a transparent, repeatable, and defensible decision-support tool, enabling utilities to prioritize maintenance actions, optimize resource allocation, and mitigate operational risks in distribution networks. Full article

Background/Objectives: Informal caregivers play a crucial role in healthcare, but when caregiving ends the “post-caregivers” often remain invisible and unsupported. Post-caregivers face needs such as reconstructing their identity and finding space and time to grieve. This study aimed to design a support network for informal post-caregivers by exploring perceptions of diverse stakeholders. Methods: A qualitative inductive study was conducted using three focus groups (n = 15; ages 35–70; 12 women, 3 men) held online between June and July 2023. Participants included palliative care team members, home support professionals, general practitioners, informal caregivers, post-caregivers, and members of civil society. A semi-structured guide was used, and narratives were analyzed with a Narrative Medicine-informed approach and thematic analysis. Results: Community-For-Care emerged as an overarching and distinctive concept that, while aligned with the ethos of Compassionate Communities, specifically addresses the transition after caregiving ends, a phase largely absent from existing models. It symbolizes the “living forces of the community” mobilized to accompany informal post-caregivers through identity reconstruction, bereavement, and reintegration. Three interrelated thematic axes structure this concept: (1) Compassion Axis—emphasizing a compassionate community that values caregiving; (2) Coordinated Action Axis—highlighting coordinated, continuous support across healthcare and community services; and (3) Care Literacy Axis—underscoring education and training for caregivers, post-caregivers, and professionals. These axes dynamically interact to empower post-caregivers and stitch the holes in the support network. Conclusions: A community-centered, post-caregiver-focused framework such as Community-For-Care offers a novel extension of compassionate communities by directly addressing the loneliness, identity rupture, and invisibility that often characterize the transition after caregiving. Reinforcing compassion, coordinated action, and care literacy can enable communities to better acknowledge the contributions and ongoing needs of post-caregivers, supporting their emotional recovery, social reintegration, and reconstruction of daily life. By integrating these three axes into community practice, the model introduces a post-care-specific structure that can enhance well-being, reduce preventable health decline, and relieve pressure on formal services by mobilizing local, civic, and relational assets. Full article

Electrical insulation systems (EISs) are the principal reliability bottleneck of modern electrical machines (EMs). Among the many stresses acting on insulation, thermal stress is the most pervasive because it accelerates chemical reactions that progressively erode dielectric and mechanical integrity, ultimately dictating service life. As EMs migrate into compact, high-power-density platforms—automotive, aerospace, and industrial drives—designers need lifetime models that are not merely explanatory but actionable, linking operating temperatures and missions to quantified ageing and risk. This review article traces the evolution of thermal-ageing modelling from fundamental chemistry to a practical design tool. The historical empirical lineage of Arrhenius equation, Arrhenius–Dakin model, and Montsinger model is first revisited, clarifying their assumptions, parameter definitions, and the construction of thermal endurance curves. A discussion then follows on extensions that address deviations from first-order kinetics and demonstrate how variable temperature histories can be incorporated through cumulative damage formulations suitable for duty-cycle analysis. Since models are required to be anchored in data, accelerated thermal ageing (ATA) practices on representative specimens are outlined, alongside a description of the Weibull post-processing for deriving percentile lifetimes aligned with design targets. Building upon these foundations, the Physics-of-Failure (PoF) approach is introduced as a reliability-oriented design (ROD) methodology, in which validated lifetime models guide material selection and geometry optimisation while supporting prognostics and health management during operation. The emerging trend towards a hybrid PoF–AI approach is also discussed, which integrates artificial intelligence to identify nonlinear degradation patterns and drifting parameter relationships beyond the reach of empirical models, with physical constraints ensuring that predictions remain consistent with known ageing mechanisms. Such integration enables the learning process to adapt to operational variability and coupled stress effects, thereby improving both the accuracy and physical interpretability of lifetime estimation. The review aims to provide a concise view of models, tests, and workflows that convert thermal-ageing knowledge into robust, design-time decisions. By linking empirical and physics-based insights with modern data-driven learning, these developments support proactive maintenance, sustainable asset management, and extended operational lifetimes for next-generation EMs. Full article

This research aimed to develop a comprehensive decision-making model for road rehabilitation, with the goals of extending pavement service life, minimizing major repairs, and improving the efficiency of investment and resource planning. The proposed methodology integrates structural condition, functional performance, and total economic value across the pavement lifecycle. It enables engineers and road managers to make informed decisions based on structural capacity, functional performance, asset value, and optimized rehabilitation strategies. The model was validated through case studies using data from Central European roads and accelerated pavement testing. It compared conventional and high-modulus asphalt overlays of equal thickness, demonstrating that a 3000 MPa increase in modulus extended residual life by over 30% and raised structural value by EUR 5.8/m². This approach enhances planning and prioritization of rehabilitation activities, supports the use of higher-quality materials, reduces lifecycle costs and CO₂ emissions, and facilitates integration with asset management systems. By linking pavement design, performance prediction, and asset management, the model supports strategic decision-making under performance and budget constraints. Full article

The increasing complexity of lunar exploration missions necessitates stricter navigation requirements, especially when human life is involved. Extensive research is currently being conducted on various positioning systems suitable for the lunar environment. These include both the exploitation of terrestrial GNSS (Global Navigation Satellite System) signals, and the deployment of a lunar-dedicated satellite system known as the Lunar Communication and Navigation Service (LCNS). In order to meet the demanding navigation requirements, the usage of one or more lunar beacons to enhance Positioning, Navigation, and Timing (PNT) performance for different assets is under investigation to complement the LCNS system. This research aims to demonstrate the improvement of PNT accuracy by exploiting Differential LCNS (DLCNS) positioning techniques. To this end, both Single Point Positioning (SPP) and DLCNS techniques along with estimation algorithms such as Weighted Least Squares (WLS) and Extended Kalman Filter (EKF) were developed in a simulated lunar environment to assess their performances. Full article

BCA methodically assesses the state of a building’s deterioration to support Maintenance, Safety, Function, and Compliance purposes. Originally used to assist in identifying urgent repair requirements, it has evolved and become one of the most used tools for assessing a building’s outstanding maintenance liability when a building is transacted or acquired. Nevertheless, current practices involve several conflicts; for example, high costs are associated with inspections, inconsistent building component registers, and ambiguity and consistency regarding reporting parameters, all of which lead to compounding errors that reduce reliability. To address these gaps, the current research, involving one hundred and eighteen (118) active facilities managers and asset inspectors, suggests the development of an extension of the deterioration scale (0–7) and methodologies to reduce errors and ambiguity. Furthermore, it suggests using weighted indices to focus on crucial building components, thus improving condition assessment. As was found, these tools improve the accuracy of BCA, facilitate better management of the asset’s life cycle, and provide support in decision-making. This study adds consistency, limits subjectivity, and provides a framework applicable to different building types, assisting future management for sustainability. It, therefore, stands to serve the field by providing detailed and concise best practices for conducting condition audits on built assets. Full article

A highly critical event in a virus’s life cycle is successfully entering a given host. This process begins when a viral glycoprotein interacts with a target cell receptor, which provides the molecular basis for target virus–host cell interactions for novel drug discovery. Over the years, extensive research has been carried out in the field of virus–host cell interaction, generating a massive number of genetic and molecular data sources. These datasets are an asset for predicting virus–host interactions at the molecular level using machine learning (ML), a subset of artificial intelligence (AI). In this direction, ML tools are now being applied to recognize patterns in these massive datasets to predict critical interactions between virus and host cells at the protein–protein and protein–sugar levels, as well as to perform transcriptional and translational analysis. On the other end, deep learning (DL) algorithms—a subfield of ML—can extract high-level features from very large datasets to recognize the hidden patterns within genomic sequences and images to develop models for rapid drug discovery predictions that address pathogenic viruses displaying heightened affinity for receptor docking and enhanced cell entry. ML and DL are pivotal forces, driving innovation with their ability to perform analysis of enormous datasets in a highly efficient, cost-effective, accurate, and high-throughput manner. This review focuses on the complexity of virus–host cell interactions at the molecular level in light of the current advances of ML and AI in viral pathogenesis to improve new treatments and prevention strategies. Full article

IoT has seen remarkable growth, particularly in healthcare, leading to the rise of IoMT. IoMT integrates medical devices for real-time data analysis and transmission but faces challenges in data security and interoperability. This research identifies a significant gap in the existing literature regarding a comprehensive ontology for vulnerabilities in medical IoT devices. This paper proposes a fundamental domain ontology named MIoT (Medical Internet of Things) ontology, focusing on cybersecurity in IoMT (Internet of Medical Things), particularly in remote patient monitoring settings. This research will refer to similar-looking acronyms, IoMT and MIoT ontology. It is important to distinguish between the two. IoMT is a collection of various medical devices and their applications within the research domain. On the other hand, MIoT ontology refers to the proposed ontology that defines various concepts, roles, and individuals. MIoT ontology utilizes the knowledge engineering methodology outlined in Ontology Development 101, along with the structured life cycle, and establishes semantic interoperability among medical devices to secure IoMT assets from vulnerabilities and cyberattacks. By defining key concepts and relationships, it becomes easier to understand and analyze the complex network of information within the IoMT. The MIoT ontology captures essential key terms and security-related entities for future extensions. A conceptual model is derived from the MIoT ontology and validated through a case study. Furthermore, this paper outlines a roadmap for future research, highlighting potential impacts on security automation in healthcare applications. Full article

Accurate navigation is a crucial asset for safe aviation operation. The GNSS (Global Navigation Satellite System) is set to play an always more important role in aviation but needs to cope with the risk of interference, possibly causing signal disruption and loss of navigation capability. It is crucial, therefore, to evaluate the impact of interference events on the GNSS system on board an aircraft, in order to plan countermeasures. This is currently obtained through expensive and time-consuming flight measurement campaigns. This paper shows on the other hand, a method developed to create a virtual digital twin, capable of reconstructing the entire flight scenario (including flight dynamics, actual antenna, and impact of installation on aircraft) and predicting the signal and interference reception at airborne level, with clear benefits in terms of reproducibility and easiness. Through simulations that incorporate jamming scenarios or any other interference scenarios, the effectiveness of the aircraft’s satellite navigation capability in the real environment can be evaluated, providing valuable insights for informed decision-making and system enhancement. By extension, the method shown can provide the ability to predict real-life outcomes even without the need for actual flight, enabling the analysis of different antenna-aircraft configurations in a specific interference scenario. Full article

This research raises questions about the possibilities and options of using the BIM methodology associated with software for the wood design and construction of structure modeling along an asset’s cycle life. Likewise, several academic and research initiatives are reviewed. In this sense, this paper aims to establish an appropriate link between two agendas that the architecture, engineering, and construction (AEC) industry, academia, and governments normally handle separately. By conducting several literature reviews (book, journals, and congresses) and extensive software tests (BIM software: Revit v2023, Archicad v27, Tekla, and wood plug-ins: AGACAD, Archiframe, Timber Framing 2015, WoodStud Frame, etc.), the state-of-the-art was assessed in both fields, and several cases linking BIM and wood are shown in detail and discussed. Various theoretical samples are modelled and shown, and the advantages and disadvantages of each technique and stage are explained. On the other hand, although wood construction has been most common for hundreds of years, this is not the case of BIM software developments associated with this materiality. Furthermore, since the appearance of materials such as steel and reinforced concrete, all software developments have focused on these materials, leaving aside the possibility of developing applications for use in wood projects. According to that previously discussed, it can be concluded that BIM for wood has been used more frequently in academia, that both fields have several common processes, and, in many cases, that only a few BIM-wood tools have been used, thus disregarding the high potential and high level of benefits that result with the application of these methodologies for the complete building life cycle (design, construction, and operation). Full article

The frequency and severity of natural or human-induced disaster events, such as floods, earthquakes, hurricanes, fires, pandemics, hazardous material spills, groundwater contamination, structural failures, explosions, etc., as well as their impacts, have greatly increased in recent decades due to population growth and extensive urbanization, among other factors. The World Bank estimates that the total cost of cities’ and communities’ vulnerability to these types of disasters could reach more than USD 300 billion per year by 2030. However, it has been argued that investment to improve the quality and resilience of engineered physical assets that are the backbone of modern societies, such as critical infrastructure, industrial facilities, and buildings, could significantly contribute to more sustainable and prosperous societies. Engineered assets are key to the delivery of essential services, such as transport, food, water, electricity supply, health and safety, etc. Some of these physical assets are integrated into asset systems and national or regional networks, with life cycles of several decades or even centuries. It is, therefore, of great importance that strategies and life cycle decisions, such as those related to short- and long-term capital investment planning, maintenance strategies, operational plans, and asset disposal, lead to the maximization of the value derived from these assets. Moreover, it is essential that the achievement of these goals is sustainable over time. Organizations dealing with engineering assets, both public and private, must, therefore, integrate sustainability and resilience concerns into everyday operations, using budgets that are often restricted, while also meeting demanding performance requirements in risky and uncertain environments. This Special Issue collates a selection of papers reporting the latest research and case studies regarding the trends and emerging strategies used to address these challenges, with contributions discussing how asset management principles and techniques can help to push the boundaries of sophistication and innovation to improve the life cycle management of engineered assets to ensure more sustainable and resilient cities and societies. Full article

A key goal of structural health monitoring (SHM) systems applied to infrastructure is to improve asset management. SHM systems yield benefits by providing information that allows improved asset management decisions. Often, improvement is measured in monetary terms, whereby lower expenses are sought. The value of information (VoI) is often evaluated through the quantification of the incremental benefit, resulting from the information provided by the SHM system. The VoI can be considered as having two components: value derived from the improved operation of the infrastructure and value derived from increased useful life. This work focuses on the latter source of value in the context of concrete decks in US highway bridges. To estimate the lifecycle extension potential and the connected VoI, we need to simulate bridge deck condition degradation over time to support a discounted cash flow analysis of bridge replacement cost. We accomplish this by utilizing a neural network-based survival analysis combined with Monte Carlo simulation. We present a case study using the developed methods. We have chosen to study the southbound portion of the bridge on the US Highway 202, located in Wayne, NJ. The selected bridge is a representative concrete highway overpass, the type of which there are large numbers in the US. The case study demonstrates the applicability of the methods developed for the general evaluation of the VoI obtained via SHM. The results are encouraging for the widespread use of SHM for lifecycle extension purposes; the potential value in such applications is large. Full article

Large stadiums are highly visible assets for large-scale ‘mega-events’, inspiring built environment professionals to innovate in structure and aesthetics. In recent years environmental performance—or environmental sustainability—has been increasing in focus, with events such as the Olympics calling for ‘green games’ and countries committing to reducing built environment carbon emissions. This paper presents a systematic literature review of large stadiums’ environmental sustainability discourse over the last five years related to design and construction. Using the PRISMA methodology, 18 relevant conceptual and empirical research papers were distilled from 159 extracted papers. Energy consumption and material composition were the most discussed topics. Emergent technologies and processes were also extensively discussed regarding significant embodied energy and indoor air-quality improvements, and greenhouse gas emissions reductions. There was a lack of best practices, or whole life cycle considerations, and minimal demonstration of other attributes of environmental sustainability. This paper provides a baseline to assess progress on environmental sustainability for the built environment sector. A practical definition is presented for Environmentally Sustainable Stadiums (ESS) and a checklist is provided to support leading practices in design and construction. This paper is relevant for built environment professionals and asset owners and managers considering new-build and refurbishments. Full article