<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Xuan Zhou</title><link>https://xuanzhou.ac.cn/authors/xuan-zhou/</link><atom:link href="https://xuanzhou.ac.cn/authors/xuan-zhou/index.xml" rel="self" type="application/rss+xml"/><description>Xuan Zhou</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><lastBuildDate>Fri, 24 Oct 2025 00:00:00 +0000</lastBuildDate><image><url>https://xuanzhou.ac.cn/media/icon_hu5971c73a93cd34c6a54b40261e8ec7c0_134755_512x512_fill_lanczos_center_3.png</url><title>Xuan Zhou</title><link>https://xuanzhou.ac.cn/authors/xuan-zhou/</link></image><item><title>A novel study on hybrid physics-data-driven reduced-order modeling for aerodynamic load inversion under structural field uncertainties</title><link>https://xuanzhou.ac.cn/publication/cmame2026/</link><pubDate>Fri, 24 Oct 2025 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/cmame2026/</guid><description/></item><item><title>Structural damage diagnosis and prognosis with fleet digital twin considering similarity of individual structural features</title><link>https://xuanzhou.ac.cn/publication/ast2025/</link><pubDate>Tue, 07 Oct 2025 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/ast2025/</guid><description/></item><item><title>Parametric Symbolic Regression for Discovering Unified Crack Growth Models from Diverse Experiments</title><link>https://xuanzhou.ac.cn/publication/aiaaj2025a/</link><pubDate>Fri, 01 Aug 2025 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/aiaaj2025a/</guid><description/></item><item><title>Real-Time In-Service Load Tracking Toward Airframe Digital Twins</title><link>https://xuanzhou.ac.cn/publication/aiaaj2025/</link><pubDate>Fri, 01 Aug 2025 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/aiaaj2025/</guid><description/></item><item><title>Variational Neural Network Embedded with Digital Twins for Probabilistic Structural Damage Quantification</title><link>https://xuanzhou.ac.cn/publication/aiaaj2024a/</link><pubDate>Tue, 17 Dec 2024 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/aiaaj2024a/</guid><description/></item><item><title>ON THE DEVELOPMENT OF THE STRUCTURAL DIGITAL TWIN OF AN UNMANNED AERIAL VEHICLE</title><link>https://xuanzhou.ac.cn/publication/icas2024/</link><pubDate>Tue, 01 Oct 2024 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/icas2024/</guid><description/></item><item><title>In-service Load Monitoring for an UAV Digital Twin</title><link>https://xuanzhou.ac.cn/publication/ewshm2024/</link><pubDate>Mon, 01 Jul 2024 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/ewshm2024/</guid><description/></item><item><title>B-Spline Surface-Based Reduced-Order Modeling of Nonplanar Crack Growth in Structural Digital Twins</title><link>https://xuanzhou.ac.cn/publication/aiaaj2024/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/aiaaj2024/</guid><description/></item><item><title>Copula-Based Collaborative Multistructure Damage Diagnosis and Prognosis for Fleet Maintenance Digital Twins</title><link>https://xuanzhou.ac.cn/publication/aiaaj2023a/</link><pubDate>Sun, 01 Oct 2023 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/aiaaj2023a/</guid><description/></item><item><title>Generating High-Resolution Flight Parameters in Structural Digital Twins Using Deep Learning-based Upsampling</title><link>https://xuanzhou.ac.cn/publication/phm2023/</link><pubDate>Tue, 27 Jun 2023 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/phm2023/</guid><description/></item><item><title>Setting Adaptive Inspection Intervals in Helicopter Components, Based on a Digital Twin</title><link>https://xuanzhou.ac.cn/publication/aiaaj2023/</link><pubDate>Thu, 01 Jun 2023 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/aiaaj2023/</guid><description/></item><item><title>A Fuzzy-set-based Joint Distribution Adaptation Method for Regression and its Application to Online Damage Quantification for Structural Digital Twin</title><link>https://xuanzhou.ac.cn/publication/mssp2023/</link><pubDate>Thu, 02 Feb 2023 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/mssp2023/</guid><description/></item><item><title>Cluster-Based Joint Distribution Adaptation Method for Debonding Quantification in Composite Structures</title><link>https://xuanzhou.ac.cn/publication/aiaaj2022a/</link><pubDate>Wed, 01 Feb 2023 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/aiaaj2022a/</guid><description/></item><item><title>Weakly Singular Symmetric Galerkin Boundary Element Method for Fracture Analysis of Three-Dimensional Structures Considering Rotational Inertia and Gravitational Forces</title><link>https://xuanzhou.ac.cn/publication/cmes2022/</link><pubDate>Tue, 19 Apr 2022 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/cmes2022/</guid><description/></item><item><title>Real-Time Prediction of Probabilistic Crack Growth with a Helicopter Component Digital Twin</title><link>https://xuanzhou.ac.cn/publication/aiaaj2022/</link><pubDate>Fri, 01 Apr 2022 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/aiaaj2022/</guid><description/></item><item><title>An Intelligent Digital-Twin-Based Strategy for the Inspection and Maintenance of Aircraft Skin Cracks</title><link>https://xuanzhou.ac.cn/publication/gtlxxb2021/</link><pubDate>Thu, 17 Jun 2021 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/gtlxxb2021/</guid><description>&lt;p>In Chinese&lt;/p></description></item><item><title>Key technologies for modeling and simulation of airframe digital twin</title><link>https://xuanzhou.ac.cn/publication/hkxb2021/</link><pubDate>Mon, 15 Mar 2021 00:00:00 +0000</pubDate><guid>https://xuanzhou.ac.cn/publication/hkxb2021/</guid><description>&lt;p>In Chinese&lt;/p></description></item></channel></rss>