MULTI-POINT DESIGN OF A SUPERSONIC WING USING MODIFIED PAR-SEC AIRFOIL REPRESENTATION

This paper describes the numerical design optimization and experimental study of centrifugal compressors with leaned curvilinear element blades. The design targets were a fully shrouded centrifugal impeller and a low-solidity vaned diffiiser. A new method of defining the curvilinear element blade was developed for centrifugal turbomachinery using coordinate transformations between a revolutionary flow-surface coordinate system and a cylindrical coordinate system. Geometries of model compressors with curvilinear element blades were then numerically optimized at a suction flow coefficient of 0.073, using a multi-objective genetic algorithm, Kriging surrogate model, and steady Reynolds-averaged Navier Stokes simulations. The optimal impeller had a concave blade suction surface and a concave leading edge. Although clear patterns in geometrical features for optimal diffiiser vanes could not be captured, we found that the dihedral profile had a predominant effect on aerodynamic performance. The performance of model compressors was experimentally measured and compared with traditional compressors as to their aerodynamic performance. The results demonstrated that the models' adiabatic efficiency was higher by 1.4% at the design point. The stall margin stayed unchanged and the surge margin expanded by 6.7%.

In 2007, NASA announced several goals that future supersonic transports (SSTs) should accomplish, including cruise emissions, airport noise and sonic boom criteria. The sonic boom target is so aggressive that some breakthroughs will be required to achieve it. The authors propose that liquid hydrogen (LH 2) fuel can be a solution. The purpose of this study is to discuss the feasibility of a LH 2-fueled low boom SST which is designed to meet the N+3 goals by a method which considers the effects of hydrogen and incorporates the sonic boom minimization theory. An initial SST model was constructed. The results show that great reduction in sonic boom level can be expected by using LH 2 fuel. A comparative study was conducted with a conventional kerosene-fueled SST. The results show that a weight reduction of 30% and a sonic boom reduction of 13 PLdB are possible by using LH 2 fuel. A multi-point optimization using Genetic Algorithm (GA) was also conducted to explore better solutions. The objective functions were to maximize range, to minimize take-off weight WTO + + = ( ) ( ) ( )

In this study, high efficient design tool is developed with several informatics approaches for Multidisciplinary Design Optimization (MDO) and knowledge discovery of supersonic wing design. In this design, Multi-Objective Genetic Algorithm (MOGA) is applied as an optimizer, while Kriging model is also used to reduce computational cost. To obtain the information of the design space, functional ANalysis Of VAriance (ANOVA) and Parallel Coordinate Plot (PCP) is applied. For Kriging model construction, 107 sample points are evaluated. This tool is applied to the multidisciplinary design problem of supersonic wing. The objective functions are to maximize lift to drag ratio and to minimize sonic boom intensity at supersonic cruise, and to minimize wing weight. According to the results, there are trade-off relationships among three objective functions. The ANOVA results indicate that the cambers of the wing section at the root and the kink have an influence on the lift to drag ratio, the inner wing sweep back angle affects the sonic boom intensity, and the camber of wing section at the kink and aspect ratio affect the wing weight. The design space information could be visualized quantitatively from the sampling results with PCP technique. Since the design space exploration using MOGA is carried out based on Kriging surrogate models, the proposed MDO process is effective in terms of computational cost.

In order to improve the efficiency and quality of a permanent magnet synchronous generator (PMSG) for vehicles, the parametric model and finite‐element model of the generator are established. The influence of seven structure parameters on three performance parameters is obtained by simulation analysis, and the sensitivity values of the parameters are given. According to the simulation results, it can be seen that the structure design parameters have higher degrees of freedom, and the relationship among parameters is complex. Using three multidimensional functions as test functions, the precision of the fitting method proposed in this paper is compared with that of the traditional methods. The test results show that, compared with the other methods, maximum projection (MaxPro) sampling and the Kriging method can select as fewer samples as possible while guaranteeing the higher fitting precision. Then, the Kriging surrogate model, which reflects the nonlinear relationship between the structure and performance parameters, is established, and the prediction precision of the model is verified. Based on the surrogate model, the performance of the generator with three performance parameters as optimized objects is optimized by use of elitist nondominated sorting genetic algorithm (NSGA‐II), and a Pareto optimal solution set of the objective function is obtained. Three of the optimal solutions are selected for finite‐element verification. The results show that the Kriging surrogate model can provide better global and local prediction between input and output variables. It is further proved that the samples obtained by MaxPro sampling can fully reflect the characteristics of the design space. The optimized objects can be weighed according to the optimal decision based on the results of multiobjective optimization through the Kriging surrogate model. The effectiveness of the optimization method is verified. It is of great engineering significance to improve the performance of generators, and the optimal model obtained by this method has an important reference value for prototype trial production. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

In this paper a coupled longitudinal and lateral control strategy for an autonomous automotive vehicle is proposed. The proposed control scheme consists of a lateral guidance module based on a NonLinear Model-based Predictive Controller (NLMPC) and a cruise speed generation and regulation module. A cruise speed-profile generator allows the calculation of the cruise speed which preserves the lateral stability of the vehicle during lateral maneuvers. The calculation of the cruise speed profile is done considering road geometry as well as lateral dynamics criteria. The handling of both longitudinal and lateral dynamics in addition to the calculation of the limit cruise speed profile by considering lateral stability criteria illustrate the interest of the proposed approach. The developed control architecture is tested through simulation and shows good performance for guidance at high cruise speeds.

Creep rupture life prediction for the A231 T91 alloy steel has been optimized using the Kriging surrogate model. Creep rupture data published by NIMS data sheet was used in this optimization, and isothermal creep rupture life-stress and TTP(Time-Temperature Parameter)-stress curves were optimized with Kriging model. The creep rupture data having the rupture life of less than 10,000 hours was interpolated with the K海ing surrogate model and theKriging extrapolation to the creep life of 100,000 hours was verified by comparing with experimental data. It was found that the Kriging model could fit to the data within 3% of relative error. Furthermore, the Kriging surrogate model was compared to Wilshire, Manson-Brown, Manson-Haferd, and MCX models. It can be found that the creep rupture stress extrapolated to 100,000 hours by Kriging surrogate showed a relatively good accuracy and uncertainty of 4% - 16%.

High-speed forming processes, such as electrohydraulic forming, have recently attracted attention with the development of forming technology. However, because the high-speed operation (above 100 m/s) raises safety concerns, most experiments are conducted in a closed die, which hides the forming process. Therefore, the experimental process can only be observed in a numerical simulation with accurate material properties. The conventional quasistatic material properties are improper for high-speed forming simulations with high strain rates (>102 s−1). In this study, the material properties of Al 6061-T6, which reflect the deformation behavior in the high-strain-rate region, were investigated in a numerical approach based on a reduced order model and a surrogate model in which the numerical results resemble the experimental results. The strain rate effect on the material was determined by the Cowper–Symonds constitutive equation, and two strain rate parameters were predicted. The surrogate model takes two material parameters as inputs and outputs a weighting coefficient calculated by the reduced order model. The surrogate model is based on the Kriging method to reduce the simulation cost. Next, the optimal material parameters that minimize the error between the surrogate model and the experiments are estimated by nonlinear least-squares optimization using a genetic algorithm and the constructed surrogate model. The predicted optimal parameters were verified by comparing the results of the experiment, numerical simulation, and surrogate model.

This paper discusses the use of surrogate modelling focusing on the performance comparison of different Kriging surrogate models. The different Kriging surrogate models are investigated and applied to design of superconducting magnetic energy storage system and switched reluctance motor. Finally, some comments on selection of proper surrogate model are given for optimal design of electromagnetic problems.

The low-boom inverse design method is of great interest for the preliminary design of supersonic transport (SST), owing to its good capability of reducing sonic boom at low computational cost. However, the main challenge is how to prescribe an attainable target. This paper proposes an inverse design method using a new target-generation strategy to address this challenge. Unlike existing methods such as the Jones–Seebass–George–Darden method and the mixed-fidelity inverse design method [the Li–Shields–Geiselhart (LSG) method], the proposed method directly parameterizes the near-field overpressure distribution of a reference configuration and minimizes the ground perceived level in decibels (PLdB) predicted by solving the augmented Burgers equation to obtain an optimal target distribution, subject to cruise lift and volume constraints. The proposed method is demonstrated by the Japan Aerospace Exploration Agency (JAXA) Wing Body case, which shows that it mitigates sonic boom under lift constraint and achieves a reduction of 2.07 PLdB more than the LSG method. The proposed method is applied to the low-boom design of a large SST configuration called NPU-T7104, which is close in size to the Tupolev Tu-144; results show that aerodynamic performance is maintained while shock wave coalescence is effectively prevented, and ground-boom intensity is dramatically reduced.

In the present work, a parametric design study in the conceptual design phase of a low-boom supersonic airliner (LBSSA) is presented. The low-boom constraint is of great importance to the near future supersonic airliners, in order for them to be certified for overland operation, but is also usually associated with a penalty in their aerodynamic performance (e.g. increased drag) and subsequently a higher fuel consumption. In this work, a dedicated low-fidelity design tool for the conceptual and early preliminary design of a LBSSA is developed which includes both Class-I and Class-II weight calculations. The design tool is also capable of predicting the aircraft’s aerodynamic performance in both the subsonic and supersonic cruise segments of its mission. The aerodynamic behavior of the LBSSA is then compared against the results obtained from high fidelity Computational Fluid Dynamics (CFD) modeling. Regarding the acoustic behavior of the LBSSA, Carlson’s simplified method is employed, which is based on the equivalent area distribution of the aircraft, in order to provide representative trends and results in the conceptual design phase. Finally, the contribution of the examined design parameters, in the aerodynamic and acoustic performance of the resultant LBSSA is presented and clear trends are indicated.

Multi-objective optimization of vortex generators on a transonic infinite wing is performed using computational fluid dynamics and a multi-objective genetic algorithm coupled with surrogate models. Vortex generator arrangements are defined by five design variables: height, length, incidence angle, chord location, and spacing. The objective functions are to maximize the lift-to-drag ratio at low angle of attack, to maximize lift coefficient at high angle of attack, and to the shift chordwise separation location downstream at high angle of attack. To evaluate these objective functions of each individual in the multi-objective genetic algorithm, the ordinary kriging surrogate model and the radial-basis-function/kriging hybrid surrogate model are employed because numerical analysis of the wing with vortex generators requires a large amount of computational time. Nondominated solutions are classified into five clusters with different aerodynamic characteristics. Comparison of the five clusters revealed that the balance among three objective functions is controlled mainly by vortex generator height, spacing, and their ratio. The solutions in each cluster have specific values of these three parameters, which identify the aerodynamic characteristics. In addition, appropriate values of design variables for generating the vortex most effectively are investigated.

This study investigates the differences in sound emissions of multi-rotor unmanned aerial systems (UAS) between hover and cruise. We therefore conducted onboard acoustic measurements on two different UAS types, each equipped with multiple propeller configurations. The recorded data allowed for a detailed comparison of noise emissions at fixed emission angles, focusing on both traditional acoustic metrics and psychoacoustic parameters. The results reveal notable differences between hover and cruise, with certain configurations exhibiting a sudden increase in sound emission levels of up to 4 dB above specific cruise speeds. While some UAS/propeller combinations showed a linear relationship between cruise speed and sound emission levels, others experienced abrupt level increases beyond a critical velocity of 2-4 m/s, along with changes in loudness and roughness. These variations were not directly correlated with rotor speed changes, indicating that aerodynamic transitions, such as shifts in blade-wake/blade-vortex interactions, strongly influence sound generation. Spectral analyses support the occurrence of an aerodynamic regime change between hover and cruise, with the effect saturating at higher cruise speeds. Consequently, noise and auralization models, but also evaluations on low-noise propellers that are based on measurements at hover state only may yield substantial inaccuracies when extrapolated to cruise state.

The National Aeronautics and Space Administration, in conjunction with major aerospace companies, is investigating the technical and economic feasibility of a new generation of supersonic transport airplanes. Efforts are being devoted to an examination of the feasibility of designing and operating a supersonic transport that will yield a sonic boom acceptable to the affected population. This work is focused on sonic boom signatures that differ from the classical N wave. The presentation will discuss the results of a series of studies conducted using a sonic boom simulator at the NASA−Langley Research Center in which human subjects assessed a wide range of shapes of sonic boom signatures. Various psychophysical scaling techniques were employed and the results were examined in terms of their relationship with several calculated noise measures. For the situation in which people are exposed to sonic booms while indoors, building vibration and rattle are potentially important factors in need of consideration. Structural response to sonic boom is reviewed and compared with human vibration response criteria. A review of existing data is used to determine the acceleration required to induce rattle of wall-mounted objects.

Spiral acoustic structures hold significant potential for noise suppression in fluid flow systems; however, their aerodynamic performance has often been overlooked in previous studies. To bridge this gap, the present study develops a sequential optimization strategy aimed at simultaneously maximizing acoustic transmission loss (TL) and minimizing flow drag (FD). The strategy integrates a multi-objective genetic algorithm with surrogate models for initial global exploration of the design space, followed by an adjoint optimization method for local refinement of the inner wall geometry. Under fixed outer dimensions, the spiral geometry is parameterized using inner diameter, spiral angular frequency, spiral position, and dimensionless pitch. Sensitivity analysis is employed to identify the key structural parameters. Surrogate models are constructed to efficiently map the structural parameters to FD and total transmission loss (TY), respectively. A multi-objective genetic algorithm identifies a multi-objective optimization structure achieving TY higher than 7 dB and reducing FD by 306.35 Pa at 10 m/s compared to the original structure. The adjoint optimization, building upon this multi-objective optimization structure result, further reduces the FD by an additional 89.33 Pa without compromising the TL. The sequential optimization strategy ultimately delivers a 23% increase in TY and a 53.6% reduction in FD relative to the original structure. Furthermore, the optimization results are validated through impedance tube experiments. The sequential optimization strategy provides an efficient solution for applications demanding both effective noise control and low flow drag.

This paper proposes geometry parameterization of a complete single centrifugal compressor stage and applies CFD-driven optimization using artificial neural networks and a Kriging surrogate model. Kinematic velocity triangle analysis is used to arrive at an initial design, which is then improved by using automated optimization algorithms and fundamental flow physics using CFD simulation. By allowing the design to evolve, guided by CFD, new and untested optimum designs are possible. This work deals specifically with design and optimization of the flow path. Design for structural aspects such as vibration, rotor dynamics and other mechanical aspects is outside the scope of this work. The CAD parameterization enables robust specification of the flow path geometry while maintaining a sufficiently small set of parameters for practical design space exploration. The parameterization includes an impeller with optional splitter blades, a vaneless diffuser and volute. Steady-state, RANS-based CFD is employed in the analysis of both the rotationally-periodic components and the volute geometry. Direct optimization and response surface optimization are demonstrated for rotationally periodic components to maximize design-point efficiency of the flow path using a multi-objective genetic algorithm (MOGA). Improvements in total-total isentropic efficiency of between 4 and 5 percent are achieved. Optimization of the flow path of the volute is likewise demonstrated. In the case of the volute, a Kriging response-surface model is used and a 1.4 percentage point improvement is shown. Further research in the utilization various implementations of Artificial Intelligence (AI) machine learning techniques in conjunction with parameterized turbomachinery flow paths to enable enhanced designs to be generated effectively is proposed.