Dual-Solver Hybrid Computational Approach to Integrated Propulsion Aerodynamics

An analytical jet spread model has been developed for determining the boundary of an axisymmetric jet ejecting into a two-fluid, coflowing stream. When the circumferential velocity of the jet is assumed to be small, the model can be coupled with the conventional computational fluid dynamics (CFD) method for simulation of the fuel dumping from an aircraft. Application of the model is demonstrated by considering the fuel dumping from a V-22 aircraft flying at Mach 0.345 and angles of attack from 7 and 16 deg. The model provides a first-order correction to the CFD simulated results with the jet dispersion boundaries to yield an integrated solution that represents a realistic aircraft fuel dumping environment. UMPING excessive fuel from an aircraft before landing may be necessary due to safety concerns. During fuel dumping, massive fuel can be successfully dumped without any contact be- tween the fuel jet and the aircraft surface. Fuel mist, which is caused by the thickening of the fuel jet boundary, may impinge onto the aircraft even though the main fuel stream does not touch the surface. The thickening of the jet boundary is commonly known as the jet dispersion, the jet spread, or the jet entrainment. It consists of par- ticles of the surrounding medium carried along with it and particles of the jet itself that have been slowed down. To avoid any fuel and/or fuel mist impingement onto any part of the aircraft surface during dumping, the geometry of the fuel jettison probe (FJP) must be properly designed and its location carefully de- termined. This is an important aerodynamic issue requiring resolu- tion by combining the results from wind-tunnel tests, computational fluid dynamics (CFD) simulations, and flight tests. The role of the CFD simulation is to provide an initial design study regarding the FJP geometry configuration, jet orientation, and its location on the aircraft, and also to gain insights into the complex flowfield about a complete aircraft with the FJP for fuel jettison. The problem is complicated not only by the complex geometry, but also the fuel jet characteristics due to jet dispersion. The jet dispersion, or the jet spread, is a subproblem that is embedded in the overall flowfield. It must be accounted for if the simulation truly represents a realistic aircraft fuel dumping environment. Unfortunately, the present capability of the conventional CFD method 1−4 lacks the ability to solve the whole problem in one formulation. The problem would have to be solved separately for the aircraft flowfield and for the embedded jet flow and then coupled together to yield an overall solution that depicts the physical problem. In the present paper, an analytical jet spread model for the fuel dispersion is proposed and described. The model can be coupled with the conventional, Navier-Stokes solution-based CFD method for simulation of the aircraft fuel dumping. The coupling is per- formed by a first-order correction in which the jet boundary due to the jet spread is calculated based on the simulated flowfield, but the flowfield is not updated by the presence of the jet volume. Al- though the work is specially aimed at the V-22 aircraft fuel dumping,

Lattice Boltzmann methods (LBM) is a class of computational fluid dynamics (CFD) methods for fluid simulation. Instead of solving the Navier–Stokes equations directly, a fluid density on a lattice is simulated with streaming and collision (relaxation) processes The method is versatile as the model fluid can straight forwardly be made to mimic common fluid behavior like vapor/liquid coexistence, and so fluid systems such as liquid droplets can be simulated. LBM is a relatively new simulation technique for complex fluid systems and has attracted interest from researchers in computational physics. Unlike the traditional CFD methods, which solve the conservation equations of macroscopic properties (i.e., mass, momentum, and energy) numerically, LBM models the fluid consisting of fictive particles, and such particles perform consecutive propagation and collision processes over a discrete lattice. Due to its particulate nature and local dynamics, LBM has several advantages over other conventional CFD methods, especially in dealing with complex boundaries, incorporating microscopic interactions, and parallelization of the algorithm.

As Computational Fluid Dynamics (CFD) methods evolve and mature, more engineering problems are being solved through computer simulation to reduce reliance on the costly and time-consuming experimental methods. This trend is also occurring in the gear manufacturing industry, where an increasing number of quality issues related to the oil quenching process are being investigated by CFD methods to find solutions. However, while the CFD theory and numerical methods have made significant advancements, gaps still exist between the academic research and industrial applications. In the case of the oil quenching processes, the prospect of using CFD methods to visualize and study the oil flow pattern in the gear quenching tank is promising yet challenging. The obstacle to simulating the oil quenching process using CFD methods lies not in the numerical method itself for solving the Navier-Stokes equation, but in building a computer simulation model that encompasses all the geometrical details of the quenching tank, fixtures, centrifugal pumps, and gears, including all the gear teeth. This task is particularly challenging for Finite Volume Method (FVM) CFD solvers, as the computation mesh could take days or weeks to build. In this research, a new solution method based on Smoothed Particle Hydrodynamics (SPH) is introduced to simulate the oil flow in the gear quenching tank. Since SPH is a mesh-free Lagrangian method, it not only greatly simplifies the mesh generation task for building the computational models but also handles the complex physics of the free surface flow and fluid-structure interaction with great ease. In addition, the oil flow in the gear quenching tank usually is driven by centrifugal pumps whose dynamics can be simulated directly in SPH methods, as opposed to FVM methods which require complicated moving mesh computation.

Aerodynamic characteristics of a guided rocket projectile are numerically simulated. Simulations are performed in a range of flight conditions using a commercial CFD software FLUENT, and variations of lift coefficients and drag coefficients with Mach numbers and angles of attack were demonstrated. The numerical results also indicate that the angle of canard deflection has significant influence on the flow field near tailfins.

Emergency condition should be evaluated during the siting of Nuclear Power Plants (NPP). One of the criteria is the capability of emergency evacuation for the purpose of protecting the NPP staff and public. Exposure dose received by evacuees is a key factor to evaluate the effectiveness of emergency evacuation, which can be characterized by the atmospheric dispersion factors over the evacuation paths. Gaussian plume model is usually applied in the atmospheric dispersion factor calculation for NPPs. However, for some NPP sites with complex terrain like mountain and lake which has significant influence on the local flow field and the nuclides transportation, the calculations based on Gaussian model will not be accurate enough for the evaluation of the evacuation capability. In such cases, Computational Fluid Dynamics (CFD) method with fine calculation grids and rich physical models can be used in the atmospheric dispersion modeling of small-scale region, to get much more accurate results. This paper is devoted to the research on the impact of these complex terrain on atmospheric dispersion with CFD method. The local atmospheric dispersion around a NPP site located on an island is modeled, where there is a mountain on the way of evacuation. For the limitation of the geographic barrier, two evacuation paths, which are located closely with small difference in direction, are planned along different sides of the mountain. Utilizing STAR-CCM+ CFD software, local atmospheric dispersion factors are fine simulated under six worse wind directions. Based on the simulation results, the impact of the mountain on the flow field and of the radiological plume on the evacuation paths is analyzed. Results show that due to the blocking effect of the mountain, those two evacuation paths have little probability to be simultaneously covered by the radiological plume. By the choosing of suitable routes during the evacuation, the radiological risk of public is acceptable and emergency evacuation can be carried out effectively. These results also demonstrate that CFD modeling method is effective in the evaluation of local atmospheric dispersion over complex terrain, which can be applied in the analysis of emergency evacuation of NPP sites with complex terrain.

Computational modelling and experimental validation of drug entrainment in a dry powder inhaler

This paper implements the parameter identification of ship roll motion based on vibration tests and the computational fluid dynamics (CFD) method. By applying sinusoidal moment excitations from a shaker, we successfully simulate the quasi-roll motion behavior of the ship model in the air. We conduct two vibration tests, including a constant-amplitude angular displacement test and a constant-amplitude angular velocity test, to identify the restoring moment and the damping moment coefficients of the quasi-roll motion. In addition, we perform the approximate equivalence of the fluid around the ship through the CFD method and the fluid-solid coupling technique. Thus, we obtain the hydrodynamic coefficients, such as the added mass moment of inertia and the equivalent damping, to accomplish the parameter identification of the ship’s real roll motion. Finally, the accuracy of the identified parameters is verified by means of numerical simulations based on the Runge–Kutta method.

Fires in underground metal mines pose significant risks to worker safety and operational continuity. This study analyses the performance of the ventilation system after a fire in an underground metal mine using the Computa-tional Fluid Dynamics (CFD) method. Three different fire scenarios were modelled, examining temperature distri-bution, toxic gas dispersion, and airflow dynamics during the fire. Simulation results reveal how the fire spreads in other areas and assess the efficiency of the existing ventilation system. Findings indicate that the ventilation system is insufficient in certain areas for smoke extraction, and the post-fire gas clearance process varies across different locations. In particular, the positioning of auxiliary fans and the airflow direction are key factors in determining the spread of smoke after a fire. Based on these analyses, optimising post-fire ventilation strategies and enhancing emergency action plans are recommended. This study highlights the critical role of CFD analyses in the mining in-dustry in improving safety and efficiency and contributes to developing safer underground mine ventilation sys-tems. Furthermore, this study stands to make a substantial impact on the practical implementation of the "ventila-tion on demand" concept, advancing our understanding and application of this critical approach. On the other hand, the most important result of this study is that an underground mine with a very large volume is subject to cdf analysis as a whole. Because it is the first study to reveal that the direction of air flow changes as a fire in any part of the mine changes the thermodynamic conditions of the entire mine.

This study designed a vertical take-off and landing tailsitter unmanned aerial vehicle (UAV) with a long endurance time. Nine parameters of the tailsitter UAV were investigated. Using a 2k full factorial test, 512 experiments on the nine parameters were conducted at their maximum and minimum values. The time coefficient and air resistance were calculated using the computational fluid dynamics (CFD) method under different parameter combinations. The analysis of variance determined that the specific factors influencing the time coefficient and air resistance were the root chord, wingtip chord, wingspan, and sweep angle. By carrying out a central composite design (CCD) test, 25 sample points of the four particular factors were constructed. The time coefficient and air resistance were simulated under different structural parameter combinations using the CFD method. CFD simulation was verified by carrying out a wind tunnel test, and the results revealed that the aerodynamic coefficient error was less than 5%, while the air resistance error was less than 6%. The response surface methodology (RSM) for the time coefficient and air resistance was established using a genetic aggregation method. A multi-objective genetic algorithm (MOGA) was used to optimize the parameters with regard to the maximum time coefficient and minimum air resistance. The optimal structural parameters were wing root chord length at 315 mm, wingtip chord length at 182 mm, wingspan length at 1198 mm, and sweep angle at 16°. Compared with the original layout and size, the time coefficient of the new design of the tailsitter UAV improved by 19.5%, while the air resistance reduced by 34.78%. The results obtained by this study are significant for the design of tailsitter UAVs.

The heat dissipation of electronic elements in a mini-space is investigated by using Computational Fluid Dynamics (CFD) methods in this paper. The velocity and temperature fields of mini-space are simulated on the condition of several schemes with air as fluid. The synergetic effects of temperature and velocity field for mini-space have been analyzed by field coordination principle. Then a cooling effect number has been put forward to evaluate the cooling effects of electronic elements. The optimized scheme of mini-space has been obtained by comparing the cooling effect number of different schemes, which has established a solid foundation for discussing the cooling techniques of micro-electronic elements further.

In order to correct the solar radiation error of relative humidity, the mainstream capacitive sounding humidity sensor HC103M2 is selected and investigated by simulation analysis and experimental verification. First, the basic theories for solar radiation error and sensor error itself are elaborated, and simulational and experimental platforms are introduced. The computational fluid dynamics (CFD) method is utilized to theoretically investigate the dry error of the humidity sensor caused by solar radiation heating, which is related to radiation intensity, altitude, and solar elevation angle as well as reflectivity, thickness, and shape of the shield. Then, in order to verify the accuracy of the simulation, an experimental platform including a humidity sensor and two temperature sensors to measure the solar radiation heating is built to analyze the relative error of humidity obtained by the CFD simulation and experiment. It is found that their maximum deviation is 3.30% and the average error is 1.94%, which indicates that the calculation using the CFD method is accurate and feasible. In order to easily and operationally predict the solar radiation heating of the humidity sensor, a back propagation (BP) neural network fusion algorithm based on three inputs of radiation intensity, air pressure, and solar elevation angle is proposed. Compared with the solar radiation heating obtained by CFD simulation, the maximum absolute error is about 0.2K, and the relative error of humidity is about ±1.30%. Finally, a case of vertical humidity profile correction considering the temperature-sensitive error of HC103M2 is analyzed. The response time of sensor measurement and the airflow into the shield are discussed as well. The corrected results after taking solar radiation heating into account are more similar to those measured by RS92 and cryogenic frost point hygrometer (CFH). This result shows that the prediction model is accurate, which may be applied to correct the dry error and further improve the accuracy of humidity measurement.

With the development of the wind power industry, wind turbine blades are increasingly adopting ultra-large-scale designs. However, as the size of blades continues to increase, existing aerodynamic calculation methods struggle to achieve both relatively high computational accuracy and efficiency simultaneously. To tackle this challenge, this research focuses on the low accuracy issues of the traditional Blade Element Momentum theory (BEM) in predicting the aerodynamic performance of wind turbine blades. Consequently, a correction framework is proposed, to integrate the Computational Fluid Dynamics (CFD) method with the Multilayer Perceptron (MLP) neural network. In this approach, the CFD method is used to predict the airflow characteristics around the blades, and the MLP neural network is employed to model the intricate functional relationships between multiple influencing factors and key aerodynamic parameters. This process results in high-precision predictive functions for key aerodynamic parameters, which are then used to correct the traditional BEM. When this correction framework is applied to the rotor of the IEA 15 MW wind turbine, the effectiveness of MLP in predicting key aerodynamic parameters is demonstrated. The research findings suggest that this framework can enhance the accuracy of BEM aerodynamic load predictions to a level comparable to that of RANS.

Tracheal Bronchus (TB) is a rare congenital anomaly characterized by the presence of an abnormal bronchus originating from the trachea or main bronchi and directed toward the upper lobe. The airflow pattern in tracheobronchial trees of TB subjects is critical, but has not been systemically studied. This study proposes to simulate the airflow using CT image based models and the computational fluid dynamics (CFD) method. Six TB subjects and three health controls (HC) are included. After the geometric model of tracheobronchial tree is extracted from CT images, the spatial distribution of velocity, wall pressure, wall shear stress (WSS) is obtained through CFD simulation, and the lobar distribution of air, flow pattern and global pressure drop are investigated. Compared with HC subjects, the main bronchus angle of TB subjects and the variation of volume are large, while the cross-sectional growth rate is small. High airflow velocity, wall pressure, and WSS are observed locally at the tracheal bronchus, but the global patterns of these measures are still similar to those of HC. The ratio of airflow into the tracheal bronchus accounts for 6.6-15.6% of the inhaled airflow, decreasing the ratio to the right upper lobe from 15.7-21.4% (HC) to 4.9-13.6%. The air into tracheal bronchus originates from the right dorsal near-wall region of the trachea. Tracheal bronchus does not change the global pressure drop which is dependent on multiple variables. Though the tracheobronchial trees of TB subjects present individualized features, several commonalities on the structural and airflow characteristics can be revealed. The observed local alternations might provide new insight into the reason of recurrent local infections, cough and acute respiratory distress related to TB.

Through the combination of experimental measurement and CFD (computational fluid dynamics) method, the fluid flow characteristics in the pipe of magnetic capsule robot for intestinal tract are studied. The PIV (particle imaging velocimetry) system is used to measure the fluid flow field around the magnetic-controlled capsule robot under certain translational and rotational speeds, and the rich flow field information (streamline, velocity, and vorticity) is obtained. At the same time, the CFD software is used to calculate the corresponding flow field and the force acting on the capsule robot, and the calculated value is basically consistent with the experimental value. The results show that, driven by the external permanent magnet, the magnetic capsule robot makes corresponding precession movement in the pipe filled with silicone oil, and the movement track is wavy. When the pipe diameter is increased, the fluid streamline around the capsule robot is more stable, the vorticity value is smaller, the resistance and resisting moment of the capsule robot in the forward direction become smaller. The PIV measurement method and CFD method used in this paper can be applied to the fluid flow field measurement and mechanical analysis of the smaller size capsule robot in the liquid environment.

Optimal Pressure in Bypass Graft to Prevent Failure Bypass Graft in Carotid Artery to Middle Cerebral Artery Bypass using Computational Fluid Dynamic Method