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Flight Performance Optimization Considering Environmental Impact Under multi-RTA Constraints

INTERNATIONAL JOURNAL OF AERONAUTICAL AND SPACE SCIENCES 2019年第4期20卷 964-977页

作者： Gu, Runping Yuan, Jie Han, Xiaolan Wei, Zhiqiang Li, Na Civil Aviat Univ China Coll Air Traff Management Tianjin Peoples R China China Acad Civil Aviat Sci & Technol Beijing Peoples R China

To optimize the flight performance under multi-waypoint required time of arrival constraints, characteristics of the vertical flight trajectory during the en route descent process are studied. A multi-constraint segment sequence model including flight distance, flight altitude and arrival time is constructed. To ensure the rationality of constraints, the rationality detection model for multi-constraint is established. The control variables and their variation ranges are determined by analyzing the optimization process. Mathematical models of optimization objectives are studied from three aspects: fuel economy, greenhouse effect and variation of flight speed. Based on the multi-objective genetic algorithm, the optimization solution model is established. Effects of speed on the objectives are analyzed. The results indicate that the optimization model can effectively optimize the flight parameters with multiple RTA constraints. The impact of aviation on the environment can be effectively reduced. And the optimization method has a good trade-off between fuel consumption and temperature rise by changing weighted factors. Optimization results of the flight parameters are mainly affected by the maximum RTA time constraint. The proposed optimization method provides a reference for the optimization of flight parameters and trajectory under multi-RTA constraints in four dimensions.

关键词： Flight performance Required time of arrival multi-objective genetic algorithm Vertical profile

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Sounding rocket SS-520 as a CubeSat launch vehicle

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ACTA ASTRONAUTICA 2020年 170卷 206-223页

作者： Ito, T. Yamamoto, T. Nakamura, T. Habu, H. Ohtsuka, H. Japan Aerosp Explorat Agcy Chuo Ku 3-1-1 Yoshinodai Sagamihara Kanagawa 2525210 Japan IHI AEROSP Co Ltd 900 Fujiki Tomioka Gunma 3702398 Japan

This paper investigates the launch capability of the SS-520 as a CubeSat launch vehicle. The SS-520 was developed by JAXA originally as a two-stage, spin-stabilized, solid-propellant sounding rocket. With less than 2.6 tons in total mass and 10 m in length, the SS-520-5 successfully launched a single 3U-sized CubeSat into orbit on February 3, 2018. The SS-520-5 obtained its capability as a CubeSat launch vehicle by installing a 3rd stage solid motor in addition to the RCS between the 1st and 2nd stages. However, its launch capability was limited due to its rocket system configuration. In order to pursue the SS-520's launch capability, two effective modifications from the SS-520-5 are proposed: thrust enhancement of the 1st stage motor and installation of an additional RCS between the 2nd and 3rd stages. The framework of launch capability analysis is established by a multi-objective genetic algorithm (MOGA), where its two objectives are selected as the altitudes of perigee and apogee. The analysis reveals that the two proposed modifications to the SS-520-5 work effectively but differently. The 10% increase of the 1st stage enhancement is particularly effective when the target altitude of perigee is low (e.g., 200 km), whereas the installment of the additional RCS with 30 kg increases accessibility to a much higher altitude of perigee, even to circular orbit reaching altitudes of 550 km for a 1U-sized CubeSat and 280 km for a 6U-sized CubeSat. The simultaneous application of both modifications would result in launch capability able to deliver a 10-kg payload. From a more general perspective, the results in this paper suggest that it is possible for a very small launch vehicle (VSLV) of the 3-ton class and 10m in length to deliver a 10-kg-class payload into low Earth orbit.

关键词： SS-520 Very small launch vehicle (VSLV) Mission design and analysis multi-objective genetic algorithm Attitude control for spinning spacecraft

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Optimization of heat transfer enhancement of nanofluid in a channel with winglet vortex generator

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APPLIED THERMAL ENGINEERING 2015年 91卷 1116-1126页

作者： Abdollahi, Azita Shams, Mehrzad KN Toosi Univ Technol Fac Mech Engn Tehran Iran

A numerical simulation was performed to investigate the effect of the nanoparticles, vortex generator and combination of them on heat transfer and fluid flow characteristics in a rectangular channel using Commercial Computational Fluid Dynamics Code FLUENT. Euler-Lagrangian approach was utilized in the numerical modeling of the nanofluids. The fluid was considered as a continuous phase and the heat and flow fields were analyzed by solving Navier-Stokes and energy equations and the nanoparticles were simulated as a discrete phase in a Lagrangian frame. The thermal and hydraulic performances of the channel were investigated at different nanoparticle concentration, shape and angle of attack of the vortex generator. According to the results, the Nusselt number increases by raising the nanoparticles concentration and adding nanoparticles is more effective than placing VG from thermal point of view in the range of study. Using a combination of these heat transfer enhancers maximizes the thermal performance of the channel as well as the flow resistance. So, in order to achieve the best thermal-hydraulic performance, combination of the computational fluid dynamics analyses, artificial neural networks and multi-objective genetic algorithm was used to determine the optimal values of these parameters. Finally, a set of optimal solutions as well as the best shape, angle of attack of the VG and nanoparticles volume fraction was obtained. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Heat transfer enhancement Vortex generator Nanofluids multi-objective genetic algorithm Artificial neural network

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Application of entransy theory on structure optimization of serrated fin in plate-fin heat exchanger

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APPLIED THERMAL ENGINEERING 2020年 173卷 114809-114809页

作者： Li, Ke Wen, Jian Liu, Yuce Liu, Huaqing Wang, Simin Tu, Jiyuan Xi An Jiao Tong Univ Sch Energy & Power Engn Dept Refrigerat & Cryogen Engn Xian 710049 Peoples R China Xi An Jiao Tong Univ Sch Chem Engn & Technol Dept Proc Equipment & Control Engn Xian 710049 Peoples R China Tsinghua Univ Inst Nucl & New Energy Technol Key Lab Adv Reactor Engn & Safety Minist Educ Beijing 100084 Peoples R China

The effects of geometrical parameters of serrated fin in plate-fin heat exchanger (PFHE) on entransy-dissipationbased thermal resistance (EDTR) caused by heat transfer (R-ht) and fluid friction (R-ff ) are investigated by design of experiment(DOE) and response surface methodology (RSM) in this paper. The results show that the fin height, fin interrupted length and fin space are positively correlated with R-ht, while the fin thickness and PFHE length are negatively correlated with R-ht. R-ff is far larger than R-ht, for about an order of magnitude, and R-ff increases almost linearly with the increase of Re when geometric parameters are fixed. R-ff increases with fin thickness and PFHE length, and decreases with fin height, fin interrupted length and fin space. Furthermore, multi-objective genetic algorithm (MOGA) is carried out. Compared with the original design, R-ht of optimal structure 1 and 2 obtained based on two objectives of minimizing R-ff and minimizing R-ht reduces by 27.9% and 41.2%, respectively, and R-ff reduces by 65.3% and 55.8% respectively. Compared with the optimal results based on traditional objective functions (maximize j and minimize f), R-ht and R-ff obtained based on EDTR objective functions reduce by an average of 37.6% and 30.3% respectively, and the JF factor of EDTR optimal results increases by an average of 10.1%.The results show that the optimization results based on EDTR objective functions are better than that based on traditional objective functions for serrated fin in PFHE.

关键词： Plate-fin heat exchanger Serrated fin Response surface multi-objective genetic algorithm Entransy-dissipation-based thermal resistance

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A numerical investigation and design optimization of impingement cooling system with an array of air jets

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INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER 2017年第PartA期108卷 880-900页

作者： Lam, Prasanth Anand Kumar Prakash, K. Arul IIT Madras Dept Appl Mech Fluid Mech Lab Madras 600036 Tamil Nadu India

In the present study, fluid flow, heat transfer and entropy generation in impingement cooling system with an array of air jets for different values of Reynolds number (Re), Velocity Ratio (VR) and Channel Height (H/L) are investigated. The magnitude of overall Nusselt number ((NUo) over bar((v)) over bar) and global total entropy generation (S-tot,(Omega)) is found to increase with increasing Re,VR and decreasing H/L. Further, spectral and proper orthogonal decomposition analyses are performed to analyze spatio-temporal dynamics of vortex structures for unsteady configurations of impingement cooling system. It is observed that, along the interface of jet (both primary and secondary) and ambient fluid, the destabilizing effect of shear forces overcome the stabilizing effect of momentum diffusion. This results in evolution of counter-rotating vortex rings along the interfaces of jet and ambient fluid due to shear layer instability. Finally, multi objective genetic algorithm (MOGA) has been implemented to obtain optimum configurations of impingement cooling system where a trade-off between two performance parameters,(NUo) over bar((v)) over bar and S-tot,S-Omega is obtained. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Impinging jet array SUPG-finite element method Entropy generation Proper orthogonal decomposition multi-objective genetic algorithm

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Quasi-perfect and wideband absorption with gradient non-uniform micro-slit array absorber via a hierarchical optimization method

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APPLIED ACOUSTICS 2023年第1期206卷

作者： Liao, Weiwei Hu, Run Xing, Guanying Luo, Xiaobing Huazhong Univ Sci & Technol Sch Energy & Power Engn Wuhan 430074 Peoples R China

Gradient micro-slit array absorber, a kind of acoustic metamaterial, made of multiple quarter-wavelength resonators, is holding a promising future in industrial utilization due to its flexible adaptation and simple structure. However, designing a perfect and broadband absorber remains a huge challenge because of the larger number of the design parameters and complicated coupling effect between different resonators. In this study, a hierarchical optimization method is developed for gradient micro-slit array absorber. First, a prior test based on two-slit absorber is conducted using transfer matrix method (TMM) to give directions on designing a multi-slit absorber. And then an original absorber model is constructed in the range of 1000-1800 Hz. For the first step, the optimal width of the slit is obtained through the analysis of the qual-ity factor. For the second step, the spacings between slits is optimized by maximizing absorption and minimizing the total length of the waveguide. After optimization, the absorption performance of the opti-mized model increased by 15.6% and the length decreased by 46% compared with the original model. Finally, the gradient micro-slit array absorber is experimentally investigated and achieves a quasi-perfect and flat absorption ranging from 1000 Hz to 1800 Hz.(c) 2023 Elsevier Ltd. All rights reserved.

关键词： Transfer matrix method Visco-thermal analysis multi-objective genetic algorithm optimization Quarter-wavelength resonator

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An efficient hybrid multi-objective memetic algorithm for the frequency assignment problem

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2020年 87卷 103265-000页

作者： Kiouche, Abd Errahmane Bessedik, Malika Benbouzid-SiTayeb, Fatima Keddar, Mohamed Reda Ecole Natl Super Informat ESI LMCS BP 68M 16309 Algiers Algeria

This paper investigates hybridization of multi-objective memetic algorithm and artificial immune system (AIS) for the Frequency Assignment Problem (FAP) in cellular mobile networks. The considered objectives to minimize are the total interference, the maximal interference, and the number of used frequencies. The proposed approach integrates FAP-specific local search into the evolutionary process to overcome the shortcoming of the multi-objective genetic algorithm, as well as clonal selection and receptor editing, which aims to improve the algorithm exploration and exploitation abilities. Based on the hypervolume metric, the proposed hybrid multi-objective algorithm produces high quality solutions as proved by the tests performed over COST259 instances and corroborated by the comparisons with the most frequently referred algorithms in the related literature. Furthermore, the effect and the behaviour of the main parameters of our algorithm and the interaction between them are analysed using the Design of Experiment (DOE).

关键词： multi-objective genetic algorithm Memetic algorithm Local search Clonal selection Receptor editing Frequency assignment problem

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Streamline-based history matching of bottomhole pressure and three-phase production data using a multiscale approach

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2017年 154卷 217-233页

作者： Kam, Dongjae Jichao Datta-Gupta, Akhil Texas A&M Univ Dept Petr Engn College Stn TX 77843 USA

Reconciling geological models to the available dynamic information, commonly known as history matching, is an essential step for optimizing reservoir management and field development strategies, including improved recovery methods. There are several challenges in the current history matching workflow, particularly for high resolution geologic models with multimillion cells and complex geologic architecture. Streamline-based inverse modeling has shown great promise in this respect because of computational efficiency and analytic calculation of sensitivity of production response to reservoir properties. However, the current streamline-based approach has mostly been applied to history matching water-cut and tracer response in two-phase flow. More recently streamline-based sensitivity calculations have been extended to bottomhole pressure and gas oil ratio. This allows for generalization of streamline-based history matching to the three-phase. In this paper we present an integrated application of the streamline-based three-phase history matching by incorporating water-cut, gas-oil ratio and bottomhole pressure data while updating high resolution geologic models. The crux of our approach lies in the analytic computation of well response sensitivities based on streamline which allows for efficient inversion of production and pressure data. We also validate the accuracy and efficiency of the streamline-based bottomhole pressure sensitivities by comparison with an adjoint-based method using a finite difference simulator. In the history matching workflow, we incorporate the streamline-based method within a multiscale framework to account for the disparity in resolution of different types of history data. This integrated method proposed in this paper leads to capturing of the large- and fine-scale heterogeneity while matching the pressure and production responses efficiently. We demonstrate the power and utility of the streamline-based approach using synthetic and field appli

关键词： Three-phase history matching Bottomhole pressure matching Streamlines multiscale approach multi-objective genetic algorithm

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Evolutionary-modified fuzzy nearest-neighbor rule for pattern classification

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EXPERT SYSTEMS WITH APPLICATIONS 2017年 88卷 258-269页

作者： Kassani, Peyman Hosseinzadeh Teoh, Andrew Beng Jin Kim, Euntai Yonsei Univ Sch Elect & Elect Engn Seoul 120749 South Korea

This paper presents an improved version of the well-established k nearest neighbor (k-NN) and fuzzy NN (FNN), termed the multi-objective genetic-algorithm-modified FNN (MOGA-MFNN). The MFNN design problem is converted into a multi-modal objective maximization problem constrained by four objective functions. Thereafter, the associated parameter set of the MFNN and the feature attributes can be determined optimally and automatically via the non-dominated sorting genetic algorithm II. We introduce two new objective functions termed the Margin-I and Margin-II, which are used to improve the generalization capability of the MFNN for the unknown data, along with two existing performance functions: the geometric mean and the area under the receiver-operated characteristic curve for the training accuracy. Moreover, we proposed a novel data-dependent weight-assignment technique for local class membership functions of the MFNN. The technique enables the MFNN to determine its local neighbors adaptively through the MOGA algorithm. To expedite the classification, the MOGA-MFNN is implemented on a graphical processing unit (GPU), which significantly increases the computation speed. Furthermore, the local class-membership function of the MFNN can be computed in advance, rather than delaying it to the classification stage. This again can improve the classification speed. The MOGA-MFNN is evaluated on 20 datasets obtained from the repository of the University of California, Irvine (UCI). The experiments with rigorous statistical significance tests demonstrate that the proposed method performs competitively with the existing methods. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Pattern classification Fuzzy nearest-neighbor rule multi-objective genetic algorithm Graphical-processing unit

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Research on optimization method of stainless steel sawing process parameters based on multi-tooth sawing force prediction model

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2023年第9-10期128卷 4513-4533页

作者： Ni, Pengcheng Wang, Yangyu Tan, Dapeng Zhang, Yongle Chen, Zhenzhen Wang, Zheng Yi, Chunhong Shao, Lu Lu, Yanhui Zhejiang Univ Technol Coll Mech Engn Hangzhou 310014 Zhejiang Peoples R China Zhejiang Univ Technol Key Lab Special Purpose Equipment & Adv Proc Tech Minist Educ Hangzhou 310014 Zhejiang Peoples R China Zhejiang Sany Equipment Co Ltd Huzhou 313000 Peoples R China Hangzhou Wheeler Gen Machinery Co Ltd Hangzhou 311400 Peoples R China

In this study, a multi-tooth sawing force prediction model is proposed for the stainless steel sawing process, combined with the classical cutting theory of band saw and the introduction of tooth equivalent cutting width. Through the numerical simulation of sawing process and sensitivity analysis method, the influence law of feed speed and cutting speed on cutting force was analyzed. A sawing process parameter optimization design model with sawing force and sawing efficiency as the optimization objectives was established and solved by multi-objective optimization algorithm to determine the optimal combination of coordinated sawing force and sawing efficiency process parameters. The stainless steel sawing test results show that the multi-tooth sawing force prediction model and the experimental results match;the maximum error does not exceed 6%, making it better to achieve the prediction of sawing force in high-frequency strong impact conditions. With the optimized design of process parameters, the sawing force decreased by a maximum 20.43%, and the sawing efficiency increased by a maximum 54.72%. This study provides a reference for metal sawing force prediction and process parameter optimization, and also offers theoretical guidance for developing high-end sawing equipment.

关键词： Sawing force prediction model Numerical simulation of sawing process multi-objective genetic algorithm Optimization of sawing parameters

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