Model reduction of aerothermodynamic for hypersonic aerothermoelasticity based on POD and Chebyshev method

2018 ◽  
Vol 233 (10) ◽  
pp. 3734-3748
Author(s):  
Yan Xiaoxuan ◽  
Han Jinglong ◽  
Zhang Bing ◽  
Yuan Haiwei
Keyword(s):  
Computational Cost ◽  
Maximum Error ◽  
Control Surface ◽  
Alternative Approach ◽  
Average Maximum ◽  
Optimization And Control ◽  
Efficient Alternative ◽  
Computational Fluid Dynamics Cfd ◽  
And Control ◽  
Proper Orthogonal

Accurate modeling of aerothermodynamics with low computational cost takes on a crucial role for the optimization and control of hypersonic vehicles. This study examines three reduced-order models (ROMs) to provide a reliable and efficient alternative approach for obtaining the aerothermodynamics of a hypersonic control surface. Coupled computational fluid dynamics (CFD) and computational thermostructural dynamics (CTSD) approaches are used to generate the snapshots for ROMs considering the interactions between aerothermodynamics, structural dynamics and heat transfer. One ROM adopts a surrogate approach named Kriging. The second ROM is constructed by the combination of Proper Orthogonal Decomposition (POD) and Kriging, namely, POD-Kriging. The accuracy of Kriging-based ROM is higher than that of POD-Kriging-based ROM, but the efficiency is lower. Therefore, to address the shortcomings of the above two approaches, a new ROM is developed that is composed of POD and modified Chebyshev polynomials, namely, POD-Chebyshev. The ROM based on POD-Chebyshev has the best precision and efficiency among the three ROMs and generally has less than 2% average maximum error for the studied problem.

scholarly journals An Approach for Model Reduction of Biochemical Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Yen-Chang Liu ◽  
Chun-Liang Lin ◽  
Chia-Hua Chuang
Keyword(s):  
Model Reduction ◽  
System Analysis ◽  
Computational Cost ◽  
Biochemical Networks ◽  
State Variables ◽  
Optimization And Control ◽  
Multiobjective Analysis ◽  
Value Decomposition ◽  
And Control ◽  
Great Complexity

Biochemical networks are not only complex but also extremely large. The dynamic biological model of great complexity resulting in a large number of parameters is a main difficulty for optimization and control processes. In practice, it is highly desirable to further simplify the structure of biological models for the sake of reducing computational cost or simplification for the task of system analysis. This paper considers the S-system model used for describing the response of biochemical networks. By introducing the technique of singular value decomposition (SVD), we are able to identify the major state variables and parameters and eliminate unimportant metabolites and the corresponding signal transduction pathways. The model reduction by multiobjective analysis integrates the criteria of reactive weight, sensitivity, and flux analyses to obtain a reduced model in a systematic way. The resultant model is closed to the original model in performance but with a simpler structure. Representative numerical examples are illustrated to prove feasibility of the proposed method.

scholarly journals A Review of Computational Methods and Reduced Order Models for Flutter Prediction in Turbomachinery

Aerospace ◽  
2021 ◽  
Vol 8 (9) ◽  
pp. 242
Author(s):  
Marco Casoni ◽  
Ernesto Benini
Keyword(s):  
Computational Cost ◽  
Order Reduction ◽  
Computational Techniques ◽  
Fluid Structure Interactions ◽  
Reduction Techniques ◽  
Flow Induced Vibrations ◽  
Computational Fluid Dynamics Cfd ◽  
Complex Phenomena ◽  
Coupling Algorithms ◽  
And Control

Aeroelastic phenomena in turbomachinery are one of the most challenging problems to model using computational fluid dynamics (CFD) due to their inherent nonlinear nature, the difficulties in simulating fluid–structure interactions and the considerable computational requirements. Nonetheless, accurate modelling of self-sustained flow-induced vibrations, known as flutter, has proved to be crucial in assessing stability boundaries and extending the operative life of turbomachinery. Flutter avoidance and control is becoming more relevant in compressors and fans due to a well-established trend towards lightweight and thinner designs that enhance aerodynamic efficiency. In this paper, an overview of computational techniques adopted over the years is first presented. The principal methods for flutter modelling are then reviewed; a classification is made to distinguish between classical methods, where the fluid flow does not interact with the structure, and coupled methods, where this interaction is modelled. The most used coupling algorithms along with their benefits and drawbacks are then described. Finally, an insight is presented on model order reduction techniques applied to structure and aerodynamic calculations in turbomachinery flutter simulations, with the aim of reducing computational cost and permitting treatment of complex phenomena in a reasonable time.

Five-Lump Kinetic Model for the Catalytic Cracking Process\

2018 ◽  
Vol 69 (10) ◽  
pp. 2633-2637
Author(s):  
Raluca Dragomir ◽  
Paul Rosca ◽  
Cristina Popa
Keyword(s):  
Kinetic Model ◽  
Programming Language ◽  
Catalytic Cracking ◽  
Computational Method ◽  
Industrial Data ◽  
New Model ◽  
Optimization And Control ◽  
Cracking Process ◽  
And Control ◽  
Matlab Programming

The main objectives of the present paper are to adaptation the five-kinetic model of the catalytic cracking process and simulation the riser to predicts the FCC products yields when one of the major input variable of the process is change. The simulation and adaptation are based on the industrial data from Romanian refinery. The adaptation is realize using a computational method from Optimization Toolbox from Matlab programming language. The new model can be used for optimization and control of FCC riser.

Optimization and Control Petroleum Refinery Wastewater Treatment Systems — Status, Trends and Needs

1989 ◽  
Vol 24 (3) ◽  
pp. 463-477
Author(s):  
Stephen G. Nutt
Keyword(s):  
Wastewater Treatment ◽  
Process Control ◽  
Petroleum Refinery ◽  
Control Strategies ◽  
Refinery Wastewater ◽  
Statistical Process ◽  
Petroleum Refinery Wastewater ◽  
Optimization And Control ◽  
And Control ◽  
Wastewater Treatment Systems

Abstract Based on discussions in workshop sessions, several recurring themes became evident with respect to the optimization and control of petroleum refinery wastewater treatment systems to achieve effective removal of toxic contaminants. It was apparent that statistical process control (SPC) techniques are finding more widespread use and have been found to be effective. However, the implementation of real-time process control strategies in petroleum refinery wastewater treatment systems is in its infancy. Considerable effort will need to be expended to demonstrate the practicality of on-line sensors, and the utility of automated process control in petroleum refinery wastewater treatment systems. This paper provides a summary of the discussions held at the workshop.

scholarly journals Vertical Jumping for Legged Robot Based on Quadratic Programming

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3679
Author(s):  
Dingkui Tian ◽  
Junyao Gao ◽  
Xuanyang Shi ◽  
Yizhou Lu ◽  
Chuzhao Liu
Keyword(s):  
Quadratic Programming ◽  
Stance Phase ◽  
Center Of Mass ◽  
Maximum Error ◽  
Legged Robot ◽  
Flight Phase ◽  
Programming Framework ◽  
Vertical Jumping ◽  
Control Schemes ◽  
And Control

The highly dynamic legged jumping motion is a challenging research topic because of the lack of established control schemes that handle over-constrained control objectives well in the stance phase, which are coupled and affect each other, and control robot’s posture in the flight phase, in which the robot is underactuated owing to the foot leaving the ground. This paper introduces an approach of realizing the cyclic vertical jumping motion of a planar simplified legged robot that formulates the jump problem within a quadratic-programming (QP)-based framework. Unlike prior works, which have added different weights in front of control tasks to express the relative hierarchy of tasks, in our framework, the hierarchical quadratic programming (HQP) control strategy is used to guarantee the strict prioritization of the center of mass (CoM) in the stance phase while split dynamic equations are incorporated into the unified quadratic-programming framework to restrict the robot’s posture to be near a desired constant value in the flight phase. The controller is tested in two simulation environments with and without the flight phase controller, the results validate the flight phase controller, with the HQP controller having a maximum error of the CoM in the x direction and y direction of 0.47 and 0.82 cm and thus enabling the strict prioritization of the CoM.

scholarly journals A Multi-Timescale Bilinear Model for Optimization and Control of HVAC Systems with Consistency

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 400 ◽  
Author(s):  
Zelin Nie ◽  
Feng Gao ◽  
Chao-Bo Yan
Keyword(s):  
Optimization Model ◽  
Air Conditioning ◽  
State Of The Art ◽  
Hvac Systems ◽  
Practical Significance ◽  
Hvac System ◽  
Bilinear Model ◽  
Optimization And Control ◽  
And Control ◽  
Slow Timescale

Reducing the energy consumption of the heating, ventilation, and air conditioning (HVAC) systems while ensuring users’ comfort is of both academic and practical significance. However, the-state-of-the-art of the optimization model of the HVAC system is that either the thermal dynamic model is simplified as a linear model, or the optimization model of the HVAC system is single-timescale, which leads to heavy computation burden. To balance the practicality and the overhead of computation, in this paper, a multi-timescale bilinear model of HVAC systems is proposed. To guarantee the consistency of models in different timescales, the fast timescale model is built first with a bilinear form, and then the slow timescale model is induced from the fast one, specifically, with a bilinear-like form. After a simplified replacement made for the bilinear-like part, this problem can be solved by a convexification method. Extensive numerical experiments have been conducted to validate the effectiveness of this model.

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