Smart Forecasting and Corrosion Risk Assessment of Urban Steel Pipeline Networks: A Case Study of Guangzhou (2002–2022)

As a conventional NDT method, eddy Current testing (ET) has been greatly developed both in instrumentation and technique in recent years. Remote Field Eddy Current Testing (RFET) is a representation of this advancement. The principle of RFET and the composition of the testing system are detailedly discussed in this paper. And then, its application in the ferromagnetic heat exchanger tubes is described simply.

Detection of hidden defects of aircraft long truss structures (aluminum alloy) is a challenging problem. The shape of the aircraft truss structure is complex, and the crack defects are buried in a large depth. Without the restriction of skin effect, remote field eddy current (RFEC) has great advantages in detecting buried depth defects. In this paper, in order to detect the hidden defects of the aluminum alloy aircraft long truss structure, the remote field eddy current probe is improved from two aspects of magnetic field enhancement and near-field signal suppression using the finite element method. The results show that indirect coupling energy is greatly enhanced when the connected magnetic circuit is added to the excitation coil. By adding a composite shielding structure outside the excitation coil and the detection coil, respectively, the direct coupling energy is effectively restrained. As a result, the size of the probe is reduced. By optimizing the coil spacing and probe placement position, the detection sensitivity of the probe is improved. The simulation is verified by experiments, and the experimental results are consistent with the simulation conclusions.

Transportation agencies utilize key performance indicators (KPIs) to measure the performance of their traffic networks and business processes. To make effective decisions based on these KPIs, there is a need to align the KPIs at the strategic, tactical, and operational decision levels and to set targets for these KPIs. However, there has been no known effort to develop methods to ensure this alignment producing a correlative model to explore the relationships to support the derivation of the KPI targets. Such development will lead to more realistic target setting and effective decisions based on these targets, ensuring that agency goals are met subject to the available resources. This paper presents a methodology in which the KPIs are represented in a tree-like structure that can be used to depict the association between metrics at the strategic, tactical, and operational levels. Utilizing a combination of business intelligence and machine learning tools, this paper demonstrates that it is possible not only to identify such relationships but also to quantify them. The proposed methodology compares the effectiveness and accuracy of multiple machine learning models including ordinary least squares regression (OLS), least absolute shrinkage and selection operator (LASSO), and ridge regression, for the identification and quantification of interlevel relationships. The output of the model allows the identification of which metrics have more influence on the upper-level KPI targets. The analysis can be performed at the system, facility, and segment levels, providing important insights on what investments are needed to improve system performance.

Purpose: The purpose of this publication is to present the applications of usage of business analytics in maintenance resources allocation. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: The integration of business analytics with condition monitoring technologies heralds a transformative shift in maintenance resource allocation. Through the utilization of real-time data from sensors and monitoring devices, organizations can craft dynamic and adaptive maintenance strategies. These strategies, grounded in the current equipment condition, strike a nuanced balance between preventive and corrective actions. Business analytics enriches decision-making by factoring in critical elements such as equipment importance, operational impact, resource availability, and budget constraints. This integration instigates a paradigm shift, fostering proactive, adaptive, and efficient resource allocation, resulting in heightened asset reliability, diminished downtime, and amplified operational performance. The evolving synergy between business analytics and maintenance practices is becoming integral to the future of asset management and industrial operations. The diverse applications of business analytics in maintenance, as outlined in Table 1, underscore its versatility, encompassing predictive maintenance, condition monitoring, asset performance management, work order prioritization, resource optimization, cost-benefit analysis, inventory management, and performance metrics monitoring. Concurrently, the adoption of advanced software solutions in Industry 4.0 conditions, exemplified by IBM Maximo Asset Management, SAP Intelligent Asset Management, and Fiix CMMS, reflects a commitment to efficiency and innovation in maintenance resource allocation. Despite the substantial advantages, addressing challenges outlined in Table 4, including data quality, integration complexities, implementation costs, and skill development, is crucial. These challenges underscore the necessity for a strategic and holistic implementation approach that considers technology, personnel training, and organizational readiness. In essence, the evolution of maintenance resource allocation through business analytics signifies a data-driven revolution poised to optimize current operations and position organizations for sustained success amid rapid technological advancements and the transformations of Industry 4.0. Originality/value: Detailed analysis of business analytics in the case of maintenance resource allocation. Keywords: business analytics, Industry 4.0, digitalization, artificial intelligence, real-time monitoring; maintenance resource allocation. Category of the paper: literature review.

In today’s competitive industrial landscape, effective performance measurement is crucial for achieving operational success. Key Performance Indicators (KPIs) are widely used to track progress, but their implementation often lacks a comprehensive framework that considers both financial outcomes and managerial insights. A quali-quantitative analysis model is introduced to optimize the implementation of KPIs in industrial settings, demonstrated through a case study of a Cambodian charcoal factory. By integrating Cost–Benefit Analysis (CBA) and Fuzzy Analytic Hierarchy Process (FAHP), the model combines both quantitative financial analysis and qualitative managerial evaluations to assess and rank a selected set of KPIs. This dual approach ensures a more comprehensive understanding of KPI impacts, enabling informed decision-making. The results highlight the critical need for balancing measurable financial benefits with qualitative insights, particularly in industries within developing nations that are forced to compromise in constrained environments, and where both economic outcomes and strategic considerations are essential for sustainable growth. Furthermore, the proposed model has universal applicability across different industrial contexts, providing a flexible and adaptable framework for KPI selection beyond the specific case study analyzed.

The urban rail transit network provides the possibility for people to shift from car to public transit for travel. This paper clarified the relationships among public transit, accessibility, and equity and studied the impact of rail transit on public transit accessibility that incorporates the measure of travel time and transit fare and the impacts’ spatial equity. The results show that rail transit contributes to the similar distribution between high rate of changes of time-based accessibility communities and fare-based accessibility communities, which are located nearby the rail transit lines. The degree of inequity in travel time is higher than the degree in transit fare in two scenarios. Due to the well-connected bus transit in the city center, absolute changes in travel time are slight, while relative changes are high. The rail transit has promoted the improvement of public transit equity in some areas. The difference between the time-based accessibility of Conghua District, northern and southern Baiyun District, Huadu District, Nansha District and southern Panyu District, and other communities is getting smaller, which is conducive to the improvement of spatial equity. The results provide theoretical support for the development of an integrated multimodal public transit system.

Analysis and Comparisons of Macroscopic Fundamental Diagram on Urban Road Networks: A Case Study of Guangzhou in China

Anthropogenic activities are increasingly impacting the quality of urban surface water, particularly in regions undergoing intensive urbanization, such as Guangzhou of South China with a large urban stream network. To examine such impacts, we conducted field sampling on December 24, 2010, May 24, 2011, and August 28, 2011, representative of the low-, normal-, and high-flow periods, respectively. The first sampling was timed immediately after the closing of the 16th Asian Games (November 12-27, 2010) and the 10th Asian Para Games (December 12-19, 2010) held in Guangzhou. Assessments based on a pollution index method showed that the urban streams under investigation were extremely polluted, with direct discharge of untreated domestic sewage identified as the main pollution contributor. In addition, stream water quality around urban villages with high population densities was worse than that within business districts away from the urban villages. Pollution control measures implemented in preparation for the Asian Games were effective for urban streams within the business districts, but less effective for those adjacent to the urban villages. However, short-term efforts may not be able to achieve sustainable urban water quality improvements. In the case of Guangzhou, minimizing or even eliminating direct point-source inputs to the urban streams is perhaps the best option.

Compared with penetration testing technology and eddy current testing technology, Alternating current field measurement testing technology can detect the surface opening crack defects of metal specimens without polishing the surface coating. The detection signal can locate the crack defects and calculate the crack length and depth information, Which significantly improves the detection efficiency, so this technology has received more and more attention and research. After years of development, Alternating current field measurement technology has become increasingly powerful. Based on the literature in recent years, this article discusses the detection theory model, sensor design, detection signal processing methods, development trends, etc., pointing out further research issues of this technology, and better promoting the development of AC electromagnetic detection technology.

Quality reliability analysis of flash welding joint of cold-rolled 50JW800 silicon steel strip

Background Orthogeriatric services have been shown to improve quality of care for older patients post hip fracture and have an impact on length of stay (LOS), both acutely and in the rehab setting(1) but other key performance indicators (KPIs) have not been examined in detail. Methods Data was prospectively collected on all hip fracture patients seen by the Orthogeriatric service from Aug 2018-Feb 2019 and was retrospectively compared with patients admitted with hip fractures from Aug 2017-Feb 2018. We examined KPIs including LOS on the orthopaedic ward, rehab admissions, rehab LOS, new nursing home (NH) admissions. We compared the proportions discharged directly home instead of to convalescence, and conducted a preliminary cost benefit analysis. Results Similar numbers of patients were seen in each time period (n=146 v n=139). Mean reduction in LOS on the orthopedic ward was 3.5 days (15.5 days vs 19 days). The proportion of patients admitted to rehabilitation increased from 8.8% to 17.5% (p = 0.02). Patients got to rehabilitation faster and for those patients who availed of rehabilitation they had significantly shorter total length of stays (51.1 days vs 71.6 days, p=0.029). Fewer patients went to convalescence. Although not statistically significant there was a trend towards an increased proportion of patients discharged directly home (32.7% to 43.6%) and less new nursing home admissions (6.8% vs 8.4%). A cost benefit analysis incorporating shortened acute and rehab LOS and a reduction in spending on convalescence resulted in a projected saving of €480,390 over a six month period. Conclusion Introduction of OrthoGeriatric services has improved care for older people with hip fractures and has resulted in positive improvements to KPIs, resulting in meaningful improvements in clinical outcomes for patients in a cost effective manner. Monies saved should be redirected into further developing orthogeriatric services.

The eddy current testing technology, principle and applications were presented, and while also the eddy current probe production of the detection system were highlighted, and ultimately a set of eddy current testing system is given . Enterprise application showed that it can meet the measuring ability and it smash up the foreign monopoly market to similar equipment in China.

A simple method for sizing and estimating the performance of PV systems in trolleybus grids

Automated vehicles (AVs) will appear on the road soon and will influence the properties of road traffic networks such as capacity and safety. While the impact of AV on traffic operations has been discussed extensively, most existing literature in this direction focuses on microscopic and mesoscopic levels. This study examines the effect of AVs on traffic flow operations and crash risks at a network scale. In addition, this study discusses the implications for designing and operating safe, low‐speed urban road networks. Simulation experiments were carried out in a grid road network with AVs and human‐driven vehicles operating in mixed flow conditions. To assess traffic performance, the macroscopic fundamental diagram (MFD) relationships were estimated, specifically focusing on speed‐density correlations. From this analysis, it was possible to extract key traffic performance indices such as capacity and critical speed. Using time‐to‐collision surrogate safety measures, macroscopic safety diagrams were generated which associate the level of congestion with the potential crash conflicts among vehicles at an aggregated spatial scale. Utilizing this knowledge, a novel multiobjective optimization based on the NSGA‐II algorithm was applied to identify the optimal trade‐off between efficiency and safety. The presence of AVs was found to have a positive impact on the capacity, critical density, and average speed on a system level, even in low‐speed scenarios. Moreover, AVs can result in increased critical density in the network, which suggests that the road system can serve more vehicles at its capacity, thus improving efficiency, while decreasing the number of conflicts. These findings are useful for both traffic planners and operators.

To solve the problem of wall thickness reduction and defects of oil and gas pipeline caused by corrosion or erosion, a remote field eddy current (RFEC) testing method with coaxial double coil structure is proposed to detect corrosion residual wall thickness of oil and gas gathering pipelines. Based on electromagnetic field theories, RFEC technology is theoretically analyzed. The theoretical model of RFEC detection for coaxial double coil structure is established. The relationship between the voltage phase of detection signal and the wall thickness of pipeline is derived, and an evaluation method of the residual wall thickness of the pipeline based on the phase trough time of the RFEC detection signal is proposed. The parameters of RFEC probe are optimized by Finite Element Method, and the detection system is designed on the basis of it. The practicability and the correctness of the theoretical model of the detection system are verified by experiments. It can be used to detect the residual wall thickness of pipelines in real time under different media conditions.