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Interactive Uncertainty Allocation and Tradeoff for Early Stage Design of Complex Systems

AIAA JOURNAL 2020年第3期58卷 1356-1368页

作者： Molina-Cristobal, Arturo Chen, Xin Guenov, Marin D. Riaz, Atif van Heerden, Albert S. J. Cranfield Univ Sch Aerosp Transport & Mfg Ctr Aeronaut Cranfield MK43 0AL Beds England

A common probabilistic approach to perform uncertainty allocation is to assign acceptable variability in the sources of uncertainty, such that prespecified probabilities of meeting performance constraints are satisfied. However, the computational cost of obtaining the associated tradeoffs increases significantly when more sources of uncertainty and more outputs are considered. Consequently, visualizing and exploring the decision (trade) space becomes increasingly difficult, which, in turn, makes the decision-making process cumbersome for practicing designers. To address this problem, proposed is a parameterization of the input probability distribution functions, to account for several statistical moments. This, combined with efficient uncertainty propagation and inverse computation techniques, results in a computational system that performs order(s) of magnitude faster than a state-of-the-art optimization technique. The approach is demonstrated by means of an illustrative example and a representative aircraft thermal system integration example.

关键词： Probability Distribution Functions Surrogate Model Heat Dissipation Avionics Airframes Sensitivity Analysis Aircraft Conceptual Design Heat Transfer Coefficients optimization algorithm Material Properties

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Spare Aeroengine Demand Prediction Model Based on Deep Croston Method

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2020年第2期17卷 125-133页

作者： Liu, Lie Lin, Lin Li, Zhen Guo, Hao Lv, Yancheng Harbin Inst Technol Sch Mechatron Engn Harbin 150001 Peoples R China

The spare aeroengine demand prediction is a crucial issue in aeroengine fleet management. For more accurate predictions, a spare aeroengine demand prediction model is proposed based on the deep Croston method. The Croston framework is adopted to deal with the intermittent demand characteristic. The demand interval prediction model and the demand amount prediction model were developed by the long short-term memory deep learning network. Accompanied with the proposed spare aeroengine demand prediction model, a comprehensive evaluation method of intermittent demand prediction is proposed. The actual spare aeroengine demand data of an airline company were adopted to validate the proposed spare aeroengine demand prediction model. The traditional Croston method was regarded as the benchmark comparison model. Under the Croston framework, the machine learning methods, including back propagation neural network, support vector machine, gradient boosting decision tree, extreme gradient boosting tree, and multilayer perceptron network, were also adopted as the comparison models. The prediction results showed that the proposed spare aeroengine demand prediction model based on the deep Croston method achieved evident advantages. Compared with the traditional Croston method, the machine learning methods provide a satisfactory way for intermittent demand prediction.

关键词： Aeroengine Recurrent Neural Network Support Vector Machine Turbofan Stochastic Gradient Descent optimization algorithm Inventory Management Hydraulic Systems Civil Aircraft Flight Planning

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Parameter extraction of photovoltaic cell and module: Analysis and discussion of various combinations and test cases

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SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS 2020年 40卷

作者： Oulcaid, Mostapha El Fadil, Hassan Ammeh, Leila Yahya, Abdelhafid Giri, Fouad Ibn Tofail Univ LGS Lab Kenitra 14000 Morocco Univ Caen Lab Automat Caen Bd Marechal JuinBP 8156 F-14032 Caen France

A reliable model for photovoltaic (PV) cell/panel is of great interest;it helps to simulate and better understand the behavior of PV systems. Consequently, better control and optimization of the system can be achieved. The most used models of PV cell/panel in literature are the one-diode (ODM) and double-diode (DDM) models. Their accuracy strongly depends on their parameters which must be obtained carefully. optimization-based approaches are widely adopted for this purpose. In this context, this paper presents two main references studies: The first one focuses on optimization methods and their three basic elements: model, objective function and algorithm. The study highlights the improvement that can be made to the accuracy of the final I-V curve and to the CPU-time required for the extraction by choosing the right combination of the three elements. This is done through the analysis of more than 50 results obtained by different combinations of algorithms, objective functions and models applied to benchmark PV cells and panels widely used in literature. The best combinations are identified and recommended. The second is a detailed comparison and classification of 47 I-V curve estimation methods based on three different approaches: optimization techniques, analytical methods and explicit models of PV cells/panels.

关键词： Photovoltaic cell model optimization algorithm Parameter extraction Analytical approach Explicit models

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Hierarchical Nondeterministic optimization of Curvilinearly Stiffened Panel with Multicutouts

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AIAA JOURNAL 2018年第10期56卷 4180-4194页

作者： Hao, Peng Wang, Yutian Liu, Chen Wang, Bo Tian, Kuo Li, Gang Wang, Qun Jiang, Liangliang Dalian Univ Technol Dept Engn Mech State Key Lab Struct Anal Ind Equipment Dalian 116023 Liaoning Peoples R China China Acad Launch Vehicle Technol Beijing Inst Astronaut Syst Engn Beijing 100076 Peoples R China

The concept of a curvilinearly stiffened panel is promising for aerospace and aircraft structures with cutouts, since the stiffness distribution and loading path can be flexibly tailored in terms of cutouts. However, uncertainties from the manufacturing process can significantly reduce the practical load-carrying capacity of a curvilinearly stiffened panel. Traditional nondeterministic design optimization methods would suffer from a high computational burden because numerous discrete-continuous variables, in which thousands of finite element analyses are usually required, are involved. Therefore, a hierarchical nondeterministic optimization framework of a curvilinearly stiffened panel is established, containing two steps (global search and local search) and four main parts (layout design, nondeterministic design optimization, reshape layout design, and stress validation). In the first-step deterministic optimization, all variables are considered, and a rough result set will be obtained by a global search. In the second-step nondeterministic optimization, all discrete-continuous layout parameters are fixed in the initial stage, and the efficient adaptive-loop method is applied to significantly increase the computational efficiency, in which the variations of material properties and geometric dimensions are considered as uncertainties. The layout also will be reshaped to explore the potential of the load-carrying capacity. Finally, the stress constraint and crippling constraint are verified for the optimum design. An illustrative example indicates the advantage of the proposed framework not merely provides a competitive efficiency and robustness over other nondeterministic approaches but also improves the rationality of deterministic design optimization.

关键词： Material Properties Aircraft Structures Structural Weight Elastic Modulus Cumulative Distribution Function Postbuckling Analysis Finite Element Method Principal Stresses Numerical Stability optimization algorithm

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Joint edge offloading and caching for cooperation scheme reasearch

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Procedia Computer Science 2020年 174卷 280-285页

作者： Yaojia Chen Feng Zeng Wenjia Li School of Computer Science and Engineering Central South University Changsha 410082 China Department of Computer Science New York Institute of Technology Address New York 10023 USA

In order to provide a low latency and high experience of quality vehicular network environment, this paper proposes an application cache scheme which combines computational offloading and edge cache in vehicular edge computing. Based on vehicle requests, the scheme caches high popularity applications and related data to quickly meet subsequent vehicles with the same requirements. Considering the selfishness of vehicles and the limitation of computing resources in edge servers, we design a cooperation scheme to encourage vehicle users to share their applications and data with others. Simulation results show that the scheme is superior to the traditional schemes in terms of transmission delay and quality of experience (QoE).

关键词： VEC cooperation scheme application cache optimization algorithm

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Variable-Fidelity optimization of Film-Cooling Hole Arrangements Considering Conjugate Heat Transfer

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JOURNAL OF PROPULSION AND POWER 2018年第5期34卷 1140-1151页

作者： Kim, Yoonki Lee, Sanga Yee, Kwanjung Seoul Natl Univ Dept Mech & Aerosp Engn Seoul 08826 South Korea Seoul Natl Univ Dept Mech & Aerosp Engn Inst Adv Aerosp Technol Seoul 08826 South Korea

In spite of its crucial importance, conjugate heat transfer has been ignored in most film-hole-array optimization studies due to the burdensome associated with added complexity and computational requirements. To cope with this issue and to consider the conduction cooling effects, the hierarchical kriging model was applied to optimize the film-cooling hole array on a high-pressure turbine nozzle. The hierarchical kriging model used in this study consists of three levels and was constructed effectively using both adiabatic-condition-based analyses and conjugate-heat-transfer analyses. The expected-improvement-based efficient globala* optimization algorithm was coupled with the hierarchical kriging model to improve the efficiency of the whole optimization process. As a result, the required computation time to obtain the optimum solution was markedly reduced to a quarter compared to the time without the hierarchical kriging model, and the viability of the method for highly nonlinear and time-consuming problems was proved. Additionally, the conjugate-heat-transfer-based optimum film-hole array showed that it has improved the overall cooling effectiveness and could have a different shape compared to the array obtained under the adiabatic wall condition. The detailed causes of the resultant hole arrangement were thoroughly examined with respect to both the external and internal cooling aspects.

关键词： Conjugate Heat Transfer Analysis Film Cooling Kriging Model Turbine Inlet Temperature Adiabatic Conditions Wall Temperature optimization algorithm Coolant Aerodynamic Properties Nozzle Geometry

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Mimicking the collective intelligence of human groups as an optimization tool for complex problems

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CHAOS SOLITONS & FRACTALS 2018年 110卷 259-266页

作者： De Vincenzo, Ilario Massari, Giovanni F. Giannoccaro, Ilaria Carbone, Giuseppe Grigolini, Paolo Politecn Bari Dept Mech Math & Management Vle Japigia 182 I-70126 Bari Italy UOS Bari CNR Inst Photon & Nanotechnol Phys Dept M Merlin Via Amendola 173 I-70126 Bari Italy Imperial Coll London Dept Mech Engn South Kensington Campus London SW7 2AZ England Univ North Texas Ctr Nonlinear Sci POB 311427 Denton TX 76203 USA

A large number ofa* optimization algorithms have been developed by researchers to solve a variety of complex problems in operations management area. We present a novela* optimization algorithm belonging to the class of swarm intelligence optimization methods. The algorithm mimics the decision making process of human groups and exploits the dynamics of such a process as a tool for complex combinatorial problems. In order to achieve this aim, we employ a properly modified version of a recently published decision making model [ 64,65], to model how humans in a group modify their opinions driven by self-interest and consensus seeking. The dynamics of such a system is governed by three parameters: (i) the reduced temperature beta J, (ii) the self-confidence of each agent beta', (iii) the cognitive level 0 <= p <= 1 of each agent. Depending on the value of the aforementioned parameters a critical phase transition may occur, which triggers the emergence of a superior collective intelligence of the population. Our algorithm exploits such peculiar state of the system to propose a novel tool for discrete combinatorial optimization problems. The benchmark suite consists of the NK-Kauffman complex landscape, with various sizes and complexities, which is chosen as an exemplar case of classical NP-complete optimization problem. A comparison with genetic algorithms (GA), simulated annealing (SA) as well as with a multiagent version of SA is presented in terms of efficacy in finding optimal solutions. In all cases our method outperforms the others, particularly in presence of limited knowledge of the agent. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： optimization algorithm Artificial intelligence Collaborative decisions Decision making Group decision Social interactions Complexity Markov chains

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Fine Reconstitution of Trajectories of Airdropped Systems to Complete CARP Approach and Trajectory Analysis

Fine Reconstitution of Trajectories of Airdropped Systems to...

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AIAA Aviation Forum and Exposition

作者： Bergotti, David Perin, Basile Galetta, Clement Antier, Romeo DGA Aeronaut Syst 47 Rue St Jean F-31131 Balma 3 France Univ Paris Sud Univ Paris Saclay ENS Cachan LURPA F-94235 Cachan France Univ Paris Diderot Univ Sorbonne ESPCI PSL Res Univ PMMHCNRS Paris France

ISBN: (数字)9781624105890

ISBN: (纸本)9781624105890

Since parachutes exist, anticipating paratrooper or load trajectories has been one key topic for airdrop operations. The widely used trajectory computation model called CARP (Computed Air Release Point), which decomposes a trajectory into a sum of a straight line segments, needs to be fed with a few parameters able to approximate the load behavior. Live trajectories need to be precisely recorded, mainly manually processed and then statistically merged in order to provide the figures for each of the parameters required as inputs in the CARP calculations. A numerical tool has been developed to process almost automatically the recorded trajectories and to diminish the number of assumptions needed for trajectory analysis when compared to the manual processes. In parallel, a three-point (extractor parachute;parachute;load) refined airdrop simulation model has been developed. This model uses the "ingested volume" parachute inflation theory and has been tuned to mimic one live trajectory with an accuracy of one to two meters from aircraft exit until ground impact. By modifying simulation input conditions, mainly wind conditions, the previously mentioned post-processing trajectory tool accuracy can be demonstrated when fed with the simulated trajectories. In addition, more in-depth simulation conditions changes (i.e. load mass, drop altitude, air mass considered within the parachute) were followed by visual subsequent trajectory analysis as well as automatic post-processing. On the one hand this approach gives an insight to the influence that these changes have on the trajectory itself. On the other hand it allows to estimate quantitatively the impact of any single condition change on the various CARP parameters. This paper merges parachute inflation numerical simulation approach with new airdrop trajectories post-treatment methods and allows CARP parametric evaluations with regards to changes in drop conditions.

关键词： Computed Air Release Point Numerical Simulation Cargo Hold Aircraft Speed optimization algorithm Drag Coefficient Altimeter Lift Coefficient Flight Testing Wind Tunnels

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Incorporating stochastics into optimal collision avoidance problems using superquadrics

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Journal of Air Transportation 2020年第2期28卷 65-69页

作者： Smith, Nathan E. Cobb, Richard G. Baker, William P. Air Force Institute of Technology Wright-Patterson Air Force Base U.S. Air Force Ohio45433 United States Department of Aeronautics & Astronautics Air Force Institute of Technology Wright-Patterson Air Force Base Ohio45433 United States Department of Mathematics & Statistics Air Force Institute of Technology Wright-Patterson Air Force Base Ohio45433 United States

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Retrieving tow paths from a fiber angle distribution on single, and double curved surfaces

Retrieving tow paths from a fiber angle distribution on sing...

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AIAA Science and Technology (SciTech) Forum and Exposition

作者： Pupol, C. van Zanten, F. J. Barazanchy, D. van Tooren, M. Univ South Carolina Columbia SC 29208 USA Delft Univ Technol NL-2628 CD Delft Netherlands

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

A framework utilizing the dual mesh approach previously used for the optimization of variable stiffness laminates [1] is now employed to retrieve tow paths on single and double curved surfaces. Previously the tow path generation was performed on a single mesh containing the optimized design variables, because the optimized mesh does not follow the 3D geometry accurately for fiber placement, an expansion for mapping of the fiber paths on the 3D shells was necessary. The new approach has been tested with multiple inhouse benchmark cases. Since, tow path generation is highly dependent on seed point positioning, seeding strategies previously developed for 2D cases have been expanded to the 3D tow path planner. The framework provided satisfying results in the generation of tow paths on single and double curved surfaces later shown.

关键词： Finite Element Analysis Triangular Element Python optimization algorithm Composite Materials Abaqus CATIA

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