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The purpose of this paper is to introduce a new method called simultaneous elimination and back-substitution method (SEBSM) to solve a system of linear equations as a new finite element method (FEM) solver.

In this paper, a new technique assembling the global stiffness matrix will be proposed and meanwhile the direct method SEBSM will be applied to solve the equations formed in FEM.

The SEBSM solver for FEM with the present assembling technique has distinct advantages in both computational time and memory space occupation over the conventional methods, such as the Gauss elimination and LU decomposition methods.

The developed solver requires less memory space no matter the coefficient matrix is a typical sparse matrix or not, and it is applicable to both symmetric and unsymmetrical linear systems of equations. The processes of assembling matrix and dealing with constraints are straightforward, so it is convenient for coding. Compared to the previous solvers, the proposed solver has favorable universality and good performances.

In this paper, a light-weight, low-power atmospheric multi-parameter sensor (AMPS), which could be mounted on small flying platforms such as a tethered balloon, a quad-rotor unmanned aerial vehicle (UAV), a UAV helicopter, etc., is implemented and integrated to sample vertical distribution of aerosols with integrated parameters of aerosol particle concentration, temperature, relative humidity and atmospheric pressure.

The AMPS integrates three kinds of probes in an embedded system. A synchronous method based on GPS is proposed to drive the laser aerosol particle sensor, the temperature and humidity probe and the pressure probe to sample four channels approximately simultaneously. Different kinds of housing are designed to accommodate various flying platforms, and the weight is controlled to adapt the payload of each platform.

A series of validation tests show that while the AMPS achieves high precision, its power consumption is less than 1.3 W, which is essential for light flying platforms. The AMPS was mounted on different flying platforms and the difference was evaluated. For three times every five days, vertical profiles of PM2.5 and PM10 concentrations were observed by the AMPS mounted on a quad-rotor UAV, which revealed the significant correlation between the aerosol particle concentration and atmospheric parameters.

A new light-weight and low-power AMPS for small flying platforms is designed and tested, which provides an effective way to explore the properties of aerosol vertical distribution, and to monitor pollutants flexibly.

By analyzing the shortcomings of existing insulator robots, a novel ultra high voltage (UHV) insulator climbing robot, which could transfer between adjacent insulator strings, is proposed for operation on 800KV multiple-string insulators. An extended inchworm-like configuration was chosen and a stable gripping claw suitable for the insulator string was designed to enable the robot to multiple-string insulators. Then a set of nonheuristic structural parameters that can influence energy consumption was chosen to formulate a nonlinear optimization problem based on the configuration, which improved the energy efficiency of the robot during progressing along a string of insulator.

The purpose of this paper is to design an insulator climbing robot for operation on UHV multiple-string insulators, which could transfer between adjacent insulator strings and progressed along a string of insulator with high energy efficiency.

A physical prototype was constructed that can operate at the speed of six pieces per minute (approximately 1.44 meters per minute) on a single string and complete transference between adjacent strings in 45 s. The energy consumption of joints during progressed along a string of insulator had been reduced by 38.8% with the optimized parameters, demonstrating the consistency between the experimental and simulation results.

An insulator climbing robot for operation on UHV multiple-string insulators has been developed with energy consumption optimization design. The robot can transfer between adjacent insulator strings and progressed along a string of insulator with high energy efficiency. The CLIBOT could be expanded to detect or clean the insulators with similar specification.

The developed plasto-elastohydrodynamic lubrication (PEHL) model is used to demonstrate the permanent change of macro morphology by critical high local stress at micro asperities in contact, which may further affect the fluid-film characteristics.

Geometric morphology is integrated into the PEHL model to elucidate the fluid-film properties governed by both macro- and micromorphologies.

Results show the model, accounting for combination of elastic and plastic deformations, realistically reveals fluid film distribution affected by the significant pressure highly concentrated within surface micro roughness interaction. The designed macroscopic textured surface mitigates the fluid film rupture phenomenon and prevents accumulated wear degradation from plastic deformation.

The PEHL model takes into account both elastic and plastic deformations and realistically reveals the fluid film distribution affected by large pressures that are highly concentrated in surface micro-roughness interactions. The macro-textured surfaces are designed to mitigate fluid film rupture phenomena and prevent cumulative wear caused by plastic deformation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0170/

This paper aims to address the challenges of the capacitor tower maintenance robot during bolt tightening in high-voltage substations, including difficulties in bolt positioning due to tilted angles and anti-bird cover occlusion and issues with fast and accurate docking of bolts while the base is moving.

This paper proposes a visual servoing method for the capacitor tower maintenance robot, including bolt pose estimation and visual servoing control. Bolt pose estimation includes four components: constructing a keypoint detection network to identify the approximate position, precise positioning, rapid prediction and calculation of bolt pose. In visual servoing, an improved position-based visual servoing (PBVS) is proposed, which eliminate steady-state error and enhance response speed during dynamic tracking by incorporating integral and differential components.

The bolt detection method exhibits high robustness against varying lighting conditions, partial occlusions, shooting distances and angles. The maximum positioning error at a distance of 250 mm is 2.8 mm. The convergence speed of the improved PBVS is 10% higher than that of the traditional PBVS when the base and target remain relatively stationary. When the base moves at a constant speed, the improved method eliminates steady-state error in dynamic tracking. When the base moves rapidly and intermittently, the maximum error of the improved method in the tracking process is 30% smaller than that of traditional PBVS.

This method enables real-time detection and positioning of bolts in an unstructured environment with tilt angles, variable lighting conditions and occlusion by anti-bird covers. An improved PBVS is proposed to enhance its capability in tracking dynamic targets.

Cost overrun is inherent to project chaos, which is one of the key drivers of project failure. The purpose of this paper is to explore the critical elements of complexity-risk interdependency for cost-chaos in the construction management domain by utilizing a multi-criteria decision model.

A total of 12 complexity and 60 risk attributes are initially identified from the literature and using expert’s judgements. For the development of a structured hierarchy of key complexity and risk drivers, a real-time Delphi process is adopted for recording and evaluating the responses from experts. Afterwards, a pair-wise comparison using analytical network processing is performed to measure complexity-risk interdependencies against cost alternatives.

The findings of the integrated priority decision index (IPDI) suggest that uncertainties related to contingency and escalation costs are the main sources of cost overrun in project drift, along with the key elements such as “the use of innovative technology,” “multiple contracts,” “low advance payment,” “change in design,” “unclear specifications” and “the lack of experience” appear to be more significant to chaos in complexity-risk interdependency network.

This study did not address the uncertainty and vulnerability exit in the judgment process, therefore, this framework can be extended using fuzzy logic to better evaluate the significance of cost-chaos drivers.

These results may assist the management of cost overrun to avoid chaos in a project. The proposed model can be applied within project risk management practices to make better-informed technical decisions in the early phases of the project life cycle where uncertainty is high.

This research addresses the importance of cost overruns as a source of project chaos in dynamic systems where projects reach the edge of chaos and progress stops. A new IPDI index contributes toward evaluating the severity of complexity and risk and their interdependencies which create cost-chaos in infrastructure transport projects.

Conversion of the correlated random variables into independent variables, especially into independent standard normal variables, is the common technology for estimating the statistical moments of response and evaluating reliability of random system, in which calculating the equivalent correlation coefficient is an important component. The purpose of this paper is to investigate an accurate, efficient and easy to implement estimation method for the equivalent correlation coefficient of various incomplete probability systems.

First, an approach based on the Mehler’s formula for evaluating the equivalent correlation coefficient is introduced, then, by combining with polynomial normal transformations, this approach is improved to be valid for various incomplete probability systems, which is named as the direct method. Next, with the convenient linear reference variables for eight frequently used random variables and the approximation of the Rosenblatt transformation introduced, a further improved implementation without iteration process is developed, which is named as the simplified method. Finally, several examples are investigated to verify the characteristics of the proposed methods.

The results of the examples in this paper show that both the proposed two methods are of high accuracy, by comparison, the proposed simplified method is more effective and convenient.

Based on the Mehler’s formula, two practical implementations for evaluating the equivalent correlation coefficient are proposed, which are accurate, efficient, easy to implement and valid for various incomplete probability systems.

Direct additive manufacturing of ceramics (DAMC) is a highly promising ceramics preparation technology because of its simple process and rapid response capability, but the cracking issue prevents its industrial application. The purpose of this paper is to propose aluminum titanate (Al₂TiO₅) with low coefficient of thermal expansion (CTE) to suppress cracks during the DAMC.

Al₂O₃/Al₂TiO₅ (A/AT) composite ceramic samples with different compositions were in-situ synthesized from Al₂O₃/TiO₂ (A/T) powder in a directed laser deposition (DLD) process. The relationship between the content of TiO₂ and cracking characteristics of fabricated sample was discussed. Phase composition, microstructure and properties of the fabricated samples were also investigated.

The results of this paper show that the doping of TiO₂ can obtain Al₂TiO₅ synthesized in situ by reaction with Al₂O₃ and effectively suppress cracks during DAMC. When the content of TiO₂ reaches 30 wt.per cent, cracks hardly occur even under conditions of slow deposition. Crack-free structures such as vane, cone and pyramid were successfully prepared, with a maximum cross-sectional dimension of 30 mm and maximum length of 150 mm. A continuous matrix phase formed of the low CTE of Al₂TiO₅ is the major cause of crack suppression. The dispersed distribution of a-Al₂O₃ columnar dendrites has the effect of increasing the strength of the matrix. Under current process conditions, the prepared sample with 10 wt.per cent TiO₂ has micro-hardness of 21.05 GPa and flexural strength of 170 MPa.

This paper provides a new method and inspiration for direct additive manufacturing of large-sized crack-free ceramics, which has the potential to promote practical application of the technology.

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.

This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.

The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.

This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.

These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.

This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.

The coronavirus disease 2019 (COVID-19) pandemic caused significant disruption to the global labor market, resulting in a rapid transition toward remote work, e-commerce and workforce automation. This shift has sparked a considerable amount of public discussion. This study aims to explore the online public's sentiment toward remote work amid the pandemic.

Based on justice theory, this paper examines user-generated content on social media platforms, particularly Twitter, to gain insight into public opinion and discourse surrounding remote work during the COVID-19 pandemic. Employing content analysis techniques such as sentiment analysis, text clustering and evolutionary analysis, this study aims to identify prevalent topics, temporal patterns and instances of sentiment polarization in tweets.

Results show that people with positive opinions focus mainly on personal interests, while others focus on the interests of the company and society; people's subjectivities are higher when they express extremely negative or extremely positive emotions. Distributive justice and interactional justice are distinguishable with a high degree of differentiation in the cluster map.

Previous research has inadequately addressed public apprehensions about remote work during emergencies, particularly from a justice-based perspective. This study seeks to fill this gap by examining how justice theory can shed light on the public's views regarding corporate policy-making during emergencies. The results of this study provide valuable insights and guidance for managing public opinion during such events.