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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Predictive Self-Healing Seals for Gas Transmission

Damaged elastomeric diaphragms within pneumatic controllers used in the oil and gas industry lead to an unintended release of methane. Self-healing microvascular materials capable of healing various types of damage have been fabricated. These microvascular materials are designed to replace currently available commercial diaphragms found in pneumatic controllers and provide a solution to reduce unintended methane leaks. This project demonstrated the ability of these materials to reduce methane release by more than 80% in lab and pilot settings. Additionally, ML approaches successfully identified leaking systems based on training using synthetic and real data.

03 NATURAL GAS↗
DOE OSTI2021

Modeling Coupled Chemo-Mechanical Behavior of Randomly Oriented NMC811 Polycrystalline Li-Ion Battery Cathodes

This paper develops a three-dimensional, transient, chemo-mechanical model that predicts the performance of single secondary particle Li-ion battery cathodes. The secondary particles are composed of numerous (approximately 60) randomly oriented single-crystal primary particles. The model incorporates concentration-dependent and anisotropic material properties. As much as possible, electrochemical, transport, and structural properties for crystalline NMC811 (Li x Ni 0.8 Mn 0.1 Co 0.1 O 2 ) are taken from prior publications. Weak Van der Waals bonding between primary particles is modeled empirically using a spring analogy, which enables local primary-particle separations (disintegration) and subsequent reattachments. The model fully couples Li diffusion and the mechanical response. Results include predictions of local Li-concentrations and stresses. High stresses are found near grain boundaries, especially when the lattice orientations are greatly misaligned. Particle separations are characterized in terms of a damage parameter. The model is used to predict the effects of design and operating conditions, including charge/discharge rates, cycling scenarios, and particle sizes.

25 ENERGY STORAGE↗
DOE OSTI2025

An FFT-based micromechanical model for gradient enhanced brittle fracture

Damage models incorporated within FFT-based micromechanical methods have received much attention recently because of the need to better understand and predict brittle and ductile fracture. An important aspect of a damage model is non-local regularization, which removes the mesh dependence of the predictions that otherwise become physically unacceptable upon grid refinement. In this work, the Helmholtz-type equation for non-local gradient regularization of a damage model on a distorted grid is solved using an FFT-based approach. Further, the resulting system of equations is solved using the Jacobi iterative method. The model is applied to simulate brittle fracture of an intermetallic. The influence of the time and space discretization, the length-scale parameter, and intermetallic crystallographic orientation on crack evolution is studied.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scenario adaptive disruption prediction study for next generation burning-plasma tokamaks

Next generation High Performance (HP) tokamaks risk damage from unmitigated disruptions at high current and power. Achieving reliable disruption prediction for a device's HP operation based on its Low Performance (LP) data is a key to its success. In this letter, through explorative data analysis and dedicated numerical experiments on multiple existing tokamaks, we demonstrate how the operational regimes of tokamaks can affect the power of a trained disruption predictor. First, our results suggest data-driven disruption predictors trained on abundant LP discharges work poorly on the HP regime of the same tokamak, which is a consequence of the distinct distributions of the tightly correlated signals related to disruptions in these two regimes. Second, we find that matching operational parameters among tokamaks strongly improves cross-machine accuracy which implies our model learns from the underlying scalings of dimensionless physics parameters like q 95 , β p and confirms the importance of these parameters in disruption physics and cross machine domain matching from the data-driven perspective. Finally, our results show in the absence of HP data from the target devices, the best predictivity of the HP regime for the target machine can be achieved by combining LP data from the target with HP data from other machines. Furthermore, these results provide a possible disruption predictor development strategy for next generation tokamaks, such as ITER and SPARC, and highlight the importance of developing baseline scenario discharges of future tokamaks on existing machines to collect more relevant disruptive data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

ACCELERATED CREEP TEST (ACT) QUALIFICATION OF CREEP RESISTANCE USING THE WCS CONSTITUTIVE MODEL AND STEPPED ISOSTRESS METHOD (SSM)

In this study, a qualification of accelerated creep-resistance of Inconel 718 is assessed using the novel Wilshire-Cano-Stewart (WCS) model and the stepped isostress method (SSM) and predictions are made to conventional creep data. Conventional creep testing (CCT) is a long-term continuous process, in fact, the ASME B&PV III requires that 10,000+ hours of experiments must be conducted to each heat for materials employed in boilers and/or pressure vessel components. This process is costly and not feasible for rapid development of new materials. As an alternative, accelerated creep testing techniques have been developed to reduce the time needed to characterize the creep resistance of materials. Most techniques are based upon the time-temperature-stress superposition principle (TTSSP) that predicts minimum-creep-strain-rate (MCSR) and stress-rupture behaviors but lack the ability to predict creep deformation and consider deformation mechanisms that occur for experiments of longer duration. The stepped isostress method (SSM) has been developed which enables the prediction of creep deformation response as well as reduce the time needed for qualification of materials. The SSM approach has been successful for polymer, polymeric composites, and recently has been introduced for metals. In this study, the WCS constitutive model, calibrated to SSM test data, qualifies the creep resistance of Inconel 718 at 750°C and predictions are compared to CCT data. The WCS model has proven to make long-term predictions for stress-rupture, minimum-creep-strain-rate (MCSR), creep deformation, and damage in metallic materials. The SSM varies stress levels after time interval adding damage to the material, which can be tracked by the WCS model. The SSM data is calibrated into the model and the WCS model generates realistic predictions of stress-rupture, MSCR, damage, and creep deformation. The calibrated material constants are used to generate predictions of stress-rupture and are post-audit validated using the National Institute of Material Science (NIMS) database. Similarly, the MCSR predictions are compared from previous studies. Finally the creep deformation predictions are compared with real data and is determined that the results are well in between the expected boundaries. Material characterization and mechanical properties can be determined at a faster rate and with a more cost-effective method. This is beneficial for multiple applications such as in additive manufacturing, composites, spacecraft, and Industrial Gas Turbines (IGT).

36 MATERIALS SCIENCE↗
DOE OSTI2025

AI Improves the Accuracy, Reliability, and Economic Value of Continental‐Scale Flood Predictions

Accurate flood early warnings are critical to minimize damage and loss of life. Current large‐scale operational forecasting systems, however, have limited accuracy, description of uncertainty, and computational efficiency. While Artificial intelligence (AI) can address these limitations in principle, the accuracy and reliability of AI forecasts have thus far proven insufficient. Here we present a novel hybrid framework that integrates AI‐based machinery termed Errorcastnet (ECN) with the National Water Model (NWM) to showcase the potential of ensemble AI flood forecasts over the contiguous U.S. ECN boosts prediction accuracy four‐ to six‐fold across lead times of 1–10 days, while providing uncertainty quantification. It also outperforms Google's state‐of‐the‐art global AI model. ECN‐based forecasts offer superior economic value (up to four‐fold) for decision‐making as compared to those from NWM alone. ECN performs well in varied ecoregions, physiography, and land management conditions. The framework is computationally efficient, enabling national‐scale ensemble forecasts in minutes.

artificial intelligence↗
DOE OSTI2023

Development of a Machine-Learned Cruise Guide Indicator for Rotorcraft

This paper presents a machine-learned virtual cruise guide indicator (vCGI) for Chinook helicopters. Two temporal neural networks were trained and evaluated on measured data from 55 flight tests, one for the fore rotor and another for the aft rotor, to predict a vCGI value, which protects 23 components from fatigue damage during steady-state conditions. Three different classes of machine learning architectures were evaluated for prediction of the vCGI from time sequences: a temporal convolutional neural network with 1D dilated causal convolutions, a long short-term memory recurrent neural network, and an attention-based transformer architecture. The final average model accuracy on unseen flight data is currently greater than 93% for CGI values which could result in fatigue damage and 90% for normal operation CGI values. Model accuracy was improved through a series of advancements in:(1) selection of optimal training data using temporal collective variables and unsupervised learning, (2) dataset augmentation with maximum-entropy temporal collective variables, and (3) implementation of a mixture-of-experts classification- regression approach using an adversarial classification approach to assign maneuver labels. The results are presented for each advancement in model development along with lessons learned in training machine learning models on real- world, time-dependent rotorcraft data.

Boyer, Mathew↗
DOE OSTI2024

Synthesis of results for Brine Availability Test in Salt (BATS) DECOVALEX-2023 Task E

In the 2023 phase of the international collaborative DECOVALEX modeling project, Task E focused on understanding thermal, hydrological, and mechanical (THM) processes related to predicting brine migration in the excavation damaged zone around a heated excavation in salt. Salt is attractive as a disposal medium for radioactive waste because it is self-healing and is essentially impermeable and non-porous in the far field. Investigation of the short-term, near-field behavior is important for radioactive waste disposal because this early period strongly controls the amount of inflowing brine. Brine leads to corrosion of waste forms and waste packages, and possible dissolution of radionuclides with brine transport being a potential transport vector to the accessible environment.The Task was divided into steps. Step 0 included matching unheated brine inflow data from boreholes at the Waste Isolation Pilot Plant (WIPP) and matching temperature observations during a Brine Availability Test in Salt (BATS) heater test. Step 1 included validation of models against a thermo-poroelastic analytical solution, and two-phase flow around an excavation. Finally, Step 2 required all the individual components covered in steps 0 and 1 to come together to match observed brine inflow behavior during the same BATS heater test.There were a range of approaches from the teams, from mechanistic to prescriptive. Given the uncertainties in the problem, some teams used one- or two-dimensional models of the processes, while other teams included more geometrical complexity in three-dimensional models. Task E was a learning experience for the teams involved, and feedback from the modeling teams has led to changes in follow-on BATS experiments at WIPP. The primary Task E lessons learned were the impact of hydrologic initialization methods (wetting up vs. drying down), the difference between confined and unconfined thermal expansion, and the large changes in permeability associated with heating and cooling.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Global variations in critical drought thresholds that impact vegetation

ABSTRACT Identifying the thresholds of drought that, if crossed, suppress vegetation functioning is vital for accurate quantification of how land ecosystems respond to climate variability and change. We present a globally applicable framework to identify drought thresholds for vegetation responses to different levels of known soil-moisture deficits using four remotely sensed vegetation proxies spanning 2001–2018. The thresholds identified represent critical inflection points for changing vegetation responses from highly resistant to highly vulnerable in response to drought stress, and as a warning signal for substantial vegetation impacts. Drought thresholds varied geographically, with much lower percentiles of soil-moisture anomalies in vegetated areas covered by more forests, corresponding to a comparably stronger capacity to mitigate soil water deficit stress in forested ecosystems. Generally, those lower thresholds are detected in more humid climates. State-of-the-art land models, however, overestimated thresholds of soil moisture (i.e. overestimating drought impacts), especially in more humid areas with higher forest covers and arid areas with few forest covers. Based on climate model projections, we predict that the risk of vegetation damage will increase by the end of the twenty-first century in some hotspots like East Asia, Europe, Amazon, southern Australia and eastern and southern Africa. Our data-based results will inform projections on future drought impacts on terrestrial ecosystems and provide an effective tool for drought management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

DECOVALEX-2023: Task E Final Report

This is the Task E final report for DECOVALEX-2023. Task E is focused on understanding thermal, two-phase hydrological, and mechanical (TH2M) processes, especially related to predicting brine migration in the excavation damaged zone around a heated excavation in salt. Salt is attractive as a disposal medium for radioactive waste because it is self-healing and is essentially impermeable and essentially non-porous in the far field (away from excavations). Investigation of the short-term (days to years) near-field (centimeters to tens of meters) behavior of salt is important for radioactive waste disposal because this early period strongly controls the amount of brine in a salt repository. Brine leads to corrosion of waste forms and waste packages, and possible dissolution of radionuclides with brine transport being a potential transport vector to the accessible environment. The main test case used in Task E is the ongoing Brine Availability Test in Salt (BATS) heater test located underground at the Waste Isolation Pilot Plant (WIPP) near Carlsbad, New Mexico, USA. The Task was divided into a series of Steps. Step 0 was an introduction to processes in salt, that included matching historical unheated brine inflow data from boreholes at WIPP and matching temperature observations during BATS heater test 1a. Step 1 included validation of models against a thermo-poroelastic analytical solution relevant to heated boreholes in salt, and two-phase flow around an excavation in salt. Step 2 required all the individual components covered in steps 0 and 1 to come together to match observed brine inflow behavior during the BATS 1a heater test. There were a range of approaches from the teams, from mechanistic to prescriptive. Given the uncertainties in the problem, some teams used one- or two-dimensional models of the processes, while other teams included more geometrical complexity in three-dimensional models. The key learning points from Task E have been: • Heat conduction through salt typically requires non-linear thermal conductivity (as a function of temperature), but most models do a good job matching observations, given appropriate adjustments to the applied power and some thermocouple locations. • Thermal pressurization requires coupled thermal-hydrological-mechanical (THM) responses that consider the thermal expansion of the fluid and solid phases. • Initialization of two-phase flow models around a borehole or excavation in salt are more realistically represented as “wetting up”, rather than “drying down” (i.e., the initial state after excavation is mostly dry, rather than mostly wet). • The BATS 1a heater test includes a significant release of brine after the end of heating, which requires a large increase in permeability to recreate. Task E has been a great learning experience for all the teams involved, and feedback from the modeling teams has led to changes in the design of follow-on BATS experiments, which are now ongoing underground at WIPP. There was a balance throughout the task between freedom to model phenomena how each team saw fit, and prescriptiveness in problem design to bring the modeling teams closer together to allow attribution of smaller differences between models to different modeling choices. The modeling approaches seem to go through two phases: an early phase of discovery or testing, and a later phase of refinement and improvement. In future modeling efforts, different field data could be used (e.g., BATS 2) and more time should be included in the processes for teams to make multiple model refinement or even significant changes to their conceptual model or setup, based on lessons learned from the modeling exercise.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Implementation of Creep-Damage Model for Concrete Fracture in MOOSE

Numerical implementation of an isotropic creep-damage model for concrete in multiphysics object-oriented simulation environment (MOOSE) finite element framework is presented in this paper. The constitutive model considers the combined effect of instantaneous and delayed strains on damage propagation. The implementation considers creep using generalized Maxwell or Kelvin-Voigt models. Using strain splitting assumptions, the total mechanical strains are split into elastic and creep components. Damage is considered to evolve as a function of the elastic and creep strains. This work considers damage as a function of fracture energy using the characteristic length of each finite element. This approach preserves the energy release rate of each element and avoids vanishing energy dissipation as the mesh is refined. Further, a creep-damage parameter is used to quantify the effect of creep strain on damage. The model is tested against published results on notched three-point bending specimens involving non-linear creep and predicts that about a third of the creep strain contributes towards damage for the experiments simulated. Results show that the proposed framework has predictive capabilities, and the model can be extended for more complex systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Pulse duration dependent effects of ultrafast laser induced damage on a 1030 nm multi-layer dielectric mirror for high repetition rate, high average power laser systems

High repetition rate, high peak, and average power laser systems are crucial for next-generation particle accelerators, inertial confinement fusion, and secondary particle sources. These applications demand durable laser optics, particularly interference coatings on optics lasting millions of shots at high fluence. This study focuses on designing, testing, and simulating multi-layer dielectric (MLD) mirrors for pulse durations of 260 fs, 77 fs, and 25 fs at 1030 nm wavelength and 45-degree incidence angle with p -polarization. S-on-1 laser-induced damage thresholds (LIDT) for varying pulse numbers were determined, with single-shot LIDT values of 0.98 Jcm -2 , 1.63 Jcm -2 , and 2.3 Jcm -2 for 25 fs, 77 fs, and 260 fs respectively. A strong correlation between blister shape and local fluence was observed, implying that the layer expansion in a blister depends on local fluence. We have also examined mechanisms responsible for laser-induced stress generation and energy release rates in blister formation. Damage mechanisms are further explored by finite-difference time-domain (FDTD) simulations, incorporating Keldysh strong field ionization, whose predictions were in excellent agreement with the onset of damage determined experimentally. These findings offer insights for enhancing MLD coating technology, promising more efficient and resilient laser systems for diverse scientific and industrial applications.

Noor, Mohamed Yaseen (ORCID:000000021036644X)↗
DOE OSTI2025

Graph neural networks for mechanical property prediction of 2D fiber composites

This work investigates the ability of graph neural networks (GNNs) to homogenize 2D fiber composite microstructures. We use different inhomogeneity and anisotropy indices to motivate and show that the Volume Elements (VEs) used in ML methods should ideally be far from their Representative Volume Element (RVE) size limit and, consequently, are notably anisotropic. Hence, training only the isotropic limit properties may not be acceptable. Another aspect is the need to normalize elastic stiffness values for ML, especially when high elastic contrast ratios are encountered between composite phases or in the material set. We introduce a normalization technique based on the mean-field method (MFM) to handle such high contrast ratios and train for the entire stiffness tensor. We show that the proposed GNN approaches exhibit high accuracy and efficiency compared to traditional methods and convolutional neural networks, utilizing unstructured graphs constructed from microstructure topology. Our model successfully predicts the stiffness tensor, peak strength under bulk damage, and brittle fracture initiation strength across diverse microstructure configurations while maintaining high accuracy even for extreme material contrasts and volume fractions. We also present a method to improve prediction accuracy for small dataset sizes using Voronoi partitioning.

Brittle strength↗
DOE OSTI2021

Modeling Lithium Diffusion in Battery Cathodes Considering Chemo-Mechanically Induced Damage

This talk will present a 3D, continuum-level damage model for simulating Lithium diffusion within generated Li_{x}Ni_{0.5}Mn_{0.3}Co_{0.2} (NMC 532) secondary cathode particles. The primary motivation of the particle-level model is to inform cathode-particle design and determine charging profiles that reduce cathode fracture. The model considers NMC 532 secondary particles containing an agglomeration of anisotropic, randomly oriented grains. The model predicts that secondary-particle fracture is primarily due to non-ideal grain interactions with slight dependence on high-rate charge demands. The model predicts that small secondary-particles with large grains develop significantly less damage than larger secondary particles with small grains. Finally, the model predicts most of the chemo-mechanical damage accumulates in the first high-rate cycles. This chemo-mechanical “damage saturation” effect indicates that initial secondary-particle fracture occurs within the first few cycles, while long-term cathode degradation is not solely chemo-mechanically induced.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

An algorithmic approach to predicting mechanical draft cooling tower fan speeds from infrasound signals

Mechanical draft cooling towers (MDCTs) serve a critical heat management role in a variety of industries. For nuclear reactors in particular, the consistent, predictable operation of MDCTs is required to avoid damage to infrastructure and reduce the potential for catastrophic failure. Accurate, reliable measurement of MDCT fan speed is therefore an important maintenance and safety requirement. To that end, we have developed an algorithm for automatically predicting the rotational speeds of multiple, simultaneously operating fan rotors using contactless, infrasound measurements. The algorithm is based on identifying the blade passing frequencies (BPFs), their harmonics, as well as the motor frequencies (MFs) for each fan in operation. Using the algorithm, these frequencies can be automatically identified in the acoustic waveform’s short-time Fourier transform spectrogram. Attribution is aided by a set of filters that rely on the unique spectral and temporal characteristics of fan operation, as well as the intrinsic frequency ratios of the BPF harmonics and the BPF/MF signals. The algorithm was tested against infrasound data acquired from infrasound sensors deployed at two research reactors: the Advanced Test Reactor (ATR) located at Idaho National Laboratory (INL) and the High Flux Isotope Reactor (HFIR) located at Oak Ridge National Laboratory (ORNL). After manually identifying the MDCT gearbox ratio, the algorithm was able to quickly yield fan speeds at both reactors in good agreement with ground truth. Ultimately, this work demonstrates the ease by which MDCT fans may be monitored in order to optimize operational conditions and avoid infrastructure damage.

42 ENGINEERING↗
DOE OSTI2020

30 cm Drop Modeling

This report documents modeling and analysis of the 30 cm cask drop scenario for spent nuclear fuel (SNF) casks. The 30 cm drop is an important hypothetical dynamic loading scenario for SNF because 10 CFR 71.71 defines testing requirements for normal conditions of transport (NCT) of SNF packages, and free drop (of 30 cm for the heaviest packages) tests are required. Other NCT conditions specified in 10 CFR 71.71 include vibration normally incident to transport, and DOE’s multimodal transportation test (MMTT) and related analysis concluded that mechanical shock and vibration incident to transportation is negligible for SNF structural integrity because the loads are so small. The SNF cask 30 cm drop has a lot more potential to cause damage to SNF because the kinetic energy and momentum of the system is stopped abruptly during the cask impact event. Test data and model predictions both agree that the SNF assemblies are subjected to significantly higher loads in a cask drop event than normal transportation shock and vibration, but currently there is no reason to expect gross structural damage of the fuel assembly or widespread SNF cladding failure as a result of a 30 cm cask drop. The ultimate goal of this work is to close the knowledge gap of stress profiles on SNF rods and fuel assembly components during NCT, and this report describes the progress toward reaching that goal as well as a plan for finishing this work over the next year or two. Key remaining tasks include refining the fuel assembly model, calculating a selection of specific fuel assembly cases to populate the damage model, and finally running the damage model to predict the full general response range of 30 cm drop loads on SNF.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Understanding spectral dependance of laser-induced damage precursors in dielectric materials (Full report_23-ERD-006)

The performance of high-energy laser systems is constrained by laser-induced damage in dielectric coatings, particularly those containing hafnium oxide (HfO 2 ). While thresholds at fundamental Nd harmonics are well studied, the spectral dependence of damage initiation—especially under dual-wavelength irradiation—remains poorly characterized. This project provides the first systematic investigation of wavelength-dependent laser damage in hafnia coatings, focusing on nanoscale precursors such as craze lines, nanobubbles, stoichiometric variations, nodules, and controlled crystallization. Coatings were fabricated via ion beam sputtering and electron-beam deposition and characterized using spectrophotometry, ellipsometry, AFM, GI-XRD, RBS, PCI absorption, and fs/ns laser damage testing. Results show that craze lines, benign under infrared light, strongly initiate damage under UV due to wavelength-selective field intensification. Substituting xenon for argon suppresses nanobubbles and improves UV thresholds by up to 32%. Oxygen modulation reveals that fully oxidized films maximize UV resistance, though at the cost of porosity and stress in multilayers. HfO 2 –SiO 2 composites resist crystallization and defects while achieving ppm-level absorption and elevated thresholds, whereas full crystallization of HfO 2 enhances LIDT by reducing defects and improving thermal transport. Collectively, these findings link photon energy, defect states, and bandgap collapse, providing a predictive framework for wavelength-dependent laser damage. The outcomes directly inform the design of durable, multi-wavelength coatings for facilities such as NIF, MEC, HAPLS, and DPAL, advancing the readiness of next-generation optics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Liquid lithium as divertor material to mitigate severe damage of nearby components during plasma transients

The successful operation of thermonuclear fusion reactors such as ITER, DEMO, and future commercial plants is mainly determined by the optimum choice of materials for various components. The objective of this work is to accurately and comprehensively simulate the entire device in 3D to predict pros and cons of various materials, e.g., liquid lithium in comparison to tungsten and carbon to predict future ITER-like and DEMO divertor performances. We used our comprehensive HEIGHTS simulation package to investigate ITER-like components response during transient events in exact 3D geometry. Starting from the lost hot core plasma particles through SOL, deposition on the divertor surface, and the generation of secondary plasma of divertor materials. Our simulations predicted significant reduction in the heat loading and damage to the divertor nearby and internal components in the case when lithium is used on the divertor plates. While if tungsten or carbon are used on the divertor plate, significant melting areas and vaporization spots can occur (less for carbon) on the reflector, dome, and stainless steel tubes, and even parts of the first walls can melt due to the high radiation power of the secondary divertor plasma. Lithium photon radiation deposition into the divertor and nearby surfaces was decreased by two orders of magnitude compared to tungsten and by one order of magnitude compared to carbon. This analysis showed that using liquid lithium for ITER-like surfaces and future DEMO can lead to significant enhancement in components lifetime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗