Luigi Crema

Graphene-based technologies for energy applications, challenges and perspectives

Here we report on technology developments implemented into the Graphene Flagship European project for the integration of graphene and graphene-related materials (GRMs) into energy application devices. Many of the technologies investigated so far aim at producing composite materials associating graphene or GRMs with either metal or semiconducting nanocrystals or other carbon nanostructures (e.g., CNT, graphite). These composites can be used favourably as hydrogen storage materials or solar cell absorbers. They can also provide better performing electrodes for fuel cells, batteries, or supercapacitors. For photovoltaic (PV) electrodes, where thin layers and interface engineering are required, surface technologies are preferred. We are using conventional vacuum processes to integrate graphene as well as radically new approaches based on laser irradiation strategies. For each application, the potential of implemented technologies is then presented on the basis of selected experimental and modelling results. It is shown in particular how some of these technologies can maximize the benefit taken from GRM integration. The technical challenges still to be addressed are highlighted and perspectives derived from the running works emphasized.

Light-opals interaction modeling by direct numerical solution of Maxwell’s equations

This work describes a 3-D Finite-Difference Time-Domain (FDTD) computational approach for the optical characterization of an opal photonic crystal. To fully validate the approach we compare the computed transmittance of a crystal model with the transmittance of an actual crystal sample, as measured over the 400 ÷ 750 nm wavelength range. The opal photonic crystal considered has a face-centered cubic (FCC) lattice structure of spherical particles made of polystyrene (a non-absorptive material with constant relative dielectric permittivity). Light-matter interaction is described by numerically solving Maxwells equations via a parallelized FDTD code. Periodic boundary conditions (PBCs) at the outer edges of the crystal are used to effectively enforce an infinite lateral extension of the sample. A method to study the propagating Bloch modes inside the crystal bulk is also proposed, which allows the reconstruction of the ω-k dispersion curve for k sweeping discretely the Brillouin zone of the crystal.

Incorporating domain knowledge into the optimization of energy systems

Graphical abstractDisplay Omitted HighlightsDomain knowledge related to energy systems is incorporated into the algorithms.The proposed technique provides better starting points for the optimization.The adopted state-of-the-art stopping criterion increases computational efficiency.The combined approach produces better energy systems in shorter time. Energy plays a key factor in the advancement of humanity. As energy demands are mostly met by fossil fuels, the world-wide consciousness grows about their negative impact on the environment. Therefore, it becomes necessary to design sustainable energy systems by introducing renewable energies. Because of the intermittent availability of different renewable resources, the designing of a sustainable energy system should find an optimal mix of different resources. However, the optimization of this combination has to deal with a number of possibly contradictory objectives.Multi-objective evolutionary algorithms (MOEA) are widely used to solve this kind of problems. As optimizing an energy system by using a MOEA is computationally costly, it is necessary to solve the problem efficiently. For this purpose, we propose the incorporation of domain knowledge related to energy systems into different phases (i.e., initialization and mutation) of a MOEA run. The proposed approaches are implemented for two widely used MOEAs and evaluated on the Danish Aalborg test problem. The experimental results show that each approach individually achieves significant improvements of the energy systems, which is expressed in better trade-off sets. Moreover, a state-of-the-art stopping criterion is adapted to detect the convergence in order to save computational resources. Finally, all proposed techniques are merged within two MOEAs with the result that our combined approaches yield significantly better results in less time than generic approaches.

Development of a pellet boiler with Stirling engine for m-CHP domestic application

A new sustainable technology has been designed by Fondazione Bruno Kessler through its unit Renewable Energies and Environmental Technologies. This technology is realized integrating in a single system (1) a Stirling engine (mRT-1K) from a pre-engineering design of Allan J. Organ; (2) a micro-heat exchanger technology, to reduce the net transfer unit deficit on the hot side of the heat engine; (3) a customized pellet boiler, able to extract electrical and thermal power; and (4) a customized hydraulic circuit, connecting the cool side of the Stirling engine and the heat generation on the second section of the pellet boiler. The objective of this paper was to present a new technology for the micro-cogeneration of energy at a distributed level able to be integrated in domestic dwellings. Most part of the available biomass is used in buildings for the generation of thermal power for indoor heating and, in minor cases, for hot sanitary water. In the Province of Trento, 88% of the biomass is used for this purpose. The full system is actually under integration for the test phase and not yet tested. The first tests on the single components have confirmed preliminary results on the Stirling engine with respect to the tolerances, pressurization, and proper integration of the electrical generator-driven control system. The pellet boiler has been tested separately, confirming an overall thermal efficiency of 90%.

Heat Transfer Analysis for a Small-Size Direct-Flow Coaxial Concentrating Collector

A coaxial evacuated solar tube has been analyzed. The tube is included in a small-scale concentrated solar power (CSP) system, which runs a cogeneration Stirling engine unit. The engine provides electricity and at the same time generates hot water for heating and sanitary purposes, by cooling down the compression cylinder. The present work is focused on the thermodynamic characterization for a forced-flow in the coaxial evacuated tube, which can heat thermal oil up to 300 C, when coupled with a parabolic trough collector. The single coaxial tube is 2 m long, it has one glass penetration, it is provided with a glass–metal seal and it has an absorber tube in the focal point with a diameter of 12 mm. A model based on heat transfer analysis coupled with fluid dynamic is presented and discussed. The model is then used to investigate spatial temperature profiles and thermal behaviors for the whole solar collector. It improves previous works in the field of concentrating solar collectors and covers the research in small-size concentrating system using thermal oil as heat transfer fluid. [DOI: 10.1115/1.4007297]

Numerical analysis of radiation propagation in innovative volumetric receivers based on selective laser melting techniques

Volumetric absorbers constitute one of the key elements in order to achieve high thermal conversion efficiencies in concentrating solar power plants. Regardless of the working fluid or thermodynamic cycle employed, design trends towards higher absorber output temperatures are widespread, which lead to the general need of components of high solar absorptance, high conduction within the receiver material, high internal convection, low radiative and convective heat losses and high mechanical durability. In this context, the use of advanced manufacturing techniques, such as selective laser melting, has allowed for the fabrication of intricate geometries that are capable of fulfilling the previous requirements. This paper presents a parametric design and analysis of the optical performance of volumetric absorbers of variable porosity conducted by means of detailed numerical ray tracing simulations. Sections of variable macroscopic porosity along the absorber depth were constructed by the fractal growth of sing...

Improving Robustness of Stopping Multi-objective Evolutionary Algorithms by Simultaneously Monitoring Objective and Decision Space

Appropriate stopping criteria for multi-objective evolutionary algorithms (MOEA) are an important research topic due to the computational cost of function evaluations, particularly on real-world problems. Most common stopping criteria are based on a fixed budget of function evaluations or the monitoring of the objective space. In this work, we propose a stopping criterion based on monitoring both the objective and decision space of a problem. Average Hausdorff distance (AHD) and genetic diversity are used, respectively. Two-sided t-tests on the slope coefficients after regression analyses are used to detect the stagnation of the AHD and the genetic diversity. The approach is implemented for two widely used MOEAs: NSGA-II and SPEA2. It is compared to a fixed budget, the online convergence detection approach, and the individual monitoring of each space on four bi-objective and two three-objective benchmark problems. Our experimental results reveal that the combined approach achieved significantly better results than the approaches considering only one of the spaces. In particular, we find that the combined consideration runs longer and hence more robustly ensures a well-approximated Pareto front. Nevertheless, on average 29% and 17% function evaluations are saved for NSGA-II and SPEA2, respectively, compared to standard budget recommendations.

Multi-objective Optimisation with Multiple Preferred Regions

The typical goal in multi-objective optimization is to find a set of good and well-distributed solutions. It has become popular to focus on specific regions of the objective space, e.g., due to market demands or personal preferences.

Model-Based Design of an Energy-System Embedded Controller Using Taste

Model-based design has become a standard practice in the development of control systems. Many solutions provide simulation, code generation, and other functionalities to minimize the design time and optimize the resulting control system implementation.