Synchronisation effects on the behavioural performance and information dynamics of a simulated minimally cognitive robotic agent

Oscillatory activity is ubiquitous in nervous systems, with solid evidence that synchronisation mechanisms underpin cognitive processes. Nevertheless, its informational content and relationship with behaviour are still to be fully understood. In addition, cognitive systems cannot be properly appreciated without taking into account brain–body– environment interactions. In this paper, we developed a model based on the Kuramoto Model of coupled phase oscillators to explore the role of neural synchronisation in the performance of a simulated robotic agent in two different minimally cognitive tasks. We show that there is a statistically significant difference in performance and evolvability depending on the synchronisation regime of the network. In both tasks, a combination of information flow and dynamical analyses show that networks with a definite, but not too strong, propensity for synchronisation are more able to reconfigure, to organise themselves functionally and to adapt to different behavioural conditions. The results highlight the asymmetry of information flow and its behavioural correspondence. Importantly, it also shows that neural synchronisation dynamics, when suitably flexible and reconfigurable, can generate minimally cognitive embodied behaviour

Enhancement of Power-to-Gas via Multi-catalyst Reactors Tailoring Reaction Rate and Heat Exchange

The Sabatier reaction is a key element of power-to-gas development. For this reason, even though the process is known since more than one century, the Sabatier reaction is currently the object of important research efforts towards the development of new catalysts for performance improvement. However, the industrial exploitation of the Sabatier reaction depends on the development of reactors that match the best catalyst with an appropriate heat management. For this reason, this paper develops a methodology for the contemporary optimization of the reactor concept and the catalysts. It is observed that the reactor can be divided into three sections with contrasting requirements. In the first section, the main requirement concerns the reach of the reaction activation conditions. Hence, an adequate match between catalyst and reactor is needed, for example with an appropriate pre-heater. Once the reaction is activated, a reaction hotspot is formed, so that the cooling becomes determining and the main requirement for the catalyst is the resistance to poisoning and sintering. In the last section of the reactor, the low temperature activity of the catalyst is determining, so that a high-performing catalyst is needed. This paper indicates a strategy for the rational design of this catalyst, based on mechanistic evidences

Neuronal oscillations, information dynamics, and behaviour: an evolutionary robotics study

Oscillatory neural activity is closely related to cognition and behaviour, with synchronisation mechanisms playing a key role in the integration and functional organization of different cortical areas. Nevertheless, its informational content and relationship with behaviour - and hence cognition - are still to be fully understood. This thesis is concerned with better understanding the role of neuronal oscillations and information dynamics towards the generation of embodied cognitive behaviours and with investigating the efficacy of such systems as practical robot controllers. To this end, we develop a novel model based on the Kuramoto model of coupled phase oscillators and perform three minimally cognitive evolutionary robotics experiments. The analyses focus both on a behavioural level description, investigating the robot’s trajectories, and on a mechanism level description, exploring the variables’ dynamics and the information transfer properties within and between the agent’s body and the environment. The first experiment demonstrates that in an active categorical perception task under normal and inverted vision, networks with a definite, but not too strong, propensity for synchronisation are more able to reconfigure, to organise themselves functionally, and to adapt to different behavioural conditions. The second experiment relates assembly constitution and phase reorganisation dynamics to performance in supervised and unsupervised learning tasks. We demonstrate that assembly dynamics facilitate the evolutionary process, can account for varying degrees of stimuli modulation of the sensorimotor interactions, and can contribute to solving different tasks leaving aside other plasticity mechanisms. The third experiment explores an associative learning task considering a more realistic connectivity pattern between neurons. We demonstrate that networks with travelling waves as a default solution perform poorly compared to networks that are normally synchronised in the absence of stimuli. Overall, this thesis shows that neural synchronisation dynamics, when suitably flexible and reconfigurable, produce an asymmetric flow of information and can generate minimally cognitive embodied behaviours

Evolutionary robotics and neuroscience

No description supplie

Regeneration Section of CO2 Capture Plant by MEA Scrubbing with a Rate-Based Model

CO2 capture from exhaust gas of power plants, natural gas and refinery gas can be successfully achieved by chemical absorption with alkanolamines. CO2 capture from exhaust gas is often obtained by absorption with monoethanolamine (MEA) which is the most frequently used solvent for this purpose. Thermodynamics, kinetics and mass transfer influence the chemical absorption process. Acidic gases and amines are weak electrolytes, which partially dissociate in the aqueous phase: the high non-ideality of the liquid phase must be properly taken into account, by employing a γ/φ method. Kinetics and mass transfer can be described using two different approaches: the “equilibrium-based stage efficiency” model or the “rate-based” one. ASPEN Plus® uses the rate-based model, but the prediction of mass transfer coefficients is based on the film theory by Lewis and Whitman, while other theories can more conveniently be used, i.e. the Eddy Diffusivity theory. Since ASPEN Plus® simulator is suitable to be user customized, it has been chosen as framework for the model proposed in this work, that was validated by comparing simulation results with experimental data of a pilot plant for the purification of exhaust gas from power plant by means of MEA washing

Regeneration section of CO2 capture plant by MEA scrubbing with a rate-based model

CO2 capture from exhaust gas of power plants, natural gas and refinery gas can be successfully achieved by chemical absorption with alkanolamines. CO2 capture from exhaust gas is often obtained by absorption with monoethanolamine (MEA) which is the most frequently used solvent for this purpose. Our paper focuses on the regeneration section, where the amine solution is separated from the absorbed CO2 and recirculated to the absorber. Since regeneration is obtained in a stripper or a distillation column, it is the most energy demanding unit of the plant, so a careful modeling is required. Thermodynamics, kinetics and mass transfer influence the chemical absorption process. Acidic gases and amines are weak electrolytes, which partially dissociate in the aqueous phase: the high non-ideality of the liquid phase must be properly taken into account, by employing a γ/φ method. Kinetics and mass transfer can be described using two different approaches: the “equilibrium-based stage efficiency” model or the “rate-based” one. ASPEN Plus® uses the rate-based model, but the prediction of mass transfer coefficients is based on the film theory by Lewis and Whitman, while other theories can more conveniently be used, i.e. the Eddy Diffusivity theory. Since ASPEN Plus® simulator is suitable to be user customized, it has been chosen as framework for the model proposed in this work, that was validated by comparing simulation results with experimental data of a pilot plant for the purification of exhaust gas from power plant

Simulation of CO2 Capture by MEA Scrubbing with a Rate-Based Model

n/

Assessment of global sustainability of bioenergy production in a water-food-energy perspective

One of most demanding problems for decision makers and for process engineers is the design of a proper energy strategy to guarantee clean energy supply. This problem is complex and cannot be assessed considering only the standard efficiency criteria used in the past. The process of energy production needs to be analyzed in its completeness, from seed to consumption. This paper deals with the issue of bioenergy production following a nexus perspective, considering the link among water, food and energy. In particular, an objective function depending on the most important resources required in bioenergy production is defined so that it can be simply optimized. Considering the parameter interrelationship among water, food and land (the so-called water-food-energy nexus) the method gives the instruments to determine, in one single function, the optimal condition with respect to these resources. Two cases of study are analysed, dissimilar regarding the geographical location, environmental resources availability for energy production and food security. Results show how the proposed method is able to describe the present sustainability of bioenergy production in a certain site. Furthermore, it can help to investigate the existence of bottlenecks related to the current situation of the site and, at the same time, it can highlight future opportunities in producing sustainable bioenergy