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Evolving a Novel Blade Shape of a Savonius Wind Rotor Using an optimization Technique Coupled With Numerical Simulations and Wind Tunnel Tests

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JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME 2024年第4期146卷 041301-041301页

作者： Mohan, Man Saha, Ujjwal K. Indian Inst Technol Guwahati Dept Mech Engn Gauhati 781039 Assam India

The global adoption of Savonius wind rotors as an eco-friendly means of small-scale power production is on the rise. However, their suboptimal performance remains a significant challenge due to the generation of higher unproductive torque. This paper aims to address this issue by obtaining an optimal blade profile considering the power coefficient (C-P) as an output function using optimization techniques. The objective function includes the overlap ratio, intermediate points on the curve, inlet velocity, and tip speed ratio (TSR) as the optimization geometric parameters. To achieve this, the simplex search method and the non-dominated sorting genetic algorithm II are opted to develop the blade profile. The blade profile is developed using a natural cubic spline curve with fixed end points and variable intermediate points along with other parameters. The computational analysis is done using ansys fluent software with shear stress transport k-omega turbulence model. The solver setup employs the finite volume method to simulate the transient 2D flow around the blade profile. A direct comparison is made between the optimized blade profile and the conventional semicircular one over a range of TSRs. The results clearly indicate the superior performance of the former, exhibiting a higher C-Pmax by 23% compared to the conventional one at TSR = 0.8. Finally, experiments have been conducted in a wind tunnel to find the practical feasibility of the optimized blade profile generated through the simplex search method.

关键词： Savonius wind rotor power coefficient tip speed ratio overlap ratio optimization algorithm wind tunnel alternative energy sources energy conversion/systems energy extraction of energy from its natural resource renewable energy

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Efficient 3D Alignment of Physical Structures with CAD Model Nominals in Manufacturing: A Genetic algorithm Approach 10th

Efficient 3D Alignment of Physical Structures with CAD Model...

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International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent Systems

作者： Janez, Gotlih Pisek, Marko Timi, Karner Rok, Belsak Miran, Brezocnik Univ Maribor Fac Mech Engn Smetanova Ulica 17 Maribor 2000 Slovenia SMM Prod Syst Ltd Maribor 2000 Slovenia

ISBN: (纸本)9783031662676;9783031662683

In modern industry, the accurate alignment of components and machines in three-dimensional space is amajor challenge, especially in fields such as automotive and aerospace. This work addresses the critical issue of aligning physical structures with their corresponding CAD models, a crucial step in ensuring accurate assembly and manufacturing processes. A novel alignment method is presented using genetic algorithms to optimize the six degrees of freedom of the measured coordinate system. This optimization minimizes the need for subsequent manual adjustments, increasing efficiency and accuracy. The method is applied to a practical case involving the assembly of sheet metal parts for truck cabins, using FARO tracker technology for measurements and MATLAB for analysis. The results of applying the genetic algorithm show a remarkable reduction in the number of fixture support elements to be adjusted from 16 to only 1, highlighting the effectiveness of this approach in streamlining the alignment process and improving overall manufacturing productivity.

关键词： fixture assembly measurement alignment laser tracker optimization algorithm

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Task Allocation for Heterogeneous Multi-Robot Systems with Diverse Capabilities 24

Task Allocation for Heterogeneous Multi-Robot Systems with D...

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24th International Conference on Control, Automation and Systems

作者： Lee, Goeun Lee, Donggil Lim, Yoonseob Korea Inst Sci & Technol Artificial Intelligence & Robot Inst Seoul 02792 South Korea Incheon Natl Univ Dept Elect Engn Incheon 22012 South Korea

ISBN: (纸本)9798331517939;9788993215380

This paper presents an algorithm for task allocation in a team of robots with diverse capabilities, aiming to minimize overall costs. Each robot's abilities are described by a capability vector, and the algorithm forms subgroups within the team to ensure they can collectively complete individual tasks. We particularly address cases where each robot can only handle a subset of the tasks due to physical limitations. The algorithm's effectiveness and practical application are demonstrated through simulations, which validate its ability to optimize task allocation in multi-robot teams.

关键词： Heterogeneous multi-robot system task-specific capabilities task allocation optimization algorithm

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Identifying Inter-agent Interaction Graph Networks from Time Series Records of Flying Insect Groups

Identifying Inter-agent Interaction Graph Networks from Time...

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AIAA SciTech Forum

作者： Ahmed, Ishriak Faruque, Imraan A. Oklahoma State Univ Sch Mech & Aerosp Engn Stillwater OK 74078 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

As aerospace systems grow to incorporate multi-agent systems with both dynamics and nontrivial neighbor interactions, identifying network topologies from observed data is a growing challenge. This paper develops a concise method to identify the adjacency matrix of a graph from limited-length time histories of simultaneous individuals in groups. The adjacency matrix identification problem is written as a constrained linear least-squared error minimization problem amenable to implementation in ubiquitous convex optimization routines, such as linear matrix inequality solvers. The constraints come from the graph adjacency matrix definition and provide theoretical bounds on recorded trajectory length. The approach is applied to experimental honey bee flight data gathered by vision-based digitization while tracking a stimulus injecting a sum of sinusoids and triangle wave motion. The results on insect flight data indicate that honey bees primarily interact with a small number of neighbors (2-3) while tracking stimuli, even in the presence of a larger number of nearby individuals. These tools can enable us to identify the underlying mechanisms of unknown swarming systems, translating those into engineered aerial systems.

关键词： Flight Data Multi Agent System Convex optimization Aerospace System Dynamic Mode Decomposition optimization algorithm Digital Signal Processing Flight Dynamics Fluid Mechanics Dynamic Modelling

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Design of an Application Programming Interface for the Program to Optimize Simulated Trajectories II

Design of an Application Programming Interface for the Progr...

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AIAA SciTech Forum

作者： Williams, R. Anthony Lugo, Rafael A. Hoffman, James A. NASA Langley Res Ctr Atmospher Flight & Entry Syst Branch Hampton VA 23681 USA Analyt Mech Assoc Atmospher Flight & Entry Syst Branch Hampton VA 23666 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

A significant effort to upgrade the Program to Optimize Simulated Trajectories II (POST2), a heritage flight mechanics tool developed at NASA Langley Research Center, is ongoing to support current and future NASA missions. To meet mission requirements, it may be necessary for multiple specialized computational tools to interact to properly assess a system. An application programming interface for POST2 was developed to allow easier access for users and to enable communication between external applications. A demonstration of the POST2 application programming interface is presented by utilizing common engineering platforms such as MATLAB and Python.

关键词： Application Programming Interface Flight Mechanics NASA langley research center NASA Flight Path Angle Aerodynamics optimization algorithm Graphical User Interface Monte Carlo Simulation Drogue Parachute

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The impact of optimal climate change control on rice production in critical regions: the case of Southeast Asia 22

The impact of optimal climate change control on rice product...

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22nd IFAC Conference on Technology, Culture and International Stability (TECIS)

作者： De Nardi, Sabrina Sangiorgi, Lucia Raccagni, Sara Carnevale, Claudio Univ Brescia Dept Mech & Ind Engn Via Branze 38 I-25123 Brescia Italy

This study presents a novel data-driven approach designed to address the intricate link between climate change and agriculture, focusing on rice farming in Southeast Asia. By using advanced modelling and optimization tools, namely ARX models and Model Predictive Control, it aims to control the temperature anomaly across fifteen world's subregions. Using ARX models to downscale the global temperature anomaly, the approach allows the evaluation of local climate effects. The methodology is applied to evaluate the impact of climate change on rice production in Southeast Asia, projecting potential outcomes under different emission scenarios. By optimizing greenhouse gas emissions, particularly carbon dioxide and methane, the goal is to keep the temperature anomaly below critical thresholds, ensuring resilient rice production, supporting food security, and minimizing economic and social costs. Copyright (C) 2024 The Authors.

关键词： Data-driven modelling ARX models Model Predictive Control optimization algorithm Climate Change Climate Downscaling Social Security

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A Model-Based Parameter Estimation algorithm for Tire-Soft Soil Contact Model from Off-Road Longitudinal Tests 5th

A Model-Based Parameter Estimation Algorithm for Tire-Soft S...

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5th International Conference of International-Federation-for-the-Promotion-of-Mechanism-and-Machine-Science Italy (IFToMM Italy)

作者： Vella, Angelo Domenico Zerbatol, Luca Galvagnol, Enrico Viglianil, Alessandro Data, Silvio Sacchi, Matteo Eugenio Politecn Torino Turin Italy Stellantis Europe Turin Italy Stellantis Europe Balocco Italy

ISBN: (纸本)9783031645716;9783031645693;9783031645686

Virtual simulation of wheeled and tracked vehicles on soft terrain is progressively assuming a central role in the design and validation of vehicles, especially for planetary missions, agriculture, and military framework. Over the years, various approaches have been developed for studying the off-road locomotion with different levels of detail, fundamental assumptions, and computational time. On the other hand, the objective measurement of parameters underlying the interaction between soil and wheel is still a challenging task. The goal of this research work is to develop a model-based estimator capable of identifying tire-soft soil parameter for semi-empirical contact models using vehicle measurements. An experimental campaign is conducted to gather wheel torques and angular velocities while driving straight-forward on a sandy terrain. The experimental campaign for validating the contact model and the parameter estimator is conducted on a flat sandy playground using a B-SUV vehicle in All-Wheel Drive (AWD) locked mode. The experimental test consists of wide-open throttle (WOT) accelerations A 5 Degrees Of Freedom (DOF) virtual vehicle equipped with semi-empirical wheel contact model and fed with the experimental wheel torques is exploited for simulating the real longitudinal maneuvers. An optimization process aiming at minimizing the difference between experimental and numerical wheel angular velocities is defined to tune the main contact parameters. Two distinct experimental data sets are integrated in the optimization loop for pursuing a better estimation. Finally, the algorithm and the contact model are validated through a different experimental dataset.

关键词： Off-road mobility tire-soft soil interaction vehicle dynamics simulation parameters estimation optimization algorithm

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A Kernel Method Approach to Orbital Debris Blast Point Determination

A Kernel Method Approach to Orbital Debris Blast Point Deter...

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AIAA SciTech Forum

作者： Kulik, Jackson Oertell, Owen Savransky, Dmitry Cornell Univ Ctr Appl Math Ithaca NY 14850 USA Cornell Univ Comp Sci Ithaca NY 14850 USA Cornell Univ Mech & Aerosp Engn Ithaca NY 14850 USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

Given a known parent object, we determine the epoch and velocity distribution of an orbital break-up given unassociated observations of the debris cloud positions at multiple times. Using a tentative guess of the break-up time, we solve Lambert's problem to determine an initial velocity distribution for each debris cloud observation. Agreement of proposed initial velocity distributions depends on the assumed break-up time. We use maximal mean discrepancy in a reproducing kernel Hilbert space to quantify the difference between tentative initial velocity distributions, and optimize this metric to determine the time of break-up.

关键词： Lambert's Problem Hilbert Space Orbital Debris Boundary Value Problems Kernel Functions Low Earth Orbit Satellites Earth Radar Data optimization algorithm Computing

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High-Dimensional Bayesian Optimisation with Large-Scale Constraints - An Application to Aeroelastic Tailoring

High-Dimensional Bayesian Optimisation with Large-Scale Cons...

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AIAA SciTech Forum

作者： Maathuis, Hauke De Breuker, Roeland Castro, Saullo G. P. Delft Univ Technol Aerosp Struct & Mat Fac Aerosp Engn Delft Netherlands AIAA Washington DC USA

ISBN: (数字)9781624107115

ISBN: (纸本)9781624107115

Design optimisation potentially leads to lightweight aircraft structures with lower environmental impact. Due to the high number of design variables and constraints, these problems are ordinarily solved using gradient-based optimisation methods, leading to a local solution in the design space while the global space is neglected. Bayesian Optimisation is a promising path towards sample-efficient, global optimisation based on probabilistic surrogate models. While for problems with a low number of design variables, Bayesian Optimisation methods have demonstrated their strength, the scalability to high-dimensional problems while incorporating large-scale constraints is still lacking. Especially in aeroelastic tailoring where directional stiffness properties are embodied into the structural design of aircraft, to control aeroelastic deformations and to increase the aerodynamic and structural performance, the safe operation of the system needs to be ensured by involving constraints resulting from different analysis disciplines. Hence, a global design space search becomes even more challenging. The present study attempts to tackle the problem by using high-dimensional Bayesian Optimisation in combination with a dimensionality reduction approach to solve the optimisation problem occurring in aeroelastic tailoring, presenting a novel approach for high-dimensional problems with large-scale constraints. Experiments on well-known benchmark cases with black-box constraints show that the proposed approach can incorporate large-scale constraints.

关键词： Bayesian optimization Iterative Solution Black Box Multi Disciplinary Design optimization Aircraft Configurations optimization algorithm Structural Design Stiffness Matrices Nonlinear Aeroelastic Systems Probability Density Functions

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Research on Wireless Charging Queues optimization Method of UAV Swarm 10th

Research on Wireless Charging Queues Optimization Method of ...

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10th International Conference on Communications, Signal Processing, and Systems

作者： Wang, Changfu Wang, Yaohui Zhang, Bin Wang, Mengyi Wang, Xudong Acad Mil Sci Inst Syst Engn Beijing 100300 Peoples R China 94559 Troops Peoples Liberat Army China Beijing Peoples R China

ISBN: (纸本)9789811903908;9789811903892

UAV swarm inevitably have charging queues problems, especially when the number of UAVs is more than that of charging platforms. The charging queues make the system inefficient. In this paper, we study the charging queues problem of UAV swarm, analyze the queuing model, evaluation indexes and optimization algorithms from the basic principles of the queuing system, and focus on the principles of genetic algorithm, particle swarm algorithm and firefly algorithm with autonomous optimization function algorithms and their key applications in the queuing problem, in order to seek better solutions and improve the charging efficiency of UAV swarm.

关键词： UAV Charging queues Queuing theory optimization algorithm

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