Maintenance Challenges Research Articles

Operation and Maintenance Challenges in Building Life Cycle Management: A Literature Review with Insights from Nigeria

Building life cycle management is crucial for ensuring the longevity and efficiency of buildings. However, operation and maintenance challenges hinder the effective management of buildings, leading to dilapidation and reduced lifespan. This literature review explores the reasons for building dilapidation, the impact of professionalism and finance on building life cycle, and the essential aspects of operations and maintenance. The study reveals that poor maintenance, lack of professionalism, and inadequate funding are significant contributors to building dilapidation. Furthermore, effective operations and maintenance involve regular inspections, preventive maintenance, and timely repairs. The findings have implications for building managers, policymakers, and stakeholders in the Nigerian building industry.

Simulation of a Line Voltage Regulator in a Low-Voltage Grid That Is Subject to Strong Voltage Surges Due to the Provision of Fast Frequency Reserve

The increasing adoption of battery storage units alongside private PV systems may prove to be a new challenge for distribution grid operators. This study explored the potential impact of marketing aggregated battery discharge power as a Fast Frequency Reserve (FFR) and its effect on the distribution grid stability. We investigated the efficacy of Line Voltage Regulators (LVRs) in mitigating voltage surges caused by simultaneous battery activation. For this purpose, a simulation was developed via Matlab (Version R2023a) to simulate the voltage at the nodes of an arbitrary distribution grid, using the feed-in and consumed power of the customers as the input. We applied the model to a distribution grid section in Sundsvall (Sweden). The results confirmed that LVRs can amplify voltage surges when their adjustments are not synchronized with the FFR activation. This study underscored the need for proactive measures to address the voltage maintenance challenges arising from the integration of battery storage units and renewable energy sources.

High-precision Lamb wave evaluation for corrosion damage with model-based Bayesian Optimization and Gaussian meta-modeling strategy

The presence of corrosion damage in metallic structures is a critical problem affecting system safety, which poses challenges for structural maintenance. Ultrasonic Lamb wave testing has shown many benefits, including high sensitivity and a large coverage area. However, multiple external factors are causing a mismatch between the imaging result and the actual damage. This study proposes a Bayesian Optimization-based model calibration framework, incorporating a Gaussian process (GP) measurement model, for accurate corrosion damage quantification. In this method, one critical problem is obtaining the high-fidelity Finite Element Method (FEM) model. The initial FEM model usually has inevitable modeling errors due to necessary simplifications and idealized constraints. Here we introduced Bayesian Optimization by which the numerical model could be calibrated. The calibrated FEM model, which had fewer discrepancies with actual experiments, could generate high-fidelity signals corresponding to various damage severity. Then, the GP measurement model outputted the mean and variance of the corrosion width and depth corresponding to the differences between experiment signals and model outputs. The inversion of damage information from the established GP model was accomplished by the genetic algorithm. Hence, both the damage size and depth could be evaluated with high accuracy. Once the corrosion information along different propagation paths was obtained, it can be combined with the location of the corrosion damage center for locating the edge points of the corrosion damage. In the end, the edge points were fitted using the least square algorithm. Validations were experimentally performed, and the detection result showed good consistency with the actual damage.

RECLAIMING PUBLIC OPEN SPACE WITHIN LOCALIZATION OF SUSTAINABLE DEVELOPMENT GOAL 11: THE PERSPECTIVE OF THE CITY OF NIŠ, SERBIA

<p class="TEXT" style="tab-stops: 72.0pt;">Public space is a highlighted topic in the 2030 Agenda for Sustainable Development. The City of Niš has undertaken the process of Voluntary Local Review, and selected, among others, to report on the progress in achieving the Sustainable Development Goal 11, including the indicator related to public open space (POS). This paper explores the phenomenon of POS, with a particular focus on residential areas. Global practices are discussed to provide background on the issue, along with some particularities of Serbian context involving legislative and planning treatment of POS. Current state of POS is explored in the territory of the City of Niš, as well as exploitation and maintenance challenges. These findings are used to establish context-specific POS typology and discuss potential pathways towards inclusive, safe, resilient and sustainable local communities.</p>

In-situ engineering catalytically active surfaces for tribocatalysis with layered double hydroxide nanoparticles

Ensuring long-lasting lubrication is vital for sustainable machinery operation, made possible by self-regenerating carbon-based tribofilms via tribocatalysis. Conventional methods use expensive catalytic coatings, posing challenges for replacement and maintenance in practice. Here, we are proposing catalytic layered double hydroxide (LDH) nanoparticles as cost-effective and easily replenished lubricant additives to engineer catalytically active surfaces in situ where binary and ternary LDHs with Ni2+, Co2+, and/or Cu2+ divalent cations alongside Al3+ trivalent cations are investigated for lubrication performance. Under 100 °C sliding condition equivalent to the lubricating temperature in an internal combustion engine, NiCoAl–CO3 LDH exhibits the lowest wear losses alongside the durable low-friction regime. This excellent performance is attributed to Co-containing spinel and oxide phases in the catalytic tribo-oxide layer which help stabilize and maintain the microstructures of the tribo-oxide layer. In contrast, deterioration in lubrication performance at this temperature was observed for copper-containing LDHs, especially NiCuAl–CO3 LDHs, which is due to the reduction of metallic oxides that drive phase separation in the catalytic oxide tribo-layers. The more stable tribo-oxide layers can result in thick, durable carbon-based tribofilm during sliding along with higher resistance to plastic deformation bulk interlayer. This study offers valuable insight into the synergy of catalytic oxide materials, opening avenues for a rational design of innovative catalytic nano-materials for tribocatalysis processes.

Collaborative governance arrangements: what makes nature-based solutions endure?

ABSTRACT ‘Nature-based Solutions’ (NbSs) are considered key actions to address urban regeneration and foster greener cities. Such actions are based on collaborative governance arrangements, where public administration, private companies, research and citizens cooperate to test and manage innovative solutions. Reflecting a quadruple helix logic, these arrangements display different actors leading responsibility for maintenance while cultivating collaborative relations. Hence, collaborative governance arrangements can assume the shape of public-led, private-led, research-led or community-led types, addressing specific maintenance challenges. Yet, the conditions that allow different types of collaborative governance arrangements to make NbSs endure are still poorly investigated. Through an in-depth analysis of the proGIreg Urban Living Laboratory in Turin (Italy), this paper analyses different types of collaborative governance arrangements, exploring which challenges, risks and potentials characterise them. Particularly, the paper investigates conditions that make NbSs endure over time. The results outline how legitimacy, institutional leadership and administrative commitment, networking capacities, integration of resources, competencies, co-responsibility, knowledge transfer and empowerment play a pivotal role in making NbSs endure. Overall, this article contributes to contemporary research and practices on urban experimentation, NbSs and maintenance.

Comprehensive Safety Strategies and Innovations for Infrastructure Resilience in Bridges

This study explores the critical elements of ensuring bridge safety, covering design, construction, maintenance, personal protective equipment (PPE), community engagement, and public perception. It draws lessons from historical bridge failures, like the Morandi Bridge collapse, highlighting the necessity for stringent safety protocols in infrastructure development. Innovative solutions, such as heating systems to prevent ice formation and seismic resilient designs, are explored to address maintenance challenges and environmental impacts. In addition, the study also examines the role of public perception, education, and community engagement in bridge safety. It discusses the positive and negative aspects of safety measures like nets and Fall Protection Systems (FPS) and evaluates the impact of public education programs on safety awareness. Visual standards, clear signage, and innovations in bridge design, such as smart sensors and self-healing materials, are explored for their contributions to safety and longevity. A comparative analysis of safety standards worldwide, such as AASHTO, BSI, CSA, Austroad, Eurocodes, JRA, TB, IRC, ABNT, and SANS, highlights global efforts to establish consistent safety measures. Historical data and case studies, including the Tacoma Bridge Collapse and the Minneapolis I-35W Collapse, provide insights into safety measures' evolution. In conclusion, there is a need for a comprehensive approach to bridge safety, on the backend by implementing policies and ensuring safety protocols are being met, as well as a good public perception using visual components, like safety nets. Success hinges on collaborative efforts, robust risk reduction, and fostering public confidence in infrastructure development.

Breast Cancer Education and Empowerment in Ethiopia: Evaluating Community-Based Cancer Prevention Efforts Using the RE-AIM Framework

Cancer prevention challenges in Ethiopia include limited community awareness and low uptake of screening, which are in part driven by a lack of culturally and linguistically relevant cancer education appropriate for the diverse indigenous communities of this never-colonized nation. In 2022, a comprehensive multi-media breast cancer (BC) awareness campaign was implemented, featuring local cancer experts and survivors, with community-based screening events in the towns of Adama and Mojo. The RE-AIM framework was used to evaluate and describe its reach, effectiveness, adoption, implementation, and maintenance. Educational pamphlets, videos, social media posts, and interviews were distributed in person and through local and national media networks, reaching tens of millions of people and resulting in 525 individuals screened, with one diagnosis of early-stage cancer. During the free screening events, an interview-administered survey of BC knowledge, attitudes, and screening practices was conducted to inform future cancer education for this population. Among 287 survey respondents, about half correctly identified swelling (46%) or changing nipples/discharge (48.4%) as signs of BC. Maintenance challenges include the lack of a national screening program. Educational resources and a mobile app, translated into the local language, encourage continued patient empowerment to perform breast self-exams. In the absence of established BC prevention programs, “pop-up” mobile screening events can be effective for mobilizing communities to get screened. The paper highlights challenges and lessons gleaned from this community-based BC awareness campaign and screening event to inform future cancer education initiatives in Ethiopia and similar resource-limited settings.

Optimalisasi Sistem Manajemen Barang dalam Bisnis Sewa Properti melalui Implementasi Appsheet (Studi Kasus: Sewa Rumah BSB)

BSB House Rental, a property rental enterprise situated in Kartasura Subdistrict, Sukoharjo Regency, encounters challenges in asset maintenance, notably the loss of approximately 2 items per tenant turnover. With frequent turnovers, facilities often undergo damage requiring repairs. This study aims to address these issues by developing a no-code-based asset management system using AppSheet technology. Employing a qualitative-experimental methodology, the research involves interviews with the business owner to identify challenges and prototyping the system using AppSheet. The application, designed to inventory assets and streamline replacement requests, is subjected to blackbox testing to assess its effectiveness in recording and processing item replacements.

Advances in common in vitro cellular models of pulmonary fibrosis.

The development of in vitro models is essential for a comprehensive understanding and investigation of pulmonary fibrosis (PF) at both cellular and molecular levels. This study presents a literature review and an analysis of various cellular models used in scientific studies, specifically focusing on their applications in elucidating the pathogenesis of PF. Our study highlights the importance of taking a comprehensive approach to studing PF, emphasizing the necessity of considering multiple cell types and organs and integrating diverse analytical perspectives. Notably, primary cells demonstrate remarkable cell growth characteristics and gene expression profiles; however, their limited availability, maintenance challenges, inability for continuous propagation and susceptibility to phenotypic changes over time significantly limit their utility in scientific investigation. By contrast, immortalized cell lines are easily accessible, cultured and continuously propagated, although they may have some phenotypic differences from primary cells. Furthermore, in vitro coculture models offer a more practical and precise method to explore complex interactions among cells, tissues and organs. Consequently, when developing models of PF, researchers should thoroughly assess the advantages, limitations and relevant mechanisms of different cell models to ensure their selection is consistent with the research objectives.

Student Result Management System using PHP

Our educational institution maintains digital records of student data to ensure ease of access and management. However, these records are currently dispersed across various formats, posing challenges in maintenance, especially with the growing student population. This fragmentation often results in redundant data entry and inconsistencies, as students are required to repeatedly provide the same information. In response, we propose the development of a comprehensive web application designed to function as an integrated platform for aggregating and categorizing student data. This platform aims to consolidate all student-provided information into a centralized repository, which can then be categorized and selectively accessed by different user types according to their respective needs. Additionally, the web application will empower students to effortlessly update their information while facilitating efficient retrieval of selected student data by college staff. Moreover, it will streamline the online admission process by offering the option of online payment through a secure payment gateway. Furthermore, the application will include features for recording student marks in their respective courses, as well as tracking attendance. It will also inform students of new placement opportunities offered by the college and maintain records of faculty and departments. Additionally, it will log online transactions conducted by students during the admission process. The development of this application will utilize HTML, CSS, and JavaScript for the front-end, ensuring an intuitive and visually appealing user interface. On the backend, PHP and MySQL will be employed to provide robust data management and processing capabilities

AI-Driven Refactoring: A Pipeline for Identifying and Correcting Data Clumps in Git Repositories

Data clumps, groups of variables that repeatedly appear together across different parts of a software system, are indicative of poor code structure and can lead to potential issues such as maintenance challenges, testing complexity, and scalability concerns, among others. Addressing this, our study introduces an innovative AI-driven pipeline specifically designed for the refactoring of data clumps in software repositories. This pipeline leverages the capabilities of Large Language Models (LLM), such as ChatGPT, to automate the detection and resolution of data clumps, thereby enhancing code quality and maintainability. In developing this pipeline, we have taken into consideration the new European Union (EU)-Artificial Intelligence (AI) Act, ensuring that our pipeline complies with the latest regulatory requirements and ethical standards for use of AI in software development by outsourcing decisions to a human in the loop. Preliminary experiments utilizing ChatGPT were conducted to validate the effectiveness and efficiency of our approach. These tests demonstrate promising results in identifying and refactoring data clumps, but also the challenges using LLMs.

Assessment of Intelligent Unmanned Maintenance Construction for Asphalt Pavement Based on Fuzzy Comprehensive Evaluation and Analytical Hierarchy Process

Conventional human-involved maintenance methods for asphalt pavement pose significant challenges when applied to high-traffic road sections, often leading to congestion and safety risks, as well as reduced maintenance efficiency. In recent years, explorations into unmanned construction technology for newly constructed expressways have yielded beneficial and encouraging results. However, its application in road maintenance in more complex environments still needs to be expanded. In this study, an intelligent unmanned maintenance technology for asphalt pavement was applied to the Lilong Highway in Zhejiang Province, China, and the compactability, thickness, surface smoothness, permeability coefficient, and constructure depth of maintenance road sections were measured. Then, based on fuzzy comprehensive mathematics and the analytic hierarchy process, a comprehensive evaluation was performed on the intelligent unmanned maintenance technology, considering the aspects of road quality, safety, application, and socio-economic benefits. The results show that the road quality of intelligent unmanned maintenance technology can meet the road specification requirements. In addition, the membership degree of unmanned maintenance technology in the excellent grade is the highest, reaching 0.805, and the quantified value for the overall evaluation of the application effectiveness of unmanned maintenance technology is 92.10. This means that the final comprehensive evaluation result of unmanned maintenance technology is rated as excellent. The research findings provide decision-makers with valuable insights into the unmanned automation maintenance challenges faced by asphalt pavement, enabling them to implement appropriate measures to elevate the maintenance standards of road transportation.

Student Result Management System using PHP

Our educational institution maintains digital records of student data to ensure ease of access and management. However, these records are currently dispersed across various formats, posing challenges in maintenance, especially with the growing student population. This fragmentation often results in redundant data entry and inconsistencies, as students are required to repeatedly provide the same information. In response, we propose the development of a comprehensive web application designed to function as an integrated platform for aggregating and categorizing student data. This platform aims to consolidate all student-provided information into a centralized repository, which can then be categorized and selectively accessed by different user types according to their respective needs. Additionally, the web application will empower students to effortlessly update their information while facilitating efficient retrieval of selected student data by college staff. Moreover, it will streamline the online admission process by offering the option of online payment through a secure payment gateway. Furthermore, the application will include features for recording student marks in their respective courses, as well as tracking attendance. It will also inform students of new placement opportunities offered by the college and maintain records of faculty and departments. Additionally, it will log online transactions conducted by students during the admission process. The development of this application will utilize HTML, CSS, and JavaScript for the front-end, ensuring an intuitive and visually appealing user interface. On the backend, PHP and MySQL will be employed to provide robust data management and processing capabilities

Effects of soil erosion–deposition on corn yields in the Chinese Mollisol region

Soil erosion is a major challenge for crop production maintenance and improvement in agricultural regions worldwide. However, quantifying the impacts of soil erosion rate on crop yield has not been carried out often, and there are few reports on impacts of soil deposition crop yields, especially in the Chinese Mollisol Region. Thus, this study quantified soil erosion–deposition rates (SEDRs) at three agricultural catchments in the Chinese Mollisol region using the 137Cs technique and assessed soil erosion–deposition impacts on corn (Zea mays L.) yield. The results showed that SEDRs varied from −5471.7 (deposition) to 9956.0 (erosion) t km−2 yr−1. The distributions of both soil erosion and deposition in the three catchments were in coexistence, but soil erosion was dominant. In addition, above 2500 t km−2 yr−1 of soil erosion rates (larger than slight erosion rates) in the three catchments accounted for 41.0 %, indicating that soil erosion was severe. Moreover, corn yields in the three catchments ranged from 1.9 to 14.6 t ha−1. Compared with deposited sites, corn yields in eroded sites were 19.2 %–40.6 % lower. Furthermore, when soil erosion rates were moderate (2500–5000 t km−2 yr−1), corn yields were 32.4 % lower than those in non-eroded sites. The spatial distribution of corn yield was opposite to that of soil erosion rate at catchment and slope scales. The relationship between corn yields and soil erosion rates had a negative linear relationship (p < 0.01), which was validated with acceptable accuracy. There was a positive linear relationship between corn yields and soil deposition rates without statistical significance (p > 0.05). These findings are valuable for assessing how soil erosion–deposition affects crop yields to implement countermeasures for controlling soil erosion and maintaining sustainable agricultural development.

Isolation of Cardanol Fractions from Cashew Nutshell Liquid (CNSL): A Sustainable Approach

Exploring sustainable approaches to replace petroleum-based chemicals is an ongoing challenge in reducing the carbon footprint. Due to the complexity and percentage variation in nature-generated molecules, which further varies based on geographical origin and the purification protocol adopted, a better isolation strategy for individual components is required. Agrowaste from the cashew industry generates phenolic lipid (cardanol)-rich cashew nutshell liquid (CNSL) and has recently shown extensive commercial utility. Cardanol naturally exists as a mixture of three structurally different components with C15-alkylene chains: monoene, diene, and triene. The separation of these three fractions has been a bottleneck and is crucial for certain structural designs and reproducibility. Herein, we describe the gram-scale purification of cardanol into each component using flash column chromatography within the sustainability framework. The solvent used for elution is recovered and reused after each stage (up to 82%), making it a cost-effective and sustainable purification strategy. This simple purification technique replaces the alternative high-temperature vacuum distillation, which requires substantial energy consumption and poses vacuum fluctuation and maintenance challenges. Three components (monoene 42%, diene 22%, and triene 36%) were isolated with good purity and were fully characterized by 1H and 13C NMR, GC-MS, HPLC, and FTIR spectroscopy. The present work demonstrates that greener and simpler strategies pave the way for the isolation of constituents from nature-sourced biochemicals and unleash the potential of CNSL-derived fractions for high-end applications.

Subgraph Isomorphic Decision Tree to Predict Radical Thermochemistry with Bounded Uncertainty Estimation.

Detailed chemical kinetic models offer valuable mechanistic insights into industrial applications. Automatic generation of reliable kinetic models requires fast and accurate radical thermochemistry estimation. Kineticists often prefer hydrogen bond increment (HBI) corrections from a closed-shell molecule to the corresponding radical for their interpretability, physical meaning, and facilitation of error cancellation as a relative quantity. Tree estimators, used due to limited data, currently rely on expert knowledge and manual construction, posing challenges in maintenance and improvement. In this work, we extend the subgraph isomorphic decision tree (SIDT) algorithm originally developed for rate estimation to estimate HBI corrections. We introduce a physics-aware splitting criterion, explore a bounded weighted uncertainty estimation method, and evaluate aleatoric uncertainty-based and model variance reduction-based prepruning methods. Moreover, we compile a data set of thermochemical parameters for 2210 radicals involving C, O, N, and H based on quantum chemical calculations from recently published works. We leverage the collected data set to train the SIDT model. Compared to existing empirical tree estimators, the SIDT model (1) offers an automatic approach to generating and extending the tree estimator for thermochemistry, (2) has better accuracy and R2, (3) provides significantly more realistic uncertainty estimates, and (4) has a tree structure much more advantageous in descent speed. Overall, the SIDT estimator marks a great leap in kinetic modeling, offering more precise, reliable, and scalable predictions for radical thermochemistry.

The Role of Urban Green Spaces in Mitigating Climate Change: An Integrative Review of Ecological, Social, and Health Benefits

Urban green spaces (UGS) are increasingly recognized as essential components of cities for mitigating climate change and enhancing environmental, social, and public health outcomes. This integrative review explores the multifaceted benefits of UGS, focusing on their ecological contributions such as carbon sequestration, biodiversity support, and air quality improvement. It also highlights the social and economic benefits of green spaces, including community cohesion, enhanced property values, and opportunities for environmental stewardship. Furthermore, the review examines the positive impacts of UGS on physical and mental health, particularly in mitigating the adverse health effects of urban heat islands and climate-induced stress. The findings emphasize the critical role of UGS in creating resilient, sustainable, and livable cities. Finally, the review discusses the challenges of equitable access, land use, and maintenance while offering policy recommendations for integrating green infrastructure into urban planning.

Current Challenges in Operation, Performance, and Maintenance of Photovoltaic Panels

The installed solar capacity in the European Union has expanded rapidly in recent years. The production of these plants is stochastic and highly dependent on the weather. However, many factors should be considered together to estimate the expected output according to the weather forecast so that these new PV plants can operate at maximum capacity. Plants must be operated in coordination with maintenance operations and considering actual energy market prices. Various methods have recently been developed in the literature, ranging from the most impactful artificial-intelligence-based generation estimation methods to various diagnostic and maintenance methods. Moreover, the optimal operational and maintenance strategy usually depends on market regulation, and there are many concerns related to the distribution system operator. This review article aims to summarize and illustrate the challenges of operating and maintaining solar power plants and the economic and technical importance of these problems.

Earth's Long-Wave Infrared: Review and Study of Scalable Applications

The Earth's infrared energy storage is substantial, and its large-scale utilization could effectively ameliorate the greenhouse effect on Earth. Several applications of utilizing Earth's infrared radiation for cooling and power generation are summarized based on existing literature. Building upon this foundation, the use of water as an excellent energy storage medium is proposed, and a long-wave energy storage system is designed. This system can harness the immense energy density of long-wave infrared radiation with fixed bandwidth or wavelength. A comprehensive study on large-scale application is outlined in four aspects, leveraging the energy storage and radiation advantages of the system: (a) Long-wave infrared is efficiently transported using hollow glass infrared fibers for room cooling and heating. This addresses the issues of separate terminals for capillary radiation air conditioning, high costs, and maintenance challenges. (b) Building on existing literature, taking Hainan as an example, the utilization of a temperature difference of approximately 15 °C between the lowest and highest temperatures in a day for power generation is suggested. (c) The composition and structure of planar antennas are derived, and parameter selection for rectifying diodes is proposed based on radiation fluctuation theory and antenna theory. This lays a theoretical and practical foundation for converting long-wave radiation waves using rectifying antennas. (d) The long-wave radiation quantum theory is utilized to propose the concept of manufacturing components that can directly convert energy from long-wave radiation. In each of these four aspects of large-scale utilization, the emphasis is on water's excellent insulation, storage, and radiation properties, presenting new perspectives for the widespread utilization of Earth's infrared and offering a quick pathway for humanity to explore new energy sources and mitigate the greenhouse effect on Earth, facilitating a harmonious coexistence between humans and nature.