【标题】Classification of Damages in Composite Material using Multi-support Vector Machine
【参考中译】基于多支持向量机的复合材料损伤分类
【类型】 期刊
【关键词】 Composite material; Damage; SVM
【参考中译】 复合材料；损伤；支持向量机
【作者】 Rajiv B.; Kalos Pritam; Pantawane Prakash; Chougule Vikas; Chavan Vishwanath
【摘要】 The mechanical properties of composite-reinforced natural fibres depend on parameters like fibre strength, length and chemical behaviour of fibre–matrix interfacial bond. The clarification of the research and development of composite-reinforced natural fibres improve the mechanical properties along with end applications. In this paper, multi-support vector machine (MSVM) is used to test the durability of composite material and the classification of damages in composite material. The images are collected across a composite material with 5–7?mm impingement. The images are filtered initially using an anisotropic filter. The classification is finally estimated out with MSVM classifier. Experimental validation is conducted over various composite materials, and the results are tested in real-time images. The validation shows that the proposed method attains the improved rate of accuracy in classifying the images than other existing state-of-the art models. Further, the durability of the material is tested in terms of material removal rate, wear resistance rate and material strength.
【参考中译】 复合材料增强天然纤维的力学性能取决于纤维强度、长度和纤维-基质界面粘结的化学行为等参数。阐明了复合增强天然纤维的研究和发展，提高了其力学性能和终端应用。本文利用多支持向量机(MSVM)对复合材料的耐久性进行检测，并对复合材料的损伤进行分类。图像是通过5-7毫米撞击的复合材料收集的。最初使用各向异性过滤器对图像进行滤波。最后利用最小二乘支持向量机分类器对分类结果进行估计。对各种复合材料进行了实验验证，并在实时图像中对结果进行了检验。验证结果表明，与现有的其他分类模型相比，该方法具有更高的分类正确率。此外，从材料去除率、耐磨性和材料强度方面测试了材料的耐久性。
【来源】 Journal of The institution of engineers (India), Series C 2022, vol.103, no.4
【入库时间】 2023/2/3
【标题】Erosion model for abrasive water jet machining of composite materials
【参考中译】磨料水射流加工复合材料的冲蚀模型
【关键词】 Abrasive water jet machining; Erosion; Composite material; Erosion model; Dimensional analysis technique; Machining parameters; CUTTING PERFORMANCE; SURFACE-ROUGHNESS; ALUMINA CERAMICS; CARBON; OPTIMIZATION; HOLE; PREDICTION; PARAMETERS; IMPACT; GLASS
【参考中译】 磨料水射流加工；冲蚀；复合材料；冲蚀模型；量纲分析技术；加工参数；切割性能；表面粗糙度；氧化铝陶瓷；碳；优化；孔；预测；参数；冲击；玻璃
【作者】 Dhanawade, Ajit; Wazarkar, Seema; Kumar, Shailendra
【摘要】 This paper describes study of abrasive particle impingement in abrasive water jet machining of carbon fiber-reinforced polymer. A mathematical model is derived through a hybrid approach for erosion of material during machining to predict depth of jet penetration on the basis of abrasive impingement results and dimensional analysis. The depth of cut, i.e., jet penetration, is examined by machining non-through straight slit cuts on carbon fiber epoxy resin composite workpiece. Machining parameters precisely abrasive flow rate, jet pressure and traverse rate are observed as substantial factors to control jet penetration. It is observed that the increase in the jet pressure and abrasive flow rate results in the increase in the depth of jet penetration. But the decrease in traverse rate results in the increase in the depth of jet penetration. The defects including delamination, fiber pullout, fiber and matrix washout and abrasive embedment are also studied. These defects are prominent in samples machined under low pressure and high traverse rate. In the present study, an attempt is made to study and analyze physics behind abrasive impingement during machining. Therefore, abrasive particle velocity is studied quantum mechanically. A mathematical model in general form is developed on the basis of abrasive impingement, quantum mechanical study for abrasive energy and dimensional analysis technique. The experimental results and model results are in good agreement with each other. Validation experiments confirm the adequacy of the model. The model is efficiently applicable to AWJM of any layered composite material.
【参考中译】 本文对磨料水射流加工碳纤维增强聚合物中的磨粒冲击进行了研究。在磨料冲击结果和量纲分析的基础上，通过加工过程中材料磨损的混合方法建立了预测射流侵彻深度的数学模型。通过对碳纤维-环氧树脂复合材料工件进行非直缝切割，检测了切割深度，即射流穿透深度。精确的加工参数、磨料流量、射流压力和横移速率是控制射流穿透的重要因素。实验结果表明，射流压力和磨料流量的增加会导致射流穿透深度的增加。但穿透速度的减小会导致射流侵彻深度的增加。并对分层、纤维拔出、纤维与基质冲刷、磨料嵌入等缺陷进行了研究。这些缺陷在低压和高加工速度下加工的样品中尤为突出。在本研究中，试图研究和分析机械加工过程中磨粒碰撞背后的物理现象。因此，对磨粒速度进行了量子力学研究。在磨料撞击、磨料能量的量子力学研究和量纲分析技术的基础上，建立了一般形式的数学模型。实验结果与模型结果吻合较好。验证实验证实了该模型的充分性。该模型适用于任何层状复合材料的AWJM。
【来源】 Journal of the Brazilian Society of Mechanical Sciences and Engineering 2022, vol.44, no.7
【标题】Fabrication, characterization, and selection using FAHP‐TOPSIS technique of zirconia, titanium oxide, and marble dust powder filled dental restorative composite materials
【参考中译】氧化锆、氧化钛和大理石粉尘填充牙科修复复合材料的制备、表征和FAHP-TOPSIS技术选择
【关键词】 biomaterials; dental restorative composite materials; FAHP; FTOPSIS; Optimization technique
【参考中译】 生物材料；牙科修复复合材料；FAHP；FTOPSIS；优化技术
【作者】 Ramkumar Yadav; Hae‐Hyoung Lee
【摘要】 The article aimed to develop and characterize the nano‐micro ceramic particle‐filled polymer‐based composite as dental materials. The current study also deals with the ranking of dental composites using a hybrid fuzzy analytic hierarchy process (FAHP)‐fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) methodology. Dental composites were fabricated from resin matrix and ceramic particulates. Two different series were fabricated. Zirconia, titanium oxide, and marble dust powder were used as ceramic particles in the dental composite. Bis‐GMA, TEGDMA, CQ, and DMAEMA were employed for the resin matrix of dental composite. The physical and mechanical properties were investigated for both dental formulations. The maximum and minimum compressive strengths were recorded in DM‐6 (321?MPa) and DT‐0 (190?MPa). Polymerization shrinkage was gradually decreased in both hybrid nZr‐TiO2 and hybrid nZr‐MDP formulations. The FTOPSIS was used to determine the rank of alternatives as DT‐6?>DM‐6?>DM‐4?>DT‐4?>DM‐2?>DM‐0?>DT‐0?>DT‐2.
【参考中译】 本文旨在开发和表征纳米微米陶瓷颗粒填充聚合物基复合材料作为牙科材料。目前的研究还涉及使用一种混合模糊层次分析过程(FAHP)-按理想解决方案的相似性排序(FTOPSIS)方法对牙科复合材料进行排序。牙科复合材料是由树脂基质和陶瓷颗粒制成的。制作了两个不同的系列。在牙科复合材料中使用了氧化锆、氧化钛和大理石粉尘作为陶瓷颗粒。采用BIS-GMA、TEGDMA、CQ和DMAEMA作为牙科复合材料的树脂基质。研究了这两种牙科制剂的物理和机械性能。最大和最小抗压强度分别为DM-6(321 Mpa)和DT-0(190 Mpa)。在杂化NZR-二氧化钛和杂化NZR-MDP配方中，聚合收缩逐渐降低。用FTOPSIS法确定备选方案的等级为DT‐6？>DM‐6？>DM‐4？>DT‐4？>DM‐2？>DM‐0？>DT‐0？>DT‐2.
【来源】 Polymers for advanced technologies 2022, vol.33, no.10