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|a Space engineering :
|b modeling and optimization with case studies /
|c Giorgio Fasano, János D. Pintér, editors.
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|a Switzerland :
|b Springer,
|c 2016.
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|a Springer optimization and its applications,
|x 1931-6828 ;
|v volume 114
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|a Preface; Acknowledgments; MSC 2010 Classification: Suggested Categories and Keywords for the Book; Contents; Editors; Advanced Space Vehicle Design Taking into Account Multidisciplinary Couplings and Mixed Epistemic/Aleatory Uncertainties ; Nomenclature; 1 Introduction; 2 MDO Decomposition Strategy for Launch Vehicle Design; 2.1 General MDO Formulation and Review of Main MDO Approaches; 2.2 Stage-Wise decomposition for Optimal Rocket Design; 2.2.1 Theoretical Formulations; 2.2.2 Application of SWORD to Launch Vehicle Design; 3 Introduction of Uncertainty in the Design Process.
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|a 3.1 Optimization of Design Rules and Safety Margins Taking into Account Mixed Epistemic/Aleatory Uncertainties3.2 Uncertainty Multidisciplinary Design Optimization; 3.2.1 Theoretical Approach for Interdisciplinary Coupling Satisfaction in the Presence of Uncertainty; 3.2.2 Application for Launch Vehicle Design; 4 Conclusion; References; Using Direct Transcription to Compute Optimal Low Thrust Transfers Between Libration Point Orbits; 1 The Optimal Control Problem; 2 Transcription Method; 3 Runge-Kutta Methods; 3.1 Lobatto IIIA, S = 2; 3.2 Lobatto IIIA, S = 3; 3.3 Lobatto IIIA, S = 4.
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|a 3.4 Lobatto IIIA, S = 54 Nonlinear Programming; 5 Mesh Refinement; 6 Optimal Low Thrust Transfers Between Libration Point Orbits; 6.1 Introduction; 6.2 Dynamic Model; 6.3 Lyapunov Orbits; 6.4 Adjoint Equations; 7 Numerical Results; 7.1 Short Transfer; 7.2 Long Transfer; 8 Computational Comparisons; 8.1 Spline Approximation; 8.2 Mesh Refinement Strategy; 8.3 Indirect Collocation; 9 Summary; Appendix: Lobatto IIIA Method Coefficients; References; Tentative Solutions for Indirect Optimization of SpacecraftTrajectories; 1 Introduction; 2 Optimal Control Problem.
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|a 3 Application to Space Trajectories Optimization4 BVP Solution and Improvements of Numerical Accuracy; 4.1 Gradient Evaluation; 4.2 Thrust Discontinuities; 4.3 Multiple Shooting; 5 Techniques to Improve Convergence; 6 Final Remarks; References; Resource-Constrained Scheduling with Non-constant Capacity and Non-regular Activities; 1 Introduction; 2 Time-Indexed Formulation; 3 Applications and Computational Results; 3.1 Basic Test Set; 3.2 Test Sets A, B, C, D, E and F; 3.3 Test Set G; 3.4 Tests Extracted from Fekete's and Shepers' Set; 4 Conclusions; Appendix; Test Set F Power Consumption.
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|a Test set B Power FunctionTest Set C Power Function; Test Set D Power Function; Test Set E Power Function; Test set F Power Function; Test Set G: Resource 1 Function; Test Set G: Resource 2 Function; Test Set G: Resource 3 Function; References; Packing Problems in Space Solved by CPLEX: An Experimental Analysis; 1 Introduction; 2 MILP Model and Heuristic Approach; 3 Experimental Framework and Results; 4 Conclusive Remarks; Appendix; References; Designing Complex Interplanetary Trajectories for the Global Trajectory Optimization Competitions; 1 Introduction; 2 Building Blocks.
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|a Includes index.
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|a This book presents a selection of advanced case studies that cover a substantial range of issues and real-world challenges and applications in space engineering. Vital mathematical modeling, optimization methodologies and numerical solution aspects of each application case study are presented in detail, with discussions of a range of advanced model development and solution techniques and tools. Space engineering challenges are discussed in the following contexts:?Advanced Space Vehicle Design?Computation of Optimal Low Thrust Transfers?Indirect Optimization of Spacecraft Trajectories?Resource-Constrained Scheduling,?Packing Problems in Space?Design of Complex Interplanetary Trajectories?Satellite Constellation Image Acquisition?Re-entry Test Vehicle Configuration Selection?Collision Risk Assessment on Perturbed Orbits?Optimal Robust Design of Hybrid Rocket Engines?Nonlinear Regression Analysis in Space Engineering<?Regression-Based Sensitivity Analysis and Robust Design?Low-Thrust Multi-Revolution Orbit Transfers?Modeling and Optimization of Balance Layout Problems?Pilot-Induced Oscillations Alleviation?Modeling and Optimization of Hybrid Transfers to Near-Earth Objects?Probabilistic Safety Analysis of the Collision Between Space Debris and Satellite?Flatness-based Low-thrust Trajectory Optimization for Spacecraft Proximity Operations The contributing authors are expert researchers and practitioners in either the space engineering and/or in the applied optimization fields. Researchers and practitioners working in various applied aspects of space engineering will find this book practical and informative. Academics, graduate and post-graduate students in aerospace engineering, applied mathematics, operations research, optimization, and optimal control, will find this book useful.
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|a Pintér, J.,
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