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The purpose of this work is to apply and compare surrogate-assisted and multi-fidelity, multi-objective optimization (MOO) algorithms to simulation-based aerodynamic design exploration.

The three algorithms for multi-objective aerodynamic optimization compared in this work are the combination of evolutionary algorithms, design space reduction and surrogate models, the multi-fidelity point-by-point Pareto set identification and the multi-fidelity sequential domain patching (SDP) Pareto set identification. The algorithms are applied to three cases, namely, an analytical test case, the design of transonic airfoil shapes and the design of subsonic wing shapes, and are evaluated based on the resulting best possible trade-offs and the computational overhead.

The results show that all three algorithms yield comparable best possible trade-offs for all the test cases. For the aerodynamic test cases, the multi-fidelity Pareto set identification algorithms outperform the surrogate-assisted evolutionary algorithm by up to 50 per cent in terms of cost. Furthermore, the point-by-point algorithm is around 27 per cent more efficient than the SDP algorithm.

The novelty of this work includes the first applications of the SDP algorithm to multi-fidelity aerodynamic design exploration, the first comparison of these multi-fidelity MOO algorithms and new results of a complex simulation-based multi-objective aerodynamic design of subsonic wing shapes involving two conflicting criteria, several nonlinear constraints and over ten design variables.

Biocontaminants represent higher risks to occupants' health in shared spaces. Natural ventilation is an effective strategy against indoor air biocontamination. However, the relationship between natural ventilation and indoor air contamination requires an in-depth investigation of the behavior of airborne infectious diseases, particularly concerning the contaminant's viral and aerodynamic characteristics. This research investigates the effectiveness of natural ventilation in preventing infection risks for coronavirus disease (COVID-19) through indoor air contamination of a free-running, naturally-ventilated room (where no space conditioning is used) that contains a person having COVID-19 through building-related parameters.

This research adopts a case study strategy involving a simulation-based approach. A simulation pipeline is implemented through a number of design scenarios for an open office. The simulation pipeline performs integrated contamination analysis, coupling a parametric 3D design environment, computational fluid dynamics (CFD) and energy simulations. The results of the implemented pipeline for COVID-19 are evaluated for building and environment-related parameters. Study metrics are identified as indoor air contamination levels, discharge period and the time of infection.

According to the simulation results, higher indoor air temperatures help to reduce the infection risk. Free-running spring and fall seasons can pose higher infection risk as compared to summer. Higher opening-to-wall ratios have higher potential to reduce infection risk. Adjacent window configuration has an advantage over opposite window configuration. As a design strategy, increasing opening-to-wall ratio has a higher impact on reducing the infection risk as compared to changing the opening configuration from opposite to adjacent. However, each building setup is a unique case that requires a systematic investigation to reliably understand the complex airflow and contaminant dispersion behavior. Metrics, strategies and actions to minimize indoor contamination risks should be addressed in future building standards. The simulation pipeline developed in this study has the potential to support decision-making during the adaptation of existing buildings to pandemic conditions and the design of new buildings.

The addressed need of investigation is especially crucial for the COVID-19 that is contagious and hazardous in shared indoors due to its aerodynamic behavior, faster transmission rates and high viral replicability. This research contributes to the current literature by presenting the simulation-based results for COVID-19 as investigated through building-related and environment-related parameters against contaminant concentration levels, the discharge period and the time of infection. Accordingly, this research presents results to provide a basis for a broader understanding of the correlation between the built environment and the aerodynamic behavior of COVID-19.

The present work aims to investigate the capabilities of accurately predicting the six-degrees-of-freedom (6DoF) trajectory and the flight behavior of a flare-stabilized projectile using computational fluid dynamics (CFD) and rigid body dynamics (RBD) methods.

Two different approaches are compared for calculating the trajectory. First, the complete matrix of static and dynamic aerodynamic coefficients for the projectile is determined using static and dynamic CFD methods. This discrete database and the data extracted from free-flight experiments are used to simulate flight trajectories with an in-house developed 6DoF solver. Second, the trajectories are simulated solving the 6DoF motion equations directly coupled with time resolved CFD methods.

Virtual fly-out simulations using RBD/CFD coupled simulation methods well reproduce the motion behavior shown by the experimental free-flight data. However, using the discrete database of aerodynamic coefficients derived from CFD simulations shows a slightly different flight behavior.

A discrepancy between CFD 6DoF/RBD simulations and results obtained by the MATLAB 6DoF-solver based on discrete CFD data matrices is shown. It is assumed that not all dynamic effects on the aerodynamics of the projectile are captured by the determination of the force and moment coefficients with CFD simulations based on the classical aerodynamic coefficient decomposition.

This paper aims to introduce the take-off and landing performance analysis modules of the software library named Java toolchain of Programs for Aircraft Design (JPAD), dedicated to the aircraft preliminary design. An overview of JPAD is also presented.

The calculation of the take-off and landing distances has been implemented using a simulation-based approach. This expects to solve an appropriate set of ordinary differential equations, which describes the aircraft equations of motion during all the take-off and landing phases. Tests upon two aircraft models (ATR72 and B747-100B) have been performed to compare the obtained output with the performance data retrieved from the related flight manuals.

The tool developed has proven to be very reliable and versatile, as it performs the calculation of the required performance with almost no computational effort and with a good accuracy, providing a less than the 5 per cent difference with respect to the statistical trend and a difference from the flight manual or public brochure data around 10 per cent.

The use of a simulation-based approach to have a more accurate estimation of the ground performance with respect to classic semi-empirical equations. Although performing the simulation of the aircraft motion, the approach shown is very time-saving and can be easily implemented in an optimization cycle.

A numerical study on the aerodynamic noise generation of a high efficiency propeller is carried out.

Three-dimensional numerical simulation based on Reynolds averaged N-S model is performed to obtain the aerodynamic performance of the propeller. Then, the result of the aerodynamic analysis is given as input of the acoustic calculation. The sound is calculated using the Farassat 1A which was derived from Ffowcs Williams–Hawkings equation and is compared with the measurements.

Moreover, the fan is modified for noise reduction by changing its geometrical parameters such as span, chord length and torsion angle.

The variation trend of aerodynamic and acoustic are compared and discussed for different modification tasks. Some meaningful conclusions are drawn on the noise reduction of propeller.

This paper aims to present the novel methodology of computational simulation of a helicopter flight, developed especially to investigate the vortex ring state (VRS) – a dangerous phenomenon that may occur in helicopter vertical or steep descent. Therefore, the methodology has to enable modelling of fast manoeuvres of a helicopter such as the entrance in and safe escape from the VRS. The additional purpose of the paper is to discuss the results of conducted simulations of such manoeuvres.

The developed methodology joins several methods of computational fluid dynamics and flight dynamic. The approach consists of calculation of aerodynamic forces acting on rotorcraft, by solution of the unsteady Reynold-averaged Navier–Stokes (URANS) equations using the finite volume method. In parallel, the equations of motion of the helicopter and the fluid–structure-interaction equations are solved. To reduce computational costs, the flow effects caused by rotating blades are modelled using a simplified approach based on the virtual blade model.

The developed methodology of computational simulation of fast manoeuvres of a helicopter may be a valuable and reliable tool, useful when investigating the VRS. The presented results of conducted simulations of helicopter manoeuvres qualitatively comply with both the results of known experimental studies and flight tests.

The continuation of the presented research will primarily include quantitative validation of the developed methodology, with respect to well-documented flight tests of real helicopters.

The VRS is a very dangerous phenomenon that usually causes a sudden decrease of rotor thrust, an increase of the descent rate, deterioration of manoeuvrability and deficit of power. Because of this, it is difficult and risky to test the VRS during the real flight tests. Therefore, the reliable computer simulations performed using the developed methodology can significantly contribute to increase helicopter flight safety.

The paper presents the innovative and original methodology for simulating fast helicopter manoeuvres, distinguished by the original approach to flight control as well as the fact that the aerodynamic forces acting on the rotorcraft are calculated during the simulation based on the solution of URANS equations.

An aircraft engine control system consists of a large scale of control parameters and variables because of the complex structure of aero-engine. Monitoring and adjusting control variables and parameters such as detecting, isolating and reconfiguring the system faults/failures depend on the controller design. Developing a robust controller is based on an accurate mathematical model.

In this study, a small-scale turboprop engine is modeled. Simulation is carried out on MATLAB/Simulink for design and off-design operating conditions. Both steady-state and transient conditions (from idle to maximum thrust levels) are tested. The performance parameters of compressor and turbine components are predicted via trained Neuro-Fuzzy model (ANFIS) based on component maps. Temperature, rotational speed, mass flow, pressure and other parameters are generated by using thermodynamic formulas and conservation laws. Considering these calculated values, error calculations are made and compared with the cycle data of the engine at the related simulation conditions.

Simulation results show that the designed engine model’s simulation values have acceptable accuracy for both design and off-design conditions from idle to maximum power operating envelope considering cycle data. The designed engine model can be adapted to other types of gas turbine engines.

Different from other literature studies, in this work, a small-scale turboprop engine is modeled. Furthermore, for performance prediction of compressor and turbine components, ANFIS structure is applied.

The main purpose of the study was mechanical designing, simulation and manufacturing process for a new model of octocopter V-frame and to achieve simple manufacturing with 3D printing technology. Moreover, the octocopter PID controller was simulated on the Simulink environment to get performance on the roll and pitch angle control.

Octocopter is one kind of multirotor vehicle (a rotorcraft with more than two rotors), that has lately gained a lot of attention for both the scientific and commercial spheres. With a greater number of rotors, the multirotor is very maneuverable and robust. Multi-copter makes an important contribution to the technological revolution in the military, industry, transportation, mapping and especially agriculture. Nowadays, we are heading to the four-industrial revolutions as well as the new technological application in the agricultural field such as precision agriculture, mapping and surveillance. Due to recently advanced technology about sensors, electronics, 3D printing, battery with high performance, multi-copter can be manufactured at low cost.

The V-frame octocopter was chosen to design in this paper; it had better performance scores including high redundancy rotors, high payload capability and affordable cost than another multi-copter family. The V-frame octocopter increasing freedom field of view of the camera was considered to place the camera position in the front of the drone.

For the future aspects, the mechanical structure of the octocopter could be improved by using more advanced metal 3D printing to produce the aluminum or titan alloy materials for lighter and more rigid compared with ABS material, and finally the assembly to the real test.

The study shows the new platform of the V-frame octocopter kinematics analysis, designed on the CAD software, with some important mechanical parts using FEM analysis to find the highest stress and displacement under high load applied, the result of all connecting the joints 3D printing part is completely safe. Mechanical parts were manufactured by using 3D printing technology and CNC milling. Moreover, the study has shown V-frame octocopter simulation based on Simulink using the second method Ziegler- Nichols to find suitable parameters of the PID controller for roll and pitch angle. Using the block simulation is good for implementing and fast checking the new algorithm when building the new platform of the robot.

The purpose of this paper is to design a robust angle-of-attack (AOA) tracking control system for the hypersonic reentry vehicle (HRV) based on the linear parameter varying (LPV) theory, as the aerodynamic coefficients of the hypersonic vehicle vary quickly during the reentry phase.

First, longitudinal moment trim is done along the desired flight trajectory. The linearized system at each trim point is built and the dynamic characteristics analysis is made. Then the LPV control law with parameter-dependent quadratic Lyapunov function (PDQLF-LPV) is applied to design the AOA tracking autopilot at each trim point. Frequency performance of the autopilot is assessed and the step response simulation is conducted to validate the effectiveness of the control system. Finally, actual AOA command tracking simulations based on the time-varying nonlinear model are carried out to test the correctness and robustness of the PDQLF-LPV autopilot.

Analysis results demonstrate that the PDQLF-LPV control system can track the AOA command perfectly during the whole flight envelop with dynamics parameter variation or disturbances, which indicates that it is effective to integrate the PDQLF-LPV control theory with a parameter-varying reference model for control system design of HRV.

A reference model with varying parameters is utilized to guarantee the transient performance of the autopilot, and induced L2-norm analysis is introduced to describe and guarantee the robust stability of the autopilot.

This study aims to use computational fluid dynamics (CFD) to understand and quantify the overall blockage within a transonic axial flow compressor (AFC), and to develop an efficient collaborative design optimization method for compressor aerodynamic performance and stability in conjunction with a surrogate-assisted optimization technique.

A quantification method for the overall blockage is developed to integrate the effect of regional blockages on compressor aerodynamic stability and performance. A well-defined overall blockage factor combined with efficiency drives the optimizer to seek the optimum blade designs with both high efficiency and wide-range stability. An adaptive Kriging-based optimization technique is adopted to efficiently search for Pareto front solutions. Steady and unsteady numerical simulations are used for the performance and flow field analysis of the datum and optimum designs.

The proposed method not only remarkably improves the compressor efficiency but also significantly enhances the compressor operating stability with fewer CFD calls. These achievements are mainly attributed to the improvement of specific flow behaviors oriented by the objectives, including the attenuation of the shock and weakening of the tip leakage flow/shock interaction intensity.

CFD-based design optimization of AFC is inherently time-consuming, which becomes even trickier when optimizing aerodynamic stability since the stall margin relies on a complete simulation of the performance curve. The proposed method could be a good solution to the collaborative design optimization of aerodynamic performance and stability for transonic AFC.