This paper focuses on addressing the optimization scheduling problem of multi-UAV power inspection tasks. In the context of power inspections, it is often not feasible for a single UAV to complete the inspection due t...
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ISBN:
(纸本)9798350389814;9798350389807
This paper focuses on addressing the optimization scheduling problem of multi-UAV power inspection tasks. In the context of power inspections, it is often not feasible for a single UAV to complete the inspection due to limitations such as power endurance, UAV hardware constraints, and task settings. Consequently, multiple UAVs are required to perform inspections in a continuous manner. The study models the complex scenario of power line inspection as a multi-objective optimization problem, considering various risk factors associated with UAV operations. By examining these risks, the study proposes a solution based on the Non-dominated Sorting Genetic algorithm III (NSGA-III) algorithm. The proposed approach aims to minimize both the total risk and the maximum risk faced by UAVs during the inspection process. Comparative experiments are conducted to validate the effectiveness of the proposed algorithm. The results demonstrate that, compared to traditional rule-based methods, the NSGA-III algorithm significantly reduces both total risk and maximum risk, ensuring efficient and safe power inspection. Furthermore, the study also considers the failure continuation case, where the remaining UAVs can effectively take over and complete the inspection tasks in case of failure of one UAV. This contributes to the development of more reliable and robust UAV-based power inspection techniques.
An algorithm for the integral calculation of efficiency maps of variable flux machines under consideration of the relative flux level is presented. The general idea and the algorithm logic are presented in detail and ...
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ISBN:
(纸本)9798350387605;9798350387599
An algorithm for the integral calculation of efficiency maps of variable flux machines under consideration of the relative flux level is presented. The general idea and the algorithm logic are presented in detail and the efficiency map calculation is validated against a conventional gradient based efficiency map calculation algorithm. Instead of calculating efficiency maps for discrete flux levels and interpolating these maps afterwards, the algorithm presented here directly includes the relative magnet flux in the efficiency calculation. The presented approach uses torque and voltage surfaces in a plane of current, current angle and flux level. As results, the an exemplary efficiency map calculated with the algorithm is presented and the effect of different numbers of underlying data sets are discussed. Finally, a short outlook on practical applications is given.
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 ...
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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.
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 al...
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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.
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 miss...
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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.
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 ...
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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.
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 framew...
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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.
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 brea...
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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.
Long-wave antennas are extensively employed in extra long-distance communications and navigation, ocean surveillance, and radio broadcasting, owing to their superior propagation characteristics at low frequencies. Lon...
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ISBN:
(数字)9798350353129
ISBN:
(纸本)9798350353129;9798350353136
Long-wave antennas are extensively employed in extra long-distance communications and navigation, ocean surveillance, and radio broadcasting, owing to their superior propagation characteristics at low frequencies. Long-wave signals, characterized by strong penetrating power and extended propagation ranges, are well-suited for remote communications and signal transmission in unique environments. As information and communication technologies continue to evolve, the design and optimization of long-wave antennas have emerged as a focal research area. This article systematically reviews the fundamental principles, common types, design methodologies, and recent research advancements of long-wave antennas, aiming to offer a comprehensive reference framework to facilitate further advancements and applications in long-wave antenna technology.
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...
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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.
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