1,721,687 research outputs found
On the optimal mix of renewable energy sources, electrical energy storage and thermoelectric generation for the de-carbonization of the Italian electrical system
No full textThe integration of intermittent renewable energy sources (RES) requires a substantial amount of electrical energy storage and significant increase of the grid capabilities. To keep these upgrades within reasonable limits, strategies maintaining a moderate but flexible thermoelectric power have been investigated. Based on the experimental loads for Italy in 2013, the implications of increasing the contribution of scalable RES, particularly wind and photovoltaic, are investigated in detail. The optimal value of the storage depends on its round-trip efficiency (1.3 TWh for hydroelectric storage and 6 TWh for power to gas). For RES producing 100% of the annual demand, the use of the optimal storage and of about 10 GW of thermoelectric power allows a substantial de-carbonization (more than 90%) of the electricity production still maintaining a capacity factor of the thermoelectric generators above 40%. Avoiding thermoelectric generation is possible but it requires overproduction by RES, between 120 and 200% of the annual electricity demand, depending on the storage technology and the mix between wind and photovoltaic generation. The calculations have been performed for realistic values of the storage round-trip efficiency and for various combinations of photovoltaic and wind powers. The capital costs required are also estimated at current costs of present day technologies
Testing the consistency of multimachine databases for physical studies of regression
No full textThe investigation of various aspects of tokamak physics is performed with a combination of experiments carried out in different machines, to improve the statistical basis of the results and to cover a sufficient wide region of the operational space. Therefore, in the last decades, various multimachine databases have been built to address general and specific physical questions, particularly related to the extrapolation of present results to the next generation of devices. In this paper, a methodology of analysis is presented, to assess whether a multimachine data set is sufficiently coherent to really substantiate the conclusions, which are expected to be derived from it. A series of statistical and information theoretical tools have been refined to address the consistency of the data provided by the different devices. The developed techniques allow determination of whether it is reasonable to expect that the physics is the same in the various devices and/or that the entries do not present unacceptable bias. To exemplify the potential of the proposed approach, a systematic analysis of the ITPA database of the confinement time has been performed, using both dimensional and dimensionless quantities. The results obtained strongly suggest that better care should be taken in ensuring the coherence of data obtained from different experiments on different devices
New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing
Full text linkThe construction and operation of the first generation of magnetically controlled nuclear fusion power plants require the development of proper physics and the engineering bases. The analysis of data, recently collected by the actual largest and most important tokamak in the world JET, that has successfully completed his second deuterium and tritium campaign in 2021 (DTE2) with a full ITER like wall main chamber, has provided an important consolidation of the ITER physics basis. Thermonuclear plasmas are highly nonlinear systems characterized by the need of numerous diagnostics to measure physical quantities to guide, through proper control schemes, external actuators. Both modelling and machine learning approaches are required to maximize the physical understanding of plasma dynamics and at the same time, engineering challenges have to be faced. Fusion experiments are indeed extremely hostile environments for plasma facing materials (PFM) and plasma-facing components (PFC), both in terms of neutron, thermal loads and mechanical stresses that the components have to face during either steady operation or off-normal events. Efforts are therefore spent by the community to reach the ultimate goal ahead: turning on the first nuclear fusion power plant, DEMO, by 2050. This editorial is dedicated at reviewing some aspects touched in recent studies developed in this dynamic, challenging project, collected by the special issue titled “New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing”
Causality detection methods applied to the investigation of malaria epidemics
Full text linkMalaria, a disease with major health and socio-economic impacts, is driven by multiple factors, including a complex interaction with various climatic variables. In this paper, five methods developed for inferring causal relations between dynamic processes based on the information encapsulated in time series are applied on cases previously studied in literature by means of statistical methods. The causality detection techniques investigated in the paper are: a version of the kernel Granger causality, transfer entropy, recurrence plot, causal decomposition and complex networks. The methods provide coherent results giving a quite good confidence in the conclusions
Robust scaling laws for energy confinement time, including radiated fraction, in Tokamaks
No full textIn recent years, the limitations of scalings in power-law form that are obtained from traditional
log regression have become increasingly evident in many fields of research. Given the wide
gap in operational space between present-day and next-generation devices, robustness of the
obtained models in guaranteeing reasonable extrapolability is a major issue. In this paper,
a new technique, called symbolic regression, is reviewed, refined, and applied to the ITPA
database for extracting scaling laws of the energy-confinement time at different radiated
fraction levels. The main advantage of this new methodology is its ability to determine the
most appropriate mathematical form of the scaling laws to model the available databases
without the restriction of their having to be power laws. In a completely new development,
this technique is combined with the concept of geodesic distance on Gaussian manifolds so
as to take into account the error bars in the measurements and provide more reliable models.
Robust scaling laws, including radiated fractions as regressor, have been found; they are not
in power-law form, and are significantly better than the traditional scalings. These scaling
laws, including radiated fractions, extrapolate quite differently to ITER, and therefore
they require serious consideration. On the other hand, given the limitations of the existing
databases, dedicated experimental investigations will have to be carried out to fully understand
the impact of radiated fractions on the confinement in metallic machines and in the next
generation of devices
A comprehensive study of the uncertainties in bolometric tomography on JET using the maximum likelihood method
No full textEssential physical quantities of magnetically confined plasmas are derived on a routine basis from bolometric reconstructions. In the last few years at the Joint European Torus (JET), the Maximum Likelihood method has demonstrated the capability of providing reliable reconstructions for this class of ill-posed problems. The article is focused on quantifying the effects of important sources of errors, usually underestimated, that can influence both the reconstructions and the derived quantities. A complete set of phantoms has been used to test the robustness of the technique. The main sources of uncertainties investigated in this contribution are random noise, presence of outliers in the measurements, uncertainty of the position of the magnetic topology, and missing measurements from damaged or unreliable bolometers. The study provides a comprehensive quantification of the uncertainties to associate with most typical emissivities encountered in practice and constitutes a good basis for a more accurate evaluation of the power balances on the JET. Published under license by AIP Publishing
Adaptive quasi-unsupervised detection of smoke plume by lidar
Full text linkThe early detection of fire is one of the possible applications of LiDAR techniques. The smoke generated by a fire is mainly compounded of CO2, H2O, particulate, and other combustion products, which involve the local variation of the scattering of the electromagnetic wave at specific wavelengths. The increases of the backscattering coefficient are transduced in peaks on the signal of the backscattering power recorded by the LiDAR system, located exactly where the smoke plume is, allowing not only the detection of a fire but also its localization. The signal processing of the LiDAR signals is critical in the determination of the performances of the fire detection. It is important that the sensitivity of the apparatus is high enough but also that the number of false alarms is small, in order to avoid the trigger of useless and expensive countermeasures. In this work, a new analysis method, based on an adaptive quasi-unsupervised approach was used to ensure that the algorithm is continuously updated to the boundary conditions of the system, such as the weather and experimental apparatus issues. The method has been tested on an experimental campaign of 227 pulses and the performances have been analyzed in terms of sensitivity and specificity
Detection of causal relations in time series affected by noise in tokamaks using geodesic distance on gaussian manifolds
No full textModern experiments in Magnetic Confinement Nuclear Fusion can produce Gigabytes of data, mainly in form of time series. The acquired signals, composing massive databases, are typically affected by significant levels of noise. The interpretation of the time series can therefore become quite involved, particularly when tenuous causal relations have to be investigated. In the last years, synchronization experiments, to control potentially dangerous instabilities, have become a subject of intensive research. Their interpretation requires quite delicate causality analysis. In this paper, the approach of Information Geometry is applied to the problem of assessing the effectiveness of synchronization experiments on JET (Joint European Torus). In particular, the use of the Geodesic Distance on Gaussian Manifolds is shown to improve the results of advanced techniques such as Recurrent Plots and Complex Networks, when the noise level is not negligible. In cases affected by particularly high levels of noise, compromising the traditional treatments, the use of the Geodesic Distance on Gaussian Manifolds allows deriving quite encouraging results. In addition to consolidating conclusions previously quite uncertain, it has been demonstrated that the proposed approach permit to successfully analyze signals of discharges which were otherwise unusable, therefore salvaging the interpretation of those experiments
A Model Falsification Approach to Learning in Non-Stationary Environments for Experimental Design
Full text linkThe application of data driven machine learning and advanced statistical tools to complex physics experiments, such as Magnetic Confinement Nuclear Fusion, can be problematic, due the varying conditions of the systems to be studied. In particular, new experiments have to be planned in unexplored regions of the operational space. As a consequence, care must be taken because the input quantities used to train and test the performance of the analysis tools are not necessarily sampled by the same probability distribution as in the final applications. The regressors and dependent variables cannot therefore be assumed to verify the i.i.d. (independent and identical distribution) hypothesis and learning has therefore to take place under non stationary conditions. In the present paper, a new data driven methodology is proposed to guide planning of experiments, to explore the operational space and to optimise performance. The approach is based on the falsification of existing models. The deployment of Symbolic Regression via Genetic Programming to the available data is used to identify a set of candidate models, using the method of the Pareto Frontier. The confidence intervals for the predictions of such models are then used to find the best region of the parameter space for their falsification, where the next set of experiments can be most profitably carried out. Extensive numerical tests and applications to the scaling laws in Tokamaks prove the viability of the proposed methodology
Maximum likelihood bolometric tomography for the determination of the uncertainties in the radiation emission on JET TOKAMAK
No full textThe total emission of radiation is a crucial quantity to calculate the power balances and to understand the physics of any Tokamak. Bolometric systems are the main tool to measure this important physical quantity through quite sophisticated tomographic inversion methods. On the Joint European Torus, the coverage of the bolometric diagnostic, due to the availability of basically only two projection angles, is quite limited, rendering the inversion a very ill-posed mathematical problem. A new approach, based on the maximum likelihood, has therefore been developed and implemented to alleviate one of the major weaknesses of traditional tomographic techniques: the difficulty to determine routinely the confidence intervals in the results. The method has been validated by numerical simulations with phantoms to assess the quality of the results and to optimise the configuration of the parameters for the main types of emissivity encountered experimentally. The typical levels of statistical errors, which may significantly influence the quality of the reconstructions, have been identified. The systematic tests with phantoms indicate that the errors in the reconstructions are quite limited and their effect on the total radiated power remains well below 10%. A comparison with other approaches to the inversion and to the regularization has also been performed
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