Future Maintenance Research Articles

Development of a new control interface for the electron gun pulser of TLS Linac

The electron gun control system, which serves as the TLS LINAC’s power source, has been in operation for more than two decades. Since some components of a previously designed circuit have aged and been discontinued, the control system will become unreliable and irreparable. A new control interface of electron gun pulser has been developed to improve the operational stability and future maintenance of the electron gun control system. To achieve remote control, an SBC (single-board computer) equipped with a high-precision AD/DA expansion board was used as a control interface. The signal processing circuit module generates the bias and b-plus voltages that are output to the electron gun and also provides instant feedback voltage readings. For easier maintenance, the new electron gun pulser control modules have been assembled into a single box. Furthermore, this software architecture of control interface has been based on the EPICS framework and integrated with an existing TLS control system. The efforts of rejuvenating electron gun pulser control system are described in this paper.

Economic Viability of Solar Irrigation Pumps: A Comparative Life Cycle Cost Analysis with Diesel and Electric Pumps

In the present scenario viability of an irrigation pump is of extreme significance to set up it and get the sought after output in a more economic and better way. In this study investigation has been done about the economic viability of solar irrigation pump against the diesel and electric irrigation pump through the life cycle cost analysis. In LCC analysis, capital cost, future maintenance cost and replacement cost are converted to present worth value considering inflation rate and discount rate during its total life cycle. Annualized life cycle cost (ALCC) of solar irrigation pump has been further compared with grid connected electric and diesel irrigation pump. The results revealed that the annualized life cycle cost (ALCC) of solar irrigation pump is lower than grid connected electric and diesel irrigation pump. E.g., The ALCC of solar irrigation pump was estimated at 12383/year and 15435/year for 3 HP and 5 HP pump respectively, which is significantly leave behind electric pumps, which boast ALCC figures of 61641/year and 82371/year for 3 HP and 5 HP pumps. In the same way, when related to diesel irrigation pumps with ALCC values of 85891/year and 136088/year for 3 HP and 5 HP pumps respectively, the economic superiority of solar irrigation pumps becomes abundantly clear. . It has also been observed that the capital cost for solar irrigation pump is higher than grid connected electric and diesel irrigation pump. However, the maintenance cost and replacement cost are lower in case of solar. The comparison shows that the solar irrigation pump was more viable than the connected electric and diesel irrigation pump.

Long-term Corrosion Monitoring for Evaluating the Performance of Repair Measures

For a highway operator, such as ASFiNAG, bridges are very important assets. Despite all regular maintenance measures, these structures are strongly subjected to aging and degradation because of their exposure. Chloride contamination poses a significant challenge, gradually reducing the durability and service life of these structures, necessitating repair measures. This paper focuses on the comprehensive analysis of data collected through on-site monitoring and nearby weather stations.Bridge components that were exposed to high chloride levels were rehabilitated with different systems and monitored for more than a decade. In the paper, the rehabilitation methods, sensor principles, and initial corrosion data are presented. Seasonal corrosion trends revealed interdependencies and offered insights into repair effectiveness and durability.This study provides insights into cost-effective and prospective maintenance strategies based on key indicators such as humidity, electrical resistivity, and corrosion potential. It assesses the condition of structures rehabilitated by hydrophobic treatment and coating using long-term monitoring data from an overpass. This offers valuable insights into the effectiveness of repair measures.Continuous monitoring allows for ongoing evaluation of degradation and maintenance efficiency, guiding decisions on future maintenance intervals. This research serves as an assessment of maintenance effectiveness, ultimately contributing to cost savings, extended lifespan, and reduced lane closure time of critical road infrastructure.

Stakeholder engagement in urban water management: A SWOT analysis of the Banger polder system in Semarang

Semarang is a coastal city of more than 1.6 million people and is considered a global hotspot for land subsidence due to groundwater extraction. Large parts of the city are below sea level already. The Banger polder Project, Launched in 2016, aimed to reduce flood risk in the area by developing a technically well-functioning polder system, creating a sustainable water management organization and improving stakeholder participation. Stakeholder engagement is critical for the financial and operational support of the polder system. However, the results show that Semarang's stakeholder engagement scores the lowest on the OECD ladder of stakeholder engagement. This paper assesses the engagement of various stakeholder representatives in the water management organization and identifies key strengths, weaknesses, opportunities, and threats to the polder system through a SWOT analysis. The main threats are the lack of awareness among residents, that leads to solid waste being disposed of in waterways, the lack of adequate management and funding, and uncertainty about the future maintenance system.

“I Don’t Really Wanna Go Back. I Know What I’ve Got in Front of Me.” Lived Experiences of Emergency Nurses 2 Years Into the Global COVID-19 Pandemic

IntroductionAs the coronavirus disease 2019 pandemic continued into 2021 and beyond, unrelenting work pressures continued to mount on the emergency nursing workforce. In the second year of this longitudinal study on emergency nurse lived experiences, staff outlined the continued strain of the profession, highlighting their increasing levels of burnout and identifying early stages of trauma response. MethodsThis research aimed to continue to explore lived experiences of Australian emergency nurses working on the frontline 2 years into the coronavirus disease 2019 pandemic. A qualitative research design was used, guided by an interpretive hermeneutic phenomenological approach. A total of 9 Victorian emergency nurses from both regional and metropolitan hospitals were interviewed between October and November 2021. Analysis was undertaken using a thematic analysis method. ResultsA total of 3 major themes and 12 subthemes were extracted from the data. The 3 overarching themes included “On the floor each day,” “Can I keep going?” and “What’s around the corner?” Increasing levels of emotional exhaustion and burnout were evident, with emergency nurses stating their intentions to leave the profession. DiscussionDeep engagement with participant emergency nurses across 2 years of the coronavirus disease 2019 pandemic has revealed a need for greater emphasis on staff well-being for future maintenance of a resilient and healthy workforce. Without this, lack of support for subsequent nursing cohorts may affect the quality and reliability of care being provided in acute care centers.

Guiding decisions on the future of dams: A GIS database characterizing ecological and social considerations of Dam decisions

In the United States and elsewhere, there are a growing number of dams which have exceeded their design life and will need to be repaired or removed in the coming decades. Most of these dams no longer serve their original purpose and removal can provide ecological benefits and eliminate future maintenance costs and hazards. However, many decision-makers have been ill-prepared by community resistance to proposals to remove dams. Given the number of dam removal initiatives that have failed or been delayed due to community resistance, both ecological and social attributes of dams need to be better mapped and conveyed in understandable ways. The goal of this study was to support future decisions regarding dams by 1) developing a set of metrics to assess the social and ecological dimensions of dams, and 2) using these metrics to develop a GIS database, for the 1000+ dams in the Narragansett Bay/Rhode Island area of southern New England. The database characterizes the ecological benefits of dam removal or modification, in terms of fish passage, and the social dimensions that may need to be considered when engaging a community in discussions about the future of a dam. Our emphasis was on small-head dams (i.e. <5 m tall) which comprise most dams in the study area. We created social value metrics that used GIS data to assess dams and their impoundments for potential benefits to waterfront properties, history, sense-of-place, and recreation. We modeled our ecological metrics and ranking system after the Nature Conservancy's Northeast Aquatic Connectivity study which considered factors relating to river connectivity and watershed quality. We evaluated our social and ecological metrics using case studies of dams in the study area that had been previously removed or modified. We assumed that both sets of dams were ecologically important, but the modified dams had higher social value that prohibited their removal. Dams that had been removed or modified were both ranked as high priority in terms of value for fish passage, particularly for diadromous fish. Dams that were modified to include fish passage had substantially larger impoundments, more waterfront properties, and more features associated with recreational or cultural value (e.g. boating opportunity, visibility, etc.). Our social metrics were consistent with expectations based on the limited case studies (7 removals, 19 modifications) available in the study area. We made the dam assessment metrics readily accessible to stakeholders through an interactive ArcGIS Online web map.

Optimization of Preventive Maintenance Timing of Highway Bridges Considering China’s “Dual Carbon” Target

The dual carbon target is a two-stage carbon reduction goal proposed by China, while the bridge maintenance strategy does not consider the need for sustainable development. Therefore, this article studies the optimization of bridge maintenance timing under China’s dual carbon goals. Firstly, this paper aims to minimize the total cost of maintenance and carbon emissions, considering the continuous effects of carbon pricing and emissions in the context of the dual carbon goals. The CHINAGEM-E model is employed to predict carbon prices, and a preventive maintenance decision-making method for highway bridges is established. Secondly, based on the theory of material residual strength, a degradation model for the technical condition of highway bridges is constructed. Finally, an in-depth case analysis of an in-service highway bridge is conducted to derive optimal maintenance solutions under three scenarios. In comparison to scenarios considering only maintenance costs or those based on benchmark carbon prices, the comprehensive maintenance cost under the dual carbon targets is the highest. In the total maintenance cost, carbon emission costs constitute over 50%, emphasizing the need for increased attention to carbon emission cost studies in future maintenance research. The methodology proposed in this paper is the first to connect carbon prices with the timing of preventive maintenance for bridges, providing a more scientific and sustainable basis for future highway bridge maintenance decisions.

Application of improved support vector machine model in fault diagnosis and prediction of power transformers

AbstractPower transformers undertake the task of transforming voltage and transmitting electrical energy. Its operating status is directly connected with the stability and safety of the whole power system, and it is very important to judge the operating conditions of power transformers and diagnose fault types. The use of dissolved gas analysis technology in oil can provide preliminary fault diagnosis for transformers. However, with the increasing demand for fault diagnosis accuracy in modern electrical equipment, relying only on dissolved gas analysis technology in oil cannot satisfy the demands. To lift the transformer fault diagnosis accuracy, this study introduces the K‐means algorithm into the model and constructs a high‐precision and fast convergence diagnosis method and a power transformer fault location recognition model. In the example analysis, kernel functions were selected for training five typical gases to obtain the optimal parameters, and their prediction curves and errors were analyzed. Its diagnostic accuracy is 98.4%, and the error in all five gases is within 1 (uL/L). The average error of the improved support vector machine intelligent algorithm is lower than that of the previous model and other prediction methods. By testing the same sample data, the correctness of this method was verified. The significance of improving support vector machines lies in further improving the performance and applicability of the original support vector machine algorithm, providing a basis for future transformer maintenance and contributing to social development and continuous improvement of economic benefits.

Sensitivity analysis of asphalt pavement performance under freeze-thaw cycles by applying reliability method

Asphalt pavement performance remains pivotal in ensuring the longevity and safety of our transport networks, especially in regions that face unique environmental challenges such as the Qinghai-Tibet plateau. This study presents a groundbreaking reliability model for the evaluation of asphalt pavement performance, based on the esteemed AASHTO design equation. Four cardinal uncertainty factors, encompassing the environment, traffic loads, pavement structures and materials, and anthropogenic activities, were meticulously integrated into the performance analysis. Delving deep into the intricate dynamics of the pavement structure strength, five random variables - SN, ΔPSI, Mr, ESAL0and r - were identified and analyzed, reflecting the inherent uncertainties during its lifecycle. A notable observation was the linear decline of SNF-T with increasing freeze-thaw actions. Additionally, a comprehensive sensitivity analysis highlighted the profound influence of ESAL0 on the sensitivity of the load equation and emphasized the dominant role of SNF-T in pavement structural performance evaluation. This investigation not only unravels the complex interactions governing asphalt pavement behavior but also provides an invaluable framework for future research, design optimization, and infrastructure maintenance strategies in challenging terrains.

Enhancing Electric Vehicle Reliability and Integration with Renewable Energy: A Multi-Faceted Review

Electric vehicles (EVs) are gaining attention due to their zero carbon emissions, but concerns about their reliability, especially critical components, persist. Previous research has primarily focused on EV drive motor reliability, neglecting the motor controller. To address this gap, this study assesses the reliability of the entire motor system in electric vans, including both drive motor and motor controller components. It predicts failure rates for these components, highlighting vulnerabilities and shortcomings in existing research, which can inform future design and maintenance. In addition, the integration of EVs and renewable energy resources has garnered attention, but concerns about component reliability have arisen. A novel approach called " Innovative Incentive-Driven Fuzzy Fault Tree Analysis " (IIFFTA) is introduced for power systems incorporating EVs and renewable energy, addressing vague and imprecise events and data deficiencies in conventional fault tree analysis. IIFFTA considers different component failure rates and probability values of fault occurrences, offering a more effective risk assessment method. Lastly, plug-in electric vehicles (PEVs) impact distribution systems, and this paper explores distribution feeder reconfiguration (DFR) as a reliability-enhancing strategy for coordinating vehicle-to-grid (V2G) services from PEV fleets within a stochastic framework. The study accounts for uncertainties related to network demand, energy prices, wind power generation, and PEV fleet behavior, employing a self-adaptive evolutionary algorithm (SOS) to address the stochastic optimization problem.

Identifying equipment health status from maintenance records using Lexicon based Unsupervised Sentiment Analysis Adjusted for Negation (LUSAA-N)

During periodic inspection and repair of industrial equipment, technicians create maintenance records in the form of unstructured text to document valuable information regarding the equipment condition, operating environment, failed components, failure mechanism, etc. Inferring the equipment health status from these records can help in planning future maintenance actions to avoid expensive machine failures. However, automatic inference of the equipment health status is non-trivial due to various challenges inherent in analyzing unstructured text such as domain-specific vocabulary and negation words. Further, manual labeling of the records for supervised classification is arduous and impractical. Thus, in this paper, we present a model to automatically extract the equipment health status from maintenance records in a completely unsupervised manner. We show that using general English sentiment lexicons is highly inefficient for analyzing maintenance records, and thus propose a method that leverages sentiment lexicons curated for the maintenance domain and addresses the central issue of negation. We demonstrate the effectiveness of our proposed model over extant research using data from real-life maintenance records from oil rig equipment.

Power grid monitoring based on Machine Learning and Deep Learning techniques

&lt;p&gt;&lt;strong&gt;Background:&lt;/strong&gt; In this work, some application examples of machine learning and deep learning techniques in the monitoring of electricity distribution services and infrastructures are proposed. Three different fields of application are considered to highlight the use of techniques based on neural networks: detection and classification of power quality disturbances, monitoring of underground cables in medium voltage lines and diagnosis of joints in high voltage overhead power lines. &lt;strong&gt;Methods:&lt;/strong&gt; In the field of power grid monitoring, this work proposes a classification method based on a complex valued neural network to assess working conditions of junction regions in high-voltage overhead lines and insulating materials in medium voltage underground networks. The purpose of this method is to prevent the rupture of joint structures and the abnormal degradation of underground cables via frequency response measurements. This approach allows the direct processing of complex measurements and to reduce the computational effort compared to other methods available in the literature. &lt;strong&gt;Results:&lt;/strong&gt; The results obtained in the monitoring of underground cables and joints of high voltage lines guarantee an overall classification rate higher than 90%. In the field of power quality, several deep learning and machine learning methods are proposed to detect the most common voltage disturbances. &lt;strong&gt;Conclusions:&lt;/strong&gt; In this paper, an innovative use of widespread algorithms such as convolutional neural networks is proposed with excellent results. Furthermore, the use of a complex-valued neural network in electrical infrastructure monitoring is presented, introducing a minimally invasive classification method that could be instrumental in the transition from corrective to predictive maintenance in the near future.&lt;/p&gt;

Restorative dentistry clinical decision-making for hypodontia: peg and missing lateral incisor teeth

Peg-shaped and missing lateral incisor teeth are common features for patients affected by hypodontia. While improvements in dental appearance may be a strong motivating factor for these patients, providing dental treatment to improve the clinical condition and achieve an acceptable and stable outcome can be complex and lengthy.For patients affected by hypodontia, discussion and consideration of various approaches to their individual treatment are best achieved in a multidisciplinary team environment. This allows debate of options and joint agreement between at least orthodontic and restorative dentistry specialist colleagues, based largely on clinical factors, towards a treatment plan that is acceptable to the patient. As most patients with this lateral incisor form of hypodontia are initially treated as teenagers and young adults, there is also an understanding that treatment outcomes will have lifelong maintenance and resource implications to consider.This paper identifies and discusses the key clinical features that influence the treatment planning process for a patient with either missing or peg lateral incisor teeth. These will often involve consideration of whether to open or close the lateral incisor spaces and whether to restore or replace a peg lateral incisor tooth. The process should be patient-centred, evidence-based, and aim to minimise the lifelong treatment burden, retaining options for future maintenance and retreatment.

Performance comparison of steel fiber reinforced concrete and conventional reinforced concrete cast-in-place half-scale concrete bridge decks under bending

The most time-consuming processes involved in bridge deck construction are laying and tying conventional reinforcement and verifying the required cover. Thus, there is a need within bridge construction technology to identify opportunities for utilizing steel fibers and replacing more conventional reinforcing bars on bridge decks and this could be a significant step in speeding up bridge construction. Although the bending strength performance of reinforced concrete decks has been the subject of many experiments and research, many considerations still need to be explored. Hence, the current experiment aims to compare and evaluate the bending strength and ductility of two half-scale concrete bridge decks reinforced by steel fiber reinforcement (SFRC) with two half-scale concrete bridge decks reinforced by conventional reinforcement (RC), 27.6 MPa (4000 psi) concrete compressive strength is used in this study, all four decks were tested under flexural loads. Load–displacement curves (P-∆) are recorded as a tool to measure the ductility index (μE) (Spadea et al.). The result showed that the flexural stiffness of the SFRC concrete deck specimens is improved and load carrying capacity increased by 12.3% compared to RC decks. Moreover, crack width and crack are reduced by 14% since the SFRC decks offer more concrete ductility than RC decks, meaning less future maintenance and corrosion. Therefore, the use of steel fiber in concrete mixtures could be a significant step in speeding up bridge construction since it does not require laying, tying, and verifying clear cover, in addition to increasing the lifespan of bridge decks.

Core Competencies for Cataloging and Metadata Professional Librarians: Assessment of Community Use and Recommendations for the Future of the Document

The Association for Library Collections &amp; Technical Services (ALCTS) Board of Directors approved the Core Competencies for Cataloging and Metadata Professional Librarians, hereafter referred to as the “Core Competencies,” in January 2017. The Core Competencies lists the skills required of professionals performing cataloging and metadata work in libraries of all types. In the six years since the document’s release, the cataloging and metadata community has adopted new cataloging standards, experimented with new tools, and engaged in conversations and reparative efforts around inclusive metadata. In this paper, we, the authors of the Core Competencies, report the results of our survey research that assessed the current use of the document within the cataloging and metadata community and solicited comments on ways in which the document might be revised. We conclude with recommendations for immediate changes to the document, and for its future use and maintenance.

정비지원계획구역 지정이 부동산 가격에 미치는 영향에 관한 연구

This study investigated the impact of the maintenance support plan system introduced in September 2021 on real estate prices for rapid housing supply in Seoul. In particular, while designating the maintenance support plan area, the land transaction permit system and the base date for calculating rights were designated for the purpose of preventing the rise in real estate prices, and the impact of these policies on real estate prices was analyzed. Based on the actual transaction price, this study confirmed whether real estate prices were stabilized using a double-difference method that measures policy effects before and after the public offering by dividing into groups that applied real estate regulations and groups that did not. As a result of the analysis, it was found that there was no effect of suppressing the rise in real estate prices due to the application of the land transaction permit system to stabilize housing prices and the base date for calculating rights. Therefore, based on the results of this study, it is necessary to prepare additional measures to block speculative demand when designating a future maintenance support plan.

Digital twinning during load tests of railway bridges - case study: the high-speed railway network, Extremadura, Spain

This article presents a case study with various developments of digital twinning of a sample of load tests performed on several railways bridges. The case study is located in Extremadura, South Western Spain and its aim is the generation of a validated, multi-layered information construct in the form of a digital twin as the result of a load test. This result is conceived, not only to verify the assumptions of the design of the bridge but also, to optimize future maintenance plans of the network. This particular case study is framed within a vaster European effort on digitization of the construction sector. Research and Innovation Actions within this demo case are aimed at integrating routine requirements and procedures of load tests with cutting edge digital technologies for the generation of validated virtual replica of these physical bridges. The generated twins during these load tests behaviourally match the obtained response during loading and as such, represent an ideal model for future simulations and behavioural predictions. Different data-gathering techniques and numerical models are integrated within a Common Data Environment (CDE). All efforts related to measurement, simulation, 3D modelling, assessment and validation can be wrapped up systematically for further use during regular operation of the asset.

Structural Assessment of Historical Stone Bridges with the Finite Element Method under Dynamic Effects of Arch Shape: The Antik Iscehisar Bridge

In this study, the effect of the variation of the arch form in thickness and height on the bridge was investigated as a numerical analysis. For this purpose, the historic Antik Iscehisar Bridge located in the Iscehisar district of Afyonkarahisar in the Aegean Region was elected as a numerical application. The bridge was subjected to its own weight and moving load as a static analysis. For dynamic analysis, the effect of 10 different fault movements with historical character obtained from The Pacific Earthquake Engineering Research Center (PEER) on the bridge was investigated. The areas of principal stress and deformation resulting from the applied analyses were determined. Contour diagrams, tables, and charts were given in a comparative manner based on the results of the analysis applied to the bridge. At the end of the analysis, it was observed that the displacements decreased as the arch thickness increased under its own weight in the bridge. In addition, under the influence of live loads and earthquakes, it was observed that the displacements decrease as the arch thickness increases. A seismic reliability assessment was made using the performance criteria provided in this study. If the security level is below what it should be, reinforcement applications can be designed. Accordingly, future maintenance and monitoring planning can be made.

Measuring intra-individual physical activity variability using consumer-grade activity devices.

Many existing sedentary behavior and physical activity studies focus on primary outcomes that assess change by comparing participants' activity from baseline to post-intervention. With the widespread availability of consumer-grade devices that track activity daily, researchers do not need to rely on those endpoint measurements alone. Using activity trackers, researchers can collect remote data about the process of behavior change and future maintenance of the change by measuring participants' intra-individual physical activity variability. Measuring intra-individual physical activity variability can enable researchers to create tailored and dynamic interventions that account for different physical activity behavior change trajectories, and by that, improve participants' program adherence, enhance intervention design and management, and advance interventions measurements' reliability. We propose an application of intra-individual physical activity variability as a measurement and provide three use cases within interventions. Intra-individual physical activity variability can be used: prior to the intervention period, where relationships between participants' intra-individual physical activity variability and individual characteristics can be used to predict adherence and subsequently tailor interventions; during the intervention period, to assess progress and subsequently boost interventions; and after the intervention, to obtain a reliable representation of the change in primary outcome.

Concept for a digital twin of railway bridges on the example of the new Filstal bridges

AbstractThe preservation of infrastructure is becoming increasingly important. The current reactive maintenance management only initiates maintenance measures after damage has occurred. Short‐term measures can lead to unforeseen restrictions in infrastructure availability and thus cause high social and economic damage.High‐quality measurement technology, automated data analysis, structured data management and collaborative work are just a few technological developments that form the cornerstones for a future predictive maintenance strategy. The digital twin, a digital representation of the real object, combines these developments and is a promising method for a sustainable preservation of infrastructure.Using the example of the Filstal bridges, a concept for a digital bridge twin is introduced. The digital twin combines measurement data, bridge information, inspection results as well as structural safety verifications and aggregates them to continuously display the current bridge condition and thus supports the maintenance of bridges. For intuitive use, all information is located and presented in a way that is consumable by the user.