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激光冲击强化有限元分析的综合综述

A Comprehensive Review on Finite Element Analysis of Laser Shock Peening.

作者信息

Wakchaure Mayur B, Misra Manoranjan, Menezes Pradeep L

机构信息

Department of Mechanical Engineering, University of Nevada, Reno, NV 89557, USA.

Department of Chemical and Materials Engineering, University of Nevada, Reno, NV 89557, USA.

出版信息

Materials (Basel). 2024 Aug 23;17(17):4174. doi: 10.3390/ma17174174.

DOI:10.3390/ma17174174
PMID:39274564
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11395919/
Abstract

Laser shock peening (LSP) is a formidable cold working surface treatment that provides high-energy precision to enhance the mechanical properties of materials. This paper delves into the intricacies of the LSP process, offering insights into its methodology and the simulation thereof through the finite element method. This review critically examines various points, such as laser energy, overlapping of shots, effect of LSP on residual stress, effect of LSP on grain refinement, and algorithms for simulation extrapolated from finite element analyses conducted by researchers, shedding light on the nuanced considerations integral to this technique. As the significance of LSP continues to grow, the collective findings underscore its potential as a transformative technology for fortifying materials against mechanical stress and improving their overall performance and longevity. The discourse encapsulates the evolving landscape of the LSP, emphasizing the pivotal role played by finite element analysis in advancing our understanding and application of this innovative surface treatment.

摘要

激光冲击强化（LSP）是一种强大的冷加工表面处理技术，它能提供高能量精度以增强材料的机械性能。本文深入探讨了LSP工艺的复杂性，通过有限元方法对其方法及模拟进行了深入分析。本综述批判性地研究了多个要点，如激光能量、冲击重叠、LSP对残余应力的影响、LSP对晶粒细化的影响，以及研究人员通过有限元分析推断出的模拟算法，揭示了该技术所涉及的细微考量因素。随着LSP的重要性不断提升，这些共同的研究结果突显了其作为一种变革性技术的潜力，可强化材料抵御机械应力的能力，并提高其整体性能和使用寿命。该论述概括了LSP不断发展的态势，强调了有限元分析在深化我们对这种创新表面处理技术的理解和应用方面所发挥的关键作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b658/11395919/bec8577f06d4/materials-17-04174-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b658/11395919/3625a59977df/materials-17-04174-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b658/11395919/bcab267aa5de/materials-17-04174-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b658/11395919/65fd16d6a003/materials-17-04174-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b658/11395919/52e46e6afd8c/materials-17-04174-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b658/11395919/2c21ef495901/materials-17-04174-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b658/11395919/bec8577f06d4/materials-17-04174-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b658/11395919/3625a59977df/materials-17-04174-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b658/11395919/bcab267aa5de/materials-17-04174-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b658/11395919/65fd16d6a003/materials-17-04174-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b658/11395919/52e46e6afd8c/materials-17-04174-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b658/11395919/2c21ef495901/materials-17-04174-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b658/11395919/bec8577f06d4/materials-17-04174-g006.jpg

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本文引用的文献

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2
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Materials (Basel). 2022 Oct 11;15(20):7051. doi: 10.3390/ma15207051.
3
Peening Techniques for Surface Modification: Processes, Properties, and Applications.用于表面改性的喷丸技术：工艺、性能及应用
用于减轻核应用干式储存罐中氯致应力腐蚀开裂的喷丸技术
Materials (Basel). 2025 Jan 18;18(2):438. doi: 10.3390/ma18020438.
Materials (Basel). 2021 Jul 9;14(14):3841. doi: 10.3390/ma14143841.
4
Using an artificial neural network to predict the residual stress induced by laser shock processing.使用人工神经网络预测激光冲击处理引起的残余应力。
Appl Opt. 2021 Apr 10;60(11):3114-3121. doi: 10.1364/AO.421431.
5
Simulation and Experimental Study on Residual Stress Distribution in Titanium Alloy Treated by Laser Shock Peening with Flat-Top and Gaussian Laser Beams.平顶和高斯激光束激光冲击强化处理钛合金残余应力分布的模拟与实验研究
Materials (Basel). 2019 Apr 24;12(8):1343. doi: 10.3390/ma12081343.
6
Laser Peening Process and Its Impact on Materials Properties in Comparison with Shot Peening and Ultrasonic Impact Peening.激光喷丸工艺及其与喷丸和超声冲击喷丸相比对材料性能的影响。
Materials (Basel). 2014 Dec 10;7(12):7925-7974. doi: 10.3390/ma7127925.
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Five parameters you must understand to master control of your laser/light-based devices.掌握激光/光设备控制必须了解的五个参数。
Aesthet Surg J. 2013 Sep 1;33(7):1059-64. doi: 10.1177/1090820X13501174. Epub 2013 Aug 22.
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Tuning of the structure and parameters of a neural network using an improved genetic algorithm.使用改进的遗传算法对神经网络的结构和参数进行调整。
IEEE Trans Neural Netw. 2003;14(1):79-88. doi: 10.1109/TNN.2002.804317.