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The purpose of this study is to investigate structure parameters that influence the mixing process of droplets-gas in underwater depth-adjustable launcher cooling chamber and help engineers who design the launcher to distinguish the most important factor that impacts mixing performance in the cooling chamber.

Euler–Lagrangian droplet tracking method was used to simulate droplets-gas mixing process in the cooling chamber. The SST k-w model was adopted to simulate turbulence. Droplet breakup was described by KHRT hybrid model using modified contains which are more fit to the supersonic main flow condition.

The results show the counter-rotating vortex pairs which caused by injected liquid accelerate the mixing process. High-pressure supersonic freestream makes the liquid jet break into more small droplets due to the high momentum of the main stream. Axial injection angle has the greatest influence on Sauter mean diameter (SMD). Penetration height, SMD and total pressure loss slightly change in different tangential injection conditions. However, mixedness decreases with reduction of tangential injection angle due to a more limited space for spray developing. Enlarging orifice diameter raises penetration and mixedness greatly, while SMD and total pressure loss increase slightly.

The findings of this study confirm the key structure parameter to improve mixing performance in the cooling chamber. Engineers who design the underwater depth-adjustable launcher can refer the findings in this study to make control of launching power more accurate.

The purpose of this study is to investigate the effect of the injection angle α on the spray structures of an air-blast atomizer and help enhance the understanding of droplet-gas mixing process in such atomizers in the engineering domain.

The phenomena in the air-blast atomizer were numerically modelled using the computational fluid dynamics software Fluent 17.2. The Euler-Lagrange approach was applied to model the droplet tracking and droplet-gas interaction in studied cases. The standard k-ε model was used to simulate the turbulent flow. A model with a modified drag coefficient was used to consider the effects of the bending of the liquid column and its penetration in the primary breakup region. The Kelvin-Helmholtz, Rayleigh-Taylor model was applied to consider the secondary breakup of the droplets.

The basic spatial distribution and spray structures of the droplets corresponding to the angled liquid jet (α = 60°) were similar to those reported in liquid jets injected transversely into a gaseous crossflow studies. The injection angle α did not considerably influence the averaged Sauter to mean diameter (SMD) of the cross-sections. However, the spray structures pertaining to α = 30°, α = 60° and α = 90° were considerably different. In the case of the atomizer with multiple injections, a “collision region” was observed at α = 60° and characterized by a higher ci and larger averaged SMD in the central parts of the cross-sections.

The injection angle α is a key design parameter for air-blast atomizers. The findings of this study can help enhance the understanding of the droplet-gas mixing process in air-blast atomizers. Engineers who design air-blast atomizers and face new challenges in the process can refer to the presented findings to obtain the desired atomization performance. The code has been validated and can be used in the engineering design process of the gas-liquid jet atomizer.

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.

The purpose of this study is to design carbon electrode materials for high performance electric double-layer capacitors (EDLCs) with pores that are large enough and have suitable pore size distribution for the electrolyte to access completely to improve EDLCs’ electrochemical performance.

This study develop an improved traditional KOH activation method, and a series of micro-meso hierarchical porous carbons have been successfully prepared from phenol formaldehyde resin by combining polyethylene glycol (PEG) and conventional KOH activation.

As evidenced by N₂ adsorption/desorption tests, the obtained samples present Types IV and I-IV hybrid shape isotherms compared with KOH-activated resin (typical of Type I). The sample AC2-7-1, which the addition quantity of PEG is 25 per cent PF (weight ration) activated at 700? For 1 h is considered as the optimum preparation condition. It exhibits the highest specific capacitance value of 240 F/g in 30 wt% KOH aqueous electrolytes because of its higher specific surface area (2085 m2/g), greater pore volume (1.08 cm3/g) and the maximum mesoporosity (43 per cent). In addition, the capacity decay of this material is only 3.1 per cent after 1000 cycles.

The materials that are rich in micropores and mesopores show great potential in EDLC capacitors, particularly for applications where high power output and good high-frequency capacitive performances are required.

Organic coatings are widely used for protecting metal equipment and structures from corrosion. Accurate detection and evaluation of the protective performance and service life of coatings are of great importance. This paper aims to review the research progress on performance evaluation and lifetime prediction of organic coatings.

First, the failure forms and aging testing methods of organic coatings are briefly introduced. Then, the technical status and the progress in the detection and evaluation of coating protective performance and the prediction of service life are mainly reviewed.

There are some key challenges and difficulties in this field, which are described in the end.

The progress is summarized from a variety of technical perspectives. Performance evaluation and lifetime prediction include both single-parameter and multi-parameter methods.

Despite rapid growth in blockchains, there was limited discussion about non-technical and technical factors on blockchain governance in the extant literature. This study aims to contribute new knowledge to the literature on potential factors affecting the adoption, governance and scale-up of blockchain technologies in the health-care and energy sectors, presented in a holistic framework.

This study adopts the qualitative case study research methodology to research blockchain governance in practice. The authors contacted a national blockchain consortium to conduct their research on the governance issue of blockchain. Two leading case organizations, one from the health-care industry and another from the energy industry, were deliberately selected for their study for their active role and reputation in the consortium and practical experience in blockchain governance.

The developed framework helps identify potential research gaps or concerns on adopting a blockchain as well as assessing blockchain implementation and governance in other industries. Depending on the circumstances, some of the factors can be either drivers or obstacles to further blockchain development. The different forces may also be more or less evident over time as blockchains develop. The two real-world case studies contribute to the information technology governance literature on blockchain governance.

The results of this case studies will be beneficial for developing theories and empirical models to determine antecedents for achieving consensus and trust in blockchain and testing the relationship between these factors and blockchain governance at different levels. As a result, theories related to the governance of blockchain technologies could be further developed.

Construction safety resilience is gradually gaining attention in the field of engineering construction as a new management concept and way to improve safety performance. However, how to cope with the dilemma of the unclear relationship of construction safety resilience elements at the practice level and promote the harmonization of construction safety goals and resilience enhancement paths has become an urgent challenge for safe construction.

This study analyzes the components of construction safety resilience elements. A relationship network model of construction safety resilience elements is developed by using the social network analysis method. The location and influence of each element in the network and the interrelationships among the elements are explored in depth.

The findings reveal a robust interconnection among the elements of safety resilience in the construction industry. Key components such as safety behavior, risk prevention and control mechanisms, disaster prevention and mitigation technologies as well as information technology, are positioned at the core of the network. Notably, safety behavior exerts the most significant influence over the other elements, serving as the linchpin of safety management in the construction industry. Moreover, the interplay among safety resilience elements in the construction sector can alter the structure of the relationship network.

This study adopts the social network approach to solve the problem that it is difficult to quantitatively analyze the elements of construction safety resilience and their interrelationships and to clarify the interactions among the core elements, which can help to further assist the construction project manager to continuously optimize safety resilience and improve construction safety.

This paper aims to propose a framework for optimizing the pose in the assembly process of the non-ideal parts considering the manufacturing deviations and contact deformations. Furthermore, the accuracy of the method would be verified by comparing it with the other conventional methods for calculating the optimal assembly pose.

First, the surface morphology of the parts with manufacturing deviations would be modeled to obtain the skin model shapes that can characterize the specific geometric features of the part. The model can provide the basis for the subsequent contact deformation analysis. Second, the simulated non-nominal components are discretized into point cloud data, and the spatial position of the feature points is corrected. Furthermore, the evaluation index to measure the assembly quality has been established, which integrates the contact deformations and the spatial relationship of the non-nominal parts’ key feature points. Third, the improved particle swarm optimization (PSO) algorithm combined with the finite element method is applied to the process of solving the optimal pose of the assembly, and further deformation calculations are conducted based on interference detection. Finally, the feasibility of the optimal pose prediction method is verified by a case.

The proposed method has been well suited to solve the problem of the assembly process for the non-ideal parts with complex geometric deviations. It can obtain the reasonable assembly optimal pose considering the constraints of the surface morphological features and contact deformations. This paper has verified the effectiveness of the method with an example of the shaft-hole assembly.

The method proposed in this paper has been well suited to the problem of the assembly process for the non-ideal parts with complex geometric deviations. It can obtain the reasonable assembly optimal pose considering the constraints of the surface morphological features and contact deformations. This paper has verified the method with an example of the shaft-hole assembly.

The different surface morphology influenced by manufacturing deviations will lead to the various contact behaviors of the mating surfaces. The assembly problem for the components with complex geometry is usually accompanied by deformation due to the loading during the contact process, which may further affect the accuracy of the assembly. Traditional approaches often use worst-case methods such as tolerance offsets to analyze and optimize the assembly pose. In this paper, it is able to characterize the specific parts in detail by introducing the skin model shapes represented with the point cloud data. The dynamic changes in the parts' contact during the fitting process are also considered. Using the PSO method that takes into account the contact deformations improve the accuracy by 60.7% over the original method that uses geometric alignment alone. Moreover, it can optimize the range control of the contact to the maximum extent to prevent excessive deformations.

This study aims to provide a comprehensive overview of asset pricing research and identifies the general research trends in the area. The study also aims to provide future direction to the researchers in the area of asset pricing.

The study uses bibliometric analysis techniques to achieve the stated purpose. The study covers 3,007 articles published in the top 50 finance and economics journals, accessed from the Scopus database for a period of 47 years (1973–2020). After initial searching for “asset pricing” as the main keyword in “title, abstract, keywords”, the database yields 6,583 articles. This number further reduces to 3,007 articles when the search is restricted to research and review articles published in the top 50 peer-reviewed journals.

The tabular and pictorial representation obtained from the analysis exhibit that asset pricing is an extensively researched area; however, a sudden rise in the number of publications (242) observed for 2019 demonstrates a growing interest amongst researchers. Further, affiliation statistics indicate that the volume of research is mainly concentrated in the USA and other developed nations; hence it opens vistas for the exploration of risk-return dynamics in the context of emerging markets.

The work presents an exhaustive and comprehensive review along with potential research implications. The present study reconciles various contradictory views of the prior studies under asset pricing such as risk-return trade-off, low-risk anomaly and provides the researchers with potential research gaps.

This study aims to manufacture cotton fabric with thermal regulation performance by using the composite phase change material (CPCM) prepared by coating paraffin doped with expanded graphite (EG), and the thermal effect of the fabric material was evaluated and characterized.

EG/paraffin CPCM with shape stability and enhanced thermal conductivity were prepared by the impregnation method and then finished on the surface of cotton fabric with coating technology. The microstructure, crystal structure, chemical composition, latent heat property and thermal conductivity were analyzed by scanning electron microscope, x-ray diffraction, Fourier transform infrared spectroscopy, differential scanning calorimeter and thermal constant analyzer. The photo-thermal effect of the coated fabric was studied by a thermal infrared imager.

CPCM prepared with a mass ratio of EG to paraffin of 1:8 showed excellent shape stability and low paraffin leakage rate. The latent heat of the CPCM was 51.6201 J/g and the thermal conductivity coefficient was increased by 11.4 times compared with the mixed paraffin. After the CPCM was coated on the surface of the cotton fabric, the light-to-heat conversion rate of the C-EG/PA3 sample was improved by 86.32% compared with the original fabric. In addition, the coated fabric showed excellent thermal stability and heat storage performance in the thermal cycling test.

EG can improve the shape stability and thermal conductivity of paraffin but will reduce the latent heat energy.

The method developed provided a simple and practical solution to improving the thermal regulation performance of fabrics.

Combining paraffin wax with fabrics in a composite way is innovative and has certain applicability in improving the thermal properties of fabrics.