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Temperature-Dependent Material Property Databases for Marine Steels—Part 3: HSLA-80 船用钢的温度相关材料性能数据库-第3部分:hsa -80
IF 3.3 3区 材料科学 Q3 ENGINEERING, MANUFACTURING Pub Date : 2022-11-23 DOI: 10.1007/s40192-022-00288-x
Jennifer K. Semple, Daniel H. Bechetti, Wei Zhang, Charles R. Fisher

Integrated Computational Materials Engineering (ICME)-based tools and techniques have been identified as the best path forward for distortion mitigation in thin-plate steel construction at shipyards. ICME tools require temperature-dependent material properties—including specific heat, thermal conductivity, coefficient of thermal expansion, elastic modulus, yield strength, flow stress, and microstructural evolution—to achieve accurate computational results for distortion and residual stress. However, the required temperature-dependent material property databases of US Navy-relevant steels are not available in the literature. Therefore, a comprehensive testing plan for some of the most common marine steels used in the construction of US Naval vessels was completed. This testing plan included DH36, HSLA-65, HSLA-80, HSLA-100, HY-80, and HY-100 steel with a nominal thickness of 4.76 mm (3/16-in.). This report is the second part of a seven-part series detailing the pedigreed steel data. The first six reports will report the material properties for each of the individual steel grades, whereas the final report will compare and contrast the measured steel properties across all six steels. This report will focus specifically on the data associated with HSLA-80 steel.

基于综合计算材料工程(ICME)的工具和技术已被确定为缓解造船厂薄板钢结构变形的最佳途径。ICME工具需要与温度相关的材料性能,包括比热、导热系数、热膨胀系数、弹性模量、屈服强度、流动应力和微观结构演变,以获得准确的变形和残余应力计算结果。然而,美国海军相关钢材所需的温度相关材料性能数据库在文献中是不可用的。因此,美国海军舰艇建造中使用的一些最常用的船用钢材的综合测试计划已经完成。该测试计划包括DH36, HSLA-65, HSLA-80, HSLA-100, HY-80和HY-100钢,公称厚度为4.76 mm(3/16英寸)。本报告是详细介绍纯种钢材数据的七部分系列报告的第二部分。前六份报告将报告每个钢等级的材料性能,而最后一份报告将比较和对比所有六种钢的测量钢性能。本报告将特别关注与HSLA-80钢相关的数据。
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引用次数: 2
Automatic Determination of the Weak-Beam Condition in Dark Field X-ray Microscopy 暗场x射线显微镜弱光束条件的自动测定
IF 3.3 3区 材料科学 Q3 ENGINEERING, MANUFACTURING Pub Date : 2022-11-09 DOI: 10.1007/s40192-023-00295-6
P. Huang, R. Coffee, L. Dresselhaus-Marais
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引用次数: 0
Quantifying Dynamic Signal Spread in Real-Time High-Energy X-ray Diffraction 实时高能x射线衍射中动态信号传播的量化
IF 3.3 3区 材料科学 Q3 ENGINEERING, MANUFACTURING Pub Date : 2022-11-04 DOI: 10.1007/s40192-022-00281-4
Daniel Banco, E. Miller, A. Beaudoin, Matthew P. Miller, K. Chatterjee
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引用次数: 0
Reduced-Order Damage Assessment Model for Dual-Phase Steels 双相钢的降阶损伤评估模型
IF 3.3 3区 材料科学 Q3 ENGINEERING, MANUFACTURING Pub Date : 2022-10-31 DOI: 10.1007/s40192-022-00282-3
S. Thakre, A. Kanjarla
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引用次数: 1
On the Effect of Nucleation Undercooling on Phase Transformation Kinetics 成核过冷对相变动力学的影响
IF 3.3 3区 材料科学 Q3 ENGINEERING, MANUFACTURING Pub Date : 2022-10-30 DOI: 10.1007/s40192-022-00284-1
J. Mancias, V. Attari, Raymundo Arr'oyave, D. Tourret
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引用次数: 0
Predicting Melt Pool Dimensions for Wire-Feed Directed Energy Deposition Process 预测金属丝进给定向能沉积工艺的熔池尺寸
IF 3.3 3区 材料科学 Q3 ENGINEERING, MANUFACTURING Pub Date : 2022-10-19 DOI: 10.1007/s40192-022-00278-z
Zhening Yang, A. K. Verma, Lonnie Smith, Ali Guzel, Han-Ting Chen, P. Pistorius, A. Rollett
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引用次数: 0
Ontopanel: A Tool for Domain Experts Facilitating Visual Ontology Development and Mapping for FAIR Data Sharing in Materials Testing Ontopanel:领域专家的工具,促进材料测试中FAIR数据共享的可视化本体开发和映射
IF 3.3 3区 材料科学 Q3 ENGINEERING, MANUFACTURING Pub Date : 2022-10-17 DOI: 10.1007/s40192-022-00279-y
Yue Chen, Markus Schilling, Philipp von Hartrott, Hossein Beygi Nasrabadi, B. Skrotzki, J. Olbricht
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引用次数: 4
PRISMS-Plasticity TM: An Open-Source Rapid Texture Evolution Analysis Pipeline prism - plasticity TM:一个开源的快速纹理演化分析管道
IF 3.3 3区 材料科学 Q3 ENGINEERING, MANUFACTURING Pub Date : 2022-09-28 DOI: 10.1007/s40192-022-00275-2
M. Yaghoobi, J. Allison, V. Sundararaghavan
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引用次数: 3
Uncertainty Quantification Framework for Predicting Material Response with Large Number of Parameters: Application to Creep Prediction in Ferritic-Martensitic Steels Using Combined Crystal Plasticity and Grain Boundary Models 预测大量参数材料响应的不确定性量化框架:应用晶体塑性和晶界模型联合预测铁素体-马氏体钢的蠕变
IF 3.3 3区 材料科学 Q3 ENGINEERING, MANUFACTURING Pub Date : 2022-09-28 DOI: 10.1007/s40192-022-00277-0
A. Behnam, T. Truster, R. Tipireddy, M. Messner, Varun Gupta
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引用次数: 0
Additive Manufacturing Melt Pool Prediction and Classification via Multifidelity Gaussian Process Surrogates 基于多保真高斯过程替代的增材制造熔池预测与分类
IF 3.3 3区 材料科学 Q3 ENGINEERING, MANUFACTURING Pub Date : 2022-09-20 DOI: 10.1007/s40192-022-00276-1
R. Saunders, A. Rawlings, A. Birnbaum, A. Iliopoulos, J. Michopoulos, D. Lagoudas, A. Elwany
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引用次数: 8
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Integrating Materials and Manufacturing Innovation
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