Computational Fluid Dynamics Technology Research Articles

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 > •OH > aromatic C–H > C–O > C=C > 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.

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.

Statement of requirements on the accuracy of rocket CFD analysis using exterior ballistics for example rocket models

In this paper, the problem of acceptable accuracy of a rocket’s aerodynamic characteristics obtained from CFD (computational fluid dynamics) analysis for defining its aerodynamic characteristics is considered from the point of view of exterior ballistics, particularly by the estimation of the rocket’s simulated flight range change caused by CFD errors. The results obtained in this paper allow stating the requirement on acceptable accuracy of defining the aerodynamic characteristics for developing new rockets through CFD analysis based on several examples, which can be propagated to other cases of rocket design and development. Using this study as a method, the CFD engineers who work on rocket design and development can estimate the accepted accuracy margin of their CFD analysis and research solutions to get reliable results for the expected flight characteristics of the rocket.

Effect of hydrogen ratio on leakage and explosion characteristics of hydrogen-blended natural gas in utility tunnels

Based on computational fluid dynamics technology, the effect of hydrogen blending ratio (HBR) on the concentration distribution of leaked gas diffusion in utility tunnels was investigated, and based on this, the explosion characteristics of hydrogen-blended natural gas (HBNG) were studied in an inhomogeneous concentration field. The results showed that the concentration field of HBNG gradually stabilized in the downstream of the leak site, and the peak concentration increased linearly with HBR. When HBR≤5%, a high concentration region above the upper explosive limit is formed inside the gas cloud. This characteristic of the distribution induces secondary combustion in utility tunnels. The maximum flame velocity and steady acceleration distance increase with the increase of HBR. The flame shape is significantly affected by the concentration field distribution. The explosion overpressure induced by the real concentration field created multiple peak structures that exacerbated the explosion disaster complexity. The first overpressure peak at the ends was formed by the superposition of the precursor shock wave and its reflected wave, and those at other locations are caused by the shock waves. However, all maximum overpressure peaks are formed by the superposition of multiple reflections of the explosion wave. The maximum peak overpressure at both ends of the tunnel is higher than that in the middle. The explosion overpressure induced by the inhomogeneous gas cloud is lower than that caused by homogeneous gas cloud under the same volume. The research results can provide an effective reference for the anti-explosion design and risk assessment of utility tunnel.

Modeling and theoretical exploration of free surface manifestation of submarines in presence and absence of ocean waves

Maritime surveillance using remote-sensing images is one of the emerging technologies. Because of the inaccessibility of real-time remote-sensing images, it is imperative to model them. The main intention of this study is to investigate the factors influencing the detection of submarines, irrespective of the imaging sensors. In the present work, submarine wakes (Bernoulli hump and Kelvin wake) are modeled and integrated with the sea surface to examine the key features of the submarine. Here, the sea surface is simulated by linear Airy theory using the Elfouhaily spectrum, and novel submarine position projection in imaging coordinate (SPPIC) technique is introduced to generate synthetic free surface wakes in different orientations. Besides, Computational Fluid Dynamics (CFD) technology is utilized to assess and endorse the SPPIC-based simulated wake models. The Beaufort scale is used to validate the modeled sea surface, and the root mean square error of the model is 0.314 m. Then, the simulated submarine wakes are verified by analyzing its essential features and extracting the significant parameters of submarine, such as moving velocity, heading angle, and diving depth. Further, the current research explores these significant characteristics in the context of ocean waves. The Fourier transform technique is employed to retrieve the heading angle and velocity of the submarine. The introduction of variance distribution in the Radon transform method resolves the 180⁰ ambiguity problem in heading angle calculation. Additionally, negative exponential relation is established between the diving depth of the submarine and the height of the Bernoulli hump. From this empirical equation, one can fetch the diving depth of the submarine. The discrete wavelet transform approach enhances the edges of the wedge Kelvin wake in the presence of sea waves and is demonstrated with real-time synthetic aperture radar images. Moreover, primary wake features are investigated and evaluated for different classes of submarines.

Optimization of pump transient energy characteristics based on response surface optimization model and computational fluid dynamics

The global energy shortage is increasingly becoming a problem of major concern worldwide. Since the pumps represent the largest part in the energy conversion devices, improving their energy characteristics is very important for energy conservation and efficiecy. However, the traditional pump design methods have generally overlooked the transient flow characteristics inside the pumps leading to high hydraulic losses and low operatinal efficiency, especially in applications that have pronounced transient effects. To address this problem, a novel approach is proposed in this paper which combines the response surface optimization method with the computational fluid dynamics (CFD) technology to optimize the energy characteristics of pumps during the transient processes. The main objective of the study is to enhance the internal flow state and the transient energy performance of the pump during the start-up process. A comparative analysis is conducted on the energy characteristics and the internal flow field of a model pump before and after the optimization, thereby validating the effectiveness of the proposed energy characteristics optimization method. The numerical results reveal that the inlet placement angle (α), the outlet placement angle (β), the blade envelope angle (φ), and the blade thickness coefficient (θ) significantly impact the weighted average head and weighted average efficiency of the pump. After optimization, the weighted average head and the weighted average efficiency of the pump increase by 2.97% and 8.91% respectively, while the transient efficiency of the pump at all times surpasses that of the traditional, non-otimized design approach. These research findings provide valuable insights for enhancing the performance of the pumps oerating in the transient flow conditions.

Impact of the Structural Parameters on the Performance of a Regenerative-Type Hydrogen Recirculation Blower for Vehicular Proton Exchange Membrane Fuel Cells

The compact structure and stable performance of regenerative blowers at small flow rates render them attractive for the development of hydrogen recirculation devices for fuel cells. However, its optimization of structural parameters has not been yet reported in the literature. Along these lines, in this work, a mechanistic study was carried out in terms of examining the role of the flow channel structure on the performance of a regenerative-type hydrogen recirculation blower for the fabrication of automotive fuel cells. A three-dimensional computational fluid dynamics (CFDs) model of the regenerative blower was established, and the accuracy of the proposed model was verified through experimental data. The impact of structural parameter interactions on the performance of the regenerative blower was investigated using CFD technology, response surface methodology (RSM), and genetic algorithm (GA). First, the range of the structural parameters was selected according to the actual operation, and the influence of a single geometric factor on the efficiency was thoroughly investigated using CFD simulation. Then, a second-order regression model was successfully established using RSM. The response surface model was solved using GA to obtain the optimized geometric parameters and the reliability of the GA optimization was verified by performing CFD simulations. From our analysis, it was demonstrated that the interaction of the blade angle and impeller inner diameter has a significant impact on efficiency. The entropy generation analysis showed also that the internal flow loss of the optimized regenerative blower was significantly reduced, and the design point efficiency reached 51.7%, which was significantly improved. Our work provides a novel solution for the design of a recirculation blower and offers a reference for the optimization of regenerative-type hydrogen blowers.

Optimized design of smart toilet spray bar flow channel based on CFD

Currently, there are significant issues with the intelligent toilets available on the market, such as a large swing of the spray bar when spraying water column and eccentricity. This paper presents four optimization schemes for the intelligent toilet spray bar channel by analysing and redesigning a specific model. Computational Fluid Dynamics (CFD) technology was employed to analyse the water flow conditions inside the spray bar of the intelligent toilet. The calculation results indicate that for the same water inlet flow rate, the optimal structure in optimization scheme 1 is the block with a length (L) of 1.5 mm. In optimization scheme 2, the optimal structure is the block located at position (3). In optimization scheme 3, the optimal structure is a 15° rotation, which exhibits the least swirls and pressure loss while maintaining the prototype structure. When the prototype structure is modified, the optimal structure in optimization scheme 4 is the excision bend pipe. This structure exhibits the lowest swirl number and pressure loss among all the optimization schemes. The determined structure offers valuable insights for enhancing the flow characteristics of the improved product.

Optimized design of steam ejector primary nozzle based on orthogonal test method

This paper proposes an orthogonal test method to optimize the design parameters of a steam ejector. The objective of this method is to improve the cooling system’s efficiency and effectiveness. The L9(33) orthogonal table was established to simultaneously optimize the shape curve of the converging portion of the primary nozzle, the length of the throat, and the angle of the diverging portion, and the entrainment rate and the critical backpressure were used as the performance indexes to formulate 9 groups of test schemes with a total of 108 cases, which were simulated under the same conditions. Based on Computational Fluid Dynamics (CFD) technology, the influence order of the three parameters is derived by polar analysis and the flow field is analyzed at the overall as well as the primary nozzle. The results show that the shape curve of converging portion of the primary nozzle is a sensitive factor affecting the performance of the ejector, which should be emphasized in practical production applications; the Mach number shapes at the primary nozzles of different structures show similarity and overlap at a distance of about 0.03 m from the mixing chamber. The Mach number profiles at different back pressures show want similarity.

Modeling analysis and experiment for energy system of ocean energy driven unmanned marine vehicle: The Yulang II case study

AbstractIt is critical to master a marine robot's energy system characteristics adequately to ensure that the robot can perform long‐endurance tasks in complex and ever‐changing marine environments. This paper presents, for the first time, an energy system modeling and analysis method for a marine robot driven by wind, solar, and wave composite energy, using Yulang II as an example. First, an onshore experiment method was designed, and then the conversion experiment of wind, sunlight, and electrical energy was carried out based on that experiment method. At the same time, based on computational fluid dynamics technology, a resistance pole curve considering wave energy capture is constructed. In addition, the attitude, relative motion, and battery constraints of the robot in the ocean are analyzed to construct the energy system model of Yulang II. Finally, the method and model proposed in this paper were compared and verified by simulation and field tests. The results indicated that the corrected forecast deviation was 5.71% in the typical marine environment of the experiment, which supported the study of ocean energy‐driven unmanned marine vehicles strongly.

Rapid prediction of indoor airflow field using operator neural network with small dataset

Indoor airflow is one of the most critical factors affecting room comfort. The accurate prediction of indoor airflow fields is essential for efficient environmental control. However, representative methods for calculating indoor airflow organization, such as computational fluid dynamics (CFD), are complex and time consuming. Therefore, this study proposes a machine learning approach that can rapidly reconstruct indoor airflow fields. This method employs an improved deep operator network (DeepONet) and a Fourier neural operator (FNO) neural network to learn a set of solutions to a problem resembling a flow field and then realizes an accuracy-preserving prediction of an unseen domain. First, we decompose the computational domain into subdomains and then reconstruct the flow field for the subdomains. Subsequently, the subdomains are stitched into the original computational domain. Using data enhancement techniques along with a small dataset, this method achieves satisfactory training results. The results indicate that for a two-dimensional isothermal flow field problem, both the improved DeepONet and FNO models accurately reconstruct the flow field. The mean squared errors are 0.28% and 1.89% for the improved DeepONet and FNO models, respectively, with both requiring less than 0.01s. This method does not require repeated training under different operating conditions, which significantly reduces the computation time. Compared with conventional CFD technology, the proposed method improves the speed by up to three to six orders of magnitude.

Research on the hydroelastic response of ice floes and wave scattering field

Abstract The marginal ice zone (MIZ) is the area between sea ice and open water, the structure of which is mainly determined by wave and ice interactions. Thus mastering the characteristics of MIZ is of great significance to the Arctic routes opening and the natural resources development. In this paper, the hydroelastic response of ice floes in waves is studied, a three-dimensional numerical wave tank is established based on the computational fluid dynamics (CFD) technology. The finite volume method (FVM) and finite element method (FEM) are respectively utilized for discrete fluid domain and ice domain. A mapping interface at the junction of the fluid and ice floes domains is created to perform data mapping by the shape function interpolation method and the least square method. This work presents a series of numerical simulations to study the fluid-solid interaction (FSI) of waves and ice floes. Under the given incident wave parameters, the vertical bending deformation of ice floes with different shapes under the excitation of waves, the effect of ice floes' deformation on the wave field are studied, and the effect of wave overwash on the transmitted wave field is emphasized. Results show that the shape of the ice floes significantly affects its elastic deformation and scattered wave field, and the wave overwash phenomenon attenuates the scattering wave.

A comprehensive approach to prediction of fractional flow reserve from deep-learning-augmented model

The underuse of invasive fractional flow reserve (FFR) in clinical practice has motivated research towards non-invasive prediction of FFR. Although the non-invasive derivation of FFR (FFRCT) using computational fluid dynamics (CFD) principles has become a common practice, its clinical application has been limited due to the considerable time required for computation of resulting changes in haemodynamic conditions. An alternative to CFD technology is incorporating a neural network into the computational process to reduce the time necessary for running an effective model.In this study we propose a cascade of data-driven and physic-based neural networks (DP-NN) for predicting FFR (DL-FFRCT). The first network of cascade network DP-NN includes geometric features, and the second network includes physical features. We compare the differences between data-driven neural network (D-NN) and DP-NN for predicting FFR. The training and testing datasets were obtained by solving the three-dimensional incompressible Navier–Stokes equations. Coronary flow and geometric features were used as inputs to train D-NN. In DP-NN the training process involves first training a D-NN to output resting ΔP as one input feature to the DP-NN. Secondly, the physics-based microcirculatory resistance as another input feature to the DP-NN.Using clinically measured FFR as the “gold standard", we validated the computational accuracy of DL-FFRCT in 77 patients. Compared to D-NN, DP-NN improved the prediction of ΔP (R2 = 0.87 vs. R2 = 0.92). Statistical analysis demonstrated that the diagnostic accuracy of DL-FFRCT was not inferior to FFRCT (85.71 % vs. 88.3 %) and the computational time was reduced by a factor of approximately 3000 (4.26 s vs. 3.5 h).DP-NN represents a near real-time, interpretable, and highly accurate deep-learning network, which contributes to the development of high-performance computational methods for haemodynamics. We anticipate that DP-NN will enable near real-time prediction of DL-FFRCT in personalized narrow blood vessels and provide guidance for cardiovascular disease treatments.

Performance Enhancement of Falling Film Dehumidifier by Variation Number and Width Ratio Rectangular Cylinder Based on CFD Simulation

The implementation of computational fluid dynamics (CFD) technologies has grown popular in various engineering fields to solve problems because it has high efficiency, affordable cost, and requires a relatively short time. This study examines the effect of adding a rectangular cylinder to a falling film dehumidifier with modifications to the geometry of the width ratio and the number of rectangular cylinders. Model without rectangular cylinder variations and three width ratio variations of 0.1D; 0.5D; D with two variations of the number of rectangular cylinders will be simulated under isothermal conditions for the process of mass transfer, distribution of water vapor mass fraction, pressure drop, turbulence intensity, temperature, and dehumidifier performance. The RNG k-ε turbulence model is used to simulate fluid flow with the addition of a user-defined function (UDF). Significant results can be seen in the distribution of water vapor mass fraction in the geometry modification with the addition of a rectangular cylinder with mass transfer enhancement of 12.4 – 13.4% compared to no geometry modification. High Wa,in with variation C is more effective in minimizing the pressure drop of moist airflow. Vortex flow is formed behind the rectangular cylinder, which increases the mass transfer around the flow. The turbulence intensity appears near the liquid desiccant solution and the rectangular cylinder with a value of 33%. The best geometry variation design shows a dehumidification effectiveness value of 36.8%, 3.3 – 3.8% greater than the design without geometry variations.

Large‐scale homo‐ and heterogeneous parallel paradigm design based on CFD application PHengLEI

SummaryThe development of computational fluid dynamics (CFD) highly depends on high‐performance computers. Computer hardware has evolved rapidly, yet scalable CFD parallel software remains scarce. In this article, we design a highly scalable CFD parallel paradigm for both homogeneous and heterogeneous supercomputers. The paradigm achieves the separation of communication and computation and automatically adapts to various solvers and hardware environments, thus reducing programming difficulties and increasing automatic parallelization. Meanwhile, the number of communications is greatly reduced and the scalability of the program is improved through implementing centralized communication and two‐level partitioning techniques. Complex flow problems for real aircraft were then computed on different hardware platforms with a grid size of ten billion. The homogeneous computer hardware includes Intel Xeon Gold 6258R and Phytium 2000+ processors, and the heterogeneous computer platforms include NVIDIA Tesla V100 and SW26010 processors. High parallel efficiency was obtained on all computer platforms, verifying that the paradigm has good automatic parallelization, scalability, and stability. The paradigm in this article has an important reference value for CFD massively parallel computing and can promote the development and application of CFD technology.

Flushing effect of micro-bolus pulse injection and its potential impact on peripheral veins under hemostasis.

To explore the feasibility of using micro-bolus pulse injection method to reduce the dilution effect of pipeline on high concentration injection, and to understand low liquid volume bolus injection based on low injection speed. Using a programmable pulse injection pump, a 25-cm - long pipeline containing water-soluble fluorescent agent was flushed using different volumes of bolus, and the time spent for the complete disappearance of the fluorescent agent was recorded to evaluate the flushing efficiency. The finite element simulation of 2-phase flow was carried out using computational fluid dynamics (CFD) technology, and the difference of shear rate and pressure distribution in the vein of pulse injection and direct injection of bolus under hemostasis was compared and simulated. Micro-bolus pulse flushing has advantages in completing perfusion imaging applications, such as small volume imaging agent injection. Compared with non-pulse injection, the effective flushing volume decreases by 49.7%, the average injection speed decreases by 56%, and the maintenance time of high shear rate is shorter when using micro-bolus pulse injection. The impact of micro-bolus pulse injection on the vein can achieve the same or even lower negative effects as other injection methods after increasing the hemostatic distance to 100 mm. In the case of bolus injection requiring high concentration and small volume, such as for radiopharmaceutical dynamic imaging, the application of micro-bolus pulse injection is an effective way to overcome the dilution phenomenon of the imaging agent in the pipeline. During hemostasis, the micro-bolus pulse injection needs to control a longer hemostasis distance to reduce the potential impact on peripheral veins.