Object detection with an alkali-metal spin maser

2021 ◽  
Vol 130 (21) ◽  
pp. 214501
Author(s):  
P. Bevington ◽  
R. Gartman ◽  
W. Chalupczak
Keyword(s):  
Alkali Metal ◽  
Object Detection ◽  
Spin Maser

Alkali-metal spin maser for non-destructive tests

2019 ◽  
Vol 115 (17) ◽  
pp. 173502 ◽  
Author(s):  
P. Bevington ◽  
R. Gartman ◽  
W. Chalupczak
Keyword(s):  
Alkali Metal ◽  
Spin Maser ◽  
Non Destructive

Alkali-Metal Spin Maser

2015 ◽  
Vol 115 (3) ◽  
Author(s):  
W. Chalupczak ◽  
P. Josephs-Franks
Keyword(s):  
Alkali Metal ◽  
Spin Maser

Magnetic induction tomography of structural defects with alkali–metal spin maser

2020 ◽  
Vol 59 (8) ◽  
pp. 2276 ◽  
Author(s):  
Patrick Bevington ◽  
Rafal Gartman ◽  
Witold Chalupczak
Keyword(s):  
Alkali Metal ◽  
Magnetic Induction ◽  
Structural Defects ◽  
Spin Maser ◽  
Magnetic Induction Tomography

Modeling fine particles and alkali metal compound behavior in a kraft recovery boiler

TAPPI Journal ◽  
2012 ◽  
Vol 11 (7) ◽  
pp. 9-14 ◽  
Author(s):  
AINO LEPPÄNEN ◽  
ERKKI VÄLIMÄKI ◽  
ANTTI OKSANEN
Keyword(s):  
Alkali Metal ◽  
Computational Models ◽  
Fine Particles ◽  
Black Liquor ◽  
Melting Behavior ◽  
Metal Compound ◽  
Effect Of Temperature ◽  
Particle Model ◽  
Boiler Furnace ◽  
Recovery Boiler

Under certain conditions, ash in black liquor forms a locally corrosive environment in a kraft recovery boiler. The ash also might cause efficiency losses and even boiler shutdown because of plugging of the flue gas passages. The most troublesome compounds in a fuel such as black liquor are potassium and chlorine because they change the melting behavior of the ash. Fouling and corrosion of the kraft recovery boiler have been researched extensively, but few computational models have been developed to deal with the subject. This report describes a computational fluid dynamics-based method for modeling the reactions between alkali metal compounds and for the formation of fine fume particles in a kraft recovery boiler furnace. The modeling method is developed from ANSYS/FLUENT software and its Fine Particle Model extension. We used the method to examine gaseous alkali metal compound and fine fume particle distributions in a kraft recovery boiler furnace. The effect of temperature and the boiler design on these variables, for example, can be predicted with the model. We also present some preliminary results obtained with the model. When the model is developed further, it can be extended to the superheater area of the kraft recovery boiler. This will give new insight into the variables that increase or decrease fouling and corrosion

Automatic accounting of Baikal diatomic algae: approaches and prospects

2019 ◽  
pp. 295-299
Author(s):  
Кonstantin А. Elshin ◽  
Еlena I. Molchanova ◽  
Мarina V. Usoltseva ◽  
Yelena V. Likhoshway
Keyword(s):  
Object Detection ◽  
Loss Function ◽  
Classification Accuracy ◽  
Diatom Species ◽  
Bounding Box ◽  
Synedra Acus ◽  
And Training

Using the TensorFlow Object Detection API, an approach to identifying and registering Baikal diatom species Synedra acus subsp. radians has been tested. As a result, a set of images was formed and training was conducted. It is shown that аfter 15000 training iterations, the total value of the loss function was obtained equal to 0,04. At the same time, the classification accuracy is equal to 95%, and the accuracy of construction of the bounding box is also equal to 95%.

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