Powder Technology最新文献

英文中文

Real-time film thickness monitoring in complex environments using deep learning-based visual imaging

IF 4.5 2区工程技术 Q2 ENGINEERING, CHEMICAL

Powder Technology

Pub Date : 2025-02-13 DOI: 10.1016/j.powtec.2025.120795

Liang Zhong , Hengqiang Cheng , Lele Gao , Lian Li , Wenping Yin , Hui Wang , Qiyi Miao , Yunshi Zhang , Lei Nie , Hengchang Zang

Film thickness is a critical quality attribute of coated pharmaceutical pellets, as it directly influences drug release profiles and stability. In fluidized bed coating processes, accurate in-line measurements are challenging with traditional imaging methods under complex conditions, such as high material density, pellet overlap, and defocusing. Therefore, this paper introduces an innovative visual imaging strategy leveraging the Mask R-CNN algorithm for non-invasive, real-time film thickness monitoring during fluidized bed coating processes. The proposed approach achieves precise pellet segmentation and effectively addresses challenges posed by pellet overlap, defocusing, and blurring. The superiority and accuracy of the Mask R-CNN algorithm were validated against traditional methods such as Otsu thresholding, Canny edge detection, and off-line techniques, including UV–visible spectrophotometry and laser diffraction. The sensitivity and robustness of the proposed approach were further explored under conditions of high contamination, overexposure, and low contrast arising from color variations. The results of this study demonstrate the potential of deep learning-based imaging to transform process analytical technology (PAT), facilitating dynamic and precise quality monitoring in pharmaceutical production.

{"title":"Real-time film thickness monitoring in complex environments using deep learning-based visual imaging","authors":"Liang Zhong , Hengqiang Cheng , Lele Gao , Lian Li , Wenping Yin , Hui Wang , Qiyi Miao , Yunshi Zhang , Lei Nie , Hengchang Zang","doi":"10.1016/j.powtec.2025.120795","DOIUrl":"10.1016/j.powtec.2025.120795","url":null,"abstract":"<div><div>Film thickness is a critical quality attribute of coated pharmaceutical pellets, as it directly influences drug release profiles and stability. In fluidized bed coating processes, accurate in-line measurements are challenging with traditional imaging methods under complex conditions, such as high material density, pellet overlap, and defocusing. Therefore, this paper introduces an innovative visual imaging strategy leveraging the Mask R-CNN algorithm for non-invasive, real-time film thickness monitoring during fluidized bed coating processes. The proposed approach achieves precise pellet segmentation and effectively addresses challenges posed by pellet overlap, defocusing, and blurring. The superiority and accuracy of the Mask R-CNN algorithm were validated against traditional methods such as Otsu thresholding, Canny edge detection, and off-line techniques, including UV–visible spectrophotometry and laser diffraction. The sensitivity and robustness of the proposed approach were further explored under conditions of high contamination, overexposure, and low contrast arising from color variations. The results of this study demonstrate the potential of deep learning-based imaging to transform process analytical technology (PAT), facilitating dynamic and precise quality monitoring in pharmaceutical production.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"456 ","pages":"Article 120795"},"PeriodicalIF":4.5,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PLA/PBAT composite powder prepared by thermally induced phase separation for selective laser sintering

IF 4.5 2区工程技术 Q2 ENGINEERING, CHEMICAL

Powder Technology

Pub Date : 2025-02-13 DOI: 10.1016/j.powtec.2025.120799

Wanjun Li , Dongming Zou , Binling Chen , Yuan Wang

The application of selective laser sintering (SLS) across various industries is limited by the narrow range of available polymers. It is essential to develop new materials for SLS using sustainable methods. In this study, poly(lactic acid)/poly(butylene adipate-co-terephthalate) (PLA/PBAT) composite powders with great flowability were prepared in different ratios using thermally induced phase separation (TIPS). The particle size, morphology, and wide sintering window of the PLA/PBAT composite powders demonstrated their suitability for SLS. Optimized process parameters enabled the successful manufacturing of various specimens via SLS. Tensile tests revealed that the addition of PBAT improved the mechanical properties of the composite, with 3.5 wt% PBAT yielding the best results. PLA/PBAT composite powders produced via this environmentally friendly method were shown to be viable for use in SLS.

引用次数: 0

Damage evolution of UHPC under coupled high stress, temperature, and osmotic pressure: New multi-field experiment and non-destructive techniques

IF 4.5 2区工程技术 Q2 ENGINEERING, CHEMICAL

Powder Technology

Pub Date : 2025-02-12 DOI: 10.1016/j.powtec.2025.120793

Zhiyong Liu , Yunsheng Zhang , Gan Liu , Yuncheng Wang , Wanhao Yu , Jinyang Jiang

Underground structures in deep regions of ocean underground engineering are exposed to high stress, temperature, and osmotic pressure, which accelerate their damage and degradation. This work investigates the performance of ultra-high-performance concrete (UHPC) under these coupled conditions using a specially designed load-temperature-osmotic pressure coupling instrument. The damage evolution of UHPC was evaluated using ultrasonic pulse velocity (UPV), bulk density, and scanning electron microscopy (SEM). The results show that increasing the stress ratio causes greater damage to the UHPC while the damage and cracks in the UHPC under high temperatures and osmotic pressure are instead repaired. In addition, the number, width, and length of microcracks in UHPC increase with the increasing water-binder ratio. Reducing the water-cement ratio to 0.16 and incorporating 2 % steel fibers can result in the best performance in terms of damage resistance. These findings provide valuable insights into the application of UHPC in challenging underground structures in deep regions of ocean underground engineering.

海洋地下工程深层区域的地下结构暴露在高应力、高温度和高渗透压下，这加速了它们的损坏和退化。本研究使用专门设计的荷载-温度-渗透压耦合仪器，研究了超高性能混凝土（UHPC）在这些耦合条件下的性能。使用超声波脉冲速度（UPV）、体积密度和扫描电子显微镜（SEM）对超高性能混凝土的损伤演变进行了评估。结果表明，增加应力比会导致 UHPC 受到更大的破坏，而高温和渗透压条件下 UHPC 的损伤和裂缝反而会得到修复。此外，UHPC 中微裂缝的数量、宽度和长度随着水胶比的增加而增加。将水灰比降低到 0.16 并加入 2% 的钢纤维可获得最佳的抗损坏性能。这些发现为超高性能混凝土在海洋地下工程深层区域具有挑战性的地下结构中的应用提供了宝贵的见解。

{"title":"Damage evolution of UHPC under coupled high stress, temperature, and osmotic pressure: New multi-field experiment and non-destructive techniques","authors":"Zhiyong Liu , Yunsheng Zhang , Gan Liu , Yuncheng Wang , Wanhao Yu , Jinyang Jiang","doi":"10.1016/j.powtec.2025.120793","DOIUrl":"10.1016/j.powtec.2025.120793","url":null,"abstract":"<div><div>Underground structures in deep regions of ocean underground engineering are exposed to high stress, temperature, and osmotic pressure, which accelerate their damage and degradation. This work investigates the performance of ultra-high-performance concrete (UHPC) under these coupled conditions using a specially designed load-temperature-osmotic pressure coupling instrument. The damage evolution of UHPC was evaluated using ultrasonic pulse velocity (UPV), bulk density, and scanning electron microscopy (SEM). The results show that increasing the stress ratio causes greater damage to the UHPC while the damage and cracks in the UHPC under high temperatures and osmotic pressure are instead repaired. In addition, the number, width, and length of microcracks in UHPC increase with the increasing water-binder ratio. Reducing the water-cement ratio to 0.16 and incorporating 2 % steel fibers can result in the best performance in terms of damage resistance. These findings provide valuable insights into the application of UHPC in challenging underground structures in deep regions of ocean underground engineering.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"455 ","pages":"Article 120793"},"PeriodicalIF":4.5,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A barrel shape study for a twin-screw conveyor using the Discrete Element Method

IF 4.5 2区工程技术 Q2 ENGINEERING, CHEMICAL

Powder Technology

Pub Date : 2025-02-12 DOI: 10.1016/j.powtec.2025.120744

D. Rhymer, A. Ingram, C.R.K. Windows-Yule

An effective barrel design is critical for successful material transport in a twin-screw conveyor. However, geometric parameter studies are often overlooked because of their increased complexity over studying scalar parameters due to the cost of manufacturing multiple bespoke components. In recent years, advances in computing power have made simulations an attractive and low-cost method of conducting geometric parameter studies. Here a Discrete Element Method (DEM) study compares the effectiveness of eight barrel geometries in a twin-screw conveyor. The results showed that the industry-accepted figure-of-eight cylinder design was the most effective for particle transport with the greater interaction between the screw and barrel reducing the material throughput time by over 40% compared to other designs. However, alternatives might become attractive if certain specifications were desirable. A design with rounded sides and a flat centre is worse at conveying by 22% compared to the figure-of-eight but there is 15% less net force acting on the particles and similar amounts of mixing. Finally, parameter testing shows that the results will at least be qualitatively consistent across a wide range of the parameter space and should therefore be valid for most materials.

{"title":"A barrel shape study for a twin-screw conveyor using the Discrete Element Method","authors":"D. Rhymer, A. Ingram, C.R.K. Windows-Yule","doi":"10.1016/j.powtec.2025.120744","DOIUrl":"10.1016/j.powtec.2025.120744","url":null,"abstract":"<div><div>An effective barrel design is critical for successful material transport in a twin-screw conveyor. However, geometric parameter studies are often overlooked because of their increased complexity over studying scalar parameters due to the cost of manufacturing multiple bespoke components. In recent years, advances in computing power have made simulations an attractive and low-cost method of conducting geometric parameter studies. Here a Discrete Element Method (DEM) study compares the effectiveness of eight barrel geometries in a twin-screw conveyor. The results showed that the industry-accepted figure-of-eight cylinder design was the most effective for particle transport with the greater interaction between the screw and barrel reducing the material throughput time by over 40% compared to other designs. However, alternatives might become attractive if certain specifications were desirable. A design with rounded sides and a flat centre is worse at conveying by 22% compared to the figure-of-eight but there is 15% less net force acting on the particles and similar amounts of mixing. Finally, parameter testing shows that the results will at least be qualitatively consistent across a wide range of the parameter space and should therefore be valid for most materials.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"455 ","pages":"Article 120744"},"PeriodicalIF":4.5,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reconstruction of aeolian sand grain saltation based on inter-frame particle tracking algorithm and geometric constraints

IF 4.5 2区工程技术 Q2 ENGINEERING, CHEMICAL

Powder Technology

Pub Date : 2025-02-12 DOI: 10.1016/j.powtec.2025.120792

Kaiyuan Guan , Yang Zhang , Bin Yang , Yuanwei Lin , Xin Gao

The saltation trajectories of sand grains serve as a direct indicator of the two-phase interaction during the process of aeolian sand transport. Particle Tracking Velocimetry (PTV) has been employed to reconstruct these saltation trajectories. However, traditional PTV algorithms encounter difficulties due to the randomness and three-dimensional (3D) characteristics of sand-grain motion, which impede the complete reconstruction of saltation trajectories. This paper puts forward a PTV algorithm grounded on the Voronoi diagram (VD). It is demonstrated that this algorithm exhibits higher accuracy compared to other VD-based PTV algorithms. A homemade algorithm called Dual Angular Constraint (DAC) is introduced to support the proposed PTV algorithm, ensuring the most comprehensive reconstruction of saltation trajectories. Through a test using 3D artificial particle flows, the robustness of the proposed PTV algorithm in 3D space is validated. This validation offers the feasibility for the visualization of sand-grain motion in practical applications, accompanied by efficient and accurate kinematic analysis.

{"title":"Reconstruction of aeolian sand grain saltation based on inter-frame particle tracking algorithm and geometric constraints","authors":"Kaiyuan Guan , Yang Zhang , Bin Yang , Yuanwei Lin , Xin Gao","doi":"10.1016/j.powtec.2025.120792","DOIUrl":"10.1016/j.powtec.2025.120792","url":null,"abstract":"<div><div>The saltation trajectories of sand grains serve as a direct indicator of the two-phase interaction during the process of aeolian sand transport. Particle Tracking Velocimetry (PTV) has been employed to reconstruct these saltation trajectories. However, traditional PTV algorithms encounter difficulties due to the randomness and three-dimensional (3D) characteristics of sand-grain motion, which impede the complete reconstruction of saltation trajectories. This paper puts forward a PTV algorithm grounded on the Voronoi diagram (VD). It is demonstrated that this algorithm exhibits higher accuracy compared to other VD-based PTV algorithms. A homemade algorithm called Dual Angular Constraint (DAC) is introduced to support the proposed PTV algorithm, ensuring the most comprehensive reconstruction of saltation trajectories. Through a test using 3D artificial particle flows, the robustness of the proposed PTV algorithm in 3D space is validated. This validation offers the feasibility for the visualization of sand-grain motion in practical applications, accompanied by efficient and accurate kinematic analysis.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"455 ","pages":"Article 120792"},"PeriodicalIF":4.5,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Selecting effective powder characterization tests for reliable estimation of bin blending performance

IF 4.5 2区工程技术 Q2 ENGINEERING, CHEMICAL

Powder Technology

Pub Date : 2025-02-12 DOI: 10.1016/j.powtec.2025.120790

Fatemeh Mostafaei , Johannes G. Khinast , Thomas Forgber

The Discrete Element Method (DEM) has become an important tool for gaining a deeper understanding of granular blending. It allows for the evaluation of process performance in terms of blending and segregation before conducting experiments, thus shortening development times. While DEM simulations employ simplifications to overcome computational limits, they still need to accurately present the bulk granular behavior of real materials. In powder handling, ensuring the similarity between simulations and reality is achieved through model parameter calibration. Despite significant efforts in calibration, there is still no established method for selecting suitable test devices during the calibration step before applying DEM to a specific application. The current study addresses this gap by conducting a numerical investigation of pharmaceutical powders' behavior in characterization tests (including the rotating drum, compression, and shear tests) and in a lab-scale bin blender. A new parameter, called the circularity, is introduced in the data evaluation of the rotating drum process. Various statistical analyses are used to identify the most and least relevant parameters from the characterization tests that relate to the powder blending performance. In total, 15 parameters from the characterization tests were correlated with blending time and powder size segregation in the studied bin blender for 67 different powders.

{"title":"Selecting effective powder characterization tests for reliable estimation of bin blending performance","authors":"Fatemeh Mostafaei , Johannes G. Khinast , Thomas Forgber","doi":"10.1016/j.powtec.2025.120790","DOIUrl":"10.1016/j.powtec.2025.120790","url":null,"abstract":"<div><div>The Discrete Element Method (DEM) has become an important tool for gaining a deeper understanding of granular blending. It allows for the evaluation of process performance in terms of blending and segregation before conducting experiments, thus shortening development times. While DEM simulations employ simplifications to overcome computational limits, they still need to accurately present the bulk granular behavior of real materials. In powder handling, ensuring the similarity between simulations and reality is achieved through model parameter calibration. Despite significant efforts in calibration, there is still no established method for selecting suitable test devices during the calibration step before applying DEM to a specific application. The current study addresses this gap by conducting a numerical investigation of pharmaceutical powders' behavior in characterization tests (including the rotating drum, compression, and shear tests) and in a lab-scale bin blender. A new parameter, called the circularity, is introduced in the data evaluation of the rotating drum process. Various statistical analyses are used to identify the most and least relevant parameters from the characterization tests that relate to the powder blending performance. In total, 15 parameters from the characterization tests were correlated with blending time and powder size segregation in the studied bin blender for 67 different powders.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"456 ","pages":"Article 120790"},"PeriodicalIF":4.5,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fines migration and clogging under pH alteration: Stochastic model and its upscaling

IF 4.5 2区工程技术 Q2 ENGINEERING, CHEMICAL

Powder Technology

Pub Date : 2025-02-12 DOI: 10.1016/j.powtec.2025.120778

G. Loi, Y. Yang, C. Nguyen, T. Russell, P. Bedrikovetsky

Profound understanding of fine particle detachment, mobilisation, migration and consequent porous media clogging is essential for optimal design and clean-up of filter beds in water purification and wastewater treatment processes. In particular, changes in the solution pH affect the electrostatic force between particles and rocks which regulates particle detachment induced by viscous forces; fines detachment and migration usually leads to serious well rate decrease. The change in the concentration of attached particles when changing pH is quantified using a maximum retention function (MRF). Currently, this function can only be determined empirically from experiments despite strong theoretical foundations for predicting particle detachment. In this work, the microscale description of particle detachment is linked with macroscale predictions of particle detachment by averaging the condition of mechanical equilibrium over the distributions of microscale parameters. Heterogeneities of attached particles and pore space are reflected in probability distributions of relevant parameters. A Monte Carlo algorithm is implemented to combine the parameter distributions and detachment condition to calculate the MRF. The methodology allows for predictive modelling of particle detachment, and inverse modelling of the microscale parameter distributions. Inverse modelling is performed on two coreflooding tests in which the injected pH was varied. Fitting shows good agreement with the detachment model and the lever arm and aspect ratios determined during fitting are within commonly reported intervals. The model is used to recalculate the MRF versus velocity, which is then used to predict formation damage for production and injection wells at different values of pH.

{"title":"Fines migration and clogging under pH alteration: Stochastic model and its upscaling","authors":"G. Loi, Y. Yang, C. Nguyen, T. Russell, P. Bedrikovetsky","doi":"10.1016/j.powtec.2025.120778","DOIUrl":"10.1016/j.powtec.2025.120778","url":null,"abstract":"<div><div>Profound understanding of fine particle detachment, mobilisation, migration and consequent porous media clogging is essential for optimal design and clean-up of filter beds in water purification and wastewater treatment processes. In particular, changes in the solution pH affect the electrostatic force between particles and rocks which regulates particle detachment induced by viscous forces; fines detachment and migration usually leads to serious well rate decrease. The change in the concentration of attached particles when changing pH is quantified using a maximum retention function (MRF). Currently, this function can only be determined empirically from experiments despite strong theoretical foundations for predicting particle detachment. In this work, the microscale description of particle detachment is linked with macroscale predictions of particle detachment by averaging the condition of mechanical equilibrium over the distributions of microscale parameters. Heterogeneities of attached particles and pore space are reflected in probability distributions of relevant parameters. A Monte Carlo algorithm is implemented to combine the parameter distributions and detachment condition to calculate the MRF. The methodology allows for predictive modelling of particle detachment, and inverse modelling of the microscale parameter distributions. Inverse modelling is performed on two coreflooding tests in which the injected pH was varied. Fitting shows good agreement with the detachment model and the lever arm and aspect ratios determined during fitting are within commonly reported intervals. The model is used to recalculate the MRF versus velocity, which is then used to predict formation damage for production and injection wells at different values of pH.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"456 ","pages":"Article 120778"},"PeriodicalIF":4.5,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143508057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hygroscopic characteristics of salt particles based on molecular dynamics simulations

IF 4.5 2区工程技术 Q2 ENGINEERING, CHEMICAL

Powder Technology

Pub Date : 2025-02-11 DOI: 10.1016/j.powtec.2025.120787

Lingxiao Zhan , Xin Wang , Dawei Hou , Heng Chen , Suoqi Zheng , Yurui Wang , Zhihao Li , Zhanxing Chen , Hao Wu , Linjun Yang

Molecular dynamics simulations are performed to investigate the hygroscopic growth of typical salt particles and their mixtures in supersaturated water vapor. Nucleation and condensational growth are analyzed. The results showed the dominant factors controlling the growth of the salt particle are condensation and collisions thereafter. The salt particles help to the hygroscopic growth. MgCl₂ possesses the highest tendency of hygroscopicity. The self-diffusivity of water in the MgCl₂ case (1.54 × 10⁻⁶ m²/s) is much smaller than that of the homogeneous case (2.23 × 10⁻⁶ m²/s). Radial distribution analysis (RDF) confirms the dissociation of ionic bonds and the formation of the hydration shell. Particle number concentration (PNC) and particle mass concentration (PMC) have different influence mechanisms on nucleation and growth. Moreover, the supersaturation degree is modified by changing the vapor pressure and temperature. Homogeneous nucleation is found to be more susceptible to changes in supersaturation than heterogeneous nucleation.

{"title":"Hygroscopic characteristics of salt particles based on molecular dynamics simulations","authors":"Lingxiao Zhan , Xin Wang , Dawei Hou , Heng Chen , Suoqi Zheng , Yurui Wang , Zhihao Li , Zhanxing Chen , Hao Wu , Linjun Yang","doi":"10.1016/j.powtec.2025.120787","DOIUrl":"10.1016/j.powtec.2025.120787","url":null,"abstract":"<div><div>Molecular dynamics simulations are performed to investigate the hygroscopic growth of typical salt particles and their mixtures in supersaturated water vapor. Nucleation and condensational growth are analyzed. The results showed the dominant factors controlling the growth of the salt particle are condensation and collisions thereafter. The salt particles help to the hygroscopic growth. MgCl<sub>2</sub> possesses the highest tendency of hygroscopicity. The self-diffusivity of water in the MgCl<sub>2</sub> case (1.54 × 10<sup>−6</sup> m<sup>2</sup>/s) is much smaller than that of the homogeneous case (2.23 × 10<sup>−6</sup> m<sup>2</sup>/s). Radial distribution analysis (RDF) confirms the dissociation of ionic bonds and the formation of the hydration shell. Particle number concentration (PNC) and particle mass concentration (PMC) have different influence mechanisms on nucleation and growth. Moreover, the supersaturation degree is modified by changing the vapor pressure and temperature. Homogeneous nucleation is found to be more susceptible to changes in supersaturation than heterogeneous nucleation.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"455 ","pages":"Article 120787"},"PeriodicalIF":4.5,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Segmentation and tracking: A deep learning-based method for analyzing dynamic features of aluminum agglomerates

IF 4.5 2区工程技术 Q2 ENGINEERING, CHEMICAL

Powder Technology

Pub Date : 2025-02-11 DOI: 10.1016/j.powtec.2025.120785

Xiaohui Xue, Huanhuan Gao, Zhihao Sun, JianZhong Liu

The phenomenon of aluminum agglomeration, which occurs during the combustion of aluminized solid propellants, can have a series of adverse effects on solid rocket motors. High-speed microimaging has been demonstrated to be an effective technique for investigating this phenomenon. Consequently, an efficient and accurate analysis of aluminum agglomerates in high-speed video is a crucial aspect of this research. However, traditional analysis methods often produce unsatisfactory segmentation results in complex images and show low efficiency in extracting the features of the same agglomerate across multiple frames. To address these issues, this study proposes an online analysis method based on deep learning, which allows for the real-time segmentation and cross-frame tracking of aluminum agglomerates. Comparative experiments with the classical threshold-based method demonstrate the effectiveness and superior accuracy of the proposed method, with the AP50 metric improving significantly from 0.546 to 0.940, achieving impressive segmentation performance. Subsequently, the method was employed to analyze the overall velocity characteristics, features of individual agglomerates, and the second mergence phenomenon of aluminum agglomerates. The analysis captured the complete dynamic process of agglomerates from formation to exiting the frame and yield a linear correlation between the projected area and maximum vertical velocity. The proposed method markedly simplifies the analysis process for aluminum agglomerates, furnishes more detailed dynamic information, and provides robust support for further studies on aluminum particle combustion and agglomeration mechanisms.

{"title":"Segmentation and tracking: A deep learning-based method for analyzing dynamic features of aluminum agglomerates","authors":"Xiaohui Xue, Huanhuan Gao, Zhihao Sun, JianZhong Liu","doi":"10.1016/j.powtec.2025.120785","DOIUrl":"10.1016/j.powtec.2025.120785","url":null,"abstract":"<div><div>The phenomenon of aluminum agglomeration, which occurs during the combustion of aluminized solid propellants, can have a series of adverse effects on solid rocket motors. High-speed microimaging has been demonstrated to be an effective technique for investigating this phenomenon. Consequently, an efficient and accurate analysis of aluminum agglomerates in high-speed video is a crucial aspect of this research. However, traditional analysis methods often produce unsatisfactory segmentation results in complex images and show low efficiency in extracting the features of the same agglomerate across multiple frames. To address these issues, this study proposes an online analysis method based on deep learning, which allows for the real-time segmentation and cross-frame tracking of aluminum agglomerates. Comparative experiments with the classical threshold-based method demonstrate the effectiveness and superior accuracy of the proposed method, with the <em>AP50</em> metric improving significantly from 0.546 to 0.940, achieving impressive segmentation performance. Subsequently, the method was employed to analyze the overall velocity characteristics, features of individual agglomerates, and the second mergence phenomenon of aluminum agglomerates. The analysis captured the complete dynamic process of agglomerates from formation to exiting the frame and yield a linear correlation between the projected area and maximum vertical velocity. The proposed method markedly simplifies the analysis process for aluminum agglomerates, furnishes more detailed dynamic information, and provides robust support for further studies on aluminum particle combustion and agglomeration mechanisms.</div></div>","PeriodicalId":407,"journal":{"name":"Powder Technology","volume":"455 ","pages":"Article 120785"},"PeriodicalIF":4.5,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143427525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exhaust gas recirculation cooler fouling morphology: Characterisation, spatiotemporal nature, and system variable-morphology-property correlation

IF 4.5 2区工程技术 Q2 ENGINEERING, CHEMICAL

Powder Technology

Pub Date : 2025-02-11 DOI: 10.1016/j.powtec.2025.120786

Yipeng Yao , Zhiqiang Han , Liping Luo , Hai Du , Wei Tian , Xueshun Wu , Zinong Zuo , Marie-Eve Duprez , Guy De Weireld

Fouling is one of the primary causes of failure in exhaust gas recirculation (EGR) coolers. Morphology may provide a powerful perspective for understanding the mechanisms, behaviours, and properties of fouling. However, a systematic review of fouling morphology is currently lacking. Considering the substantial progress made in morphology-related studies within the industry in recent years, this work reviews the findings on EGR cooler fouling morphology from four aspects: characterisation (scale, object, category, and technique), spatiotemporal nature, variable-morphology correlation, and morphology-property correlation. Furthermore, the current challenges and opportunities in this field are discussed. Based on this, we propose a framework for the morphological characterisation of EGR cooler fouling. It is demonstrated that morphology plays a crucial role in revealing the spatiotemporal characteristics of fouling, the formation and removal mechanisms, and the correlations among system variables, morphology, and properties. Morphology still holds significant potential in four areas: multi-scale and quantitative characterisation, nomenclature and taxonomy, and full lifecycle evolution. The findings provide a morphological perspective for fouling research within the industry and contribute to advancing the science of fouling morphology.

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