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optimization of identity operation in NMR spectroscopy via genetic algorithm: Application to the TEDOR experiment

JOURNAL OF MAGNETIC RESONANCE 2016年 273卷 40-46页

作者： Manu, V. S. Veglia, Gianluigi Univ Minnesota Dept Biochem Mol Biol & Biophys Minneapolis MN 55455 USA Univ Minnesota Dept Chem Minneapolis MN 55455 USA

Identity operation in the form of it pulses is widely used in NMR spectroscopy. For an isolated single spin system, a sequence of even number of it pulses performs an identity operation, leaving the spin state essentially unaltered. For multi-spin systems, trains of it pulses with appropriate phases and time delays modulate the spin Hamiltonian to perform operations such as decoupling and recoupling. However, experimental imperfections often jeopardize the outcome, leading to severe losses in sensitivity. Here, we demonstrate that a newly designed genetic algorithm (GA) is able to optimize a train of IL pulses, resulting in a robust identity operation. As proof-of-concept, we optimized the recoupling sequence in the transferred-echo double-resonance (TEDOR) pulse sequence, a key experiment in biological magic angle spinning (MAS) solid-state NMR for measuring multiple carbon-nitrogen distances. The GA modified TEDOR (GMO-TEDOR) experiment with improved recoupling efficiency results in a net gain of sensitivity up to 28% as tested on a uniformly 13C, 15N labeled microcrystalline ubiquitin sample. The robust identity operation achieved via GA paves the way for the optimization of several other pulse sequences used for both solid- and liquid-state NMR used for decoupling, recoupling, and relaxation experiments. (C) 2016 Elsevier Inc. All rights reserved.

关键词： Composite pulses genetic algorithm optimization Dipolar recoupling REDOR/TEDOR

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Gas exchange optimization in aircraft engines using sustainable aviation fuel:A design of experiment and genetic algorithm approach

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Energy and AI 2024年第3期17卷 261-280页

作者： Zheng Xu Jinze Pei Shuiting Ding Longfei Chen Shuai Zhao Xiaowei Shen Kun Zhu Longtao Shao Zhiming Zhong Huansong Yan Farong Du Xueyu Li Pengfei Yang Shenghui Zhong Yu Zhou Hangzhou International Innovation Institute Beihang UniversityHangzhou311115China Research Institute of Aero-Engine Beihang UniversityBeijing102206China Civil Aviation University of China Tianjin300300China Aircraft/Engine Integrated System Safety Beijing Key Laboratory Beijing100083China Aero Engine Academy of China Beijing101304China School of Energy and Power Engineering Beihang UniversityBeijing100083China AVIC Chengdu Aircraft Design and Research Institute Chengdu610091China AVIC Nanjing Engineering Institute of Aircraft Systems Nanjing211106China School of Transportation Science and Engineering Beihang UniversityBeijing100083China Faculty of Science and Engineering University of Nottingham Ningbo ChinaNingbo315100China

The poppet valves two-stroke(PV2S)aircraft engine fueled with sustainable aviation fuel is a promising option for general aviation and unmanned aerial vehicle propulsion due to its high power-to-weight ratio,uniform torque output,and flexible valve ***,its high-altitude gas exchange performance remains unexplored,presenting new opportunities for optimization through artificial intelligence(AI)*** study uses validated 1D+3D models to evaluate the high-altitude gas exchange performance of PV2S aircraft *** valve timings of the PV2S engine exhibit considerable flexibility,thus the Latin hypercube design of experiments(DoE)methodology is employed to fit a response surface model.A genetic algorithm(GA)is applied to iteratively optimize valve timings for varying *** optimization process reveals that increasing the intake duration while decreasing the exhaust duration and valve overlap angles can significantly enhance high-altitude gas exchange *** optimal valve overlap angle emerged as 93°CA at sea level and 82°CA at 4000 m *** effects of operating parameters,including engine speed,load,and exhaust back pressure,on the gas exchange process at varying altitudes are further *** higher engine speed increases trapping efficiency but decreases the delivery ratio and charging efficiency at various *** effect is especially pronounced at elevated *** increase in exhaust back pressure will significantly reduce the delivery ratio and increase the trapping *** study demonstrates that integrating DoE with AI algorithms can enhance the high-altitude performance of aircraft engines,serving as a valuable reference for further optimization efforts.

关键词： Poppet valves two-stroke Design of experiment genetic algorithm optimization Heavy fuel aircraft engine High altitude gas exchange performance

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optimization of Savonius turbine clusters using an evolutionary based genetic algorithm 10

Optimization of Savonius turbine clusters using an evolution...

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10th International Conference on Applied Energy (ICAE)

作者： Zheng, Y. Bai, H. L. Chan, C. M. Hong Kong Univ Sci & Technol Kowloon Dept Civil & Environm Engn Clear Water Bay Hong Kong Peoples R China

VAWTs benefit from constructive coupling effect that significantly improves efficiency. This work aims at optimizing the configuration of turbine clusters with three Savonius turbines. To maximize the aggregate power output of a turbine cluster, two-dimensional (2D) computational fluid dynamics (CFD) is utilized, along with an evolutionary based genetic algorithm (GA). Four scenarios are investigated considering different combinations of rotational directions. For the optimal cluster obtained, a highest 37% increase in averaged power coefficient ((C) over bar (p))over an isolated Savonius turbine is achieved at Tip Speed Ratio (TSR) = 0.8. The substantial increase in efficiency for turbines in the optimal cluster is essentially due to constructive coupling in the flow field. Two major effective coupling mechanisms are proposed based on flow structures to explain the observed performance increase. Furthermore, a method to expand the optimal cluster into compact wind farms is proposed. It is verified that for a compact Savonis-type VAWT wind farm that consists of 12 turbines, a 30% increase in (C) over barp is obtained, showing the practicality of constructing efficient VAWT wind farms in areas with limited land. (C) 2019 The Authors. Published by Elsevier Ltd.

关键词： Wind energy Vertical Axis Wind Turbines Savonius turbine genetic algorithm optimization

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Shifted and Weighted LFCC Features for Hand Movements Recognition Using EEG Signals

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JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2025年第1期20卷 785-796页

作者： Reffad, Aicha Mebarkia, Kamel Univ Ferhat ABBAS Set 1 Fac Technol Electrotech Dept LAS Lab Setif 19000 Algeria Univ Ferhat ABBAS Set 1 Fac Technol Elect Dept LIS Lab Setif 19000 Algeria

The Brain computer interface (BCI) technology attracts many researchers due to its vital applications in medicine and biomedical domains. Decoding the motor imagery electroencephalography signals (MI-EEG) to find the corresponding brain activities constitutes the core of the BCI system. Researchers use both classical machine learning and deep learning to identify such activities. In this work, left/right hand movement is recognized using MI-EEG signals features. The EEG signal features vector is derived from the wavelet transformation (WT) and the linear frequency cepstral coefficient (LFCC) to feed an SVM classifier. Two publicly available MI-EEG datasets are tested, BCI competition III b and BCI competition IV 2b. Firstly, the classification is performed using all features without any modification for the LFCC features. Secondly, the LFCC features are shifted and weighted (SWLFCC) by genetic algorithm (GA) to improve the classification accuracy. The average classification accuracy was improved and achieved 92.19 and 87.23% for BCI competition III b and BCI competition IV 2b datasets respectively. Compared to the works using the same datasets, the performance to identify left and right hand is improved by 2.4% for the BCI competition III b. There was very small improvement for the second dataset though the deep learning was used for the last best accuracy. The novel SWLFCC features showed their efficiency in BCI system to identify MI left/right hand movement. The SWLFCC features are tuned by GA optimization to adapt any nonlinearity existing between tasks and MI-EEG signals.

关键词： Brain computer interface Motor imagery Features extraction Machine learning genetic algorithm optimization

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optimization and analysis of reliquefaction system utilizing hydrogen as refrigerant for liquid hydrogen carriers

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APPLIED ENERGY 2025年 384卷

作者： Choi, Minsoo Jung, Wongwan Ji, Sangmin Lee, Jinkwang Korea Adv Inst Sci & Technol Dept Mech Engn Daehak Ro 291 Daejeon 34141 South Korea Dong A Univ Dept Naval Architecture & Ocean Engn 37 Nakdong Daero 550 Beon Gil Busan 49315 South Korea Gyeongsang Natl Univ Dept Mech Convergence Engn 54 Charyong Ro 48beon Gil Chang Won 51931 Gyeongsangnam D South Korea

In this study, a reliquefaction system utilizing a reverse Brayton cycle with hydrogen as a refrigerant to handle boil-off hydrogen (BOH) generated within liquid hydrogen carriers operating in oceanic routes from a thermodynamic perspective is proposed. Furthermore, optimization targeting specific energy consumption (SEC) as the fitness function was performed using a genetic algorithm. Subsequently, an economic analysis was conducted at the equipment unit level for the reliquefaction system. Thermodynamic analysis of the optimized system revealed a SEC of 5.028 kWh/kg and an exergy efficiency of 44.48 %. During optimization, the circulation rates of BOH and refrigerant decreased, leading to a significant reduction in the exergy destruction within the heat exchangers and an improvement in the system efficiency. Notably, the optimization results indicated the significant influence of the heat exchange conditions in the heat exchangers on the overall system efficiency. It is also worth noting that the optimal BOH compression pressure was approximately 25 bara, which is similar to the pressure of the raw material hydrogen used as a feed gas in onshore hydrogen liquefaction systems. This suggests that the design experience gained from manufacturing equipment for onshore hydrogen liquefaction systems can provide significant benefits when producing equipment for onboard BOH reliquefaction systems. Economic analysis revealed that in the optimized system, it costs USD 1.09 to reliquefy 1 kg of BOH.

关键词： Boil-off hydrogen Reliquefaction system Process simulation genetic algorithm optimization Thermodynamic analysis

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optimization by genetic algorithm of a PIF A Antenna Parameters for Wifi Application

Optimization by Genetic Algorithm of a PIF A Antenna Paramet...

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International Conference on Multimedia Computing and Systems (ICMCS)

作者： Wakrim, Layla Ibnyaich, Saida Hassani, Moha M'rabet Cadi Ayyad Univ Fac Sci Semlalia Res Team Instrumentat Signals & Phys Syst Marrakech Morocco

ISBN: (纸本)9781479938247

In this paper a genetic algorithm optimization is applied to optimize PIFA antenna parameters for wireless application. The optimization procedure is included, also two novel optimized antennas are presented. Optimized antennas reach 89.93% and 88.55% bandwidth. Miniaturization is also achieved. The reliability and efficiency of this method are proved by comparing the antenna proposed in this paper to optimal antennas.

关键词： genetic algorithm optimization PIFA antenna Bandwidth Return loss Radiation pattern

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Optimizing design of openings in vibrating plates for enhanced vibro-acoustic performance using a genetic algorithm approach

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JOURNAL OF SOUND AND VIBRATION 2025年 598卷

作者： Maamoun, Khaled Said Ahmed Wrona, Stanislaw Pawelczyk, Marek Karimi, Hamid Reza Silesian Tech Univ Dept Measurements & Control Syst Gliwice Poland Politecn Milan Dept Mech Engn Milan Italy

Optimizing structural openings in vibro-acoustic systems is essential for balancing functional needs with acoustic performance in various engineering applications. This paper presents an efficient optimization approach for designing openings in plate structures within vibro-acoustic systems, aimed at enhancing acoustic performance while maintaining structural integrity. A genetic algorithm framework is developed to determine the optimal shapes and locations of openings simultaneously, utilizing an analytical model based on hyperbolic and trigonometric admissible functions within a master-slave software architecture. The proposed method accommodates a variety of opening requirements for different systems and employs a cost function that evaluates both the average and peaks of sound power responses to identify the designs with the highest fitness. This results in significant reductions in sound power levels compared to median and worst-case designs. Additionally, the method analyzes how variations in opening locations, numbers, and shapes impact acoustic performance, providing guidance for opening designs that avoid undesired acoustic outcomes and improve noise barrier performance in vibro-acoustic systems.

关键词： Vibrating plates with openings genetic algorithm optimization Vibro-acoustic system enhancement Structural-acoustic coupling Sound power reduction

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optimization of working fluid in a novel Multi-Stream heat exchange combined cycle for liquid natural gas cold energy utilization

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APPLIED THERMAL ENGINEERING 2025年 265卷

作者： Zhao, Yiming Wang, Yingguang Han, Yu Liang, Yong Hu, Dapeng Dalian Univ Technol Dept Chem Machinery Dalian 116012 Peoples R China PipeChina Engn Technol Innovat Co Ltd Tianjin 300450 Peoples R China Dalian Ocean Univ Dept Machinery & Power Engn Dalian 116023 Peoples R China

This study investigates the impact of working fluids on the performance of Liquid Natural Gas (LNG) Cold Energy power generation cycles and identifies the optimal fluid for a multi-stream cascade combined cycle (MS-CCC). A genetic algorithm with mixed integer nonlinear programming is employed to optimize the MS-CCC, comparing it with traditional combined cycles and cascade combined cycles using both single-component and binary mixed working fluids. The candidate working fluids are innovatively selected based on normal boiling point temperatures, with a uniform distribution across the range of -128 degrees C to -2 degrees C, covering most of the LNG vaporization process. Analysis results indicate that using binary mixed working fluids effectively enhances heat transfer matching within condensers in MS-CCC and significantly improves the exergy output of the bottom cycle working fluid, thereby greatly reinforcing the advantages of MS-CCC in utilizing working fluid cold energy. With the optimal mixed working fluid, MS-CCC achieves a net power output (Wnet) of 4262.2 kW and an exergy efficiency (eta ex) of 24.3 %, marking a 32.5 % increase in eta ex compared to employing optimal single-component working fluid. The selection of the base component with a lower saturated temperature in bottom cycle significantly affects MS-CCC performance by simultaneously impacting the cold energy extraction in both cycles. Variations in mole fractions of the working fluid components also impact MS-CCC efficiency. Deviations of 30 % from the optimal mole fraction can reduce Wnet by over 23 %. These findings provide valuable insights for optimizing cold energy power generation cycles.

关键词： Cold energy power generation Multi-stream heat exchange Liquefied natural gas Working fluid genetic algorithm optimization

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Scattering Reduction and Axial Resolution Enhancement in Light-Sheet Fluorescence Microscopy

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JOURNAL OF BIOPHOTONICS 2025年第5期18卷 e202400556页

作者： Zhang, Yang Li, Runze Yu, Xianghua Miao, Hao Yang, Ruiwen Li, Xing Min, Junwei Yang, Yanlong Dan, Dan Dai, Taiqiang Kong, Liang Yao, Baoli Chinese Acad Sci Xian Inst Opt & Precis Mech State Key Lab Ultrafast Opt Sci & Technol Xian Shaanxi Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Fourth Mil Med Univ Natl Clin Res Ctr Oral DisSch Stomatol State Key Lab Oral & Maxillofacial Reconstruct & R Shaanxi Clin Res Ctr Oral DisDept Oral & Maxillof Xian Peoples R China

Light-sheet fluorescence microscopy (LSFM) provides an ideal tool for long-term observation of live specimens due to its low photodamage and fast volumetric imaging speed. The wavefront distortions in the illumination path of LSFM will reduce the intensity and broaden the light-sheet thickness, thereby degrading the image quality. We propose to use the wavefront shaping technique to reduce the scattering effect and shrink the light-sheet thickness. Scanning the refocused laser beam to generate LS improves both the fluorescence intensity and the axial resolution. The axial resolution can be further enhanced by subtracting the two images captured via double scanning the samples with the refocused beam and the uncorrected scattered beam for each slice. The axial resolution is improved from 2.2 +/- 0.3 to 1.5 +/- 0.2 mu m across the field of view of 270 mu m x 270 mu m. The effectiveness of the wavefront shaping subtraction method is demonstrated by imaging fluorescent beads and Aspergillus conidiophores behind a scattering medium.

关键词： genetic algorithm optimization light-sheet fluorescence microscopy wavefront shaping

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Thermal performance optimization of a novel integrated photovoltaic thermal collector system

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RENEWABLE ENERGY 2025年 238卷

作者： Xiao, Yuling Fei, Fan Zou, Junlong Tian, Lei Liang, Qian Ma, Qingsong Fukuda, Hiroatsu Gao, Weijun Qingdao Univ Technol Innovat Inst Sustainable Maritime Architecture Res Qingdao 266033 Peoples R China Univ Kitakyushu Fac Environm Engn Kitakyushu 8080135 Japan

The construction industry is actively seeking energy-efficient solutions to reduce reliance on fossil fuels. Building-integrated photovoltaic thermal (PV-T) systems, combining electricity generation with solar heat utilization, have emerged as a promising technology. However, conventional PV-T systems often face limitations in achieving optimal PV panel angles for maximum solar gain while maintaining architectural aesthetics, especially when integrated into building facades. This study investigates the thermal performance of a novel photovoltaic thermal collector (PV-TC) system specifically designed to address these challenges. This system, intended for installation on south-facing building facades, allows for flexible PV panel angling design to optimize solar energy capture without compromising the building's aesthetic appeal. We employ a simulation-based optimization approach using EnergyPlus, Radiance, and a genetic algorithm to determine the optimal design parameters for minimizing annual energy use intensity (EUI) in Nanjing, China's climate. Our results demonstrate that a fan rate of 288 m3/h, a winter fan setpoint of 21 degrees C, a summer fan setpoint of 25 degrees C, and a PV panel angle of 41 degrees achieve the lowest EUI of 92.33 kWh/m2. This optimized configuration effectively balances electricity generation with solar heat utilization, minimizing reliance on conventional HVAC systems. We further analyzed individual parameter influences, demonstrating that increasing fan rate consistently improves heat transfer efficiency, while optimal PV angle and fan setpoint temperature are crucial for maximizing solar heat utilization and nighttime cooling, respectively. By comparison it was found that the installation of the PV-TC system reduces the annual EUI by 22.7 %. These findings provide valuable insights for designing and operating high-performance PV-TC systems that address both energy efficiency and architectural integration concerns in buildings.

关键词： Integrated photovoltaic thermal collector Energy use intensity EnergyPlus simulation genetic algorithm optimization

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