Computational Fluid Dynamics Technology Research Articles

A Study on the Effectiveness of Climate Adaptation Materials for Urban Heat Islands using Digital Twin and Computational Fluid Dynamics

This study analyzed the impact of climate adaptation materials on the mitigation of urban heat islands (UHI) using digital twin visualization and computational fluid dynamics (CFD) technology. The effects of UHI due to increased impervious surfaces have become more pronounced, and climate-adaptation materials are gaining attention as potential solutions. In this study, the impact of climate adaptation materials on UHI mitigation was analyzed using the CFD program STAR-CCM+ based on the finite volume method (FVM). The selected research site was Byeoryang-dong, Gwacheon City, and four simulation scenarios were created based on the emissivity values of the asphalt and concrete materials. The results showed that application of climate adaptation materials decreased the surface and aboveground (1.5 m) temperatures by 6.3 and 0.8 °C, respectively. This study suggests that climate adaptation materials can significantly mitigate UHI.

Post-disaster investigations of damage feature of buildings and structures due to several local strong winds in China during 2021–2024

Local strong winds such as tornadoes and downbursts are rare in terms of measured wind speed data due to their rapid formation and strong destructive power. Post-disaster investigations have become an important approach for rating the strength of these two kind of winds and analyzing structural failure mechanism. From 2021 to 2024, several tornadoes and downbursts occurred in China. This study delineated changes in the intensity levels of wind disasters along their paths based on on-site disaster investigations and established standards for the level of structural damage based on the extent of functional loss and repair. This study focused on the damage feature to light steel structures, masonry structures, steel-concrete structures, and pole structures, and discussed the causes of the damage from the perspectives of construction and force transmission mechanisms. In addition, this study estimated the equivalent wind speeds based on the damage feature of pole structures and metal roof claddings. To reproduce the damage process for a group of high-rise buildings, the computational fluid dynamic (CFD) technology is used to simulate the airflow distribution inside buildings under two conditions of open and closed interior doors. The investigation results can provide useful information for the wind intensity classification and rating standards in China. Meanwhile, compared with the interior doors being open or closed, closing indoor doors during strong winds can significantly reduce indoor wind speeds, which is beneficial for ensuring safety.

Computational study on the impact of gasoline-ethanol blending on autoignition and soot/NOx emissions under low-load gasoline compression ignition conditions

In the present work, computational fluid dynamics (CFD) simulations of a single-cylinder gasoline compression ignition (GCI) engine are performed to investigate the impact of gasoline-ethanol blending on autoignition, nitrogen oxide (NOx), and soot emissions under low-load conditions. In order to represent the test gasoline (RD5-87), a four-component toluene primary reference fuel (TPRF)+ethanol (ETPRF) surrogate (with 10% ethanol by volume; E10) is employed. A three-dimensional (3D) engine CFD model employing finite-rate chemistry with a skeletal kinetic mechanism (including NOx sub-mechanism), adaptive mesh refinement (AMR), and hybrid method of moments (HMOM) is adopted to capture the in-cylinder combustion phenomena and soot/NOx emissions. The engine CFD model is validated against experimental data for three gasoline-ethanol blends: E10, E30 and E100, with varying ethanol content by volume. Model validation is carried out for a broad range of start-of-injection (SOI) timings (−21, −27, −36, and −45 crank angle degrees (°CA) after top-dead-center (aTDC)) with respect to in-cylinder pressure, heat release rate, combustion phasing, NOx and soot emissions. For relatively later injection timings (−21 and −27 °CA aTDC), E30 yields higher amount of soot than E10; while the trend reverses for early injection cases (−36 and −45 °CA aTDC ). On the other hand, E100 yields the lowest amount of soot among all fuels irrespective of SOI timing. Further, E10 shows a non-monotonic trend in soot emissions with SOI timing: SOI-36>SOI-45>SOI-21>SOI-27, while soot emissions from E30 exhibit monotonic decrease with advancing SOI timing. NOx emissions from various fuels follow a trend of E10>E30>E100. On the other hand, NOx emissions increase as SOI timing is advanced for all fuels, with an anomaly for E10 and E100 where NOx decreases when SOI is advanced beyond −36 °CA aTDC. Detailed analysis of the numerical results is performed to investigate the soot/NOx emission trends and elucidate the impact of chemical composition and physical properties on autoignition and emissions characteristics.

Continuous Casting Tundish Dead Volume Study by Physical Modeling and Computational Investigation

Flow efficiency in a two‐strand continuous casting tundish is studied by analyzing the residential time distribution (RTD) curves in a small‐scale tundish water model using a conductive NaCl solution tracer. The velocity fields in the tundish water model are measured by particle image velocimetry, which is used to validate the results of the mathematical model in the article. It is found that the tracer concentration has a significant impact on the predicted dead volume fraction in the RTD analysis. Validated mathematical modeling of the computational fluid dynamics (CFD) technology is performed to explore the root cause of the defective results in the RTD analysis. It is found that the flow inside the tundish is sensitive to density variations caused by the injected tracer. A denser tracer will stay lower in the tundish by gravity and flow out of the tundish more quickly. A proper tracer concentration in the water model experiments is discussed to visualize the dead volume and improve tundish furniture design efficiently for future work, a new method using CFD modeling is proposed in this article, which can directly demonstrate the dead volume's location.

Numerical Study on Explosion Risk and Building Structure Dynamics of Long-Distance Oil and Gas Tunnels

To comprehensively understand the explosion risk in underground energy transportation tunnels, this study employed computational fluid dynamics technology and finite element simulation to numerically analyze the potential impact of an accidental explosion for a specific oil and gas pipeline in China and the potential damage risk to nearby buildings. Furthermore, the study investigated the effects of tunnel inner diameter (d = 4.25 m, 6.5 m), tunnel length (L = 4 km, 8 km, 16 km), and soil depth (primarily Lsoil = 20 m, 30 m, 40 m) on explosion dynamics and on structural response characteristics. The findings indicated that as the tunnel length and inner diameter increased, the maximum explosion overpressure gradually rose and the peak arrival time was delayed, especially when d = 4.25 m; with the increase in L, the maximum explosion overpressure rapidly increased from 1.03 MPa to 2.12 MPa. However, when d = 6.5 m, the maximum explosion overpressure increased significantly by 72.8% from 1.25 MPa. Evidently, compared to the change in tunnel inner diameter, tunnel length has a more significant effect on the increase in explosion risk. According to the principle of maximum explosion risk, based on the peak explosion overpressure of 2.16 MPa under various conditions and the TNT equivalent calculation formula, the TNT explosion equivalent of a single section of the tunnel was determined to be 1.52 kg. This theoretical result is further supported by the AUTODYN 15.0 software simulation result of 2.39 MPa (error < 10%). As the soil depth increased, the distance between the building and the explosion source also increased. Consequently, the vibration peak acceleration and velocity gradually decreased, and the peak arrival time was delayed. In comparison to a soil depth of 10 m, the vibration acceleration at soil depths of 20 m and 30 m decreased by 81.3% and 91.7%, respectively. When the soil depth was 10 m, the building was at critical risk of vibration damage.

Global Path Planning of Unmanned Surface Vehicle in Complex Sea Areas Based on Improved Streamline Method

In this paper, an innovative method is proposed to improve the global path planning of Unmanned Surface Vehicles (USV) in complex sea areas, combining fluid mechanic calculations with an improved A* algorithm. This method not only generates smooth paths but also ensures feasible global solutions, significantly enhancing the efficiency and safety of path planning. Firstly, in response to the water depths limitation, this study set up safe water depths, providing strong guarantees for the safe navigation of USVs in complex waters. Secondly, based on the hydrological and geographical characteristics of the study sea area, an accurate ocean environment model was constructed using Ansys Fluent software and computational fluid dynamics (CFD) technology, thus providing USVs with a feasible path solution on a global scale. Then, the local sea area with complex obstacles was converted into a grid map to facilitate detailed planning. Meanwhile, the improved A* algorithm was utilized for meticulous route optimization. Furthermore, by combining the results of local and global planning, the approach generated a comprehensive route that accounts for the complexities of the maritime environment while avoiding local optima. Finally, simulation results demonstrated that the algorithm proposed in this study shows faster pathfinding speed, shorter route distances, and higher route safety compared to other algorithms. Moreover, it remains stable and effective in real-world scenarios.

Effectiveness of respiratory protective equipment in reducing inhalation and contact exposure risks of dental workers during ultrasonic scaling

The high-concentration droplets produced from ultrasonic scaling treatments may carry many pathogens. The close contact between dental workers and patients significantly amplifies their exposure risk to these droplets. Although various types of respiratory protective equipment (RPE) are utilized by dental workers during treatments, their effectiveness in reducing the risks associated with inhalation and contact exposure remains uncertain. In this study, computational fluid dynamics technology was employed to investigate the impact of RPE type, surgery duration, air changes per hour (ACH), and air distribution on the risks related to inhalation and deposition exposure. The results revealed that wearing masks considerably reduced the risk of inhalation exposure for dental workers, with a decrease in inhalation fractions from 25.3 ppm (without RPE) to 1.3–4.5 ppm (with RPE). Combining blue surgical masks and face shields decreased the risk of inhalation fraction by 5% compared to wearing no RPE. Notably, there was over 60% of spray droplets landed on the patient's head; however, only approximately 5%, 6%, 8%, and 3% were deposited on the patient's body, doctor's body, floor, and dental chair, respectively. Increasing ventilation from 3 to 9 ACH decreased dental workers' inhalation fraction by 9.8 ppm. Type III (with the inlet and outlet at opposite walls) decreased the suspension fraction by 4.3% compared with Type II (with the inlet and outlet at the same wall) while achieving a near-zero inhalation fraction of dental workers. These findings offer valuable insights for mitigating cross-infection risks between dental workers and patients in dental clinics.

Noninvasive and fast method of calculation for instantaneous wave-free ratio based on haemodynamics and deep learning

Background and ObjectivesInstantaneous wave-free ratio (iFR) is a new invasive indicator of myocardial ischaemia, and its diagnostic performance is as good as the “gold standard” of myocardial ischaemia diagnosis: fractional flow reserve (FFR). iFR can be approximated by iFRCT, which is calculated based on noninvasive coronary CT angiography (CTA) images and computational fluid dynamics (CFD). However, the existing methods for calculating iFRCT fail to accurately simulate the resting state of the coronary artery, resulting in low computational accuracy. Furthermore, the use of CFD technology limits its computational efficiency, making it difficult to meet clinical application needs. The role of coronary microcirculatory resistance compensation suggests that microcirculatory resistance can be adaptively reduced to compensate for increases in coronary stenotic resistance, thereby maintaining stable myocardial perfusion in the resting state. It is therefore necessary to consider this compensation mechanism to establish a high-fidelity microcirculation resistance model in the resting state in line with human physiology, and so to achieve accurate calculation of iFRCT. MethodsIn this study we successfully collected clinical data, such as FFR, in 205 stenotic vessels from 186 patients with coronary heart disease. A neural network model was established to predict coronary artery stenosis resistance. Based on the compensation mechanism of coronary microcirculation resistance, an iterative solution algorithm for microcirculation resistance in the resting state was developed. Combining the two methods, a simplified single-branch model combining coronary stenosis and microcirculation resistance was established, and the noninvasive and rapid numerical calculation of iFRCT was performed. ResultsThe results showed that the mean squared error (MSE) between the pressure drop predicted by the neural network value for the coronary artery stenosis model and the ground truth in the test set was 0.053 %, and correlation analysis proved that there was a good correlation between them (r = 0.99, p < 0.001). With reference to clinical diagnosis of myocardial ischaemia (using FFR as the gold standard), the diagnostic accuracy of the iFRCT calculation model for the 205 cases was 88.29 % (r = 0.71, p < 0.001), and the total calculation time was < 8 s. ConclusionsThe results of this study demonstrate the utility of a simplified single-branch model in an iFRCT calculation method based on haemodynamics and deep learning, which is important for noninvasive and rapid diagnosis of myocardial ischaemia.

Influencing factors of particle deposition in the human nasal cavity.

To review the existing literature on the application of computational fluid dynamics methods to study nasal particle deposition and to summarize and analyze the factors affecting nasal particle deposition in order to provide theoretical references for the development of future transnasal drug delivery devices and the prevention of respiratory-related diseases. PubMed and CNKI databases. A search of all current literature (up to and including February 2023) was conducted. Search terms related to the topic of factors influencing nasal particle deposition were identified, and queries were conducted to identify relevant articles. Both the properties of the particles themselves and the environmental conditions external to the particles can affect particle deposition in the nasal cavity, with particle deposition showing a positive correlation with particle size, particle density, and airflow velocity, with increasing subject age leading to a decrease in deposition, and with the relationship between airflow temperature and humidity still requiring more research to further explore. With the popularity of computational fluid dynamics, more and more scholars have applied computational fluid dynamics technology to explore the influence of different parameters on particle deposition. By summarizing and analyzing the influence law of various factors on deposition, it can provide a theoretical basis for the future development and application of transnasal drug delivery devices and the prevention of respiratory-related diseases, which makes a significant contribution to the optimization of clinical disease prevention and treatment. NA.

Research on the explosion vent external composite disaster induced by dust explosion inside the dust collector

With the help of computational fluid dynamics (CFD) technology, this research focuses on the quantitative effects of the explosion venting area (S), static opening pressure of the vent (Pstat) and dust cloud concentration (CD) on the explosion overpressure, high-speed airflow and high-temperature flame in the explosion venting zone. The results show that the explosion disaster along the explosion venting zone in general shows an oscillating fluctuating trend of attenuation, and the closer to the explosion vent explosion disaster is more serious. The increase of S will enhance the nonlinear change of explosion disaster, and the change law of explosion overpressure is completely opposite to that of high-speed airflow and high-temperature flame. With the increase of Pstat, the coupling effect of air intake pipe and dust collector is strengthened, which further aggravates the spread of explosion disaster. The change of CD has both promoting and restraining effects on the spread of explosion disaster. The maximum overpressure (P), maximum wind speed (V), maximum flame speed (Fs) and maximum flame distance (Fd) in the explosion venting zone are 0.022 MPa, 494.5 m/s, 112.9 m/s and 10.9 m, respectively, and the venting safety distance is more than 11 m. In addition, the degree of impact on explosion disaster is in the following order: Pstat > A > CD. This research can provide a reference basis for the effective prevention and control of the composite disaster external the explosion vent induced by dust explosion inside the dust collector.

HVAC Design Optimization for Pharmaceutical Facilities with BIM and CFD

Building Information Modeling (BIM) has been widely used in the past decade to enhance the design quality of Heating, Ventilation, and Air Conditioning (HVAC) systems. However, in specialized areas such as pharmaceutical facilities, HVAC design has traditionally relied on Computer-Aided Design (CAD) drawings. This conventional approach does not allow for the simulation of temperature distribution or the verification of system efficiency, which may lead to design failures. To address these challenges in pharmaceutical facilities, this study proposed a BIM-based approach for optimizing HVAC design with Computational Fluid Dynamics (CFD). By employing CFD to simulate the dynamic airflow conditions of pharmaceutical clean rooms, the effectiveness of HVAC systems can be verified. A case study of a clean room HVAC design is presented to demonstrate the workflow. The results of the case study indicated that the pharmaceutical temperature requirements were met within 1 °C during the design optimization simulation, and there was a 95% match in the 72 h temperature mapping test during site validation. The results confirmed that using CFD with BIM not only successfully simulates the design intentions of indoor air quality but also suggests HVAC system optimization for the required clean room design. The findings of this paper contribute to the body of knowledge on overcoming the limitations of the traditional CAD-based HVAC design process and provide valuable insights on optimizing HVAC design with BIM and CFD technologies.

A self-regulation blades wind energy harvester system for self-powered wireless monitoring sensors

Using wind energy in the natural environment provides a promising solution for wireless sensor power supply for ecological, meteorological, environmental, and infrastructure monitoring. However, the uncertainty and disorder of natural wind restrict the further development of wind energy harvester systems and self-powered wireless sensor technology. Hence, this paper proposes a self-regulation blade wind energy harvester system (SBWEHS) for self-powered wireless monitoring sensors in remote field areas with power shortages. The system is mainly composed of three parts: wind harvesting mechanism, generator module, and energy storage module. The device can control the blade overlap ratio according to the wind speed while generating electricity to maximize the power coefficient. The system can control the blade’s closure in bad weather to protect the device. Based on the computational fluid dynamics technology of Ansys Fluent software, this study evaluated the impact of wind speed and blade overlap ratio on the two-stage blades. Experiments revealed that when the overlap ratio of the blades is fixed at 0.2 and the wind speed is set at 16 m/s, the maximum average power will reach 0.79 W, which fulfills the power requirements of wireless sensors. These results illustrate that the SBWEHS can effectively supply power for wireless monitoring sensors, especially in remote natural environments.

Effect of impeller structure on aerodynamic performance and noise reduction of a small multi-blade centrifugal fan

In this study, the numerical simulation and orthogonal test are combined to study the effects of blade outlet angle, blade inlet angle, and blade number on the centrifugal fan flow characteristics, stress distribution, and noise control. The experimental tests were carried out to confirm the accuracy of the computational model. The computational fluid dynamics (CFD) technology was used to establish 16 groups of impeller models and derive the optimal parameter combination form. The results show that the blade inlet angle and outlet angle have more significant effects on efficiency and flow rate of fans. Among different optimize structures, the A8 fan with an inlet angle of 60°, an outlet angle of 180°, and a blade number of 45, has the best aerodynamic performance, with a 17.4% increase in flow rate, a 3.3% increase in efficiency, a 7.6% reduction in noise and a 23.0% reduction in impeller stress, compared to the original fan. Reasonable adjustment of the inlet and outlet angles greatly improves fluid distribution and suppresses flow separation. Furthermore, the noise can be reduced by lessening the disturbance between the volute tongue and wake flow, so the flow state gets greatly improved at the volute tongue region.

Kinetics of pyrolysis and Computational Fluid Dynamics modeling of low metamorphic coal

AbstractThis study explores the low‐temperature pyrolysis kinetic of low metamorphic grade coal from Northern Shaanxi, utilizing Fourier transform infrared (FT‐IR) spectroscopy to analyze the characteristics of various functional groups over a 293–1023 K temperature range. A kinetic model, correlating with the pyrolysis behaviors of these groups, was developed through thermal analysis kinetics. Computational fluid dynamics (CFD) technology simulated the furnace's flow dynamics, allowing an examination of the physical field alterations and functional group evolution during pyrolysis. Results showed that the pyrolysis kinetic functions for aromatic C–H, C=C, C–O, and •OH, along with temperature, pressure, and velocity fields, were successfully integrated into the simulation. This integration provided detailed insights into the temperature profile, pressure distribution, flow velocities, and functional group distribution in the furnace. Aliphatics, exhibiting the largest mass fraction and wide pyrolysis temperature range, and •OH radicals with the highest activation energy were concentrated in the furnace's pyrolysis zone center. C=C's distribution was influenced by aromatic C–H and aliphatics, showing a complementary pattern. The oxygen‐containing groups C–O and C=O had similar pyrolysis mechanisms and uniform distribution. The functional groups' mass fractions were ranked from highest to lowest as follows: aliphatics &gt; •OH &gt; aromatic C–H &gt; C–O &gt; C=C &gt; C=O.

Research on the Postural Stability of Underwater Bottom Platforms with Different Burial Depths.

The bottom platform is an important underwater sensor that can be used in communications, early warning, monitoring, and other fields. It may be affected by earthquakes, winds, waves, and other loads in the working environment, causing changes in posture and affecting its sensing function. Therefore, it is of practical engineering significance to analyze the force conditions and posture changes in the bottom platform. In order to solve the problem of postural stability of the underwater bottom platform, this paper establishes a fluid and structural simulation model of the underwater bottom platform. First, computational fluid dynamics (CFD) technology is used to solve the velocity distribution and forces in the watershed around the bottom platform under a 3 kn ocean current, where the finite element method (FEM) numerical calculation method is used to solve the initial equilibrium state of the bottom platform after it is buried. On this basis, this paper calculates the forces on the bottom platform and the posture of the bottom platform at different burial depths under the action of ocean currents. Additionally, the effects of different burial depths on the maximum displacement, deflection angle, and postural stability of the bottom platform are studied. The calculation results show that when the burial depth is greater than 0.6 m, and the deflection angle of the bottom platform under the action of the 3 kn sea current is less than 5°, the bottom platform can maintain a stable posture. This paper could be used to characterize the postural stability of underwater bottom platforms at different burial depths for the application of underwater sensors in ocean engineering.

FLOATING DOCK ANALYSIS SUBJECT TO DYNAMIC WAVE LOADS USING COMPUTATIONAL FLUID DYNAMICS

Floating dock systems are widely used in marine and waterfront facilities. Environmental loading and movements applied on these systems can be challenging to predict due to the complex interaction between structures and fluids under dynamic wave loads. Design of floating dock systems requires analysis of wave induced forces, relative movements of the dock, effects of connections, and subsequent loads and deflections in piles or mooring line anchors. Supporting structures such as piles or mooring lines can have significant impacts on load distribution within a floating dock system and shall be analyzed carefully during design. Recent advances in computer hardware and multi-physics computational fluid dynamics (CFD) technology have permitted transient dynamic wave analysis of entire floating dock system, to explicitly consider fluid-structure interaction in the analysis and design of floating dock systems. In this study, a CFD technology is applied to investigate the dynamic system characteristics of a floating dock system supported by both piles and mooring lines. CFD analysis is based on software package FLOW-3D® Hydro. Floating dock, piles, and mooring lines are modeled, and analysis results are presented. It is shown to be useful for analyzing floating docks which are typically too complex to accurately evaluate using empirical methods.

FLOATING DOCK ANALYSIS SUBJECT TO DYNAMIC WAVE LOADS USING COMPUTATIONAL FLUID DYNAMICS

Floating dock systems are widely used in marine and waterfront facilities. Environmental loading and movements applied on these systems can be challenging to predict due to the complex interaction between structures and fluids under dynamic wave loads. Design of floating dock systems requires analysis of wave induced forces, relative movements of the dock, effects of connections, and subsequent loads and deflections in piles or mooring line anchors. Supporting structures such as piles or mooring lines can have significant impacts on load distribution within a floating dock system and shall be analyzed carefully during design. Recent advances in computer hardware and multi-physics computational fluid dynamics (CFD) technology have permitted transient dynamic wave analysis of entire floating dock system, to explicitly consider fluid-structure interaction in the analysis and design of floating dock systems. In this study, a CFD technology is applied to investigate the dynamic system characteristics of a floating dock system supported by both piles and mooring lines. CFD analysis is based on software package FLOW-3D® Hydro. Floating dock, piles, and mooring lines are modeled, and analysis results are presented. It is shown to be useful for analyzing floating docks which are typically too complex to accurately evaluate using empirical methods.

An efficient aerodynamic optimization method based on approximate gradient analysis

With the rapid development of the computer capability and the continuous improvement of CFD (Computational Fluid Dynamics) technology, optimization design has gradually become a powerful and reliable means to solve the aerodynamic design problems. Among all kinds of optimization methods, gradient-based optimization algorithm can find the local optimal solution quickly, which is widely used in engineering problems. However, the computation of gradient is very expensive when an engineering problem involves large number of design variables. In this paper, an optimization method based on approximate gradient analysis is introduced, where the one-dimensional linear searches during the optimization process are evaluated with high-fidelity flow field analyses, while the gradients are evaluated with low-fidelity flow field analyses, leading to a significant saving in the computational cost of high-fidelity analysis. This method is demonstrated using a numerical example and RAE2822 airfoil optimization, and it is finally applied to the aerodynamic optimization of a wing-body configuration, which obtains good optimization results.

Mechanism of respiratory protective equipment in controlling wearer’s exhaled pollutants

Respiratory protective equipment (RPE) filters and blocks exhaled pollutants to prevent their forward movement, protecting the directly exposed individuals and products. Two mechanisms of RPE in controlling wearer's exhaled pollutants, namely filtering and blocking, were examined. Leakage ratio was firstly proposed to evaluate the relative strength of leakage via gaps and leakage via face mask’s surface. Influence of various factors on the two mechanisms was investigated using validated Computational Fluid Dynamics (CFD) technology. The leakage ratio of 0.1–10 μm particles (i.e., 2–36) is generally larger than that of CO2 (i.e., 0.1–10), suggesting that face masks have a stronger blocking effect on the particles compared to the gaseous pollutants. Decreasing the initial velocity of exhaled air and increasing the diameter of exhaled particles, gap’s area, and viscous resistance of face mask’s surface increase the leakage ratio. When the viscous resistance increases from 4.34 × 106 to 4.34 × 1010, the leakage ratios of CO2 and particles increase by 4 and 23, respectively. When the initial velocity increases from 2.7 to 15 m/s, the leakage ratios of CO2 and particles decrease by 2.5 and 19, respectively. Wearing ordinary face masks alone cannot completely prevent the dispersion of exhaled pollutants, it is recommended to combine face masks with well-designed indoor ventilation to jointly control exhaled pollutants. The obtained data establishes a foundation for understanding the mechanism by which face masks control exhaled pollutants, which assists in the improvement of RPE and the formulation of effective measures to protect individuals and products directly exposed.

Harnessing CFD simulations and CAD design to optimize hydropower efficiency of a propeller turbine in the Maliringan River: acase study

This research focuses on improving hydropower production by designing a turbine for the MaliringanRiver in Kalimantan Selatan. The rotational speed and torque will be the focus of maximizing power generation. This research used Computational Fluid Dynamics (CFD) to understand how the fluid flows and how efficiently the turbine works. The simulations helped us see how the fluid flowed, the pressure differences, and the speed of the water inside the turbine. The software COMSOL Multiphysics imitates how the fluid behaves and interacts in real-life situations. The utilization of SOLIDWORKS played a crucial role in the turbine's design process, facilitating an accurate representation of the turbine's geometry and the subsequent fabrication of a prototype propeller turbine, featuring an outer diameter measuring 0.27 meters and an inner diameter measuring 0.113 meters. The methodology resulted in a power efficiency of 76.45%, showcasing the possibility of significant enhancements in the efficiency of hydropower generation. The broader ramifications of this study emphasize the feasibility of tailor-made turbines for local hydropower initiatives, thereby supporting Indonesia's renewable energy plan by providing sustainable and efficient energy alternatives. This study emphasizes the collaborative utilization of Computer-Aided Design (CAD) and CFD technologies in the progression of turbine technology, thereby establishing a basis for future investigations in hydropower optimization.