Physical insight into axisymmetric scramjet intake design via multi-objective design optimization using surrogate-assisted evolutionary algorithms

Fujio, Chihiro; Ogawa, H.

doi:10.1016/j.ast.2021.106676

Cited by 23 publications

(5 citation statements)

References 26 publications

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“…Reddy et al [3] optimized winglets, a device attached to the wing tip of an aircraft, and confirmed that they obtained a solution with high performance at both supersonic and subsonic speeds. Fujio et al [4] developed a design strategy for hypersonic intake design through multiobjective optimization of an axisymmetric intake design. However, size and shape optimization are difficult to apply even for twodimensional problems because setting the desired parameters is not easy, as optimization requires expert prior knowledge of the design problem because the design can be modified only within the degrees of freedom of the parameters.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Evolutionary Topology Optimization Algorithm Using Quadtree Encoding

Nimura,

Oyama

2024

IEEE Access

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A multiobjective high-degree-of-freedom design optimization algorithm that enables topological changes in design is proposed for multiobjective aerodynamic design optimization. In this method, a design is encoded using a regional quadtree, which is often used in computer graphics to increase the speed and save memory in image processing. The optimization problem is solved using multiobjective genetic programming with new crossover, mutation, regularization, and decoding operators designed to handle the evolution of the quadtree structure efficiently and properly. The proposed algorithm is evaluated by solving two multiobjective airfoil shape reproduction problems. The results show that the proposed method can represent typical airfoil shapes with different topologies more efficiently than the conventional evolutionary algorithm.

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Section: Introductionmentioning

confidence: 99%

Multiobjective Evolutionary Topology Optimization Algorithm Using Quadtree Encoding

Nimura,

Oyama

2024

IEEE Access

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“…Fujio and Ogawa [16] presented a multi-objective design optimization based on deep learning to predict flowfields inside scramjet intakes that could replace CFD simulations. Posteriorly, results of recent researches demonstrated that higher compression efficiency can be achieved at lower Mach number while total pressure losses can be minimized at higher Mach numbers and altitude [17,18].…”

Section: Introductionmentioning

confidence: 99%

“…This multi-ramp methodology was not tested in internal symmetrical systems, except for axisymmetric geometries [14,[16][17][18], so more detailed studies on planar are needed.…”

Section: Introductionmentioning

confidence: 99%

Conceptual study of a scramjet with symmetrical internal compression system

Araújo,

Bezerra,

Souza

et al. 2024

Preprint

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This paper focuses on the design analysis of a planar hydrogen-powered scramjet constructed with a symmetrical internal compression system of rectangular cross-sectional area, developed to demonstrate supersonic combustion in atmospheric flight at 30 km of altitude and velocity of 2050 m/s, equivalent to Mach number 6.8. In this analysis, is proposed an analytical approach based on theories of oblique shock wave optimized by the criterion of maximum total pressure recovery, Rayleigh flow’s and the area ratio coupled to Prandtl–Meyer to dimension the compression, combustion, and expansion sections. The design of the compression system was developed to provide velocity, and temperature sufficiently adequate for spontaneous supersonic combustion of the hydrogen-air mixture. The atmospheric airflow was modeled by the hypothesis of calorically perfect gas without viscous effects. A visualization of the effects of various flow phenomena, such as shock waves, combustion, and expansion waves, on the evolution of thermodynamic properties throughout the scramjet demonstrator is discussed. The results showed by conducted compression performance analysis, a major increase in entropy in the reflected shock wave where the criterion of shock waves of equal strength was not applied. Also, the airflow thermodynamic properties and velocity from the leading edge to the trailing edge were analyzed. With heat addition, the scramjet was able to produce uninstalled thrust.

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“…However, because an expensive fitness evaluation is often required in real-world applications owing to simulations or complex numerical calculations, the computational cost of EAs is typically high. To reduce the computing cost of EAs, surrogate-assisted EA (SAEA) has been studied [1,2] and applied to real-world applications such as aerospace engineering [3,4], vehicle design [5], and manufacturing process optimization [6]. An SAEA utilizes a surrogate model that estimates fitness instead of a computationally expensive fitness function and finds promising solutions for actual fitness evaluation.…”

Section: Introductionmentioning

confidence: 99%

A pairwise ranking estimation model for surrogate-assisted evolutionary algorithms

Harada

2023

Complex Intell. Syst.

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Surrogate-assisted evolutionary algorithms (SAEAs) have attracted considerable attention for reducing the computation time required by an EA on computationally expensive optimization problems. In such algorithms, a surrogate model estimates the solution evaluation with a low computing cost and is used to obtain promising solutions to which the accurate evaluation with an expensive computation cost is then applied. This study proposes a novel pairwise ranking surrogate model called the Extreme Learning-machine-based DirectRanker (ELDR). ELDR integrates two machine learning models: extreme learning machine (ELM) and DirectRanker (DR). ELM is a single-layer neural network capable of fast learning, whereas DR uses pairwise learning to rank using a neural network developed mainly for information retrieval. To investigate the effectiveness of the proposed surrogate model, this study first examined the estimation accuracy of ELDR. Subsequently, ELDR was incorporated into a state-of-the-art SAEA and compared with existing SAEAs on well-known real-valued optimization benchmark problems. The experimental results revealed that ELDR has a high estimation accuracy even on high-dimensional problems with a small amount of training data. In addition, the SAEA using ELDR exhibited a high search performance compared with other existing SAEAs, especially on high-dimensional problems.

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Physical insight into axisymmetric scramjet intake design via multi-objective design optimization using surrogate-assisted evolutionary algorithms

Cited by 23 publications

References 26 publications

Multiobjective Evolutionary Topology Optimization Algorithm Using Quadtree Encoding

Multiobjective Evolutionary Topology Optimization Algorithm Using Quadtree Encoding

Conceptual study of a scramjet with symmetrical internal compression system

A pairwise ranking estimation model for surrogate-assisted evolutionary algorithms

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