Peng Xu

Peng Xu

orcid

Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 February 2023 in Materials & Design
Verified
Journal Article
Open access
GYGuanjie Yuan
Guanjie Yuan
JFJ. Paul Forna-Kreutzer
J. Paul Forna-Kreutzer
PXPeng Xu
Peng Xu
SGSean Gonderman
Sean Gonderman
CDChristian Deck
Christian Deck
Dong LiuDong Liu
Dong Liu

18 June 2025 in Materials & Design
Verified
Journal Article
Open access
GYGuanjie Yuan
Guanjie Yuan
DCDavid H. Cook
David H. Cook
HBHarold Barnard
Harold Barnard
ELEdward Lahoda
Edward Lahoda
PXPeng Xu
Peng Xu
DLDong Liu
Dong Liu

29 December 2023 in Energies
Verified
Journal Article
Open access
PDF file
FXFei Xu
Fei Xu
TYTIANKAI YAO
TIANKAI YAO
PXPeng Xu
Peng Xu
JSJason L. Schulthess
Jason L. Schulthess
MMMario D. Matos
Mario D. Matos
NCNikolaus L. Cordes
Nikolaus L. Cordes
Silicon carbide (SiC) ceramic matrix composite (CMC) cladding is currently being pursued as one of the leading candidates for accident-tolerant fuel (ATF) cladding for light water reactor applications. The morphology of fabrication defects, including the size and shape of voids, is one of the key challenges that impacts cladding performance and guarantees reactor safety. Therefore, quantification of defects’ size, location, distribution, and leak paths is critical to determining SiC CMC in-core performance. This research aims to provide quantitative insight into the defect’s distribution under multi-scale characterization at different length scales before and after different Transient Reactor Test Facility (TREAT) irradiation tests. A non-destructive multi-scale evaluation of irradiated SiC will help to assess critical microstructural defects from production and/or experimental testing to better understand and predict overall cladding performance. X-ray computed tomography (XCT), a non-destructive, data-rich characterization technique, is combined with lower length scale electronic microscopic characterization, which provides microscale morphology and structural characterization. This paper discusses a fully automatic workflow to detect and analyze SiC-SiC defects using image processing techniques on 3D X-ray images. Following the XCT data analysis, advanced characterizations from focused ion beam (FIB) and transmission electron microscopy (TEM) were conducted to verify the findings from the XCT data, especially quantitative results from local nano-scale TEM 3D tomography data, which were utilized to complement the 3D XCT results. In this work, three SiC samples (two irradiated and one unirradiated) provided by General Atomics are investigated. The irradiated samples were irradiated in a way that was expected to induce cracking, and indeed, the automated workflow developed in this work was able to successfully identify and characterize the defects formation in the irradiated samples while detecting no observed cracking in the unirradiated sample. These results demonstrate the value of automated XCT tools to better understand the damage and damage propagation in SiC-SiC structures for nuclear applications.

5 December 2024 in Energies
Verified
Journal Article
Open access
PDF file
GSGyanender Singh
Gyanender Singh
JYJianguo Yu
Jianguo Yu
FXFei Xu
Fei Xu
TYTIANKAI YAO
TIANKAI YAO
PXPeng Xu
Peng Xu
The complex multiscale and anisotropic nature of silicon carbide (SiC) ceramic matrix composite (CMC) makes it difficult to accurately model its performance in nuclear applications. The existing models for nuclear grade composite SiC do not account for the microstructural features and how these features can affect the thermal and structural behavior of the cladding and its anisotropic properties. In addition to the microstructural features, the properties of individual constituents of the composites and fiber tow architecture determine the bulk properties. Models for determining the relationship between the individual constituents’ properties and the bulk properties of SiC composites for nuclear applications are absent, although empirical relationships exist in the literature. Here, a hierarchical multiscale modeling approach was presented to address this challenge. This modular approach addressed this difficulty by dividing the various aspects of the composite material into separate models at different length scales, with the evaluated property from the lower-length-scale model serving as an input to the higher-length-scale model. The multiscale model considered the properties of various individual constituents of the composite material (fiber, matrix, and interphase), the porosity in the matrix, the fiber volume fraction, the composite architecture, the tow thickness, etc. By considering inhomogeneous and anisotropic contributions intrinsically, our bottom-up multiscale modeling strategy is naturally physics-informed, bridging constitutive law from micromechanics to meso-mechanics and structural mechanics. The effects that these various physical attributes and thermo-physical properties have on the composite’s bulk thermal properties were easily evaluated and demonstrated through the various analyses presented herein. Since silicon carbide fiber-reinforced SiC CMCs are also promising thermal–structural materials with a broad range of high-end technology applications beyond nuclear applications, we envision that the multiscale modeling method we present here may prove helpful in future efforts to develop and construct reinforced CMCs and other advanced composite nuclear materials, such as MAX phase materials, that can service under harsh environments of ultrahigh temperatures, oxidation, corrosion, and/or irradiation.

27 November 2017 in JOM
Verified
Journal Article
Open access
PDF file
BMBenjamin Maier
Benjamin Maier
HYHwasung Yeom
Hwasung Yeom
GJGreg Johnson
Greg Johnson
TDTyler Dabney
Tyler Dabney
JWJorie Walters
Jorie Walters
KSKumar Sridharan
Kumar Sridharan
This article was updated. The title was corrected to read Light Water Reactors.

31 July 2026
Verified
Book Chapter
Closed access
SMSamuel T. Murphy
Samuel T. Murphy
PXPeng Xu
Peng Xu