TY - JOUR
T1 - Multidisciplinary modeling and dynamic Kriging assisted optimization for suborbital reusable launch vehicle
AU - Long, Teng
AU - Li, Haoda
AU - Shi, Renhe
AU - Chen, Rong
AU - Zhang, Baoshou
AU - Ye, Nianhui
N1 - Publisher Copyright:
© 2026 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
PY - 2026/5/15
Y1 - 2026/5/15
N2 - As a promising high-speed transportation system, suborbital reusable launch vehicle (SRLV) has caught significant attention. To redesign the SRLV system with higher achievable range and controllable re-entry risks (e.g., heat flux and dynamic pressure), a dynamic Kriging assisted SRLV multidisciplinary design optimization (MDO) framework is proposed in this paper. In this framework, the MDO problem is formulated to maximize the achievable range of SRLV subject to practical constraints during the reentry phase. The parameterized geometry, aerodynamics, heat-flux prediction, mass evaluation, and trajectory constitute the SRLV multidisciplinary analysis model, whose responses are considered as the objective and constraints of the MDO problem. To reduce the computational cost, a dynamic-Kriging optimization method using initial sample expansion mechanism (DKOM-ISE) is proposed as the optimizer of the MDO framework. In this approach, Kriging surrogates are constructed through an initial sample expansion mechanism to replace the expensive SRLV models for optimization. And Kriging surrogates are dynamically refined via the synthesized improvement criterion and significant sampling space method to explore the design space of SRLV efficiently and effectively. After DKOM-ISE based optimization, the achievable range is increased by 16.11% compared with that of the initial design subject to all the constraints. Moreover, the proposed DKOM-ISE yields a 33.3% computational efficiency improvement than the competitive constrained differential evolution algorithm. The optimization results demonstrate the effectiveness and engineering practicability of the proposed MDO framework for SRLV design.
AB - As a promising high-speed transportation system, suborbital reusable launch vehicle (SRLV) has caught significant attention. To redesign the SRLV system with higher achievable range and controllable re-entry risks (e.g., heat flux and dynamic pressure), a dynamic Kriging assisted SRLV multidisciplinary design optimization (MDO) framework is proposed in this paper. In this framework, the MDO problem is formulated to maximize the achievable range of SRLV subject to practical constraints during the reentry phase. The parameterized geometry, aerodynamics, heat-flux prediction, mass evaluation, and trajectory constitute the SRLV multidisciplinary analysis model, whose responses are considered as the objective and constraints of the MDO problem. To reduce the computational cost, a dynamic-Kriging optimization method using initial sample expansion mechanism (DKOM-ISE) is proposed as the optimizer of the MDO framework. In this approach, Kriging surrogates are constructed through an initial sample expansion mechanism to replace the expensive SRLV models for optimization. And Kriging surrogates are dynamically refined via the synthesized improvement criterion and significant sampling space method to explore the design space of SRLV efficiently and effectively. After DKOM-ISE based optimization, the achievable range is increased by 16.11% compared with that of the initial design subject to all the constraints. Moreover, the proposed DKOM-ISE yields a 33.3% computational efficiency improvement than the competitive constrained differential evolution algorithm. The optimization results demonstrate the effectiveness and engineering practicability of the proposed MDO framework for SRLV design.
KW - Approximate optimization
KW - Multidisciplinary design optimization
KW - Multidisciplinary modeling
KW - Suborbital reusable launch vehicle
UR - https://www.scopus.com/pages/publications/105034565895
U2 - 10.1016/j.asr.2026.03.053
DO - 10.1016/j.asr.2026.03.053
M3 - Article
AN - SCOPUS:105034565895
SN - 0273-1177
VL - 77
SP - 10640
EP - 10663
JO - Advances in Space Research
JF - Advances in Space Research
IS - 10
ER -