Search results for "force"
showing 10 items of 3423 documents
Reduction of cogging force in linear generators for wave energy harvesting
2022
Due to huge energy potential of sea waves, many technologies have been proposed in the last few years. Some concepts have been developed and sometimes also tested in the open sea. Some prototypes use linear generators to directly convert the vertical motion of buoys into electrical energy. This solution minimizes the numbers of energy conversion steps, increasing the energy efficiency. At the same time, the limited numbers of components could also increase the reliability of the wave energy converter. For this reason, the development of linear generators is considered with great interest. This paper investigated the cogging force, a magnetic force due to the interaction between the magnets …
Implementation of a fast and low cost IR-NDT technique by means of a Square Pulse modulated Lock-In Thermography
2012
This work describes the development of an IR-NDT procedure based on a lock-in signal treatment in the frequency domain to obtain phase-contrast defect signatures. Heat stimulation is obtained by periodically shattering a common low-power halogen lamp. The delivered heat is then modulated as a train of square waves with multi-frequency harmonic content. The proposed lock-in algorithm is able to selectively retrieve phase and amplitude information at various frequencies of the acquired temperature, acting also as a narrow band filter to improve defect-signature to noise ratio. The procedure is implemented and evaluated by means of low cost IR equipment to investigate artificially defected thi…
The Reinforcement Effect of Strain Gauges Embedded in Low Modulus Material
2013
The reinforcement effect of electrical resistance strain gauges is well-described in the literature, especially for strain gauges installed on surface. This paper considers the local reinforcement effect of strain gauges embedded within low Young modulus materials. In particular, by using a simple theoretical model, already used for strain gauges installed on the surface, it proposes a simple formula that allows the user to evaluate the local reinforcement effect of a generic strain gauge embedded on plastics, polymer composites, etc. The theoretical analysis has been integrated by numerical and experimental analyses, which confirmed the reliability of the proposed model.
Bipolar membrane reverse electrodialysis for the sustainable recovery of energy from pH gradients of industrial wastewater: Performance prediction by…
2021
Abstract The theoretical energy density extractable from acidic and alkaline solutions is higher than 20 kWh m−3 of single solution when mixing 1 M concentrated streams. Therefore, acidic and alkaline industrial wastewater have a huge potential for the recovery of energy. To this purpose, bipolar membrane reverse electrodialysis (BMRED) is an interesting, yet poorly studied technology for the conversion of the mixing entropy of solutions at different pH into electricity. Although it shows promising performance, only few works have been presented in the literature so far, and no comprehensive models have been developed yet. This work presents a mathematical multi-scale model based on a semi-…
Robust Discrete-Time Lateral Control of Racecars by Unknown Input Observers
2023
This brief addresses the robust lateral control problem for self-driving racecars. It proposes a discrete-time estimation and control solution consisting of a delayed unknown input-state observer (UIO) and a robust tracking controller. Based on a nominal vehicle model, describing its motion with respect to a generic desired trajectory and requiring no information about the surrounding environment, the observer reconstructs the total force disturbance signal, resulting from imperfect knowledge of the time-varying tire-road interface characteristics, presence of other vehicles nearby, wind gusts, and other model uncertainty. Then, the controller actively compensates the estimated force and as…
Roboception and adaptation in a cognitive robot
2023
In robotics, perception is usually oriented at understanding what is happening in the external world, while few works pay attention to what is occurring in the robot’s body. In this work, we propose an artificial somatosensory system, embedded in a cognitive architecture, that enables a robot to perceive the sensations from its embodiment while executing a task. We called these perceptions roboceptions, and they let the robot act according to its own physical needs in addition to the task demands. Physical information is processed by the robot to behave in a balanced way, determining the most appropriate trade-off between the achievement of the task and its well being. The experiments show …
Deep learning techniques for visual object tracking
2023
Visual object tracking plays a crucial role in various vision systems, including biometric analysis, medical imaging, smart traffic systems, and video surveillance. Despite notable advancements in visual object tracking over the past few decades, many tracking algorithms still face challenges due to factors like illumination changes, deformation, and scale variations. This thesis is divided into three parts. The first part introduces the visual object tracking problem and discusses the traditional approaches that have been used to study it. We then propose a novel method called Tracking by Iterative Multi-Refinements, which addresses the issue of locating the target by redefining the search…
Enabling peer-to-peer User-Preference-Aware Energy Sharing Through Reinforcement Learning
2020
Renewable, heterogeneous and distributed energy resources are the future of power systems, as envisioned by the recent paradigm of Virtual Power Plants (VPPs). Residential electricity generation, e.g., through photovoltaic panels, plays a fundamental role in this paradigm, where users are able to participate in an energy sharing system and exchange energy resources among each other. In this work, we study energy sharing systems and, differently from previous approaches, we consider realistic user behaviors by taking into account the user preferences and level of engagement in the energy trades. We formulate the problem of matching energy resources while contemplating the user behavior as a …
A Reinforcement Learning Approach for User Preference-aware Energy Sharing Systems
2021
Energy Sharing Systems (ESS) are envisioned to be the future of power systems. In these systems, consumers equipped with renewable energy generation capabilities are able to participate in an energy market to sell their energy. This paper proposes an ESS that, differently from previous works, takes into account the consumers’ preference, engagement, and bounded rationality. The problem of maximizing the energy exchange while considering such user modeling is formulated and shown to be NP-Hard. To learn the user behavior, two heuristics are proposed: 1) a Reinforcement Learning-based algorithm, which provides a bounded regret and 2) a more computationally efficient heuristic, named BPT- ${K}…
Damages claims for anticompetitive conduct after the Directive 2014/104/EU: Is it (still) worth talking about a private law remedy?
2019
Directive 2014/2014/EU puts the private law remedy of non-contractual liability as the pivot of the entire system of antitrust private enforcement. Neither exhaustive nor containing a “full-harmonization rule,” it promotes the approximation of national laws by introducing a set of substantial and procedural measures, whose main goal is granting the effectiveness of the individual rights to compensation conferred by the antimonopolistic provisions of the TFEU. Many elements, however, induce to wonder about the main features and ultimately the very nature of the remedy by means of which “any person” can claim for damages suffered as a consequence of anticompetitive conduct. The author argues …