Installation and Testing of a Jorin Visual Process Analyzer

Kristi M Christensen

关键词: BUBBLES;    COMPUTERIZED SIMULATION;    COMPUTERS;    EFFICIENCY;    FLUID MECHANICS;    MASS TRANSFER;    MICROSCOPES;    OPACITY;    PROCUREMENT;    SHAPE;    SIMULATION;    SOLVENT EXTRACTION;    TESTING droplet analysis;    mass transfer;    solvent e;   

DOI  :  10.2172/1004258
RP-ID  :  INL/EXT-10-20024
PID  :  OSTI ID: 1004258
Others  :  TRN: US1100956

学科分类：核能源与工程

美国|英语

来源: SciTech Connect

【 摘 要 】

The Jorin Visual Process Analyzer (ViPA) is an on-line instrument that uses video microscope imaging to detect and measure the physical characteristics of dispersed objects within a process stream or laboratory sample. Object analysis is performed by capturing an on-going sequence of single frames from the video feed and relaying the images in real time to a nearby control computer where the ViPA software then processes and transfigures the information from the images into meaningful process data. The ViPA captures and analyzes approximately 15 images per second and continuously records 17 material parameters including size, shape and optical density. The ViPA software uses the measured parameters to differentiate between different classes of objects including organic droplets, gas bubbles, and solid particles. Procurement of this instrument provides a unique capability to support predictive modeling and further understanding of mass transfer during solvent extraction processes. Organic droplet data collected using the ViPA can be used to develop dispersion profiles of the liquid-liquid mixing and disengagements sections for each type of process equipment. These profiles will provide insight into mixing dynamics and will guide the prevention of emulsion formation that leads to system losses. Additionally, the measurement capabilities of the ViPA will provide the input needed to create new two-phase Computational Fluid Dynamics (CFD) models that characterize both mixing and separation operations in the various types of equipment. These models can then be used to improve process efficiency by optimizing operation parameters for each proposed extraction cycle.