Aqueous filtration systems with granular media are increasingly implemented as a unit operation for the treatment of urban waters.Many of these aqueous filtration systems are designed with coarse granular media and ar...Aqueous filtration systems with granular media are increasingly implemented as a unit operation for the treatment of urban waters.Many of these aqueous filtration systems are designed with coarse granular media and are therefore subject to finite granular Reynolds numbers(Reg).In contrast to the Reg conditions generated by such designs,current hydrosol filtration models,such as the Yao and RT models,rely on a flow solution that is derived within the Stokes limit at low Reg.In systems that are subject to these finite and higher Reg regimes,the collector efficiency has not been examined.Therefore,in this study,we develop a 3D periodic porosity-compensated face-centered cubic sphere(PCFCC)computational fluid dynamics(CFD)model,with the surface interactions incorporated,to investigate the collector efficiency for Reg ranging from 0.01 to 20.Particle filtration induced by interception and sedimentation is examined for non-Brownian particlesfanging from 1 to 100 μm under favorable surface interactions for particle adhesion.The results from the CFD-based PCFCC model agreed well with those of the classical RT and Yao models for Reg<1.Based on 3150 simulations from the PCFCC model,we developed a new correlation for vertical aqueous filtration based on a modified gravitation number,NG^*,for the initial deep-bed filtration efficiency at lower yet finite(0.01 to 20)Reg.The proposed PCFCC model has low computational cost and is extensibile from vertical to horizontal filtration at low and finite Reg.展开更多
激光粉末床熔融(Laser powder bed fusion,LPBF)技术能够高精度制造复杂金属构件,其成形过程的质量波动与缺陷在线监测是目前研究的重点方向之一。本研究面向Ti-6Al-4V合金LPBF过程,构建了一种基于原位视觉感知的成形层形貌在线监测与...激光粉末床熔融(Laser powder bed fusion,LPBF)技术能够高精度制造复杂金属构件,其成形过程的质量波动与缺陷在线监测是目前研究的重点方向之一。本研究面向Ti-6Al-4V合金LPBF过程,构建了一种基于原位视觉感知的成形层形貌在线监测与分类识别方法,可实现对成形质量的预测。首先,通过单道熔道实验系统分析不同激光功率与扫描速度组合下的熔池行为及成形层光学形貌特征,将成形层形貌依据能量密度划分为低能区、适能区与高能区,为后续分类标注建立实验基准。随后开展9组不同工艺参数的成形实验,并采集逐层成形图像,表征成形质量,构建“工艺参数—成形层形貌—成形质量”之间的定量关联。基于采集的图像数据构建多模态增强数据集(包括几何增强、噪声注入与光照调整),并采用YOLOv5s模型学习成形层光学特征与能量输入状态之间的映射关系,实现对成形质量区间的在线识别与预测。实验结果表明,模型在100个Epoch训练后,可对高、中、低能量密度形貌的识别达到97%以上准确率(m AP>0.90)。研究揭示了成形工艺参数驱动下的成形质量与成形层光学形貌之间的对应关系,为LPBF过程质量在线监测与实时调控提供了可工程化的技术路径。展开更多
激光粉末床熔融(laser powder bed fusion, LPBF)技术作为金属增材制造领域的前沿工艺,已被成功应用于航空航天等高端制造领域。然而多物理场强耦合效应易引发熔池动态失稳,导致制件内部孔隙缺陷频发,严重影响成形质量稳定性。传统监测...激光粉末床熔融(laser powder bed fusion, LPBF)技术作为金属增材制造领域的前沿工艺,已被成功应用于航空航天等高端制造领域。然而多物理场强耦合效应易引发熔池动态失稳,导致制件内部孔隙缺陷频发,严重影响成形质量稳定性。传统监测手段受限于成本高、部署困难等瓶颈,难以满足工业化生产需求。为此,提出声发射-深度学习融合的在线监测与内部质量智能判别方法。研制了基于声发射传感器的LPBF过程在线监测系统,通过工艺过程全周期声发射信号监测揭示声发射信号特征与成形质量间的映射规律,构建了包含逾8万组样本的熔池声发射数据。针对熔池微弱波动特征提取难题,构建了基于自适应傅里叶神经算子(AFNO)的频域特征提取网络和Kolmogorov-Arnold网络(KAN)的高维特征映射分类器,通过多尺度时域特征融合机制解析熔池动态特性,并借助高维流形精确映射高维特征,实现了声发射信号中微弱波动特征的增强表征和高精度质量判别。试验结果表明:研制的监测系统可有效捕获熔池的动态行为,所提方法质量判别精度达97%以上。展开更多
基金Funding was provided through the University of Florida Graduate School Fellowship.
文摘Aqueous filtration systems with granular media are increasingly implemented as a unit operation for the treatment of urban waters.Many of these aqueous filtration systems are designed with coarse granular media and are therefore subject to finite granular Reynolds numbers(Reg).In contrast to the Reg conditions generated by such designs,current hydrosol filtration models,such as the Yao and RT models,rely on a flow solution that is derived within the Stokes limit at low Reg.In systems that are subject to these finite and higher Reg regimes,the collector efficiency has not been examined.Therefore,in this study,we develop a 3D periodic porosity-compensated face-centered cubic sphere(PCFCC)computational fluid dynamics(CFD)model,with the surface interactions incorporated,to investigate the collector efficiency for Reg ranging from 0.01 to 20.Particle filtration induced by interception and sedimentation is examined for non-Brownian particlesfanging from 1 to 100 μm under favorable surface interactions for particle adhesion.The results from the CFD-based PCFCC model agreed well with those of the classical RT and Yao models for Reg<1.Based on 3150 simulations from the PCFCC model,we developed a new correlation for vertical aqueous filtration based on a modified gravitation number,NG^*,for the initial deep-bed filtration efficiency at lower yet finite(0.01 to 20)Reg.The proposed PCFCC model has low computational cost and is extensibile from vertical to horizontal filtration at low and finite Reg.
文摘激光粉末床熔融(Laser powder bed fusion,LPBF)技术能够高精度制造复杂金属构件,其成形过程的质量波动与缺陷在线监测是目前研究的重点方向之一。本研究面向Ti-6Al-4V合金LPBF过程,构建了一种基于原位视觉感知的成形层形貌在线监测与分类识别方法,可实现对成形质量的预测。首先,通过单道熔道实验系统分析不同激光功率与扫描速度组合下的熔池行为及成形层光学形貌特征,将成形层形貌依据能量密度划分为低能区、适能区与高能区,为后续分类标注建立实验基准。随后开展9组不同工艺参数的成形实验,并采集逐层成形图像,表征成形质量,构建“工艺参数—成形层形貌—成形质量”之间的定量关联。基于采集的图像数据构建多模态增强数据集(包括几何增强、噪声注入与光照调整),并采用YOLOv5s模型学习成形层光学特征与能量输入状态之间的映射关系,实现对成形质量区间的在线识别与预测。实验结果表明,模型在100个Epoch训练后,可对高、中、低能量密度形貌的识别达到97%以上准确率(m AP>0.90)。研究揭示了成形工艺参数驱动下的成形质量与成形层光学形貌之间的对应关系,为LPBF过程质量在线监测与实时调控提供了可工程化的技术路径。
文摘激光粉末床熔融(laser powder bed fusion, LPBF)技术作为金属增材制造领域的前沿工艺,已被成功应用于航空航天等高端制造领域。然而多物理场强耦合效应易引发熔池动态失稳,导致制件内部孔隙缺陷频发,严重影响成形质量稳定性。传统监测手段受限于成本高、部署困难等瓶颈,难以满足工业化生产需求。为此,提出声发射-深度学习融合的在线监测与内部质量智能判别方法。研制了基于声发射传感器的LPBF过程在线监测系统,通过工艺过程全周期声发射信号监测揭示声发射信号特征与成形质量间的映射规律,构建了包含逾8万组样本的熔池声发射数据。针对熔池微弱波动特征提取难题,构建了基于自适应傅里叶神经算子(AFNO)的频域特征提取网络和Kolmogorov-Arnold网络(KAN)的高维特征映射分类器,通过多尺度时域特征融合机制解析熔池动态特性,并借助高维流形精确映射高维特征,实现了声发射信号中微弱波动特征的增强表征和高精度质量判别。试验结果表明:研制的监测系统可有效捕获熔池的动态行为,所提方法质量判别精度达97%以上。
