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Landing Gear Mechanical Network Synthesis for Improving Comfort at Landing Considering Aircraft Flexibility

JOURNAL OF AIRCRAFT 2021年第6期58卷 1242-1253页

作者： Stachiw, Terrin Khouli, Fidel Langlois, Robert G. Afagh, Fred F. Carleton Univ Mech & Aerosp Engn Ottawa ON K1S 5B6 Canada

The landing impact that occurs during aircraft touchdown results in the development of significant loads and accelerations within the airframe. Accurate knowledge of the landing loads is necessary not only for predicting the resulting stresses for design of the airframe, but also for designing strategies to mitigate the vibratory loads and improve the ride quality. Perceived passenger comfort is dependent both on the magnitude of the acceleration experienced by the passengers and on the frequency content of the vibrations. Using a flexible airframe model to better capture the loading regime and frequency response at landing impact, this study optimizes various single-port (two-terminal) passive mechanical networks that consist of an arrangement of springs, dampers, and inerters to minimize passenger discomfort and peak forces applied to the aircraft. The performance is compared with a baseline oleo-pneumatic shock absorber. First, the candidate layouts are optimized, and then the observations from this exercise are used to synthesize a mechanical network with a desired frequency response. All considered mechanical networks demonstrated the ability to control the frequency content of the input loading, thus resulting in a reduction in accelerations and an improvement in all comfort parameters used in this study over the oleo-pneumatic baseline.

关键词： Model Aircraft Aircraft Structures Frequency Response Functions Maximum Landing Weight Aircraft Operations Finite Element Modeling Federal Aviation Regulation optimization algorithm Damping Coefficient Recurrent Neural Network

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Analysis and Optimal Design of a Novel Actuator System for a Camera Module

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IEEE ACCESS 2021年 9卷 3441-3450页

作者： Kwon, Tae-Hoon Ro, Jong-Suk Chung Ang Univ Dept Elect & Elect Engn Seoul 06974 South Korea

Owing to the fourth industrial revolution and the recent trend for compact, high-performance, and multifunctional electrical devices, the demand for a small and high-performance camera module has dramatically increased. To address this, in this study, a novel, miniaturized, high-performance, low-cost multifunctional camera module with optical image stabilization (OIS) via a novel two-axis motional actuator with 1-Stage is proposed. To date, a systematic analysis and optimal design method for the actuators of camera modules has not been proposed yet. Accurate and rapid analysis and optimal design methods are proposed herein. Based on the proposed methods, it is possible to reduce the time and cost for the development of actuators for camera modules. The usefulness of the proposed actuator system for small, high performance, and multifunctional camera modules, and the proposed analysis and optimal design method were verified experimentally in this study.

关键词： Cameras Actuators Magnetic resonance imaging Lenses Force Springs Optical imaging Actuator chamfered magnet coil diameter optical image stabilization (OIS) optimization algorithm voice coil motor (VCM)

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Application Of Chimp-based ANFIS Model For Forecasting The Compressive Strength Of The Improved High-performance Concrete

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淡江理工学刊 2024年第4期27卷 2295-2306页

作者： Yan Yuan

In order to assess the compressive strength (CS) of high-performance concrete (HPC) prepared with fly ash and blast furnace slag, several artificial-based analytics were applied. This study, it was employed the Chimp optimizer ( CO) to identify optimal values of determinative factors of Support vector regression (SVR) and adaptive neuro-fuzzy inference system (ANFIS), which could be adjusted to improve performance. The suggested approaches were established using 1030 tests, eight inputs (a primary component of mix designs, admixtures, aggregates, and curing age), and the CS as the forecasting objective. The outcomes were then contrasted with those found in the body of existing scientific literature. Calculation results point to the potential benefit of combining CO - SVR and CO - ANFIS study. When compared to the CO - SVR, the CO - ANFIS showed much higher R^2 and lower Root means square error values. Comparing the findings shows that the created CO - ANFIS is superior to anything that has previously been published. In conclusion, the suggested CO - ANFIS analysis might be used to determine the proposed approach for estimating the CS of HPC augmented with blast furnace slag and fly ash.

关键词： High-performance concrete Compressive strength Support vector regression Adaptive neuro-fuzzy inference system optimization algorithm

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A systematic review on state of modeling, clinical issues, and advanced control approaches for artificial ventilator: traditional control to soft computing-based control approach

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INTERNATIONAL JOURNAL OF DYNAMICS AND CONTROL 2025年第1期13卷 25-25页

作者： Acharya, Debasis Das, Dushmanta Kumar Brainware Univ Dept Comp Sci & Engn Cyber Secur & Data Sci Kolkata India Natl Inst Technol Nagaland Dept Elect & Elect Engn Dimapur India

An artificial ventilator is crucial in medical emergencies, providing severely ill patients with sufficient oxygen to reduce their breathing effort. For critical patients, clinicians must set various parameters on the ventilator to ensure safe and comfortable ventilation. Accurate tracking of the patient's breathing profile by the ventilator is essential for synchronization, reducing the patient's workload and effort. Designing an effective ventilator controller requires proper system modeling and a clear understanding of its purpose. This paper offers a brief review of modeling, physiological and clinical issues, and state-of-the-art advanced control practices, guiding future control design for ventilators. It also presents detailed ventilator modeling and parameters from the literature, along with a comprehensive review of traditional and soft-computing-based control approaches.

关键词： Artificial ventilator Fuzzy logic controller PID controller optimization algorithm Patient-hose ventilator Piston-motor-driven ventilator

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Trimming Analysis Method of Quad Tilt Rotor Based on Aerodynamic Interference Model

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JOURNAL OF AIRCRAFT 2021年第2期58卷 253-265页

作者： Wang, Zhigang Wang, Qiannan Yu, Hongrui Duan, Dengyan Ding, Zhiwei Li, Jianbo Yangzhou Collaborat Innovat Res Inst Shenyang Aircraft Design & Res Inst Yangzhou 225000 Jiangsu Peoples R China Nanjing Univ Aeronaut & Astronaut Natl Key Lab Rotorcraft Aeromech Nanjing 210016 Peoples R China

The quad tilt rotor (QTR) has complex aerodynamic characteristics and strong aerodynamic interference. The flight dynamic model is the basis of control. To effectively account for the aerodynamic interference between the multiple aerodynamic surfaces of the QTR unmanned aerial vehicle, a hybrid optimization trimming analysis method based on Immune algorithm/Levenberg-Marquardt (IA/LM) and lattice Boltzmann method (LBM) is proposed. The aerodynamic characteristics between the wing and the rotor calculated by the LBM are compensated into the flight dynamics model. The IA/LM algorithm is used to reduce the dependence on the initial trimming value. The effectiveness of the hybrid optimal trimming analysis method is verified through the analysis of trimming simulation results.

关键词： Tiltrotor Aircraft Aerodynamic Characteristics LBM UAV Aircraft Flight Dynamics Fuselages Helicopters CFD optimization algorithm Lift to Drag Ratio

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Semi-Analytical Sensitivity Analysis for Multibody System Dynamics Described by Differential-Algebraic Equations

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AIAA JOURNAL 2021年第3期59卷 893-904页

作者： Peng, Haijun Zhang, Mengru Zhang, Lidan Dalian Univ Technol Dept Engn Mech State Key Lab Struct Anal Ind Equipment Dalian 116024 Peoples R China Delft Univ Technol Dept Precis & Microsyst Engn NL-2600 AA Delft Netherlands

A large number of deployable space structures involve multibody system dynamics, and in order to effectively analyze and optimize dynamic performance, the sensitivity information of multibody systems is often required. At present, the sensitivity analysis methods of multibody system dynamics, which have been widely used, are mainly finite difference method, direct differentiation method, and adjoint variable method. Among them, the finite difference method is an approximate method;the direct differentiation method and the adjoint variable method are analytical methods. Based on the dynamic problems of the multibody system in the form of differential-algebraic equations, the semi-analytical sensitivity analysis method for multibody system dynamics is proposed in this paper, which combines the simplicity of the finite difference method with the accuracy of the analytical methods. It includes the local semi-analytical method based on the element level and the global semi-analytical method based on the system level, of which the latter has higher computational efficiency. Through two numerical examples, the effectiveness and numerical stability of the method are verified. This method not only retains the accuracy and efficiency of the analytical methods, but also simplifies the derivation and coding of analytical formulas by combining with the existing programs. It has stronger versatility and is beneficial to the sensitivity calculation of large-scale complex multibody systems.

关键词： Sensitivity Analysis Multibody Dynamics Numerical Integration Finite Difference Method Space Structures Trusses Mathematical Models Structural optimization optimization algorithm Finite Element Method

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Enhancing residential energy access with optimized stand-alone hybrid solar-diesel-battery systems in Buea, Cameroon

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SCIENTIFIC REPORTS 2024年第1期14卷 1-19页

作者： Amoussou, Isaac Paddy, Eriisa Yiga Agajie, Takele Ferede Ibrahim, Fuseini Seidu Agajie, Elsabet Ferede Nsanyuy, Wirnkar Basil Bajaj, Mohit Mohammadi, Shir Ahmad Dost Univ Buea Fac Engn & Technol Dept Elect & Elect Engn POB 63 Buea Cameroon Debre Markos Univ Sch Elect & Comp Engn Debre Markos Ethiopia Graph Era Deemed Univ Dept Elect Engn Dehra Dun 248002 India Al Ahliyya Amman Univ Hourani Ctr Appl Sci Res Amman Jordan Graph Era Hill Univ Dehra Dun 248002 India Alberoni Univ Fac Engn Dept Elect & Elect Kohistan Kapisa Afghanistan

This study examined the optimal size of an autonomous hybrid renewable energy system (HRES) for a residential application in Buea, located in the southwest region of Cameroon. Two hybrid systems, PV-Battery and PV-Battery-Diesel, have been evaluated in order to determine which was the better option. The goal of this research was to propose a dependable, low-cost power source as an alternative to the unreliable and highly unstable electricity grid in Buea. The decision criterion for the proposed HRES was the cost of energy (COE), while the system's dependability constraint was the loss of power supply probability (LPSP). The crayfish optimization algorithm (COA) was used to optimize the component sizes of the proposed HRES, and the results were contrasted to those obtained from the whale optimization algorithm (WOA), sine cosine algorithm (SCA), and grasshopper optimization algorithm (GOA). The MATLAB software was used to model the components, criteria, and constraints of this single-objective optimization problem. The results obtained after simulation for LPSP of less than 1% showed that the COA algorithm outperformed the other three techniques, regardless of the configuration. Indeed, the COE obtained using the COA algorithm was 0.06%, 0.12%, and 1% lower than the COE provided by the WOA, SCA, and GOA algorithms, respectively, for the PV-Battery configuration. Likewise, for the PV-Battery-Diesel configuration, the COE obtained using the COA algorithm was 0.065%, 0.13%, and 0.39% lower than the COE provided by the WOA, SCA, and GOA algorithms, respectively. A comparative analysis of the outcomes obtained for the two configurations indicated that the PV-Battery-Diesel configuration exhibited a COE that was 4.32% lower in comparison to the PV-Battery configuration. Finally, the impact of the LPSP reduction on the COE was assessed in the PV-Battery-Diesel configuration. The decrease in LPSP resulted in an increase in COE owing to the nominal capacity of the diesel gene

关键词： Hybrid renewable energy COE LPSP optimization algorithm Diesel generator

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Application of a novel grey Bernoulli model to predict the global consumption of renewable energy

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ENERGY REPORTS 2021年 7卷 7200-7211页

作者： Duan, Huiming Wang, Siqi He, Chenglin Huang, Jiangbo Chongqing Univ Posts & Telecommun Sch Sci Chongqing 400065 Peoples R China

Accurate prediction of renewable energy can provide an important basis for national energy security and the government to formulate policies. Therefore, according to the non-linearity of energy prediction system, this paper proposes a new nonlinear grey Bernoulli optimization model by the grey Bernoulli extended model, which is a nonlinear grey prediction model, and studies the properties of the new model. The order and nonlinear coefficient of the new model are optimized by Particle Swarm optimization. Then, through the consumption of global renewable energy, such as solar, wind and hydropower as empirical analyses, the results of the four evaluation indicators show that the new model works better than the original model, which has higher prediction accuracy than before and makes the prediction model more applicable. At the same time, the model results were compared with the weighted grey model, Verhulst and the discrete grey model, and the new model has the highest accuracy. Finally, the new model is used to forecast the global consumption of wind, solar and hydropower energy in 2019-2023. The results will provide important forecasting information for global energy conservation and emission reduction policies. (C) 2021 The Authors. Published by Elsevier Ltd.

关键词： Grey prediction model Bernoulli model Renewable energy consumption optimization algorithm Forecasting

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Calculation Method of Probability Integration Method Parameters Based on MIV-GP-BP Model

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TEHNICKI VJESNIK-TECHNICAL GAZETTE 2021年第1期28卷 160-168页

作者： Chi, Shenshen Yu, Xuexiang Wang, Lei Anhui Univ Sci & Technol Sch Earth & Environm Huainan 232001 Peoples R China Anhui Univ Sci & Technol Sch Geomat Huainan 232001 Peoples R China Anhui Univ Sci & Technol Key Lab Aviat Aerosp Ground Cooperat Monitoring & KLAHEI KLAHEI18015 Huainan 232001 Peoples R China Anhui Univ Sci & Technol Coal Ind Engn Res Ctr Min Area Environm & Disaste Huainan 232001 Peoples R China

In order to guarantee the precision of the parameters of the probability integral method (PIM), starting from optimizing input and improving algorithm an algorithm integrating the genetic algorithm (GA) and particle swarm optimization (PSO) was put forward to optimize the prediction model of BP neural network and the mean impact value algorithm (MIV) was applied to optimize the input of BP neural network. The mean impact value algorithm (MIV) was applied to optimize the input of BP neural network. The measured data of 50 working faces were chosen as the training and testing sets to build the MIV-GP-BP model. The results showed that among the five parameters, the RMSE was between 0.0058 and 1.1575, the MaxRE of q, tan beta, b and theta was less than 5.42%, and the MeaRE was less than 2.81%. The RMSE of s/H did not exceed 0.0058, the MaxRE was less than 9.66% and the MeaRE was less than 4.31% (the parameters themselves were small). The optimized neural network model had higher prediction accuracy and stability.

关键词： BP neural network MIV algorithm mining subsidence optimization algorithm PIM underground mining

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Uncertainty reduction in quantitative precipitation prediction by tuning ofKain-Fritchscheme input parameters in theWRFmodel using the simulated annealing optimization method

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METEOROLOGICAL APPLICATIONS 2020年第4期27卷 e1919-e1919页

作者： Afshar, Mohaddeseh A. Azadi, Majid Rezazadeh, Maryam Univ Hormozgan Bandar Abbas Iran Atmospher Sci & Meteorol Res Ctr ASMERC Tehran Iran

In the study, using the simulated annealing (SA) optimization method, tried to reduce the uncertainty of the prediction of the Weather Research and Forecasting (WRF) numerical model in convective rainfall forecasts. To this end, three parametersP(d),P(e)andP(h)in Kain-Fritch convective scheme that's related to downdraft mass flux, entrainment mass flux and starting height of downdraft above updraft source layer, respectively, are optimized using SA algorithm to achieve better values. Two nested domain were used in the study with 30 and 10 km resolution which inner domain cover southern coasts of the Caspian Sea for the study area. Runtime of the model was 36 hr with the first 12 hr spin-up time. Study period selected October 12, 2012 for training algorithm and October 8, 2015 for test run. After 100 iteration of the algorithm, 1, 1 and 50 was obtained forP(d),P(e)andP(h)respectively, while default values of these parameters was 0, 0, and 150. Results show that in both cases, model with default values underestimates rainfall amount and after optimization, model performance improves. Also, spatial distribution of the model precipitation forecast was less than observations and after optimization, spatial distribution improves. Statistical analysis of results indicated Mean Bias (MB) and root mean square error (RMSE) in training case were -4.6 and 17.1 in model with default values and became -3.7 and 14.3 in optimized one, respectively. Also, MB and RMSE for test case increased to -8.4 and 23.8, respectively, in model result with optimized parameters from -10.6 to 29.4 in model with default parameters.

关键词： convective rainfall prediction Iran optimization algorithm simulated annealing method Weather Research and Forecasting (WRF) model

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