A5004326236- Magnetic confinement fusion research
- Fusion materials and technologies
- Nuclear reactor physics and engineering
- Ionosphere and magnetosphere dynamics
- Forecasting Techniques and Applications
- Advanced Statistical Methods and Models
- Laser-Plasma Interactions and Diagnostics
- Superconducting Materials and Applications
- Evolutionary Algorithms and Applications
- Nuclear Physics and Applications
- Fault Detection and Control Systems
- Advanced Statistical Process Monitoring
- Geomagnetism and Paleomagnetism Studies
- Neural Networks and Applications
- Model Reduction and Neural Networks
- Viral Infections and Vectors
- Time Series Analysis and Forecasting
- Laser-induced spectroscopy and plasma
- Metaheuristic Optimization Algorithms Research
- Spectroscopy and Chemometric Analyses
- earthquake and tectonic studies
- Nonlinear Dynamics and Pattern Formation
- Greenhouse Technology and Climate Control
- Financial Risk and Volatility Modeling
- Computational Physics and Python Applications
University of Rome Tor Vergata
2020-2023
To produce fusion reactions efficiently, thermonuclear plasmas have to reach extremely high temperatures, which is incompatible with their coming into contact material surfaces. Confinement of using magnetic fields has progressed significantly in the last years, particularly tokamak configuration. Unfortunately, all devices, and metallic ones, are plagued by catastrophic events called disruptions. Many disruptions preceded anomalies radiation patterns, ITER-relevant scenarios. These specific...
Abstract In many fields of science, various types models are available to describe phenomena, observations and the results experiments. last decades, given enormous advances information gathering technologies, also machine learning techniques have been systematically deployed extract from large databases. However, regardless their origins, no universal criterion has found so far select most appropriate model data. A unique solution is probably a chimera, particularly in applications...
Abstract Bolometry is an essential diagnostic for calculating the power balances and understanding of different physical aspects tokamak experiments. The reconstruction method based on Maximum Likelihood (ML) principle, developed initially JET, has been implemented ASDEX Upgrade. Due to availability a limited number views, problem mathematically ill-posed. A regularizing procedure, assumption smoothness along magnetic surfaces, given by plasma equilibrium, must also be implemented. new...
Abstract Plasma polarimetry is a diagnostic technique used in nuclear fusion reactors to measure the line integral of some plasma parameters, such as electron density and magnetic field, constrain, analyse validate equilibrium models. Despite strong link between properties light polarisation propagation, interpretation remains complex sometimes uncertain. The type 1 approximation most common hypothesis effects, Faraday rotation Cotton Mouton phase shift, with (electron fields). However, this...
The Stellarator is a magnetic configuration considered realistic candidate for future thermonuclear fusion commercial reactor. most widely accepted scaling law of the energy confinement time ISS04, which employs renormalisation factor, fren, specific to each device and level optimisation individual machines. fren coefficient believed account higher order effects not ascribable variations in 0D quantities, only ones included database used derive International Confinement database. This...
Abstract In many fields of science, various types models are available to describe phenomena, observations and the results experiments. last decades, given enormous advances information gathering technologies, also machine learning techniques have been systematically deployed extract from large databases. However, regardless their origins, no universal criterion has found so far select most appropriate model data. A unique solution is probably a chimera, particularly in applications...
Abstract In the era of Big Data, many scientific disciplines and engineering activities rely on cumulative databases, consisting entries derived from different experiments studies, to investigate complex problems. Their contents can be analysed with much finer granularity than usual meta-analytic tools, based summary statistics such as means standard deviations. At same time, not being primary also traditional statistical techniques are adequate them. New meta-analysis methods have therefore...
It can be argued that the identification of sound mathematical models is ultimate goal any scientific endeavour. On other hand, particularly in investigation complex systems and nonlinear phenomena, discriminating between alternative a very challenging task. Quite sophisticated model selection criteria are available but their deployment practice problematic. In this work, Akaike Information Criterion reformulated with help purely information theoretic quantities, namely, Gibbs‐Shannon...
The control of macroscopic instabilities, such as Edge Localised Modes (ELMs) and sawteeth, is becoming an essential ingredient in the optimisation scenarios preparation for next generation tokamaks demonstrative reactor. Various pacing experiments have been indeed successfully carried out many devices but various details their interactions with plasma remain poorly understood, particular assessment relative contribution driver phase amplitude to frequency synchronization. In this paper, a...
Laser-based methods are widely used techniques for thermonuclear plasma diagnostics, since they can probe the internal of plasma, being contactless and non-invasive. The interferometer, polarimeter Thomson scattering most widespread techniques, providing line-integral information electron density magnetic field (interferometer–polarimeter) local temperature (Thomson scattering). design diagnostics is a fundamental step, which usually requires an iterative process to maximise performances...
Model selection criteria are widely used to identify the model that best represents data among a set of potential candidates. Amidst different criteria, Bayesian information criterion (BIC) and Akaike (AIC) most popular better understood. In derivation these indicators, it was assumed model’s dependent variables have already been properly identified entries not affected by significant uncertainties. These issues can become quite serious when investigating complex systems, especially highly...
In many engineering fields and scientific disciplines, the results of experiments are in form time series, which can be quite problematic to interpret model. Genetic programming tools powerful extracting knowledge from data. this work, several upgrades refinements proposed tested improve explorative capabilities symbolic regression (SR) via genetic (GP) for investigation with objective mathematical models directly available signals. The main task is not simply prediction but consists...
Abstract On the route to commercial reactor, experiments in magnetical confinement nuclear fusion have become increasingly complex and they tend produce huge amounts of data. New analysis tools therefore indispensable, fully exploit information generated by most relevant devices, which are nowadays very expensive both build operate. The paper presents a series innovative cover main aspects any scientific investigation. Causality detection techniques can help identify right causes phenomena...