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New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing

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A special issue of Applied Sciences (ISSN 2076-3417).

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 17647

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Dr. Emmanuele Peluso

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Guest Editor

Department of Industrial Engineering, University of Rome “Tor Vergata”, via del Politecnico 1, 00133 Roma, Italy
Interests: magnetic-confinement fusion; scaling laws; confinement; inverse problems; plasma diagnostics; machine learning

Dr. Michela Gelfusa

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Guest Editor

Department of Industrial Engineering, University of Rome “Tor Vergata”, via del Politecnico 1, 00133 Roma, Italy
Interests: plasma diagnostics; inverse problems; data mining; time series analysis; genetic programming
Special Issues, Collections and Topics in MDPI journals

Dr. Ekaterina Pakhomova

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Guest Editor

Department of mechanical, chemical and materials engineering, University of Cagliari, via Marengo 2, 09123 Cagliari, Italy
Interests: plasma-facing materials; tungsten; plasma spraying; spark plasma sintering; functionally graded materials

Special Issue Information

Dear Colleagues,

A new and challenging period has recently started for the nuclear fusion community. In the new FP9 framework, we are called to provide, in the coming years, the physics and the engineering basis for the operational scenarios and exploitation of the next generation of magnetically controlled nuclear fusion devices, meaning for ITER and DEMO for the Tokamak community and HELIAS for the stellarator one. At the same time, the actual largest and most important tokamak in the world, JET, has approached a new T campaign, the first since 1997.

The already operational fusion reactors are nonlinear, complex and far from a stable equilibrium, with almost every physical parameter indirectly measured using a plethora of diagnostics. Routinely, they produce gigabytes of data that require dedicated storage systems and architectures. Modeling is a necessary step for the comprehension of the physical mechanism behind many experimental observations, but in many aspects, from control and classification to extrapolation and forecasting, statistical and machine learning approaches have been demonstrated to be fundamental.

In this multidisciplinary project, physical goals such as MHD and ELMs stable scenarios, disruption avoidance schemes based on verified chains of events, as well as the comprehension of the role of fast ions, impurities and isotopes mixtures on the plasma stability, regimes and transport are examples of open issues to be addressed in the coming years, in addition to managerial and engineering ones.

The design of diagnostics, control systems, international protocols and the quantification of costs have to be considered, but it is a matter of fact that the new generation of devices will be extremely challenging for materials.

Nuclear fusion reactors are extremely hostile environments for materials and plasma-facing components (PFC). ITER or DEMO will withstand severe steady-state thermal loads up to about 20 MW m⁻² combined with transient ones up to GW m⁻² due to edge-localized modes (ELMs). In addition, off-normal events such as the already cited disruptions or vertical displacement events (VDEs) could take place, compromising the mechanical integrity of the reactor. Thermally induced erosion of plasma-facing material (PFM) and damage of the joints between the PFM and the heat sink are to be considered; material irradiation with hydrogen isotope ions (D⁺ and T⁺) and impurities’ particles will create hydrogen-induced and neutron-induced degradation of the wall, transmutation, and activation. The appropriate choice of PFM, the design and the joining technique of PFC are a challenging issue for fusion reactors’ successful operation.

In this exciting framework, then, this issue calls for papers aimed at providing ideas, projects and discoveries elaborated in all the WP of the FP9 program to build the future and to stand as references for the coming years.

Contributions can be based on (but not limited to) the following fields:

Diagnostics: design, applications, and development (for example, microwaves and millimeter-wave diagnostics, infrared polarimetry/interferometry, spectroscopic and radiation measurements, neutron/gamma diagnostics, laser diagnostics);
Modeling;
Inverse problems (for example, tomography, equilibria reconstruction);
Data analysis and machine learning techniques;
Plasma facing materials: their behavior under steady-state and transient heat loads, irradiation effects, tritium retention, joining techniques, etc.;
Operational control scheme designs (for example, feedback and feedforward schemes);
Managerial protocol and cost evaluation.

Dr. Emmanuele Peluso
Dr. Michela Gelfusa
Dr. Ekaterina Pakhomova
Guest Editors

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Published Papers (10 papers)

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Editorial

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9 pages, 266 KiB

Open AccessEditorial

New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing

by Emmanuele Peluso, Ekaterina Pakhomova and Michela Gelfusa

Appl. Sci. 2023, 13(10), 6240; https://doi.org/10.3390/app13106240 - 19 May 2023

Cited by 2 | Viewed by 2233

Abstract

The 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”. Full article

(This article belongs to the Special Issue New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing)

Research

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20 pages, 3760 KiB

Open AccessArticle

Performance Comparison of Machine Learning Disruption Predictors at JET

by Enrico Aymerich, Barbara Cannas, Fabio Pisano, Giuliana Sias, Carlo Sozzi, Chris Stuart, Pedro Carvalho, Alessandra Fanni and the JET Contributors

Appl. Sci. 2023, 13(3), 2006; https://doi.org/10.3390/app13032006 - 3 Feb 2023

Cited by 5 | Viewed by 1839

Abstract

Reliable disruption prediction (DP) and disruption mitigation systems are considered unavoidable during international thermonuclear experimental reactor (ITER) operations and in the view of the next fusion reactors such as the DEMOnstration Power Plant (DEMO) and China Fusion Engineering Test Reactor (CFETR). In the last two decades, a great number of DP systems have been developed using data-driven methods. The performance of the DP models has been improved over the years both for a more appropriate choice of diagnostics and input features and for the availability of increasingly powerful data-driven modelling techniques. However, a direct comparison among the proposals has not yet been conducted. Such a comparison is mandatory, at least for the same device, to learn lessons from all these efforts and finally choose the best set of diagnostic signals and the best modelling approach. A first effort towards this goal is made in this paper, where different DP models will be compared using the same performance indices and the same device. In particular, the performance of a conventional Multilayer Perceptron Neural Network (MLP-NN) model is compared with those of two more sophisticated models, based on Generative Topographic Mapping (GTM) and Convolutional Neural Networks (CNN), on the same real time diagnostic signals from several experiments at the JET tokamak. The most common performance indices have been used to compare the different DP models and the results are deeply discussed. The comparison confirms the soundness of all the investigated machine learning approaches and the chosen diagnostics, enables us to highlight the pros and cons of each model, and helps to consciously choose the approach that best matches with the plasma protection needs. Full article

(This article belongs to the Special Issue New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing)

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40 pages, 20187 KiB

Open AccessArticle

Neutronics Assessment of the Spatial Distributions of the Nuclear Loads on the DEMO Divertor ITER-like Targets: Comparison between the WCLL and HCPB Blanket

by Simone Noce, Davide Flammini, Pasqualino Gaudio, Michela Gelfusa, Giuseppe Mazzone, Fabio Moro, Francesco Romanelli, Rosaria Villari and Jeong-Ha You

Appl. Sci. 2023, 13(3), 1715; https://doi.org/10.3390/app13031715 - 29 Jan 2023

Cited by 3 | Viewed by 1079

Abstract

The Plasma Facing Components (PFCs) of the divertor target contribute to the fundamental functions of heat removal and particle exhaust during fusion operation, being subjected to a very hostile and complex loading environment characterized by intense particles bombardment, high heat fluxes (HHF), varying stresses loads and a significant neutron irradiation. The development of a well-designed divertor target, which represents a crucial step in the realization of DEMO, needs the assessment of all these loads as accurately as possible, to provide pivotal data and indications for the design and structural performance prediction of the PFCs. In a particular way, this study is fully devoted to the comprehension of the distributions on the divertor target of the main nuclear loads due to neutron irradiation, performed for the first time using an extremely detailed approach. This work has been carried-out considering the latest configuration of the DEMO reactor, including the updated design of the divertor and ITER-Like PFCs geometry, varying the blanket layout (Water Cooled Lithium Lead—WCLL and Helium Cooled Pebble Bed—HCPB), thus evaluating the impact of the different blanket concept on the above-mentioned distributions. Neutronics analyses have been performed with MCNP5 Monte Carlo code and JEFF3.3 nuclear data libraries. 3D DEMO MCNP models have been created, focusing in particular on a thorough representation of the divertor and PFCs, allowing for the assessment of the distributions of the main nuclear loads: radiation damage (dpa/FPY), He-production rate (appm/FPY) and nuclear heating density (W/cm³) and total nuclear power deposition (MW). These results are presented by means of 2D maps and plots for each PFCs sub-component both for WCLL and HCPB blanket case: W-monoblocks, Cu-interlayers\CuCrZr-pipe and PFC-CB (Cassette Body) supports made of Eurofer steel. Full article

(This article belongs to the Special Issue New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing)

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15 pages, 6362 KiB

Open AccessArticle

Characterization of the Crack and Recrystallization of W/Cu Monoblocks of the Upper Divertor in EAST

by Ya Xi, Gaoyong He, Xiang Zan, Kang Wang, Dahuan Zhu, Laima Luo, Rui Ding and Yucheng Wu

Appl. Sci. 2023, 13(2), 745; https://doi.org/10.3390/app13020745 - 5 Jan 2023

Cited by 2 | Viewed by 1138

Abstract

The microstructure of and damage to the upper divertor components in EAST were characterized by using metallography, EBSD, and SEM. Under the synergistic effect of heat load and plasma irradiation, cracking, recrystallization, and interface debonding were found in the components of the upper divertor target. The crack propagates downward from the heat loading surface along the heat flux direction, and the crack propagation mode is an intergranular fracture. The thermal loads deposited on the edge of monoblocks raise the temperature higher than the recrystallization temperature of pure tungsten, and the microstructure changes from being in a rolled state to being recrystallized. Additionally, cracks exist in both recrystallized and rolled areas. EBSD boundary maps show that the range of the recrystallization area is determined via the heat flux distribution. The Cu/CuCrZr interface of the cooling components near the thermal loading area is debonded, and the structural integrity is destroyed. Full article

(This article belongs to the Special Issue New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing)

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23 pages, 1389 KiB

Open AccessArticle

Engineering of a FGM Interlayer to Reduce the Thermal Stresses Inside the PFCs

by Giacomo Dose, Selanna Roccella and Francesco Romanelli

Appl. Sci. 2022, 12(20), 10215; https://doi.org/10.3390/app122010215 - 11 Oct 2022

Cited by 3 | Viewed by 1084

Abstract

A substantial contribution of the stresses that arise inside the Plasma-Facing Components (PFCs) when a heat load is applied is caused by the mismatch of the Coefficient of Thermal Expansion (CTE) between the armor, usually made of tungsten (W), and the heat sink. A potential way to reduce such contribution to the secondary stresses is the use of an interlayer made with a Functionally Graded Material (FGM), to be interposed between the two sub-components. By tailoring the W concentration in the volume of the FGM, one can engineer the CTE in such a way that the thermal stresses are reduced inside the PFC. To minimize and, theoretically, reduce to zero the stresses due to the CTE mismatch, the FGM should ensure kinematic continuity between the armor and the heat sink, in a configuration where they deform into exactly the shape they would assume if they were detached from each other. We will show how this condition occurs when the mean thermal strain of each sub-component is the same. This work provides a methodology to determine the thickness and the spatial concentration function of the FGM able to ensure the necessary kinematic continuity between the two sub-components subjected to a generic temperature field monotonously varying in the thickness, while remaining stress-free itself. A method for the stratification of such ideal FGM is also presented. Additionally, it will be shown that the bending of the PFC, if allowed by the kinematic boundary conditions, does not permit, at least generally, the coupling of the expansion of the armor and of the heat sink. As an example of our methodology, a study case of the thermomechanical design of a steel-based PFC with an engineered W/steel FGM interlayer is presented. In such an exercise, we show that our procedure of engineering a FGM interlayer is able to reduce the linearized secondary stress of more than 24% in the most critical section of the heat sink, satisfying all the design criteria. Full article

(This article belongs to the Special Issue New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing)

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14 pages, 5824 KiB

Open AccessArticle

Acceleration of an Algorithm Based on the Maximum Likelihood Bolometric Tomography for the Determination of Uncertainties in the Radiation Emission on JET Using Heterogeneous Platforms

by Mariano Ruiz, Julián Nieto, Víctor Costa, Teddy Craciunescu, Emmanuele Peluso, Jesús Vega, Andrea Murari and JET Contributors

Appl. Sci. 2022, 12(13), 6798; https://doi.org/10.3390/app12136798 - 5 Jul 2022

Cited by 7 | Viewed by 1366

Abstract

In recent years, a new tomographic inversion method based on the Maximum Likelihood (ML) approach has been adapted to JET bolometry. Apart from its accuracy and reliability, the key advantage is its ability to provide reliable estimates of the uncertainties in the reconstructions. The original algorithm was implemented and validated using the MATLAB software tool. This work presents the accelerated version of the algorithm implemented using a compatible ITER fast controller platform with the Ubuntu 18.04 or the ITER Codac Core System distributions (6.1.2). The algorithm has been implemented in C++ using the open-source libraries: ArrayFire, ALGLIB, and MATIO. These libraries simplify the management of specific hardware accelerators such as GPUs and increase performance. The speed-up factor obtained is approximately 10 times. The work presents the methodology followed, the results obtained, and the advantages and drawbacks of implementation. Full article

(This article belongs to the Special Issue New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing)

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17 pages, 4115 KiB

Open AccessArticle

An Unsupervised Spectrogram Cross-Correlation Method to Assess ELM Triggering Efficiency by Pellets

by Riccardo Rossi, Silvia Cesaroni, Francesca Bombarda, Pasquale Gaudio, Michela Gelfusa, Marco Marinelli, Gianluca Verona Rinati, Emmanuele Peluso and JET Contributors

Appl. Sci. 2022, 12(7), 3681; https://doi.org/10.3390/app12073681 - 6 Apr 2022

Cited by 2 | Viewed by 1708

Abstract

The high confinement mode (H-mode) is considered the optimal regime for the production of energy through nuclear fusion for industrial purposes since it allows to increase the energy confinement time of the plasma roughly by a factor of two. Consequently, it has been selected at the moment as the standard scenario for the next generation of devices, such as ITER. However, pressure-driven edge instabilities, known as edge localized modes (ELMs), are a distinct feature of this plasma regime. Their extrapolated thermal and particle peak loads on the plasma-facing components (PFC) of the next generation of devices are expected to be so high as to damage such structures, compromising the normal operations of the reactors themselves. Consequently, the induced loads have to be controlled; this can be achieved by mitigating ELMs. A possibility then lays in increasing the ELMs frequency to lower the loads on the PFCs. As already demonstrated at JET, the pellet pacing of ELMs is considered one of the most promising techniques for such scope, and its optimization is therefore of great interest for present and future operations of nuclear fusion facilities. In this work, we suggest a method to access primary pieces of information to perform statistics, assess and characterize the pacing efficiency. The method, tested on JET data, is based on the clustering (k-means) of convoluted signals, using so-called spectrogram cross-correlation, between the measured pellets and ELMs time traces. Results have also been obtained by taking advantage of a new type of diagnostic for measuring the ELMs dynamic, based on synthetic diamond sensors, faster than the standard spectroscopic cameras used at JET. Full article

(This article belongs to the Special Issue New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing)

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20 pages, 4578 KiB

Open AccessArticle

Considerations on Stellarator’s Optimization from the Perspective of the Energy Confinement Time Scaling Laws

by Andrea Murari, Emmanuele Peluso, Luca Spolladore, Jesus Vega and Michela Gelfusa

Appl. Sci. 2022, 12(6), 2862; https://doi.org/10.3390/app12062862 - 10 Mar 2022

Cited by 1 | Viewed by 1797

Abstract

The Stellarator is a magnetic configuration considered a realistic candidate for a future thermonuclear fusion commercial reactor. The most widely accepted scaling law of the energy confinement time for the Stellarator is the ISS04, which employs a renormalisation factor, f_ren, specific to each device and each level of optimisation for individual machines. The f_ren coefficient is believed to account for higher order effects not ascribable to variations in the 0D quantities, the only ones included in the database used to derive ISS04, the International Stellarator Confinement database. This hypothesis is put to the test with symbolic regression, which allows relaxing the assumption that the scaling laws must be in power monomial form. Specific and more general scaling laws for the different magnetic configurations have been identified and perform better than ISS04, even without relying on any renormalisation factor. The proposed new scalings typically present a coefficient of determination R² around 0.9, which indicates that they basically exploit all the information included in the database. More importantly, the different optimisation levels are correctly reproduced and can be traced back to variations in the 0D quantities. These results indicate that f_ren is not indispensable to interpret the data because the different levels of optimisation leave clear signatures in the 0D quantities. Moreover, the main mechanism dominating transport, in reasonably optimised configurations, is expected to be turbulence, confirmed by a comparative analysis of the Tokamak in L mode, which shows very similar values of the energy confinement time. Not resorting to any renormalisation factor, the new scaling laws can also be extrapolated to the parameter regions of the most important reactor designs available. Full article

(This article belongs to the Special Issue New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing)

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15 pages, 4042 KiB

Open AccessArticle

Grain Orientation and Hardness in the Graded Interlayer of Plasma Sprayed W on CuCrZr

by Marcello Cabibbo, Alessandra Fava, Roberto Montanari, Ekaterina Pakhomova, Chiara Paoletti, Maria Richetta and Alessandra Varone

Appl. Sci. 2022, 12(4), 1822; https://doi.org/10.3390/app12041822 - 10 Feb 2022

Cited by 1 | Viewed by 1567

Abstract

In this work a W coating was deposited through PS in Ar-H₂ atmosphere on a substrate of CuCrZr with an interlayer consisting of gradually changing fractions of Cu and W. The W coating and the interlayer showed good adhesion and no cracks were observed. The hardness of W and Cu along the interlayer was determined by nano-indentation tests and the results showed that a hardness gradient does exist in both the metals. Microstructural examinations suggest that the hardness gradient depends on the texture, which exhibits significant differences along the interlayer: multiplication and movement of dislocations, and localized plasticity under the indenting tip are strongly affected by grain orientation. Full article

(This article belongs to the Special Issue New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing)

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17 pages, 9154 KiB

Open AccessArticle

Grain Refinement and Improved Mechanical Properties of EUROFER97 by Thermo-Mechanical Treatments

by Giulia Stornelli, Andrea Di Schino, Silvia Mancini, Roberto Montanari, Claudio Testani and Alessandra Varone

Appl. Sci. 2021, 11(22), 10598; https://doi.org/10.3390/app112210598 - 11 Nov 2021

Cited by 25 | Viewed by 2220

Abstract

EUROFER97 steel plates for nuclear fusion applications are usually manufactured by hot rolling and subsequent heat treatments: (1) austenitization at 980 °C for 30 min, (2) rapid cooling and (3) tempering at 760 °C for 90 min. An extended experimental campaign was carried out with the scope of improving the strength of the steel without a loss of ductility. Forty groups of samples were prepared by combining cold rolling with five cold reduction ratios (20, 40, 50, 60 and 80%) and heat treatments at eight different temperatures in the range 400–750 °C (steps of 50 °C). This work reports preliminary results regarding the microstructure and mechanical properties of all the cold-rolled samples and the effects of heat treatments on the samples deformed with the greater CR ratio (80%). The strength of deformed samples decreased as heat treatment temperature increased and the change was more pronounced in the samples cold-rolled with greater CR ratios. After heat treatments at temperature up to 600 °C yield stress (YS) and ultimate tensile strength (UTS) of samples deformed with CR ratio of 80% were significantly larger than those of standard EUROFER97 but ductility was lower. On the contrary, the treatment at 650 °C produced a fully recrystallized structure with sub-micrometric grains which guarantees higher strength and comparable ductility. The work demonstrated that EUROFER97 steel can be strengthened without compromising its ductility; the most effective process parameters will be identified by completing the analyses on all the prepared samples. Full article

(This article belongs to the Special Issue New Challenges in Nuclear Fusion Reactors: From Data Analysis to Materials and Manufacturing)

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