Solar still efficiency enhancement by using graphene oxide/ paraffin composite

Solar-driven water desalination technologies are rapidly developing with various links to other renewable sources. However, the efficiency of such systems severely depends on the design parameters. The present study focused on using graphene oxide (GO) with the ɸ = 0.2, 0.4 and 0.6 wt. % dispersed in paraffin, as phase change materials (PCMs), to improve the productivity of a solar still for desalination applications. The outcomes showed that by adding more graphene oxide to paraffin, the melting temperature reduces. Solar still with GO/ paraffin showed 25% productivity improvement in comparison with the solar still with only PCM. The obtained Nusselt number during the melting time also represented that free convection heat transfer into the melted region of the solar still has been enhanced by adding dispersed GO to the PCM, compared to the base paraffin. Also, increasing the hot wall temperature augments the Nusselt number. Finally, an empirical equation was derived to correlate the average Nusselt number as a function of Rayleigh number (Ra), the Stefan number (Ste), the subcooling factor (Sb) and the Fourier number (Fo). The obtained correlation depicted that Nusselt number enhancement has a reverse relation with Fourier number

Design and Evaluation of a Bioinspired Tendon-Driven 3D-Printed Robotic Eye with Active Vision Capabilities

The field of robotics has seen significant advancements in recent years, particularly in the development of humanoid robots. One area of research that has yet to be fully explored is the design of robotic eyes. In this paper, we propose a computer-aided 3D design scheme for a robotic eye that incorporates realistic appearance, natural movements, and efficient actuation. The proposed design utilizes a tendon-driven actuation mechanism, which offers a broad range of motion capabilities. The use of the minimum number of servos for actuation, one for each agonist-antagonist pair of muscles, makes the proposed design highly efficient. Compared to existing ones in the same class, our designed robotic eye comprises aesthetic and realistic features. We evaluate the robot's performance using a vision-based controller, which demonstrates the effectiveness of the proposed design in achieving natural movement, and efficient actuation. The experiment code, toolbox, and printable 3D sketches of our design have been open-sourced

Laser-induced radial birefringence and spin-to-orbital optical angular momentum conversion in silver-doped glasses

Samples of Ag$^+$/Na$^{+}$ ion-exchanged glass that have been subject to intense laser irradiation may develop novel optical properties, as a consequence of the formation of patterns of silver nanoparticles and other structures. Here, we report the observation of a laser-induced permanent transverse birefringence, with the optical axis forming a radial pattern, as revealed by the spin-to-orbital angular momentum conversion occurring in a probe light beam. The birefringence pattern can be modeled well as resulting from thermally-induced stresses arising in the silver-doped glass during laser exposure, although the actual mechanism leading to the permanent anisotropy is probably more complex.Comment: 3 pages, 3 figure

A Multi-Robot Task Assignment Framework for Search and Rescue with Heterogeneous Teams

In post-disaster scenarios, efficient search and rescue operations involve collaborative efforts between robots and humans. Existing planning approaches focus on specific aspects but overlook crucial elements like information gathering, task assignment, and planning. Furthermore, previous methods considering robot capabilities and victim requirements suffer from time complexity due to repetitive planning steps. To overcome these challenges, we introduce a comprehensive framework__the Multi-Stage Multi-Robot Task Assignment. This framework integrates scouting, task assignment, and path-planning stages, optimizing task allocation based on robot capabilities, victim requirements, and past robot performance. Our iterative approach ensures objective fulfillment within problem constraints. Evaluation across four maps, comparing with a state-of-the-art baseline, demonstrates our algorithm's superiority with a remarkable 97 percent performance increase. Our code is open-sourced to enable result replication.Comment: The 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023 Advances in Multi-Agent Learning - Coordination, Perception, and Control Workshop

A Flexible Responsive Load Economic Model for Industrial Demands

The best pricing method for any company in a perfectly competitive market is the pricing scheme with regards to the marginal cost. In contrast to this environment, there is a market with imperfect competition. In this market, the price can be affected by some players in the generation/demand side (i.e., suppliers and/or buyers). In the economic literature, “market power” refers to a company that has the power to affect prices. In fact, market power is often defined as the ability to divert prices from competitive levels. In the electricity market, especially because of the integration of intermittent renewable energy resources (RESs) along with the inflexibility of demand, there are levels of market power on the supply side. Hence, implementation of demand response (DR) programs is necessary to increase the flexibility of the demand side to deal with the intermittency of renewable generations and at the same time tackle the market power of the supply side. This paper uses economic theories and mathematical formulations to develop a flexible responsive load economic model (FRLEM) based on real-time pricing (RTP) to show modification of the load profile and mitigation of the energy costs for an industrial zone. This model was developed based on constant elasticity of the substitution utility function, known as one of the most popular utility functions in microeconomics

Influence of Team Interactions on Multi-Robot Cooperation: A Relational Network Perspective

Relational networks within a team play a critical role in the performance of many real-world multi-robot systems. To successfully accomplish tasks that require cooperation and coordination, different agents (e.g., robots) necessitate different priorities based on their positioning within the team. Yet, many of the existing multi-robot cooperation algorithms regard agents as interchangeable and lack a mechanism to guide the type of cooperation strategy the agents should exhibit. To account for the team structure in cooperative tasks, we propose a novel algorithm that uses a relational network comprising inter-agent relationships to prioritize certain agents over others. Through appropriate design of the team's relational network, we can guide the cooperation strategy, resulting in the emergence of new behaviors that accomplish the specified task. We conducted six experiments in a multi-robot setting with a cooperative task. Our results demonstrate that the proposed method can effectively influence the type of solution that the algorithm converges to by specifying the relationships between the agents, making it a promising approach for tasks that require cooperation among agents with a specified team structure.Comment: Accepted to Multi-Robot and Multi-Agent Systems (IEEE MRS 2023

Study on guardrail post behavior located on organic soil using simplified experimental and numerical methods

For the purpose of road safety, it is vital to reduce the severity of road accidents and increase safety around the roadway area by deploying guardrails. In case of a car crash, a guardrail post must be deformable so that such restraint is not too abrupt due to the occupant’s sensitivity. Soil type influences on the guardrail post behavior have been a somewhat unfounded variable due to the high soil heterogeneity and challenging interpretation of its real implications on the safety of guardrail systems. Since little attention is concentrated on evaluating the guardrail post behavior through simplified procedures, this article aims to provide a simplified experimental and numerical approach to study the behavior of guardrail posts located on organic soil. Results of laboratory and in-situ tests indicated that guardrail posts behavior located on organic soil depends on section orientation, driving depth, and loading speed. To confirm and compare the in-situ tests, simplified numerical simulations through Plaxis 3D software were carried out, and data from numerical modeling approved the accuracy of in-situ results.The authors acknowledge the financial support by FCT / MCTES through national funds (PIDDAC) under the R&D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE), under reference UIDB/04029/2020; and ANI through national funds (Portugal 2020), under project “BARROD - Barreiras de Segurança Rodoviária”, reference 33497