Fusion Energy Research Articles

Parametric dependencies of ion temperature profile peaking in ASDEX Upgrade high-beta scenarios

Abstract Advanced Tokamak (AT) scenarios are attractive candidates for future nuclear fusion power plants. These scenarios often feature peaked temperature profiles, suggesting a local reduction of turbulent transport. The mechanisms behind this are, as yet, not fully understood. Parameters that are thought to be connected to these transport reductions include the q-profile and the ExB-shear ωExB. Another parameter considered to be important is the fast ion content, which can reduce transport in multiple different ways.
This work presents AT experiments performed at the ASDEX Upgrade tokamak (AUG) in which these three parameters are varied to investigate their respective effect on the observed peaked ion temperature profiles. To disentangle potentially competing effects, simulations using the codes GENE and TGLF have been performed. It is found that the ExB-shear does not play a role in the AT scenarios performed at AUG, which have relatively low rotation, with vtor=100-250km/h. Experimentally, a significant dependence of R/LTi on the electron cyclotron current drive (ECCD) settings was found, indicating that either the current profile (and, therefore, the q-profile) or Te/Ti has a significant impact on the observed suppression of turbulent transport. In support of the first option, both GENE and TGLF show a q-profile dependence of R/LTi. Furthermore, according to GENE, electromagnetic (EM) fast ion effects are essential in reproducing the experimental results. Scans with TGLF (which does not include such effects), suggest that these fast ion effects become relevant above a threshold of R/LTi= 4-5. In the presence of ICRF, additional electrostatic (ES) fast ion effects seem to come into effect, according to GENE, albeit to a smaller degree than the EM effects.

Classical-quantum simulation of non-equilibrium Marshak waves

In the radiation hydrodynamic simulations used to design inertial confinement fusion (ICF) and pulsed power experiments, nonlinear radiation diffusion tends to dominate CPU time. This raises the interesting question of whether a quantum algorithm can be found for nonlinear radiation diffusion which provides a quantum speedup. Recently, such a quantum algorithm was introduced based on a quantum algorithm for solving systems of nonlinear partial differential equations (PDEs) which provides a quadratic quantum speedup. Here, we apply this quantum PDE (QPDE) algorithm to the problem of a non-equilibrium Marshak wave propagating through a cold, semi-infinite, optically thick target, where the radiation and matter fields are not assumed to be in local thermodynamic equilibrium. The dynamics is governed by a coupled pair of nonlinear PDEs which are solved using the QPDE algorithm, as well as two standard PDE solvers: (i) Python's py-pde solver; and (ii) the KULL ICF simulation code developed at Lawrence-Livermore National Laboratory. We compare the simulation results obtained using the QPDE algorithm and the standard PDE solvers and find excellent agreement.

Prediction of performance and turbulence in ITER burning plasmas via nonlinear gyrokinetic profile prediction

Abstract Burning plasma performance, transport, and the effect of hydrogen isotope (H, D, D-T fuel mix) on confinement has been predicted for ITER baseline scenario (IBS) conditions using nonlinear gyrokinetic profile predictions. Accelerated by surrogate modeling (Rodriguez-Fernandez et al 2022 Nucl. Fusion 62 076036), high fidelity, nonlinear gyrokinetic simulations performed with the CGYRO code (Candy et al 2016 J. Comput. Phys. 324 73), were used to predict profiles of Ti , Te , and ne while including the effects of alpha heating, auxiliary power (NBI + ECH), collisional energy exchange, and radiation losses inside of r / a = 0.9. Predicted profiles and resulting energy confinement are found to produce fusion power and gain that are approximately consistent with mission goals ( P fusion = 500 MW at Q = 10) for the baseline scenario and exhibit energy confinement that is within 1σ of the H-mode energy confinement scaling. The power of the surrogate modeling technique is demonstrated through the prediction of alternative ITER scenarios with reduced computational cost. These scenarios include conditions with maximized fusion gain and an investigation of potential resonant magnetic perturbation (RMP) effects on performance with a minimal number of gyrokinetic profile iterations required (3–6). These predictions highlight the stiff ITG nature of the core turbulence predicted in the ITER baseline and demonstrate that Q > 17 conditions may be accessible by reducing auxiliary input power while operating in IBS conditions. Prediction of full kinetic profiles allowed for the projection of hydrogen isotope effects around ITER baseline conditions. The gyrokinetic fuel ion species was varied from H, D, and 50/50 D-T and kinetic profiles were predicted. Results indicate that a weak or negligible isotope effect will be observed to arise from core turbulence in IBS conditions. The resulting energy confinement, turbulence, and density peaking, and the implications for ITER operations will be discussed.

Heterogeneous Online Computational Platform for GEM-Based Plasma Impurity Monitoring Systems

The fusion energy research field presents many intricate challenges that require resolution. Many diagnostic systems employed in experiments are approaching the limits of current technology. Implementing efficient measurements requires using an appropriate set of tools to facilitate the optimal utilization of hardware. Fusion energy measurements must provide low latency processing with the capacity for future improvements and the ability to handle complex data flows efficiently. The presented work addresses these requirements and describes the implementation of a high-performance, low-latency software platform with convenient development for soft X-ray (SXR) plasma impurities emission tracing—the Asynchronous Complex Computation Platform (AC2P). This article presents the architectural design, implementation details, and performance and latency measurements based on the raw data acquired from the WEST tokamak and laboratory tests. AC2P provides the tools to develop low-latency, multi-core, multi-device complex data flow graph scale-up solutions for measuring impurities in hot plasmas. The system has been designed to operate online during experiments, calculate the energy distribution, position and occurrence time of SXR photons, monitor the data stream’s quality and archive any abnormalities for subsequent offline verification and algorithm improvement. This article presents AC2P, which operates as part of the SXR measurement system on the WEST tokamak.

Commentary on ‘the interplay of the innovation cycle, build time, lifetime, and deployment rate of new energy technologies: a case study of nuclear fusion energy’ - designing innovation strategies for rapid feasible technological change

Commentary on ‘the interplay of the innovation cycle, build time, lifetime, and deployment rate of new energy technologies: a case study of nuclear fusion energy’ - designing innovation strategies for rapid feasible technological change

Prediction of laser beam spatial profiles in a high-energy laser facility by use of deep learning

We adapt the significant advances achieved recently in the field of generative artificial intelligence/machine-learning to laser performance modeling in multipass, high-energy laser systems with application to high-shot-rate facilities relevant to inertial fusion energy. Advantages of neural-network architectures include rapid prediction capability, data-driven processing, and the possibility to implement such architectures within future low-latency, low-power consumption photonic networks. Four models were investigated that differed in their generator loss functions and utilized the U-Net encoder/decoder architecture with either a reconstruction loss alone or combined with an adversarial network loss. We achieved inference times of 1.3 ms for a 256 × 256 pixel near-field beam with errors in predicted energy of the order of 1% over most of the energy range. It is shown that prediction errors are significantly reduced by ensemble averaging the models with different weight initializations. These results suggest that including the temporal dimension in such models may provide accurate, real-time spatiotemporal predictions of laser performance in high-shot-rate laser systems.

Reply to commentary on ‘the interplay of the innovation cycle, build time, lifetime, and deployment rate of new energy technologies: a case study of nuclear fusion energy’

Reply to commentary on ‘the interplay of the innovation cycle, build time, lifetime, and deployment rate of new energy technologies: a case study of nuclear fusion energy’

An overview of the fusion landscape

ABSTRACT Fusion is very attractive as a potential energy source, but it is taking a long time to develop into a commercial reality. Given the challenges of climate change and the need for dispatchable power as a complement to renewable energy sources that vary on daily and seasonal timescales, there is great enthusiasm internationally to accelerate the commercialization of fusion energy. Forty-five private companies around the globe, with total financing of $7.1 billion, are engaged in the development of fusion energy. In the United States, the White House has put forward a “Bold Decadal Vision for Commercial Fusion Energy,” with bipartisan support from Congress. To develop commercial fusion energy, certain goals must be met. A wide variety of approaches are being pursued to meet these goals.

Machine learning powered predictive modelling of complex residual stress for nuclear fusion reactor design

Fusion In-vessel components, assembled and maintained using laser welding, one of the most promising techniques, exhibit complex distributions of residual stress, microstructures, and material properties. These residual stresses can compromise structural integrity and lifespan of critical components. Although using advanced experimental measurements can evaluate the residual stress for individual case, extending the measurements to massive number of components are costly and time-consuming. Traditional machine learning (ML) models struggle to account for the heterogeneity and anisotropy of these stress distributions. Here, we develop a novel ML framework based on the Eurofer97 steel, the structural material for in-vessel components. The ML framework is trained on high-resolution residual stress data derived from recently-developed evaluation techniques. Combining with microstructures, the model enables prediction of heterogenous and anisotropic residual stress distribution. It successfully predicts the compressive residual stress in fusion zone (∼−200 MPa) balanced by tensile residual stress in heat affected zone (∼300 MPa), aligning closely with experimental results with the R-squared value of 0.989 and the mean square error of 10−4. Unlike experiments that take hours, the ML model provides predictions within seconds. It offers valuable insights into residual stress prediction for various joints, enhancing the reliability and lifetime prediction of in-vessel components.

Fusion power: The uncertain certainty

ABSTRACT Fusion will be and needs to be achieved. But when? Its primary fuel, deuterium, exists in sufficient quantity to satisfy any conceivable energy demands for thousands of millions of years. The cost of obtaining it from water is less than one per cent the present cost of coal. Is fusion power a distant dream or a near-term possibility? The first applications could come in the 1980s. Richard F. Post, a physicist, is head of the magnetic mirror program in controlled thermonuclear research at the Lawrence Radiation Laboratory, Livermore, California. This report on progress in fusion research was adapted from his presentation on April 26, 1971 to the National Academy of Sciences Symposium on “Energy for the Future.”

The fuel supply quandary of fusion power reactors

ABSTRACT Concern about adequate tritium resources to start up deuterium-tritium (DT) fusion reactors in the near term is misplaced: Proposed demonstration reactors and pilot plants will not realistically be buildable for a great many decades. More disturbing, tritium fuel self-sufficiency of eventual DT reactors may be unattainable, because it is unlikely that tritium-breeding blankets can completely replenish burned-up fuel as well as unburned tritium that is lost in numerous reactor subsystems. The concept of doubling time is unworkable. The only viable fuel solution for sustained operation demands deuterium-based reactors where the tritium is concurrently generated and burned up in the fusioning plasma.

The entanglement of fusion energy research and bombs

ABSTRACT The recent achievement of fusion ignition—meaning more energy came out of a self-sustaining fusion reaction than was put in—at Lawrence Livermore National Laboratory’s National Ignition Facility has brought to the fore long-simmering questions about whether certain experiments violate the Comprehensive Test Ban Treaty on nuclear explosions. Fusion research for peaceful use and military use are highly intertwined, despite attempts to cloak nuclear weapons with the aura of the so-called “peaceful atom.” Ignition has been achieved, but there is still a remarkable silence around whether pure fusion weapons—weapons that could kill large numbers of humans with neutron radiation but have blast effects much smaller than current thermonuclear weapons—are an objective of the overall program. Even if not an explicit objective, would they be built if fusion technology makes them feasible?

GALADRIEL: A facility for advancing engineering science relevant to rep-rated high energy density physics and inertial fusion energy experiments.

Many current and upcoming laser facilities used to study high-energy-density (HED) physics and inertial fusion energy (IFE) support operating at high rep-rates (HRRs) of ∼0.1-10Hz, yet many diagnostics, target-fielding strategies, and data storage methods cannot support this pace of operation. Therefore, established experimental paradigms must change for the community to progress toward rep-rated operation. To this end, we introduce the General Atomics LAboratory for Developing Rep-rated Instrumentation and Experiments with Lasers, or GALADRIEL, to serve as a test bed for developing and benchmarking the engineering science advancements required for HRR experiments. GALADRIEL was constructed from the ground up around a commercial 1TW (∼25 mJ in ∼25fs at 800nm) laser with diverse experimental applications in mind. Assembly of the basic framework of GALADRIEL concluded with commissioning shots generating ∼1-4MeV electrons via laser-wakefield acceleration (LWFA) using a nitrogen gas jet. Subsequent LWFA experiments operated at 1Hz, utilized instrument feedback for optimization, and stored all data in a custom-built NoSQL database system. From this database called MORIA, or the MOngodb Repository for Information Archiving, data are retrievable via individual files or en masse by query requests defined by the user. GALADRIEL focuses on outstanding questions in engineering science, including targetry, diagnostics, data handling, environmental and materials studies, analysis and machine learning algorithm development, and feedback control systems. GALADRIEL fills a niche presently missing in the US-based user-facility community by providing a flexible experimental platform to address problems in engineering science relevant to rep-rated HED and IFE experiments.

Microstructure Refinement of Bulk Inconel 718 Parts During Fabrication with EB-PBF Using Scanning Strategies: Transition from Bidirectional-Raster to Stochastic Point-Based Melting

Inconel 718 is a widely popular aerospace superalloy known for its high-temperature performance and resistance to oxidation, creep, and corrosion. Traditional manufacturing methods, like casting and powder metallurgy, face challenges with intricate shapes that can result in porosity and uniformity issues. On the other hand, Additive Manufacturing (AM) techniques such as Powder Bed Fusion (PBF) and Direct Energy Deposition (DED) can allow the creation of intricate single-part components to reduce weight and maintain structural integrity. However, AM parts often exhibit directional solidification, leading to anisotropic properties and potential crack propagation sites. To address this, post-processing treatments like HIP and heat treatment are necessary. This study explores the effects of the raster and stochastic spot melt scanning strategies on the microstructural and mechanical properties of IN718 parts fabricated using Electron Beam Powder Bed Fusion (EB-PBF). This research demonstrates that raster scanning produces columnar grains with higher mean aspect ratios. Stochastic spot melt scanning facilitates the formation of equiaxed grains, which enhances microstructural refinement and lowers anisotropy. The highest microstructural values were recorded in the raster-produced columnar grain structure. Conversely, the stochastic melt-produced transition from columnar to equiaxed grain structure demonstrated increased hardness with decreasing grain size; however, the hardness of the smallest equiaxed grain structure was slightly less than that of the columnar grain structure. These findings underscore the vital importance of scanning strategies in optimizing the EB-PBF process to enhance material properties.

Comprehensive Screening of Plasma-Facing Materials for Nuclear Fusion

Plasma-facing materials (PFMs) represent one of the most significant challenges for the design of future nuclear fusion reactors. Inside the reactor, the divertor will experience the harshest material environment: intense bombardment of neutrons and plasma particles coupled with extremely large and intermittent heat fluxes. The material designated to cover this role in ITER is tungsten. While no other materials have shown the potential to match the properties of tungsten, many drawbacks associated with its application remain, including cracking and erosion induced by a low recrystallization temperature combined with a high ductile-brittle transition temperature and neutron-initiated embrittlement; surface morphology changes (helium bubbles and fuzz layer) due to plasma-tungsten interaction with subsequent risk of spontaneous material melting and delamination; and low oxidation resistance in the case of air contamination. Exploring alternatives to tungsten requires the design of a multivariable optimization problem. This work aims to produce a structured and comprehensive material screening of PFM candidates based on known inorganic materials. The method applied in this study to identify the most promising PFM candidates combines peer-reviewed data present in the PAULING FILE database and first-principles density-function theory calculations focusing on two key PFM defects—namely, the sputtering of surface atoms and the incorporation of interstitial hydrogen, respectively characterized by the surface binding energy and the interstitial formation energy. The crystal structures and their related properties, extracted from the PAULING FILE, are ranked according to the heat-balance equation of a PFM subjected to the heat loads in the divertor region of an ITER-like tokamak. The materials satisfying the requirements are critically compared with the state-of-the-art in plasma-facing materials research and in studies of refractory materials exposed to high temperatures, plasma, and neutron bombardment. This comparison assesses their thermo-mechanical properties under such conditions, identifying a subset of promising materials for first-principles electronic structure calculations. Most previously known and extensively studied PFMs, such as tungsten, molybdenum, and carbon-based materials, are captured by this screening process, confirming its reliability. Additionally, less familiar refractory materials suggest performance that calls for further investigations. Published by the American Physical Society 2024

Observation of magnetic islands in tokamak plasmas during the suppression of edge-localized modes

AbstractIn tokamaks, a leading platform for fusion energy, periodic filamentary plasma eruptions known as edge-localized modes occur in plasmas with high-energy confinement and steep pressure profiles at the plasma edge. These edge-localized modes could damage the tokamak wall but can be suppressed using small three-dimensional magnetic perturbations. Here we demonstrate that these magnetic perturbations can change the magnetic topology just inside the steep gradient region of the plasma edge. We identify signatures of a magnetic island, and their observation is linked to the suppression of edge-localized modes. We compare high-resolution measurements of perturbed magnetic surfaces with predictions from ideal magnetohydrodynamic theory where the magnetic topology is preserved. Although ideal magnetohydrodynamics adequately describes the measurements in plasmas exhibiting edge-localized modes, it proves insufficient for plasmas where these modes are suppressed. Nonlinear resistive magnetohydrodynamic modelling supports this observation. Our study experimentally confirms the predicted role of magnetic islands in inhibiting the occurrence of edge-localized modes. This will be beneficial for physics-based predictions in future fusion devices to control these modes.

How the Exascale Computing Project and Private Magnetic Fusion Research Stimulated Each Other

We provide a brief summary and comments on how we utilized the Exascale Computing Project (ECP) supercomputing resources for the development of the frontal research of nuclear fusion reactor development. In turn, our demand and use helped stimulate the ECP hardware and software, and our project to tackle real-world simulation of fusion experiments has stimulated the ECP and its development. We posit that thus the legacy of the ECP is important and useful and that it will continue to have a growing impact on scientific progress.

A Review of the Sustainability of Helium: An Assessment of Its Past, Present and a Zero-Carbon Future

Helium, as a by-product of the natural gas industry, will be impacted by the decline in consumption of fossil fuels as the world moves towards net-zero carbon emissions. In September 2022, all assets relating to the US government’s previous helium industry were sold. In the US, helium is now only available from private suppliers. In June 2022, Russia banned the export of helium to “unfriendly” countries, highlighting the geopolitical issues surrounding the industry. In the past, helium was popularized, and the industry was supported by its military applications (filling dirigible aircraft, welding fighter jets and purging rocket engines). It also plays an important role in supporting present-day technologies (e.g., MRI machines and spectroscopy) and will also be important for a high-tech future (e.g., in quantum computing, fusion power, and space exploration). Shortages of helium will inevitably cause skyrocketing prices and consequently lead to significant challenges for research and development (as has happened in the past) and technological progress, as well as a slowdown in world economic growth and prosperity. Anticipated declines in natural gas production, associated with moves towards net-zero carbon emissions targets, make helium less accessible. While this is problematic for industry in the short term, it perhaps preserves some low entropy helium within the ground, making it more accessible to future generations. Given anticipated limitations to the future supply of helium, technological developments are currently focused on a few areas: the replacement of helium by other gases in industrial applications, changing technological approaches to not require helium, and reducing the cost of obtaining helium from the atmosphere. This paper explores the past, present and future of helium, focusing on the sustainability of the helium industry.

Deutelio approach to fusion energy with the Polomac

Deutelio is a private initiative promoting an alternative path to fusion energy. The Tokamak research line pursued worldwide since 1970 met several difficulties, heavily jeopardising the objective of commercial energy production from fusion before 2050, as a support to the global effort towards Net Zero Emissions. As a result, new plasma magnetic confinement concepts, such as Stellarators or overlooked alternatives like the poloidal confinement are being pursued to achieve more efficiency and better performance. The Polomac is a poloidal magnetic configuration where the outboard magnetic lines are deviated aside together with the plasma, to open some accesses to the dipole coils located inside the plasma. These accesses, called magnetic tunnels, are used to support, feed and cool the dipole coil. They avoid the impact with plasma which led to abandon past poloidal experiments, despite their good stability and confinement efficiency. The poloidal confinement can achieve Deuterium-Tritium reactor conditions with a magnetic field 3 times weaker than the Tokamak, in steady state rather than pulsed. With the same high field as in the Tokamak the poloidal confinement can achieve Deuterium-Deuterium reaction, thus avoiding the development of the breeding blanket to produce the Tritium. This paper presents the Polomac system, explains the development strategy of Deutelio through a small prototype focused to tune and assess the magnetic tunnels, and describes the possibility of deuterium-deuterium reaction.

A First-Principles Study of the Structural and Thermo-Mechanical Properties of Tungsten-Based Plasma-Facing Materials

Tungsten (W) and tungsten alloys are being considered as leading candidates for structural and functional materials in future fusion energy devices. The most attractive properties of tungsten for the design of magnetic and inertial fusion energy reactors are its high melting point, high thermal conductivity, low sputtering yield, and low long-term disposal radioactive footprint. Despite these relevant features, there is a lack of understanding of how the structural and mechanical properties of W-based alloys are affected by the temperature in fusion power plants. In this work, we present a study on the thermo-mechanical properties of five W-based plasma-facing materials. First-principles density functional theory (DFT) calculations are combined with the quasi-harmonic approximation (QHA) theory to investigate the electronic, structural, mechanical, and thermal properties of these W-based alloys as a function of temperature. The coefficient of thermal expansion, temperature-dependent elastic constants, and several elastic parameters, including bulk and Young’s modulus, are calculated. Our work advances the understanding of the structural and thermo-mechanical behavior of W-based materials, thus providing insights into the design and selection of candidate plasma-facing materials in fusion energy devices.