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The paper aims to investigate the effects of slurry erosion on hydro turbine components, focusing on the experimental analysis of SS-304 using sand as the erodent material. The study was conducted on a tester under varying parameters to assess the material’s erosion behavior. In this work, the experimental investigation of SS-304 with sand was done with sand as the erodent material on a tester with various parameters. Further, the materials were made more resistant to wear by a WC-10Co-4Cr coating, done by the high-velocity oxygen fuel method. The mass loss of the specimens with and without coating was calculated. SEM was carried out on the specimens. The specimens with coating showed greater erosion resistance than the base material; however, wear mechanisms such as craters, lip formation, pores, etc. were discovered on the specimens.

The wear tests were carried out on the specimens with parameters of rotating speeds of 1,000, 1,150, 1,300 and 1,450 rpm; time duration 80, 130 and 180 min with sand concentrations of 30% and 50% in water. The base material was coated with WC-10Co-4Cr by the HVOF method of thermal spray.

In the results, it was observed that the wear resistance of the coated specimen increased significantly as compared to the uncoated material. Concentration proved to be the major factor influencing the wear erosion followed by rotational speed and time period. Various surface defects such as ploughing, crater formation, lip formation and micro-cutting were also found.

Slurry concentration was found to be the more dominant factor in increasing the wear of the specimens. The tests proved that the coating proved to be highly wear-resistant as compared to the uncoated base material and increased the wear resistance up to 3 times.

This study aims to research the erosion wear characteristics and sealing performance of V-regulating ball valve in coal chemical process pipelines, which provides a theoretical reference for improving its antiwear and sealing performance.

Taking the V-regulating ball valve as the research object, based on the computational fluid dynamics and the theory of erosion wear, the authors studied its erosion characteristics under different medium parameters and analyzed the sealing performance under the heat-fluid–solid coupling working condition.

The erosion wear mechanism of the valve sealing surface is the simultaneous action of cutting and deformation. When the medium flow velocity, particle mass flow rate and particle size increase, the maximum erosion rate and average erosion rate in the V-regulating valve increase. The inner diameter Mises contact stress of the sealing surface is symmetrically distributed in a “wing shape,” and the contact stress of the outer diameter is distributed in a “butterfly shape.” Due to the superposition of thermal stress and pressure stress in the contact transition zone to produce a significant stress concentration.

The findings will provide a theoretical basis for improving the erosion resistance and sealing performance of V-regulating ball valve in coal chemical industry.

V-type regulating ball valve is widely favored by coal chemical enterprises and petrochemical enterprises because of its wide adjustment ratio and good erosion resistance.

The V-regulating ball valve wear mechanism for cutting and deformation simultaneously, and its wear rate is positively correlated with the medium flow rate, particle mass flow rate and particle size. After the valve is opened, there is a significant stress concentration occurs in the contact transition zone due to the superposition of thermal stress and compressive stress. The findings will provide a theoretical basis for improving the erosion resistance and sealing performance of V-regulating ball valve in coal chemical industry.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0205/

How do participants navigate the sexual politics of multiracial dating and how does this relate to belonging? The results of this study illustrate that the 21 participants interviewed faced internal and external struggles and triumphs due to their mixed-race identity. For participants, trying to situate themselves into just one racial identity when they straddled both became a point of contention with romantic partners and themselves. Moreover, participants struggled with feeling like they were “enough” and if they belonged. Furthermore, mixed-race women and non-binary people were forced to navigate the racial expectations of others as well as the fetishization of their mixed-race identity. In turn, this impacted confidence levels, self-esteem, and sense of belonging and authenticity. The findings contribute to research on desirability and critical mixed-race studies by examining how mixed-race women and non-binary people perceive their own desirability.

This study aims to report the development and experimental evaluation of two kinds of PANI@semiconductor based photocathodic anti-corrosion coating, for application on stainless steel substrates.

PANI was in situ chemical polymerized on TiO₂ and BiVO₄ particles, and FT-IR and SEM/EDS were used to understand the characteristics and elemental distribution of the composite particles. Composite coatings, which consisted of epoxy, PANI@TiO₂ or PANI@BiVO₄ and graphene, were prepared on the 304L stainless steel. Photoelectrochemical response measurement, electrochemical tests and immersion tests were used to assess the anti-corrosion performance of the prepared coatings in 45°C 3.5 wt.% NaCl solution. And the corrosion protection mechanism was further explained by combining with surface observation.

The photoelectrochemical response tests revealed the good photocathodic effect of the coatings, and the reversible oxidation-reduction properties of PANI (pseudocapacitive effect) leading to the repeated usage of the coatings. Consequently, the anti-corrosion mechanism of the composite coating is attributed to the physical barrier effect of the coating, the anodic protection effect of PANI and the photocathodic and energy store effect.

These kind coatings could prevent corrosion from day to night for stainless steel, which has great engineering application prospects on stainless steel corrosion protection.

The purpose of this article is to investigate the influence that firm-specific characteristics, such as organisational capabilities, risk management methods and stakeholder relationships, have on political risks (PRs) that are associated with multinational construction projects in Pakistan.

The methodology employed in this investigation involved the acquisition of data through the use of questionnaires administered to experts in the construction industry. The research applied a quantitative method, and the sources of the data are from the Pakistani stakeholders. One hundred questionnaires were used for the data collection during field visits. Based on the data, it has been ensured that the valid questionnaires were utilised, and the data were tested for validity and reliability. The analysis tool utilised was SPSS software. For the questionnaire, a total of 15 firm-specific factors were considered in order to design the survey, which specifically targeted the identified features. The factors identified as risks were investigated using quantitative method to determine firm-specific risks.

It was found that when stakeholders have a better grasp of these dynamics, they are better able to strengthen their resilience and efficacy in managing PRs, which ultimately increases the likelihood that the project will be successful.

International construction projects (ICPs) in emerging countries are substantially impacted by PRs, which can have a considerable impact on their success and sustainability. The study is localised and not generic as it is limited to Pakistan, and the risk factors considered are firm-specific but related to PRs.

By identifying key risk factors, these firms can develop targeted risk management strategies, leading to enhanced decision-making and more efficient resource allocation. Effective strategies include diversification, local partnerships and comprehensive risk assessments tailored to the unique challenges faced by international contracting firms in Pakistan.

ICPs in emerging countries like Pakistan face critical problems, which include the presence of PRs. Although the larger political environment plays a significant part, the manner in which businesses navigate and mitigate PRs is also influenced by firm-specific elements.

The study is novel in terms of the factors looked at, the data, the conceptual framework and the findings of the study. The dynamic political scene, which is characterised by instability, policy changes, corruption and geopolitical conflicts, poses significant dangers to the timeliness of projects, the expenses of such projects and the investments that are made in those projects.

This paper divides the dyadic supply chain into three power structures according to the relative channel power of the supply chain members and consequently examines the optimal supply chain pricing decisions when both suppliers and retailers are concerned with fairness issues.

Three models are constructed, namely the Stackelberg game model with the supplier as the leader, the Nash game model with the balance of power and another Stackelberg game model with the retailer as the leader. The equilibrium solutions are solved, and their results are analyzed.

The retail price of a product increases with an increase in the fairness concerns of the leader in a supply chain in which the supplier or retailer is the leader, while the fairness concerns of the member with less channel power have no effect on the retail price. In a power-balanced supply chain, both suppliers and retailers increase their retail prices as their fairness concerns increase. The relative size of the members’ fairness concerns affects member profits and total supply chain profits.

The main contributions are as follows: First, this paper proposes a new approach to studying supply chain pricing strategy, considering fairness concerns and power structure. Secondly, three game models are constructed. The Nash equilibrium solution is introduced to study the fairness of supply chain participants in pricing decisions and overall supply chain profitability. Finally, the supply chain management theory is expanded by this study on pricing decisions and supply chain performance.

This study aims to develop a polymer cement-based waterproof coating with self-healing capability to efficiently and intelligently solve the building leakage caused by cracking of waterproof materials, along with excellent durability to prolong its service life.

Ion chelators are introduced into the composite system based on ethylene vinyl acetate copolymer emulsion and ordinary Portland cement to prepare self-healing polymer cement-based waterproof coating. Hydration, microstructure, wettability, mechanical properties, durability, self-healing performance and self-healing products of polymer cement-based waterproof coating with ion chelator are investigated systematically. Meanwhile, the chemical composition of self-healing products in the crack was examined.

The results showed that ion chelators could motivate the hydration of C₂S and C₃S, as well as the formation of hydration products (C-S-H gel) of the waterproof coating to improve its compactness. Compared with the control group, the waterproof coating with ion chelator had more excellent water resistance, alkali resistance, thermal and UV aging resistance. When the dosage of ion chelator was 2%, after 28 days of curing, cracks with a width of 0.29 mm in waterproof coating could fully heal and cracks with a width of 0.50 mm could achieve a self-healing efficiency of 72%. Furthermore, the results reveal that the self-healing product in the crack was calcite crystalline CaCO₃.

A novel ion chelator was introduced into the composite coating system to endow it with excellent self-healing ability to prolong its service life. It has huge application potential in the field of building waterproofing.

A vaccination strategy to cover the susceptible population is key to containing the spread of any virus during a healthcare emergency. This study quantifies the susceptibility of a region based on initial infection rates to prioritize optimal vaccine distribution strategies. The authors propose a metric, the regional vulnerability index (RVI), that identifies the degree of susceptibility/vulnerability of a region to virus infections for strategically locating hubs for vaccine storage and distribution.

A two-phase methodology is used to address this problem. Phase 1 uses a modified Susceptible-Infected-Recovered (SIR) model, ModSIR, to estimate the RVI. Phase 2 leverages this index to model a P-Center problem, prioritizing vulnerable regions through a Mixed Integer Quadratically Constrained Programming model, along with three variations that incorporate the RVI.

Results indicate a weighting scheme based on the population-to-RVI ratio fosters fair distribution and equitable coverage of vulnerable regions. Comparisons with the public distribution strategy outlined by the Government of India reveal similar zonal segregations. Additionally, the network generated by our model outperforms the actual distribution network, corroborated by network metrics such as degree centrality, weighted degree centrality and closeness centrality.

This research presents a novel approach to prioritizing vaccine distribution during pandemics by applying epidemiological predictions to an integer-programming framework, optimizing COVID-19 vaccine allocation based on historical infection data. The study highlights the importance of strategic planning in public health response to effectively manage resources in emergencies.

This paper aims to improve the refractive index sensor performance for analytes with large refractive index by adopting the technology of microstructured fiber (MF) and surface plasmon resonance (SPR).

The structure adopts an MF with a hexagonal lattice cladding structure composed of all-circular air holes, and three defect regions are introduced. The liquid analyte that needs to be tested is filled in the defect area. The surface plasmon polarition mode is generated and coupled with the core mode, thus forming a refractive index sensing channel. When the resonance conditions are satisfied, the resonance wavelength will be changed with the refractive index of the liquid analyte. All parameters that may affect the performance of the sensor are numerical simulated, and the structure is optimized through a large number of calculations.

The results demonstrate that the maximum dynamic sensitivity (S_R) can reach to 24,260 nm/RIU, and the average sensitivity (S_R-AV) can reach to 18,046 nm/RIU when the refractive index range is from 1.42 to 1.47. Besides, the sensitivity linearity (R²) is approximately 0.965, and its resolution is 4.1 × 10^–6 RIU. The comparison with some literature results shown that the proposed sensor has certain advantages over the sensors reported in these literatures.

This work proposed an SPR-based refractive index sensor with a simple MF structure. It has a certain reference significance for the design and optimization of SPR-based MF sensors. Moreover, owing to its simple structure, high refractive index sensitivity and linear sensing performance, this sensor will play an important role in the detection of high refractive index liquid analytes.

Firms have already begun integrating artificial intelligence (AI) as a replacement for conventional performance management systems owing to its technological superiority. This transition has sparked a growing interest in determining how employees perceive and respond to performance feedback provided by AI as opposed to human supervisors.

A 2 x 2 between-subject experimental design was employed that was manipulated into four experimental conditions: AI algorithms, AI data, highly experienced human supervisors and low-experience human supervisor conditions. A one-way ANOVA and Welch t-test were used to analyze data.

Our findings revealed that with a predefined fixed formula employed for performance feedback, employees exhibited higher levels of trust in AI algorithms, had greater performance expectations and showed stronger intentions to seek performance feedback from AI algorithms than highly experienced human supervisors. Conversely, when performance feedback was provided by human supervisors, even those with less experience, in a discretionary manner, employees' perceptions were higher compared to similar feedback provided by AI data. Moreover, additional analysis findings indicated that combined AI-human performance feedback led to higher levels of employees' perceptions compared to performance feedback solely by AI or humans.

The findings of our study advocate the incorporation of AI in performance management systems and the implementation of AI-human combined feedback approaches as a potential strategy to alleviate the negative perception of employees, thereby increasing firms' return on AI investment.

Our study represents one of the initial endeavors exploring the integration of AI in performance management systems and AI-human collaboration in providing performance feedback to employees.