Control and navigation problems for model bio-inspired microswimmers

Navigation problems for a model bio-inspired micro-swimmer, consisting of a cargo head and propelled by multiple rotating flagella or propellers and swimming at low Reynolds numbers, are formulated and solved. We consider both the direct problem, namely, predicting velocity and trajectories of the swimmer as a consequence of prescribed rotation rates of the propellers, and inverse problems, namely, find the rotation rates to best approximate desired translational and rotational velocities and, ultimately, target trajectories. The equations of motion of the swimmer express the balance of the forces and torques acting on the swimmer, and relate translational and rotational velocities of the cargo head to rotation rates of the propellers. The coefficients of these equations, representing hydrodynamic resistance coefficients, are evaluated numerically through a custom-built finite-element code to simulate the (Stokes) fluid flows generated by the movement of the swimmer and of its parts. Several designs of the propulsive rotors are considered: from helical flagella with different chirality to marine propellers, and their relative performance is assessed

Indoor Environmental Quality (IEQ): A Comparison between TOPSIS- and PROMETHEE-Based Approaches for Indirect Eliciting of Category Weights

Indoor Environmental Quality (IEQ) has received a great deal of attention in recent years due to the relationship between worker comfort and productivity. Many academics have studied IEQ from both a building design and an IEQ assessment perspective. This latter line of research has mostly used direct eliciting to obtain weights assigned to IEQ categories such as thermal comfort, visual comfort, acoustic comfort, and indoor air quality. We found only one application of indirect eliciting in the literature. Such indirect eliciting operates without the need for imprecise direct weighing and requires only comfort evaluations, which is in line with the Industry 5.0 paradigm of individual, dynamic, and integrated IEQ evaluation. In this paper, we use a case study to compare the only indirect eliciting model already applied to IEQ, based on TOPSIS, to an indirect eliciting method based on PROMETHEE and to a classical direct eliciting method (AHP). The results demonstrate the superiority of indirect eliciting in reconstructing individual preferences related to perceived global comfort

Spare Parts Replacement Policy Based on Chaotic Models

Poisson point processes are widely used to model the consumption of spare parts. However, when the items have very low consumption rates, the historical sample sizes are too small. This paper presents a modelling technique for spare parts policies in the case of items with a low consumption rate. We propose the use of chaotic models derived from the well-known chaotic processes logistic map and Hénon attractor to assess the behaviour of a set of five medium voltage motors supplying four drives in the rolling mill of a steelmaking plant. Supported by the chaotic models, we conclude that the company needs an additional motor to ensure full protection against shortages

Inter-firm exchanges, distributed renewable energy generation, and battery energy storage system integration via microgrids for energy symbiosis

Policymakers and entrepreneurs are aware that reducing energy waste and underutilization are mandatory to actually foster the green transition. Nevertheless, small-medium enterprises usually meet technical and over-whelming financial constraints. They are unable to make profits, become less energy-sensitive, and cut down on their emissions simultaneously. Industrial districts are a source of both wealth and GHG (greenhouse gas) emissions. Eco-industrial parks (EIPs) supply a suitable strategy to ease symbiotic exchanges among various organizations. Surplus electricity from larger, energy-autonomous companies will be a new input for more vulnerable ones. This type of district is challenging, and it can provide an unexplored opportunity to cooperate, invest in renewable energy sources, and form alliances. To better exploit underutilized energy in industrial districts, it is essential to explore energy symbiosis (ES), i.e., an energy-based perspective of industrial symbiosis. This study presents an original mixed-integer linear programming (MILP) optimization model that aims to identify possible inter-firm exchanges and introduce microgrid-based support for distributed renewable-energy generators (DREGs) and battery energy storage systems (BESS) over a one-year simulation period. The model simultaneously targets economic and ecological objectives. The paper compares two case studies, one with battery support and one without. The optimization model was tested using a case study and found to improve energy efficiency (with a 43.46% saving in energy costs) and reduce greenhouse gas emissions (with an 84.59% reduction in GHG) by facilitating symbiotic exchanges among SMEs in industrial districts. The inclusion of BESS support further enhanced the model's ability to utilize green and recovered energy. These findings have im-plications for policymakers, entrepreneurs, and SMEs seeking to transition to more sustainable energy practices. Future work could explore the applicability of the MILP optimization model in other contexts and the potential for scaling up the model to larger industrial districts

Empowering rural districts with Urban-Industrial Symbiosis: A multiobjective model for Waste-to-Energy cogeneration and hydrogen sustainable networks

The growing demand for sustainable energy sources and the need to mitigate greenhouse gas emissions have led to increased interest in developing efficient, cost-effective, and environmentally friendly industrial systems. This paper presents a multi-echelon multi-objective network design model for urban-industrial symbiosis, combining biogas and hydrogen production plants with locally sourced organic waste as feedstock. The integrated biogas-hydrogen system utilizes locally sourced agricultural and organic waste as feedstock, enhancing rural processes sustainability and resource efficiency. The model optimizes the location of industrial plants based on environmental and economic parameters, including transportation emissions, energy consumption, and carbon footprint. A case study set in Emilia Romagna validates the model, and a sensitivity analysis examines the impact of varying input parameters on the designed industrial park. Results demonstrate that the novel combined biogas-hydrogen system not only reduces greenhouse gas emissions but also produces hydrogen at a lower cost due to the utilization of excess power from the biogas cogeneration plant. This research has significant implications, offering a sustainable and cost-effective hydrogen source while promoting efficient supply chain management and strategic decision-making in the renewable energy sector. Further study might investigate system robustness against disruptive events, plant design, and the integration of additional renewable sources