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Topologically ordered functionally graded composite (TOFGC) biodegradable materials are needed in the field of metallic degradable implants, as they degrade over a period of time avoiding the necessity of another surgery for implant removal. Also, their rate of degradation can be tailored to match the requirement of the patient. These biomaterials also have the functionality to assist bone growth and eliminate stress shielding in orthopaedic implants.

In this study, TOFGC biomaterials were developed for the first time using additive manufacturing, pressureless microwave sintering and casting methods, and their cytocompatibility, hemocompatibility and in vitro degradation evaluations were done. Also, pure dense iron and iron scaffolds were included in the study, for the comparison of results with the iron-hydroxyapatite-zinc functionally graded composite biomaterial.

The maximum weight loss and corrosion rate were found to be 6.98% and 2.38 mmpy, respectively, in the immersion test and electrochemical test for Fe-3.5HAp-54Zn biomaterial. Zinc-infiltrated composite biomaterials exhibited excellent cytocompatibility and hemocompatibility as compared to pure dense iron and iron scaffolds. A comparative analysis was conducted, taking into account relevant literature, and it was determined that the fabricated iron-hydroxyapatite-zinc biomaterial demonstrated desirable degradation and biological characteristics, customized to meet the specific requirements of bone tissue engineering applications.

TOFGC iron-hydroxyapatite-zinc biomaterial has been fabricated for the first time using the developed novel methodology and their degradation and biological characterizations were performed.

The purpose of this paper is to propose a design method for additive manufacturing (AM) hydraulic valves based on valve body structural decomposition. The method aims to achieve the design of a hydraulic valve with minimum mass or maximum stiffness or minimum pressure loss that also satisfies the structural strength requirements.

Decompose the hydraulic valve into typical feature structures and functional structures. Generative design (GD) tools are used to perform GD on the typical feature structures while considering loads and constraints. Based on the GD results, automatically design flow channels with variable wall thickness driven by fluid pressure. The GD results under different design objectives are combined with the automatically designed variable wall thickness channels to obtain hydraulic valves with different performance characteristics.

The case study section redesigned and manufactured a minimum mass fuel regulator valve. Compared to the conventional fuel regulator valve, the mass of the redesigned valve was reduced by 77%, the pressure loss was reduced by 40% and the flow rate was increased by 38%.

The value of this work is the combination of structural and flow optimization, as well as the design of flow channels with variable wall thickness. The proposed method contributes a novel solution to the design of AM hydraulic valves.

Precise temperature measurements are crucial for understanding Earth’s energy balance and for accurately predicting future climate change. Therefore, atmospheric temperature observations using radiosonde sensors require enhanced accuracy, targeting measurements with a precision of 0.1 K or better.

First, temperature errors of radiosonde sensors were simulated using computational fluid dynamics (CFD) from sea level up to an altitude of 32 km. These simulations accounted for a range of environmental factors, including solar radiation intensity, solar radiation angle, air velocity and altitude (air density). A neural network algorithm was then applied to learn and model the CFD-derived temperature errors. Based on this, a temperature error correction algorithm for radiosonde sensors was developed.

Experimental results demonstrated that the average absolute error between the measured temperature errors and the values corrected using the algorithm was 0.019 K, with a root mean square error of 0.018 K and a correlation coefficient of 0.99. These findings suggest that the temperature error correction algorithm effectively reduces measurement errors to approximately 0.05 K.

The widespread adoption of this technology can impact various aspects of society, including enhancing the overall quality of meteorological observation networks and providing more accurate meteorological data support for multiple fields, such as agriculture, disaster early warning, and public health.

This study focuses on developing a correction algorithm for radiation-induced errors in sounding temperature sensors by integrating CFD with neural network algorithm. This approach aims to enhance the accuracy of temperature observations from sounding sensors, minimizing biases caused by solar radiation. The improved precision in temperature measurements will contribute to more reliable historical temperature data, thereby supporting research in climate change by providing accurate datasets for long-term climate analysis.

Thermal failure and incomplete separation often occur in aviation wet friction clutches. The purpose of this study is to improve the performance and reliability of the clutch, considering the influence of lubricating oil, in this paper, the finite element method is used to simulate the friction pair of clutch with separation spring.

Considering the influence of lubricating oil, based on computational fluid dynamics principle and applying multiple reference frame method, simulation is carried out in FLUENT software to study the distribution of flow field and temperature field of clutch friction pair and separation spring under the condition of maximum relative speed of 3000 r/min.

The middle friction pair has more oil distribution, while the two sides have less oil distribution, and the highest oil volume exceeds that of the lowest by a factor of 3.49. Under the influence of lubricating oil distribution and component heat conduction, the temperature of the separation spring on both sides is higher than that of the separation spring in the middle. The axial temperature distribution law of the friction pair is the same as that of the separation spring, and the difference of the highest temperature between the friction pair is 136.41°C.

The heat generation of the clutch is studied to improve the performance of the clutch and ensure the safety of the helicopter.

By analyzing the temperature and flow field of a wet friction clutch with a separation spring, engineers can help provide the service life and reliability of the clutch friction pair.

Under oil interruption, lubricant supply in the high-speed bearing cavity is interrupted, which reduces the bearing lubrication and cooling ability, thus leading to degradation of bearing performance or even its failure. This paper aims to study the effect of grooves at the noncontact outer ring area on the flow and thermal performance of high-speed bearings under oil interruption, which is expected to improve the resistance of existing bearings to oil interruption.

The groove was added to the noncontact outer ring area of the bearing, and a method of combining volume of fluid and MRF was adopted to systematically study and analyze the oil-gas flow field structure and the temperature field distribution in the bearing cavities.

Results show that the lubricating oil could be stored and guided by the grooves of the bearing outer ring into the key lubrication area inside the bearing cavity, which increased the oil content near the inner ring and made the oil distribution more uniform. As a result, lubrication cooling and heat dissipation performance of the bearing cavity was improved. Compared with the original bearing, the bearing with a V-shaped groove had the optimal lubrication and cooling performance.

A rolling bearing model of the noncontact outer ring area with grooves under oil interruption is established in the paper. The simulation results provide theoretical guidance for the research and development of high-speed bearings with stronger oil interruption resistance ability.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0199/

This paper aims to investigate the effect of different texture ratios of bionic scallop microtextures on the tribological performance of shot-peened 65Mn steel plow surfaces.

This study first uses ultrasonic shot peening to strengthen the 65Mn steel plow surface, followed by laser processing to create bio-inspired scallop shell microtexture protrusions with varying texture ratios. The hardness of the samples is measured using an HV-1000D Vickers hardness tester, and the surface roughness is assessed using a TR200 roughness tester. Tribological performance tests are conducted under lubrication with earthworm body fluid using an HSR-2M reciprocating friction and wear tester. The surface structure and wear scar morphology of the samples are observed using an M330BD-HK830 metallurgical microscope and an S-4800FE scanning electron microscope.

Ultrasonic shot peening increases the surface roughness of the 65Mn steel plow, leading to increased friction, while the enhanced hardness improves wear resistance. The single bionic scallop microtexture protrusions have limited effectiveness in improving the friction and wear resistance of the 65Mn steel plow surface. However, bionic scallop microtextures with different texture ratios can improve the friction and wear resistance of the shot-peened 65Mn steel plow surface to varying degrees. When the texture ratio is 37%, compared to the single shot-peened sample, the maximum reduction in friction coefficient under 20 N and 50 N loads is 19.86% and 22.98%, respectively, while the maximum reduction in wear rate is 84.25% and 87.91%, respectively.

The research results provide a reference for preparation methods to achieve plow surfaces with excellent anti-adhesion, drag reduction and wear resistance properties.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2024-0303/

The complex behavior of viscoelastic fluids and its flow analysis under the impact of transverse magnetic field are becoming increasingly important in numerous emerging applications including biomedical engineering, aerospace engineering, geophysics and industrial applications. Additionally, the thermal analysis and fluid flow driven by propagating membranes will aid significant applications for microscale transport in bio-thermal systems. This study aims to investigate the thermal effects of viscoelastic fluids driven by membrane-induced propagation and transverse magnetic field.

The propagation of the membranes will work as pump which pushes the fluids from bottom to top against the gravitation force; however, there is backflow due to compression and expansion phases of membrane propagation. The Jeffrey fluid model is employed to analyze the viscoelastic fluid flow, with entropy generation examined and equations solved analytically under low Reynolds number and long-wavelength assumptions.

The findings reveal that an increase in magnetic field strength impedes fluid flow, while higher values of the Grashof number, heat source parameter and Jeffrey fluid parameter enhance fluid motion. The study’s findings have significant implications for optimizing magnetohydrodynamic systems in various emerging applications, including biomedical engineering, aerospace, geophysics and industrial processes.

This study aims to investigate the impact of a transverse magnetic field on the flow and heat transfer characteristics of viscoelastic fluids driven by membrane propagation.

The purpose of this study is to (1) improve the spectral features of the second-order uniformly non-oscillatory (UNO) slope limiters, and (2) numerical simulation of the unified-form of generalized fully-coupled saturated thermo-poro-elastic systems in the axisymmetric cylindrical coordinate via cell-adaptive Kurganov-Tadmor (KT) central high-resolution scheme using the UNO limiters.

(1) The spectral features of the UNO limiter are improved by compression-adaptive MINMOD (MM) limiters, achieved by blending different types of MM limiters to achieve less numerical dissipation and dispersion. These blended MM limiters preserve the total variation diminishing (TVD) feature over non-uniform non-centered cells. Also, the spectral features of the central schemes using the UNO limiters are investigated. (2) For the thermo-poro-elastic problem, corresponding first-order hyperbolic system is provided, including flux, source, diffusion and nonlinear terms. Where, there are different interacting components in the source and flux terms. The nonlinear terms are also considered by the Picard-like linearization concept.

Compression-adaptive UNO limiters would be stable over adapted cells with centered and non-centered cells. The benchmarks confirm that both spectral features and numerical accuracy are improved. For the generalized thermo-poro-elastic problem, corresponding responses including the shock waves can properly be captured.

Studying heat effects (e.g. hot fluid or freezing) and explosions on tunnels. Also, the UNO limiters could be used for simulations of various systems of conservation laws.

The purpose of this study is to explore the integration of risk management and circular economy (CE) principles within the healthcare sector to promote sustainability and resilience. Specifically, the study aims to demonstrate how risk management can support the transition to a circular economy in healthcare supply chains. By integrating risk management practices with CE principles, healthcare organizations can identify potential risks and opportunities associated with circular initiatives.

This study adopts a qualitative research approach, using a case study methodology with semi-structured interviews conducted at primary care facilities to understand the application of CE principles in practice. The study uses fuzzy logic methods to assess and mitigate risks associated with strategies promoting CE principles. Additionally, key performance indicators are identified to evaluate the effectiveness and enhance the resilience of these strategies within healthcare supply chains.

The study highlights the critical role of robust risk management strategies in facilitating the transition to a circular economy within healthcare organizations. Primary care facilities, which are critical to frontline healthcare delivery, are particularly vulnerable to product shortages due to supply risks. This study focuses on critical protective equipment, specifically latex gloves and assesses operational risks, including supply, demand and environmental risks, using a fuzzy logic-based model. Import delays were found to be a moderate risk, typically occurring once a year. The research highlights critical KPIs for a successful CE transition within healthcare supply chains, such as on-time delivery and service quality, which are directly related to the risk of supply chain disruption. In addition, the study highlights the significant impact of other CE strategies on healthcare supply chains, including localized production and manufacturing, innovation in product development, reverse logistics, closed-loop supply chains and the adoption of lean principles.

This study provides valuable insights for healthcare organizations to optimize resource efficiency, reduce waste and promote circularity in their operations. By implementing the proposed solutions and focusing on the identified KPIs, organizations can develop strategies to achieve sustainability goals and enhance resilience in healthcare supply chains.

This study contributes to the literature by demonstrating the application of risk management in facilitating the transition to a circular economy in the healthcare sector. The use of fuzzy logic methodology offers a novel approach to assessing and mitigating risks associated with critical product failures in supply chain activities. The study’s findings provide practical guidance for healthcare organizations seeking to integrate circular economy principles and improve sustainability performance.

This study proposes a novel algorithm based on the finite volume method for simulating groundwater flows and presents the practical application of this method in geotechnical engineering.

The matrix-free implicit iteration method based on the finite volume method and preconditioning conjugate gradient algorithm was used to discretize and solve the groundwater seepage governing equation. Implicit residual smoothing and GPU parallel techniques were utilized to speed up the computation with the solver.

The new method was assessed and evaluated using benchmark and typical infiltration cases. Both the analytical solutions and solutions of the commercial software GEO-Studio were used to verify the accuracy of the proposed algorithm. The speedup performance of the GPU parallel algorithm was also well reflected.

The results demonstrate that the new algorithm is simple and practical, with fast convergence and high accuracy and can satisfy engineering application requirements.