Airflow Regimes and Thermal Pattern in Archeological Monuments

2018 ◽  
pp. 86-117
Author(s):  
MISSING-VALUE MISSING-VALUE
Keyword(s):  
Thermal Pattern

Snow on a thermal pattern

1984 ◽  
Vol 22 (1) ◽  
pp. 29-29
Author(s):  
A. B. Western
Keyword(s):  
Thermal Pattern

scholarly journals Fuzzy Controller Applied to a Remote Energy Harvesting Emulation Platform

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5874 ◽  
Author(s):  
Marcelo Miranda Camboim ◽  
Juan Moises Maurício Villanueva ◽  
Cleonilson Protasio de Souza
Keyword(s):  
Renewable Energy ◽  
Energy Harvesting ◽  
Renewable Energy Sources ◽  
Setting Time ◽  
Pi Controller ◽  
Step Response ◽  
Energy Sources ◽  
Thermal Source ◽  
Proportional Integral ◽  
Thermal Pattern

In the last decades, a lot of effort has been made in order to improve the use of environmentally friendly and renewable energy sources. In a context of small energy usage, energy harvesting takes place and thermal energy sources are one of its main energy sources because there are several unused heat sources available in the environment that may be used as renewable energy sources. To rapidly evaluate the energy potential of such thermal sources is a hard task, therefore, a way to perform this is welcome. In this work, a thermal pattern emulation system to evaluate potential thermal source in a easy way is proposed. The main characteristics of the proposed system is that it is online and remote, that is, while the thermal-source-under-test is being measured, the system is emulating it and evaluating the generated energy remotely. The main contribution of this work was to replace the conventional Proportional Integral Derivative (PID) controller to a Fuzzy-Proportional Integral (PI) controller. In order to compare both controllers, three tests were carried out, namely: (a) step response, (b) perturbation test, (c) thermal emulation of the thermal pattern obtained from a potential thermal source: tree trucks. Experimental results show that the Fuzzy-PI controller was faster than the PID, achieving a setting time 41.26% faster, and also was more efficient with a maximum error 53% smaller than the PID.

Immune Response Related With Skin Thermal Pattern in Judokas: A New Application for Infrared Thermography?

2020 ◽  
Vol 34 (10) ◽  
pp. 2886-2894 ◽  
Author(s):  
Ciro J. Brito ◽  
Danilo G. Moreira ◽  
José J. Ferreira ◽  
Alfonso L. Díaz-de-Durana ◽  
Bianca Miarka ◽  
...  
Keyword(s):  
Immune Response ◽  
Infrared Thermography ◽  
Thermal Pattern

scholarly journals Thermal Pattern Contrast Diagnostic of Microcracks With Induction Thermography for Aircraft Braking Components

2018 ◽  
Vol 14 (12) ◽  
pp. 5563-5574 ◽  
Author(s):  
Yizhe Wang ◽  
Bin Gao ◽  
Wai lok Woo ◽  
Guiyun Tian ◽  
Xavier Maldague ◽  
...  
Keyword(s):  
Thermal Pattern

Thermal pattern reconstruction of surface condition on freeform-surface using eddy current pulsed thermography

2016 ◽  
Vol 251 ◽  
pp. 248-257 ◽  
Author(s):  
Danping Huang ◽  
Kongjing Li ◽  
Gui Yun Tian ◽  
Ali Imam Sunny ◽  
Xiaotian Chen ◽  
...  
Keyword(s):  
Eddy Current ◽  
Surface Condition ◽  
Freeform Surface ◽  
Pulsed Thermography ◽  
Thermal Pattern ◽  
Pattern Reconstruction

THERMAL IMAGING AS AN ADJUNCT TOOL FOR IDENTIFYING FETAL GROWTH – A PILOT STUDY

2017 ◽  
Vol 17 (04) ◽  
pp. 1750071
Author(s):  
R. SAI DIVYA ◽  
S. MOHAMED YACIN ◽  
KAMALA SELVARAJ ◽  
NATTERI M. SUDHARSAN
Keyword(s):  
Pilot Study ◽  
Fetal Growth ◽  
Thermal Imaging ◽  
Vital Role ◽  
Temperature Pattern ◽  
Health Issues ◽  
Fetal Abnormality ◽  
Thermal Pattern ◽  
Human Interpretation ◽  
Healthy Growth

Monitoring the fetal growth and diagnosing any possible abnormality plays a vital role in ensuring the healthy growth of a fetus. Certain health issues like Hyperthermia, Premature Rupture of Membranes (PROM) and Intrauterine Growth Restriction (IUGR) has to be diagnosed early. A pilot study comprising of 27 pregnant and 2 non-pregnant subjects was conducted to check the effectiveness of Thermal imaging in predicting the fetal growth. The heat dissipated by the fetus to the maternal abdominal wall is acquired as a surface thermal distribution. These images were processed qualitatively and quantitatively for better understanding. There was a consistent higher thermal pattern for pregnant women. A more pronounced temperature pattern is notable in the umbilical region that correlates with gestation age. However, as thermal pattern varies with age, gestation period and BMI, it is advisable to track the same person and compare the images for better assessment. This pilot study justifies the need for more elaborate study in building a database for classification and interpretation of thermogram to detect fetal abnormality with reduced human interpretation.

Inverse thermal modeling and experimental validation for breast tumor detection by using highly personalized surface thermal patterns and geometry of the breast

2020 ◽  
pp. 095440622097059
Author(s):  
O Mukhmetov ◽  
A Mashekova ◽  
Y Zhao ◽  
EYK Ng ◽  
A Midlenko ◽  
...  
Keyword(s):  
Numerical Modeling ◽  
Response Surface ◽  
Inverse Modeling ◽  
Breast Tumor ◽  
Optimization Method ◽  
Efficient Design ◽  
Ir Thermography ◽  
Direct Optimization ◽  
Response Surface Optimization ◽  
Thermal Pattern

Infrared (IR) Thermography is currently a supplementary technique for breast cancer diagnosis. There have been studies using IR thermography and numerical modeling in an attempt to detect tumor inside the breast. Most of these studies focused on either the “forward modeling” problem or only used idealized or population-averaged patients’ data, whereas identification of the tumor inside the breast based on the thermal pattern is an “inverse modeling” problem dependent on personalized information of the patient. Inverse modeling is based on the idea that the surface thermal pattern of the breast can be used to determine the tumor features based on physical and physiological principles. The current study aims to develop a well-validated inverse thermal modeling framework that could be used to determine the depth and size of tumor inside a breast based on personalized patients’ breast data, such as thermogram and 3D geometry using efficient design optimization techniques and Finite Element Modeling (FEM) to support the process. The numerical modeling was validated by the experiments, conducted using artificial breasts. Results show that although DIRECT Optimization method can be employed to find the depth and size of the tumor with good accuracy, the technique can be very time consuming. On the other hand, Response Surface Optimization method is also able to find the depth and size of the tumor with less accuracy but faster when compared with DIRECT Optimization. The last method tested, Nelder-Mead method, failed to detect the tumor. The study concludes that Response Surface Optimization method should be used first, and after the range of parameters are found, the DIRECT optimization method can be applied for more accurate results. However the GA method was found to be the only viable and efficient design optimization method for reverse modeling when blood perfusion was adopted in the breast model and many parameters were searched for with patient specific data input for breast tumor diagnosis.

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