Influence of recrystallization on tungsten divertor monoblock under high heat flux

Jin, Yuzhong; Liu, Xiang; Lian, Youyun; Song, Jiupeng

doi:10.1007/s42864-021-00126-1

Cited by 10 publications

(4 citation statements)

References 25 publications

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“…Moreover, the loading conditions during thermal shocks, including high strain rate, rapid temperature variation and so on, are expected to be more severe compared to mechanical grinding. Consequently, mechanical damage and residual tensile stresses parallel to the surface [56] on the W can be exacerbated under thermal shock conditions. Hence, the absence of blisters is reasonable in samples subjected to over 500 thermal shock cycles.…”

Section: Discussionmentioning

confidence: 99%

Deuterium retention in cyclic transient heat loaded tungsten with increasing cycle numbers

Ren,

Yuan,

Feng

et al. 2024

Nucl. Fusion

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Surface damage and microscopic defect evolution of tungsten (W) armor under transient heat loads are key factors for fuel retention in fusion reactors. In this work, experiments were conducted to investigate the effects of cyclic thermal shocks on deuterium (D) retention and surface blistering in W. Thermal shock experiments were conducted on recrystallized W using an electron beam with a power density of 0.15 GW m-2 across 100-1500 cycles, followed by D plasma exposure with high-fluence (~ 1 × 1026 D m-2). The results demonstrate that samples subjected to 500 and 1500 cycles exhibit a significant presence of sub-grains within 90 μm. Notably, the inhibition of blistering induced by thermal shock leads to a substantial reduction in D retention (5.45 × 1019 D m-2) at lower cycle numbers (100 cycles) compared to the reference sample (2.35 × 1020 D m-2) which was only exposed to D plasma. When cycle numbers increase to 500 and 1500, D retention reaches 1.98 × 1020 D m-2 and 4.56 × 1020 D m-2, respectively. Based on the Tritium Migration Analysis Program, we propose that total D retention is a consequence of the competition between defects reduced by thermal shock-induced suppression of blistering and defects generated by plastic deformation induced by thermal stress. D retention initially decreases with the increase in cycle numbers, followed by a subsequent rise, with the inflection point slightly higher than 500 cycles. Additionally, due to the extensive scope of thermal stress, an escalated exposure period will result in substantial D captured by heat-induced defects, consequently intensifying the D retention. Whether there exists an upper limit to D retention induced by the increasing thermal shock cycles necessitates further experimental analysis. Nonetheless, it is evident that thermal shock significantly contributes to D retention within a profoundly deep bulk region under high cycles.

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Section: Discussionmentioning

confidence: 99%

Deuterium retention in cyclic transient heat loaded tungsten with increasing cycle numbers

Ren,

Yuan,

Feng

et al. 2024

Nucl. Fusion

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“…On the other hand, the stored energy may promote recrystallization, thereby lowering the recrystallization temperature to a relatively low value during repeated thermal loading [28]. However, the fibrous grain structure of the stacked W structures, along with the low stress along the RD and the crack deflection effect along the ND, contributed to their superior thermal fatigue resistance compared to the bulk W. According to the estimated surface temperature of the samples, which is slightly lower than the recrystallization temperature of W (ITRR 1300 °C) [32], recrystallization was observed in the stacked W structures, as shown in Figure 12. For the bulk W, due to the large variation in grain size before thermal loading, it is difficult to determine whether recrystallization occurred from the changes in microstructure alone.…”

Section: Comparison Of Thermal Fatigue Cracking Evolution Process Of ...mentioning

confidence: 99%

“…It is noteworthy that the fibrous grain structure of the foil, resulting from the rolling process, may enhance the yield strength and ultimate tensile strength of the material, which is beneficial for suppressing thermal fatigue damage [31]. According to the estimated surface temperature of the samples, which is slightly lower than the recrystallization temperature of W (ITRR 1300 • C) [32], recrystallization was observed in the stacked W structures, as shown in Figure 12. For the bulk W, due to the large variation in grain size before thermal loading, it is difficult to determine whether recrystallization occurred from the changes in microstructure alone.…”

Section: Comparison Of Thermal Fatigue Cracking Evolution Process Of ...mentioning

confidence: 99%

Finite Element Analysis and Experimental Verification of Thermal Fatigue of W-PFM with Stacked Structure

Qi,

Song

et al. 2024

Metals

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As the prime candidate for plasma-facing materials (PFM), the response of tungsten (W) to thermal shock loads is an important research topic for future fusion devices. Under heat loads, the surface of tungsten plasma-facing materials (W-PFM) can experience thermal damage, including brittle cracking and fatigue cracks. Therefore, exploring solutions for thermal damage of W-PFM remains one of the current research focuses. We propose a novel approach to mitigate thermal radiation damage in PFM, namely, the stacked structure W-PFM. The surface thermal stress distribution of the stacked structure W-PFM under heat loads was simulated and analyzed by the finite element method. As the foil thickness decreases, both the peak thermal stresses in the normal direction (ND) and rolling direction (RD) decrease. When the thickness decreases to a certain value, the peak thermal stress in the RD decreases to about 1384 MPa and no longer decreases; while the peak thermal stress in the ND approaches 0 MPa and can be neglected. In the range of approximately 5–100 mm, the accumulated equivalent plastic strain decreases sharply as the thickness decreases; in other thickness ranges, it decreases slowly. Thermal fatigue experiments were conducted on the stacked structure W composed of W foils with different thicknesses and bulk W using an electron beam facility. The samples were applied with a power density of 30 MW/m2 for 10,000 and 20,000 pulses. The cracks on the surface of the stacked structure W extended along the ND direction, while on the surface of bulk W, besides the main crack in the ND direction, a crack network also formed. The experimental results were consistent with finite element simulations. When the pulse number was 10,000, as the thickness of the W foil decreased, the number and width of the cracks on the surface of the stacked structure W decreased. Only four small cracks were present on the surface of stacked structure W (0.05 mm). When the pulse number increased to 20,000, the plastic deformation and number of cracks on the surface of all samples increased. However, the stacked structure W (0.05 mm) only added one small crack and had the smallest surface roughness (Ra = 1.536 μm). Quantitative analysis of the fatigue cracks showed that the stacked structure W-PFM (0.05 mm) exhibited superior thermal fatigue performance.

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“…• Erosion of the armour layer due to plasma surface interaction [34]. • Changes in tungsten material properties due to heating above the recrystallisation temperature [35].…”

Section: Future Workmentioning

confidence: 99%

Machine learning techniques for sequential learning engineering design optimisation

Humphrey,

Dubas,

Fletcher

et al. 2023

Plasma Phys. Control. Fusion

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When designing a fusion power plant, many first-of-a-kind components are required. This presents a large potential design space across as many dimensions as the component’s parameters. In addition, multiphysics, multiscale, high-fidelity simulations are required to reliably capture a component’s performance under given boundary conditions. Even with high performance computing (HPC) resources, it is not possible to fully explore a component’s design space. Thus, effective interpolation between data points via machine learning (ML) techniques is essential. With sequential learning engineering optimisation, ML techniques inform the selection of simulation parameters which give the highest expected improvement for the model: balancing exploitation of the current best design with exploration of uncertain areas in the design space. In this paper, the application of an ML-driven design of experiment procedure for the sequential learning engineering design optimisation of a fusion component is shown. A parameterised divertor monoblock is taken as a typical example of a fusion component requiring HPC simulation to model. The component’s geometry is then optimised using Bayesian optimisation, seeking the design which minimises the stress experienced by the component under operational conditions.

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Influence of recrystallization on tungsten divertor monoblock under high heat flux

Cited by 10 publications

References 25 publications

Deuterium retention in cyclic transient heat loaded tungsten with increasing cycle numbers

Deuterium retention in cyclic transient heat loaded tungsten with increasing cycle numbers

Finite Element Analysis and Experimental Verification of Thermal Fatigue of W-PFM with Stacked Structure

Machine learning techniques for sequential learning engineering design optimisation

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