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To enhance the load capacity and dynamic characteristics of gas foil conical bearings (GFCBs), two kinds of microgrooves (sector and Fibonacci-like shape) are arranged on the top foil surface.

The Reynolds equation considering gas rarefaction effect is solved by the finite difference method, in which the 2D plate element stiffness model is used for the grooved top foil. The influence of groove on the static characteristics is studied, and the dynamic characteristics of novel bearing are obtained by the perturbation method.

The results show that the gas rarefaction effect on the load capacities is negligible, and the novel GFCB with microgrooved top foil has higher load capacities. Moreover, the deeper groove is conductive to the dynamic stability improvement. The positive Fibonacci-like groove seems to be the most suitable shape, which can largely increase the axial load capacity with little additional torque cost. And the improvement of dynamic characteristics for the Fibonacci-like grooved GFCB is also more favorable.

As the low cost of groove processing, it is an effective way to improve GFCB’s performance and even can be used to upgrade the bearings in service.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0148/

The purpose of this paper is to research the hardened properties of non-dispersible concrete in seawater environment, especially in seawater environment.

The main approach is according to the experiment.

The findings of this paper are: first, because of the washing effect of water, the strength of underwater non-dispersible concrete is lower than that of terrestrial concrete. Second, the strength of non-dispersible underwater concrete with silica fume increases remarkably at different ages. Third, underwater non-dispersible concrete does not produce new products when it is formed and cured in seawater.

In this paper, underwater non-dispersible concrete is formed and maintained on land, freshwater and seawater by underwater pouring method. The working performance, mechanical properties and durability of underwater non-dispersible concrete mixtures after hardening are tested.

The purpose of this paper is to focus on the durability of underwater non-dispersible concrete in seawater environment.

In this paper, ten groups of underwater non-dispersible concrete mixtures were designed, and the anti-dispersibility and fluidity of the mixtures were tested.

The durability test analysis shows that different pouring methods have different effects on the durability of concrete. The durability of concrete poured on land is better than that poured in water. Different mineral admixtures have different effects on the durability of concrete: the frost resistance of the underwater non-dispersible concrete specimens with silica fume is the best; the impermeability and chloride ion permeability of the non-dispersible underwater concrete specimens with waterproofing agent are the best; and the alternation of wetting and drying has adverse effects on the durability indexes of the non-dispersible underwater concrete.

The durability of underwater non-dispersible concrete is tested and the results can be used for reference in engineering practice.

The purpose of this paper is to develop multilayer clothing assemblies consisting of fibrous battings and reflective nano-fibrous thin layers for cold protective clothing for improved thermal insulation.

Thermal insulation values of totally 20 assemblies made of varying layers of a thick polyester batting and four different types of thin interlayers were measured using a guarded hot-plate to investigate the effect of the properties of thin interlayers and construction of multilayer assemblies on thermal insulation. Cold protective jackets filled with polyester battings sandwiched with or without interlayers were also made and tested on the sweating fabric manikin-Walter.

Results show that the Rosseland mean extinction coefficients of the thin interlayer and the associated radiative thermal conductivity of the interlayers have significant influence on thermal insulation of the assembly when more than one reflective nano-fibrous interlayers are sandwiched in the assembly. The cold protective jacket filled with multilayer polyester battings and reflective nano-fibrous interlayers have better thermal insulation and moisture permeability index (i_m) than those filled with the same multilayer polyester battings, but with non-reflective nonwoven interlayers or without interlayers.

This paper clearly demonstrates the advantages of reflective nano-fibrous thin material for interlayers in the cold projective jacket.

Solder joint inspection plays a critical role in various industries, with a focus on integrated chip (IC) solder joints and metal surface welds. However, the detection of tubular solder joints has received relatively less attention. This paper aims to address the challenges of detecting small targets and complex environments by proposing a robust visual detection method for pipeline solder joints. The method is characterized by its simplicity, cost-effectiveness and ease of implementation.

A robust visual detection method based on the characteristics of pipeline solder joints is proposed. With the improved hue, saturation and value (HSV) color space, the method uses a multi-level template matching approach to first segment the pipeline from the background, and then match the endpoint of the pipeline to accurately locate the solder joint. The proposed method leverages the distinctive characteristics of pipeline solder joints and employs an enhanced HSV color space. A multi-level template matching approach is utilized to segment the pipeline from the background and accurately locate the solder joint by matching the pipeline endpoint.

The experimental results demonstrate the effectiveness of the proposed solder joint detection method in practical detection tasks. The average precision of pipeline weld joint localization exceeds 95%, while the average recall is greater than 90%. These findings highlight the applicability of the method to pipeline solder joint detection tasks, specifically in the context of production lines for refrigeration equipment.

The precision of the method is influenced by the placement angle and lighting conditions of the test specimen, which may pose challenges and impact the algorithm's performance. Potential avenues for improvement include exploring deep learning methods, incorporating additional features and contextual information for localization, and utilizing advanced image enhancement techniques to improve image quality.

The proposed pipeline solder joint detection method offers a novel and practical approach. The simplicity, cost-effectiveness and ease of implementation make it an attractive choice for detecting pipeline solder joints in different industrial applications.

This paper aims to propose a novel method to predict and alleviate feature fatigue. Many products now are loaded with an extensive number of features. Adding more features to one product generally makes the product more attractive on the one hand but, on the other hand, may result in increasing difficulty to use the product. This phenomenon is called “feature fatigue”, which will lead to dissatisfaction and negative word-of-mouth (WOM). Feature fatigue will damage the brand’s long-term profit, and ultimately decrease the manufacturer’s customer equity. Thus, a problem of balancing the benefit of increasing “attractiveness” with the cost of decreasing “usability” exists.

A novel method based on the Bass model is proposed to predict and alleviate feature fatigue. Product capability, usability and WOM effects are integrated into the Bass model to predict the impacts of adding features on customer equity in product development, thus helping designers alleviate feature fatigue. A case study of mobile phone development based on survey data is presented to illustrate and validate the proposed method.

The results of the case study demonstrate that adding more features indeed increases initial sales; however, adding too many features ultimately decreases customer equity due to usability problems. There is an optimal feature combination a product should include to balance product capability with usability. The proposed method makes a trade-off between initial sales and long-term profits to maximize customer equity.

The proposed method can help designers predict the impacts of adding features on customer equity in the early stages of product development. It can provide decision supports for designers to decide what features should be added to maximize customer equity, thus alleviating feature fatigue.

Drawing on the theory of memory-dominant logic, this study aims to examine how the substantive staging of the servicescape, experience co-creation, experiential satisfaction and experience intensification affect experience memorability and hedonic well-being in the case of unmanned smart hotels.

An online survey was used, with the target respondents being hotel guests people aged 18 years and older who had been recent guests of the FlyZoo Hotel in Hangzhou, China. Data were collected online from 429 guests who had stayed in the hotel between April and June 2023. Data analysis was undertaken using structural equation modelling.

The results suggest that all the proposed four constructs are positive drivers of a memorable unmanned smart hotel experience. The relationship between the memorability of the hotel experience and hedonic well-being was found to be significant and positive.

Unmanned smart hotels should ensure that all smart technologies function effectively and dependably and offer highly personalised services to guests, allowing them to co-create their experiences. This will lead to the guest receiving a satisfying and memorable experience. To enable experience co-creation using smart technologies, unmanned smart hotels could provide short instructional videos for guests, as well as work closely with manufacturers and suppliers to ensure that smart technology systems are regularly updated.

This study investigates the antecedents and outcomes of a novel phenomenon and extends the concept of memorable tourism experiences to the context of unmanned smart hotels.

This study aims to investigate the impact of indium (In) content on the thermal properties, microstructure and mechanical properties of Sn-3Ag-3Sb-xIn (x = 0, 1, 2, 3, 4, 5 Wt.%) solders to enhance the performance of tin-based solder under demanding conditions and to meet the urgent need for high-reliability microelectronic interconnection materials in emerging sectors such as automotive intelligent technology, 5G communication technology and high-performance computing.

In this study, Sn-3Ag-3Sb-xIn solder alloys were prepared. The thermal properties of the solder alloys were characterised by differential scanning calorimetry. Subsequently, optical microscopy, scanning electron microscopy, X-ray diffraction and an electron probe X-ray microanalyser were used to analyse the influence of the In content on the microstructure of the solder. The mechanical properties of solder alloys were determined through tensile testing.

As the In content increased, the melting temperature of the Sn-3Ag-3Sb-xIn solder decreased, accompanied by less nucleation undercooling and an expanded melting range. The incorporation of In led to an enhancement in the yield and tensile strengths of the Sn-3Ag-3Sb-xIn solder alloys, but with a concomitant decrease in plasticity. In comparison to commercial Sn-3.0Ag-0.5Cu solder alloys, the yield strength and tensile strength of the Sn-3Ag-3Sb-3In alloy increased by 8.64 and 21.69 MPa, respectively, while the elongation decreased by 11.48%.

Sn-3Ag-3Sb-3In solder alloy was the most appropriate and expected comprehensive properties. The enhancements will provide substantial assistance and precise data references for the interconnection requirements in high-strength interconnection fields, such as automotive intelligent technology, 5G communication technology and high-performance computing.

Due to the complexity and diversity of megaprojects, the architectural programming process often involves multiple stakeholders, making decision-making difficult and susceptible to subjective factors. This study aims to propose an architectural programming methodology system (APMS) for megaprojects based on group decision-making model to enhance the accuracy and transparency of decision-making, and to facilitate participation and integration among stakeholders. This method allows multiple interest groups to participate in decision-making, gathers various perspectives and opinions, thereby improving the quality and efficiency of architectural programming and promoting the smooth implementation of projects.

This study first clarifies the decision-making subjects, decision objects, and decision methods of APMS based on group decision-making theory and value-based architectural programming methods. Furthermore, the entropy weight method and fuzzy TOPSIS method are employed as calculation methods to comprehensively evaluate decision alternatives and derive optimal decision conclusions. The workflow of APMS consists of four stages: preparation, information, decision, and evaluation, ensuring the scientific and systematic of the decision-making process.

This study conducted field research and empirical analysis on a practical megaproject of a comprehensive transport hub to verify the effectiveness of APMS. The results show that, in terms of both short-distance and long-distance transportation modes, the decision-making results of APMS are largely consistent with the preliminary programming outcomes of the project. However, regarding transfer modes, the APMS decision-making results revealed certain discrepancies between the project's current status and the preliminary programming.

APMS addresses the shortcomings in decision accuracy and stakeholder participation and integration in the current field of architectural programming. It not only enhances stakeholder participation and interaction but also considers various opinions and interests comprehensively. Additionally, APMS has significant potential in optimizing project performance, accelerating project processes, and reducing resource waste.

The purpose of this paper is to study the profit optimization of manufacturers who provide personalized products to customers, thus avoiding additional operational costs and response times in the production process of personalized product design.

First, the authors present an integrated model for optimizing profit where the design and production of personalized products are both considered. The authors propose the concept of personalization level and four cases of personalization level are considered including top, high, medium and low levels. Polynomial-time optimal rules are provided for each level by analyzing 17 subcases where all possible personalized products are considered. Then, the authors compare the obtained profit of personalized products with the optimal profit of standardized products.

At low and high levels of personalization, personalized manufacturing is more profitable for specific products with specific characteristics. At the top and middle level of individuation, assuming that the product has certain characteristics, whether the best choice to produce personalized products depends on the level of individuation chosen by customers.

An important decision issue for manufacturers is whether to produce personalized or standardized products. In this study, the authors consider this decision problem and analyze the operational functions of personalized products. The authors hope to provide theoretical support in the operational management of manufacturers offering personalized products.