Fig 15 - uploaded by Nhu Van Nguyen
Content may be subject to copyright.
Source publication
The integrated missile design optimization process is proposed by implementing the aerodynamics database (Aero DB) and tactical missile design (TMD) spreadsheet to obtain a quick and relatively accurate optimal air intercept missile configuration at the conceptual design stage. The Aero DB is constructed to replace an existing aerodynamics analysis...
Citations
... Nguyen et al. have researched to optimize the body-wing-tail missile, which has been analyzed computationally. Optimization can increase the total range by 27.8% compared to the baseline form [6]. Oktay et al. have validated the unstructured 3D Euler flow solver at Mach number 2 and varied the angle of attack from 0° to 20°. ...
... Batasan ketidakpastian nilai dari parameter diperoleh dengan studi literatur hasil penelitian [15][16] [17]. Besarnya batasan ketidakpastian nilai parameter yang digunakan di dalam penelitian ini dapat dilihat pada Tabel 1. Pada setiap simulasi, nilai ketidakpastian dari parameter ini akan ditentukan secara acak, tetapi nilai tersebut berada pada batasan minimum dan maksimum yang telah ditentukan berdasarkan Tabel 1. ...
The impact point is the main parameter of the performance of an artillery rocket. During its flight, a rocket experiences uncertainty of some parameter’s value, which is caused by the condition of the rocket when it exits the launcher, the ever-changing atmospheric conditions, and fabrication imperfections. This disturbance will cause deviation on the impact point. This study aims to determine the deviation of the impact point of an artillery rocket due to the value uncertainty of several parameters that affect its flight trajectory, and this analysis will be used as a reference for designers and users in further design processes. Six degrees of freedom simulation calculates the rocket's impact point and deviation. The results showed that to minimize the impact point’s deviation, the quality of the launcher fabrication must be improved, predicting aerodynamics with CFD and firing the rocket at low wind disturbances.
... Nguyen et al. [3] accomplished a two-phase study composed of optimization and validation steps to improve the aerodynamic characteristics of a missile. The experimental data and Missile DATCOM results were utilized to attain the optimum geometry, and the ANSYS Fluent model was implemented to verify the optimized configuration. ...
The aim of this paper is to demonstrate the effects of the shape optimization on the missile performance at supersonic speeds. The N1G missile model shape variation, which decreased its aerodynamic drag and increased its aerodynamic lift at supersonic flow under determined constraints, was numerically investigated. Missile geometry was selected from a literature study for optimization in terms of aerodynamics. Missile aerodynamic coefficient prediction was performed to verify and compare with existing experimental results at supersonic Mach numbers using SST k-omega, realizable k-epsilon, and Spalart-Allmaras turbulence models. In the optimization process, the missile body and fin design parameters need to be estimated to design optimum missile geometry. Lift and drag coefficients were considered objective function. Input and output parameters were collected to obtain design points. Multiobjective Genetic Algorithm (MOGA) was used to optimize missile geometry. The front part of the body, the main body, and tailfins were improved to find an optimum missile model at supersonic speeds. The optimization results showed that a lift-to-drag coefficient ratio, which determines the performance of a missile, was improved about 11-17 percent at supersonic Mach numbers.
... The abilities of Missile DATCOM are extensive in computing a wide range of flight conditions, from subsonic to hypersonic speeds. [76][77][78] Problem formulation ...
Uncertainty-based design optimization has been widely acknowledged as an advanced methodology to address competing objectives of aerospace vehicle design, such as reliability and robustness. Despite the usefulness of uncertainty-based design optimization, the computational burden associated with uncertainty propagation and analysis process still remains a major challenge of this field of study. The metamodeling is known as the most promising methodology for significantly reducing the computational cost of the uncertainty propagation process. On the other hand, the nonlinearity of the uncertainty-based design optimization problem's design space with multiple local optima reduces the accuracy and efficiency of the metamodels prediction. In this article, a novel metamodel management strategy, which controls the evolution during the optimization process, is proposed to alleviate these difficulties. For this purpose, a combination of improved Latin hypercube sampling and artificial neural networks are involved. The proposed strategy assesses the created metamodel accuracy and decides when a metamodel needs to be replaced with the real model. The metamodeling and metamodel management strategy are conspired to propose an augmented strategy for robust design optimization problems. The proposed strategy is applied to the multiobjective robust design optimization of an expendable launch vehicle. Finally, based on non-dominated sorting genetic algorithm-II, a compromise between optimality and robustness is illustrated through the Pareto frontier. Results illustrate that the proposed strategy could improve the computational efficiency, accuracy, and globality of optimizer convergence in uncertainty-based design optimization problems.
... RENN is applied for a low-speed airfoil design [9]. The basic RSM is applied for airto-air intercept missile design [10] and fighters [11]. The surrogate models are developed and improved for the efficient aerospace system design. ...
Recently, the variable fidelity optimization (VFO) methods are widely developed to improve the accuracy and reliability of design results without a noticeable turnaround time from preliminary sizing, conceptual design stage, preliminary design stage, and detail design stage. The variable fidelity analysis are composed of low fidelity, medium fidelity, and high fidelity analysis which is used to access on the aircraft performance parameters during each design stage. The high fidelity requires more cost and time to complete an analysis. It provides more reliable and accurate results. However, it still encounters with the computational load and expensive cost during the optimization loop by using only high fidelity analysis at even later preliminary and detail design stage. Therefore, the variable fidelity optimization methods have been researching and investigating to apply into every design stage to reduce the development cost and computational cost. In this paper, the summary of variable fidelity optimization methods development in Aerodynamics Analysis and Design Lab. (AADL), Konkuk University is presented and discussed for the aerospace design applications. The future research trends of variable fidelity optimization will be addressed.
... Furthermore, the number of design variables or the dimensionality of the missile design problems is normally large. Nguyen et al. considered 16 design variables for air-to-air intercept missile design after sensitivity analysis [16]. Assume that two levels of full factorial design are used to construct the surrogate models by using the high-fidelity analysis [17,18]. ...
... The integrated AGM analysis and design tool, which includes aerodynamics, propulsion, weight, trajectory, dynamics, and stability and control (S & C) estimation modules, is developed and validated [16]. The detailed development and validation of this tool is presented in the next section. ...
... The significant and complex analysis module for the missile design framework is the aerodynamics analysis discipline, in which Missile DATCOM is selected to predict and provide the necessary aerodynamics data for trajectory and dynamics analysis. The validation of Missile DATCOM is performed by the authors for an air-to-air missile AIM 7 (AIM 7 Sparrow configuration) and several general missile configurations [16]. The Missile DATCOM analysis results show very good agreement with the maximum error, namely, 5.2% compared with the experimental data and ANSYS Fluent Version 13 [33]. ...
... Furthermore, the number of design variables or the dimensionality of the missile design problems is normally large. Nguyen et al. considered 16 design variables for air-to-air intercept missile design after sensitivity analysis [16]. Assume that two levels of full factorial design are used to construct the surrogate models by using the high-fidelity analysis [17,18]. ...
... The integrated AGM analysis and design tool, which includes aerodynamics, propulsion, weight, trajectory, dynamics, and stability and control (S & C) estimation modules, is developed and validated [16]. The detailed development and validation of this tool is presented in the next section. ...
... The significant and complex analysis module for the missile design framework is the aerodynamics analysis discipline, in which Missile DATCOM is selected to predict and provide the necessary aerodynamics data for trajectory and dynamics analysis. The validation of Missile DATCOM is performed by the authors for an air-to-air missile AIM 7 (AIM 7 Sparrow configuration) and several general missile configurations [16]. The Missile DATCOM analysis results show very good agreement with the maximum error, namely, 5.2% compared with the experimental data and ANSYS Fluent Version 13 [33]. ...
The adaptive multifidelity constraints method is developed and proposed to ensure the convergence of significant constraints to high-fidelity results for increasing the reliability and robustness of an optimal configuration at the conceptual design stage without any noticeable turnaround time. The adaptive multifidelity constraints algorithm is demonstrated for two numerical examples, with savings of 58.6 and 64% in high-fidelity evaluations, to obtain the convergence of adaptive constraints to high-fidelity results. The implementation of the adaptive multifidelity constraints algorithm is integrated into the multidisciplinary air-to-ground missile design optimization framework. The lift, drag, and longitudinal control effectiveness coefficient constraints are considered as multifidelity constraints due to their importance in the sizing of air-to-ground missile control surfaces for diving and attacking missions. The optimal air-to-ground missile configuration using adaptive multifidelity constraints yields more reliable and robust results compared with the optimal air-to-ground missile configuration using the low-fidelity analysis only, whereas the adaptive constraints converge into the high-fidelity results.
Read More: http://arc.aiaa.org/doi/abs/10.2514/1.A33312
Since 2019, Riga Technical University, Institute of Aeronautics, in partnership with Cryogenic and vacuum systems Ltd (Ventspils), executed the European Regional Development Fund Project No. 1.1.1.1/18/A/133 “Prototype development of transportable in multimodal traffic mobile space testing facility Metamorphosis.” In the process of realization of the project, the analysis of the technical failure risk was provided. Most risk components were detached, and several measures for risk prevention were performed. During the testing of the prototype, it turned out that significant vibration and shock loads acted on the prototype during movement, so some design changes were made. The development of the variational vacuum system calculation model allowed the project team to find the solutions and successfully finish the tests, proofing the concept of the mobile thermal vacuum test facility. This article describes the problem and the search for a solution and shows its implementation.
Some Results of the Mobile Space Testing Facility Metamorphosis Prototype Design, Development and Test
Sergey Kravchenko(1), Nikolay Kuleshov(2), Ilmars Blumbergs(3*), Natalia Kravchenko(4), Vladimir Shestakov(5), Daria Panova(6), Aya Medany(7)
(*) Corresponding author
Authors' affiliations
DOI: https://doi.org/10.15866/irease.v16i3.22588
Abstract
Since 2019, Riga Technical University, Institute of Aeronautics, in partnership with Cryogenic and Vacuum Systems Ltd (Ventspils), executed the European Regional Development Fund Project No. 1.1.1.1/18/A/133 “Prototype development of transportable in multimodal traffic mobile space testing facility Metamorphosis.” In the process of realization of the project, the analysis of the technical failure risk was provided. Most risk components were detached, and several measures for risk prevention were performed. During the testing of the prototype, it turned out that significant vibration and shock loads acted on the prototype during movement, so some design changes were made. The development of the variational vacuum system calculation model allowed the project team to find the solutions and successfully finish the tests, proofing the concept of the mobile thermal vacuum test facility. This article describes the problem and the search for a solution and shows its implementation.
Copyright © 2023 Praise Worthy Prize - All rights reserved.
Keywords: Mobile Thermal Vacuum Test Complex; Computational Model; Vacuum System
It is necessary to optimize the design of the missile aerodynamic shape for better performance while meeting tactical specifications. However, current design methods for aerodynamic shape are based on manual design and physical model simulations, which are very time-consuming. Therefore, we propose an optimization framework based on conditional Wasserstein Gan-GP (CWGAN-GP), convolutional neural network (CNN), multi-task learning with multi-gate mixture-of-Experts-3D (MMoE-3D) and differential evolution (DE). This method consists of four stages. In the first step, CWGAN-GP can learn the relationship between existing missile shape designs and shape conditions, generating diverse missile shapes as required. In the second step, CNN is used for feature extraction of missile design drawing, and the missile shape generated by CWGAN-GP is transformed into missile shape parameters. In the third step, the MMoE-3D model is trained in the subsonic and supersonic ranges to efficiently generate aerodynamic data corresponding to the missile shape. In the fourth step, DE is used to select the optimal missile shape by adjusting the potential variables of CWGAN-GP. The efficiency of the proposed optimization framework is verified by optimizing the rate of change of the center of pressure and the lift-to-drag ratio, with the neural network-based optimization framework achieving almost the same optimization results in a shorter time compared to conventional optimization with DATCOM.
