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Sheet-to-cloud cavitation transitions are very complex owing to the simultaneous appearance of the re-entrant jet and shock waves. The objective of this paper is to investigate the physics of compressible cavitating flows with emphasis on the simultaneous existence of the re-entrant jet and shock waves. A compressible cavitating solver, which considers the compressibility effects of both the liquid and the vapour, was used to account for the different shedding characteristics induced by the re-entrant jet mechanism (RJM), the shock wave mechanism (SWM), and both the re-entrant jet and the shock waves (RJM-SMW). The solver used Large Eddy Simulations (LES) and the Schnerr-Sauer cavitation model. The numerical results are first compared with available experimental data [1] which showed satisfactory agreement for various aspects of the flow, including the pressure distribution, cavity shapes, condensation front speed, and shedding frequency. The results first show three different cavity shedding processes induced by the re-entrant jet and the shock waves. Frequency analyses show that the shock waves produce a wider frequency distribution which indicates that shock waves induce more shedding than the re-entrant jet. The quasi-periodic characteristics of the transitions between the various cavity shedding characteristics are mainly induced by the variations of the pressure, residual cavity volume and medium compressibility. Further analyses show that the different pressure, residual cavity volume and medium compressibility amplitudes determine the cavity shedding characteristics in the subsequent shedding cycle. When the conditions favour both the re-entrant jets and the shock wave effects, both the re-entrant jet and the shock waves impact the cavity shedding. [ABSTRACT FROM AUTHOR]

Material research and development driven by data analysis necessitates a substantial volume of data. However, conventional material data sharing platforms encounter challenges in sharing and integrating data across multiple platforms. This article proposes a blockchain-based materials data discovery and sharing infrastructure—InterMat, which is a material big data management and sharing framework model integrating cloud platforms and blockchain. It could support the full lifecycle of materials data sharing, including data generation, management, discovery, sharing, traceability, and valuation. The architecture of the InterMat, its unique method of constructing a consortium chain, and the protocol for data discovery are presented in this paper. Additionally, the method for materials data identifier and blockchain certification is established, which allows for a unified identifier on the blockchain and cloud-based data addressing from various organizations. InterMat has data discovery algorithms for various materials to achieve the discovery of similar materials data from different nodes. Furthermore, we have designed some blockchain smart contracts for InterMat to encourage data sharing across nodes. These contracts include a proof smart contract that records data sharing activities, ensuring transparency and traceability in the materials data flow. The other contract is a value-estimating contract to encourage high-quality data sharing. Finally, this article introduces the application case of InterMat, using steel materials as an example to demonstrate its applications in data management, data discovery, data valuation, etc. This study successfully addresses various challenges associated with the cross-platform sharing of materials data, such as issues related to data discovery, data rights and control, and willingness to share. InterMat can assist material researchers in discovering and accessing more data, which would create a new ecology for sharing data. [ABSTRACT FROM AUTHOR]

The traditional program refinement strategy cannot be refined to an executable program, and there are issues such as low verification reliability and automation. To solve the above problems, this paper proposes a nonlinear program construction and verification method based on partition recursion and Morgan's refinement rules. First, we use recursive definition technique to characterize the initial specification. The specification is then transformed into GCL(Guarded Command Language) programs using loop invariant derivation and Morgan's refinement rules. Furthermore, VCG (Verification Condition Generator) is used in the GCL program to generate the verification condition automatically. The Isabelle theorem prover then validates the GCL program's correctness. Finally, the GCL code generates a C++ executable program automatically via the conversion system. The effectiveness of this method is demonstrated using binary tree preorder traversal program construction and verification as an example. This method addresses the problem that the construction process's loop invariant is difficult to obtain and the refinement process is insufficiently detailed. At the same time, the method improves verification process automation and reduces the manual verification workload. [ABSTRACT FROM AUTHOR]

Airborne transmission of SARS-CoV-2 via virus-laden aerosols in enclosed spaces poses a significant concern. Elevators, commonly utilized enclosed spaces in modern tall buildings, present a challenge as the impact of varying heating, ventilation, and air conditioning (HVAC) systems on virus transmission within these cabins remains unclear. In this study, we employ computational modeling to examine aerosol transmission within an elevator cabin outfitted with diverse HVAC systems. Using a transport equation, we model aerosol concentration and assess infection risk distribution across passengers' breathing zones. We calculate the particle removal efficiency for each HVAC design and introduce a suppression effect criterion to evaluate the effectiveness of the HVAC systems. Our findings reveal that mixing ventilation, featuring both inlet and outlet at the ceiling, proves most efficient in reducing particle spread, achieving a maximum removal efficiency of 79.40% during the exposure time. Conversely, the stratum ventilation model attains a mere removal efficiency of 3.97%. These results underscore the importance of careful HVAC system selection in mitigating the risk of SARS-CoV-2 transmission within elevator cabins. [ABSTRACT FROM AUTHOR]

This study employs computational fluid dynamics (CFD) simulations to evaluate the risk of airborne transmission of COVID-19 in low-ceiling rooms, such as elevator cabins, under mechanical displacement ventilation. The simulations take into account the effects of the human body's thermal environment and respiratory jet dynamics on the transmission of pathogens. The results of the study are used to propose a potential mitigation strategy based on ventilation thermal control to reduce the risk of airborne transmission in these types of enclosed indoor spaces. Our findings demonstrate that as the ventilation rate (Qv) increases, the efficiency of removing airborne particles (εp) initially increases rapidly, reaches a plateau (εp,c) at a critical ventilation rate (Qc), and subsequently increases at a slower rate beyond Qc. The Qc for low-ceiling rooms is lower compared to high-ceiling rooms due to the increased interaction between the thermal plume generated by the occupants or infectors and the ventilation. Further analysis of the flow and temperature fields reveals that εp is closely linked to the thermal stratification fields, as characterized by the thermal interface height and temperature gradient. When Qv < Qc, hT,20.7 < him (him is the height of infector's mouth) and aerosol particles are injected into the upper warm layer. As Qv increases, the hti also increases following the 3/5 law, which helps displace the particles out of the room, resulting in a rapid increase of εp. However, when Qv > Qc, hT,20.7 > him and aerosol particles are injected into the lower cool layer. The hti deviates from 3/5 law and increases at a much slower rate, causing an aerosol particle lockup effect and the εp to plateau. In addition, as the Qc increases, the local flow recirculation above the infector head is also enhanced, which leads to the trapping of more particles in that area, contributing to the slower increase in εp. The simulations also indicate that the location of infector relative to ventilation inlet/outlet affects Qc and εp,c with higher Qc and lower εp,c observed when infector is in a corner due to potential formation of a local hot spot of high infection risk when infector is near the ventilation inlet. In conclusion, based on the simulations, we propose a potential ventilation thermal control strategy, by adjusting the ventilation temperature, to reduce the risk of airborne transmission in low-ceiling rooms. Our findings indicate that the thermal environment plays a critical role in the transmission of airborne diseases in confined spaces. [ABSTRACT FROM AUTHOR]

Although many studies have reported the behaviors of thermal cycling of Sn-based solder joints, the corresponding mechanism is difficult to describe universally due to the complexity of different cases. In the present study, microstructural evolution and failure of Sn–Bi57–Ag0.7 solder joints caused by thermal cycling between − 40 and 85 °C from 0 to 1000 cycles were systematically investigated. The results indicated that the Sn–Bi–Ag solder joint was composed of Sn-rich phase, Bi-rich phase, large numbers of Bi dispersed-particles, and Ag3Sn precipitate. With the extension of time during thermal cycling, the microstructure of Sn–Bi–Ag solder joint gradually coarsened and the IMC layer became thicker (from 0.82 to 2.38 μm). However, Sn–Bi–Ag solder joints failed after 3000 thermal cycles. Two different stages of failure were found and the mechanism, related to the increment of thermal mismatch stress, was illuminated. Furthermore, Electron Backscattered Diffraction was used to detailedly elucidate the grain characteristics of the failed Sn–Bi–Ag solder joints, and the effect of thermal stress on orientations of Sn and Bi grains was also revealed. Being different from the orientation change observed in traditional Sn–Bi eutectic solder joints in previous studies, the present results demonstrated that both Sn and Bi grains did not present any preferred orientations after thermal cycling. And the reason of this phenomenon might be attributed to the Ag3Sn, which could be regarded as second-phase particles. Our present work would provide theoretical guidance for the development of new Sn–Bi-X solders with high reliabilities. [ABSTRACT FROM AUTHOR]

The construction of multifunctional sensors has attracted considerable attention due to their multifunctional properties, such as high sensitivity and rapid detection. Herein, near-infrared multifunctional fluorescent sensing materials based on core-shell upconversion nanoparticle@magnetic nanoparticle and molecularly imprinted polymers were synthesized for rapid detection of deltamethrin. The difunctional core-shell upconversion nanoparticle@magnetic nanoparticle was introduced as the optical signal and rapid separator. Firstly, the difunctional core-shell materials were prepared through solvothermal method. Then, molecularly imprinted polymers (MIPs) as recognition elements for deltamethrin were coated on the surface of upconversion nanoparticle@magnetic nanoparticle through polymerization. The structure and recognition characterizations of multifunctional fluorescent sensing materials were evaluated. Under optimal condition, the imprinting factor of sensing materials was 3.63, and the fluorescence intensity of sensing materials decreased linearly with increasing concentration of deltamethrin from 0.001 to 1 mg L−1 with a detection limit of 0.749 μg L−1, and a relative standard deviation of 3.10% was obtained with 5 mg L−1 deltamethrin. The sensing materials showed a high selectivity and were successfully utilized for the detection of deltamethrin in grapes and cabbages; the results showed that the recoveries for two samples obtained were 95.6–102% and 91.8–105%. [ABSTRACT FROM AUTHOR]

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Selective laser melting (SLM) in situ alloying is an effective way to design and fabricate novel materials in which the elemental powder is adopted as the raw material and micro-areas of elemental powder blend are alloyed synchronously in the forming process of selective laser melting (SLM). The pre-alloying process of preparation of raw material powder can be left out, and a batch of bulk samples can be prepared via the technology combined with quantitative powder mixing and feeding. The technique can be applied to high-throughput sample preparation to efficiently obtain a microstructure and performance data for material design. In the present work, bulk equiatomic FeCoCrNi high-entropy alloys with different processing parameters were fabricated via laser in situ alloying. Finite element simulation and CALPHAD calculation were used to determine the appropriate SLM and post-heating parameters. SEM (scanning electron microscope), EDS (energy dispersive spectroscopy), XRD (X-ray diffraction), and mechanical testing were used to characterize the composition, microstructure, and mechanical properties of as-printed and post-heat-treated samples. The experimental results show that the composition deviation of laser in situ alloying samples could be controlled within 20 wt %. The crystal structure of as-printed samples is a single-phase face-centered cubic (FCC), which is the same as those prepared by the traditional method. The mechanical properties of the samples prepared by laser in situ alloying with elemental powder blend are comparable to those prepared by pre-alloying powder and much higher than those prepared by the traditional method (arc melting). As-printed samples can get a homogeneous microstructure under the optimal laser in situ alloying process combined with post-heat treatment at 1200 °C for 20 h. [ABSTRACT FROM AUTHOR]