scholarly journals OPTIMIZATION OF LONG-RANGE TRAJECTORY FOR AN UNPOWERED FLIGHT VEHICLE

2020 ◽  
Vol 57 (6A) ◽  
pp. 43
Author(s):  
Tuan Hung Pham ◽  
Duc Cuong Nguyen ◽  
Duc Thanh Nguyen
Keyword(s):  
Long Range ◽  
Numerical Experiments ◽  
Optimization Problem ◽  
Normal Load ◽  
Load Factor ◽  
Flight Vehicle ◽  
Maximum Range ◽  
Normal Acceleration

This report presents problems of optimization of long-range trajectory for an unpowered flight vehicle at subsonic and transonic speed. The results may be recommended to have a new long range trajectory. The optimization problem is solved by numerical experiments while  the normal load factor (normal acceleration) is used as optimization variables with compliance to flight constraints. The focus problem of this study is the investigation of the possibility of trajectory expansion according to the criteria of the maximum range in the first stage of the trajectory.  

scholarly journals OPTIMIZATION OF LONG-RANGE TRAJECTORY FOR AN UNPOWERED FLIGHT VEHICLE

2020 ◽  
Vol 57 (6A) ◽  
pp. 43
Author(s):  
Tuan Hung Pham ◽  
Duc Cuong Nguyen ◽  
Duc Thanh Nguyen
Keyword(s):  
Long Range ◽  
Numerical Experiments ◽  
Optimization Problem ◽  
Normal Load ◽  
Load Factor ◽  
Flight Vehicle ◽  
Maximum Range ◽  
Normal Acceleration

This report presents problems of optimization of long-range trajectory for an unpowered flight vehicle at subsonic and transonic speed. The results may be recommended to have a new long range trajectory. The optimization problem is solved by numerical experiments while  the normal load factor (normal acceleration) is used as optimization variables with compliance to flight constraints. The focus problem of this study is the investigation of the possibility of trajectory expansion according to the criteria of the maximum range in the first stage of the trajectory.  

scholarly journals Discretization and machine learning approximation of BSDEs with a constraint on the Gains-process

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Idris Kharroubi ◽  
Thomas Lim ◽  
Xavier Warin
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Neural Networks ◽  
Differential Equations ◽  
Numerical Experiments ◽  
Optimization Problem ◽  
Learning Approach ◽  
The Neural Network ◽  
Machine Learning Approach ◽  
Mesh Grid

AbstractWe study the approximation of backward stochastic differential equations (BSDEs for short) with a constraint on the gains process. We first discretize the constraint by applying a so-called facelift operator at times of a grid. We show that this discretely constrained BSDE converges to the continuously constrained one as the mesh grid converges to zero. We then focus on the approximation of the discretely constrained BSDE. For that we adopt a machine learning approach. We show that the facelift can be approximated by an optimization problem over a class of neural networks under constraints on the neural network and its derivative. We then derive an algorithm converging to the discretely constrained BSDE as the number of neurons goes to infinity. We end by numerical experiments.

Feeder Ship Size Optimization in Maritime Markets with Uncertainty

2021 ◽  
Vol 38 (03) ◽  
pp. 2040014
Author(s):  
Hongtao Hu ◽  
Jiao Mo ◽  
Lufei Huang
Keyword(s):  
Dynamic Programming ◽  
Stochastic Dynamic Programming ◽  
Numerical Experiments ◽  
Optimization Problem ◽  
Planning Horizon ◽  
Dynamic Programming Method ◽  
Size Optimization ◽  
Stochastic Dynamic ◽  
Shipping Company ◽  
Decision Behaviors

This paper considers the ship size optimization problem for a liner shipping company that provides feeder service between one hub port and one feeder port. In the maritime market with uncertainty, this problem becomes more challenging. This research first analyzes the decision behaviors of the shipping company. Then, a stochastic dynamic programming method is proposed to calculate the expected total volume of containers transported within the planning horizon. Using the calculated volumes as input parameters calculate the profit of each ship sizes and then determine the suitable ship size for the feeder route. Numerical experiments are performed to validate the effectiveness of the proposed method and the efficiency of the proposed algorithm.

MODELING EXPERIMENTAL DATA WITH POLYNOMIALS CHAOS

2018 ◽  
Vol 34 (1) ◽  
pp. 14-26
Author(s):  
Emeline Gayrard ◽  
Cédric Chauvière ◽  
Hacène Djellout ◽  
Pierre Bonnet
Keyword(s):  
Experimental Data ◽  
Constrained Optimization ◽  
Numerical Experiments ◽  
Optimization Problem ◽  
Polynomial Chaos ◽  
Numerical Procedure ◽  
Chaos Expansion ◽  
Constrained Optimization Problem ◽  
Raw Data ◽  
Accurate Representation

Given a raw data sample, the purpose of this paper is to design a numerical procedure to model this sample under the form of polynomial chaos expansion. The coefficients of the polynomial are computed as the solution to a constrained optimization problem. The procedure is first validated on samples coming from a known distribution and it is then applied to raw experimental data of unknown distribution. Numerical experiments show that only five coefficients of the Chaos expansions are required to get an accurate representation of a sample.

scholarly journals A Quasiphysical and Dynamic Adjustment Approach for Packing the Orthogonal Unequal Rectangles in a Circle with a Mass Balance: Satellite Payload Packing

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Ziqiang Li ◽  
Xianfeng Wang ◽  
Jiyang Tan ◽  
Yishou Wang
Keyword(s):  
Potential Energy ◽  
Mass Balance ◽  
Energy Function ◽  
Numerical Experiments ◽  
Optimization Problem ◽  
Optimal Solution ◽  
Potential Energy Function ◽  
Resultant Force ◽  
Dynamic Adjustment ◽  
Combinational Optimization

Packing orthogonal unequal rectangles in a circle with a mass balance (BCOURP) is a typical combinational optimization problem with the NP-hard nature. This paper proposes an effective quasiphysical and dynamic adjustment approach (QPDAA). Two embedded degree functions between two orthogonal rectangles and between an orthogonal rectangle and the container are defined, respectively, and the extruded potential energy function and extruded resultant force formula are constructed based on them. By an elimination of the extruded resultant force, the dynamic rectangle adjustment, and an iteration of the translation, the potential energy and static imbalance of the system can be quickly decreased to minima. The continuity and monotony of two embedded degree functions are proved to ensure the compactness of the optimal solution. Numerical experiments show that the proposed QPDAA is superior to existing approaches in performance.

scholarly journals Identification of a Parameter in Fourth-Order Partial Differential Equations by an Equation Error Approach

2015 ◽  
Vol 65 (5) ◽  
Author(s):  
Nathan Bush ◽  
Baasansuren Jadamba ◽  
Akhtar A. Khan ◽  
Fabio Raciti
Keyword(s):  
Partial Differential Equations ◽  
Differential Equations ◽  
Fourth Order ◽  
Numerical Experiments ◽  
Optimization Problem ◽  
Short Note ◽  
Variable Parameter ◽  
Partial Differential ◽  
Convergence Results ◽  
Equation Error

AbstractThe objective of this short note is to employ an equation error approach to identify a variable parameter in fourth-order partial differential equations. Existence and convergence results are given for the optimization problem emerging from the equation error formulation. Finite element based numerical experiments show the effectiveness of the proposed framework.

scholarly journals Finding the Roots of System of Nonlinear Equations by a Novel Filled Function Method

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Wei-Xiang Wang ◽  
You-Lin Shang ◽  
Wei-Gang Sun ◽  
Ying Zhang
Keyword(s):  
Nonlinear Equations ◽  
Numerical Experiments ◽  
Function Method ◽  
Optimization Problem ◽  
Test Problems ◽  
System Of Nonlinear Equations ◽  
Global Optimization Problem ◽  
Filled Function ◽  
Filled Function Method ◽  
Constrained System

We present a novel filled function approach to solve box-constrained system of nonlinear equations. The system is first transformed into an equivalent nonsmooth global minimization problem, and then a new filled function method is proposed to solve this global optimization problem. Numerical experiments on several test problems are conducted and the computational results are also reported.

scholarly journals Quantitative Assessment of Dynamic Stability Characteristics for Jet Transport in Sudden Plunging Motion

2021 ◽  
Author(s):  
Yonghu Wang ◽  
Ray C. Chang ◽  
Wei Jiang
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Stability ◽  
Quantitative Assessment ◽  
Normal Load ◽  
Unsteady Aerodynamics ◽  
Assessment Method ◽  
Load Factor ◽  
Gravitational Acceleration ◽  
Transport Aircraft ◽  
Motion Modes

Abstract The main objective of this article is to present a training program of loss control prevention for the airlines to enhance aviation safety and operational efficiency. The assessments of dynamic stability characteristics based on the approaches of oscillatory motion and eigenvalue motion modes for jet transport aircraft response to sudden plunging motions are demonstrated in this article. A twin-jet transport aircraft encountering severe clear-air turbulence in transonic flight during the descending phase will be examined as the study case. The flight results in sudden plunging motions with abrupt changes in attitude and gravitational acceleration (i.e. the normal load factor). Development of the required thrust and aerodynamic models with the flight data mining and the fuzzy-logic modeling techniques will be presented. The oscillatory derivatives extracted from these aerodynamic models are then used in the study of variations in stability characteristics during the sudden plunging motion. The fuzzy-logic aerodynamic models are utilized to estimate the nonlinear unsteady aerodynamics while performing numerical integration of flight dynamic equations. The eigenvalues of all motion modes are obtained during time integration. The present quantitative assessment method is an innovation to examine possible mitigation concepts of accident prevention and promote the understanding of aerodynamic responses of the jet transport aircraft.

scholarly journals Solving Rich Vehicle Routing Problem Using Three Steps Heuristic

2019 ◽  
Vol 1 (1) ◽  
pp. 1-19
Author(s):  
Editor
Keyword(s):  
Vehicle Routing ◽  
Public Transportation ◽  
Vehicle Routing Problem ◽  
Optimization Problem ◽  
Maximum Load ◽  
Load Factor ◽  
Routing Problem ◽  
The Government ◽  
Hard And Soft Constraints

Vehicle Routing Problem (VRP) relates to the problem of providing optimum service with a fleet of vehicles to customers. It is a combinatorial optimization problem. The objective is usually to maximize the profit of the operation. However, for public transportation owned and operated by the government, accessibility takes priority over profitability. Accessibility usually reduces profit, while increasing profit tends to reduce accessibility. In this research, we look at how accessibility can be increased without penalizing the profitability. This requires the determination of routes with minimum fuel consumption, the maximum number of ports of call and maximum load factor satisfying a number of pre-determined constraints: hard and soft constraints. To solve this problem, we propose a heuristic algorithm. The results from this experiment show that the algorithm proposed has better performance compared to the partitioning set.

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