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。
