Exciplex Fluorescence Thermometry of Liquid Fuel

1989 ◽  
Vol 43 (2) ◽  
pp. 274-278 ◽  
Author(s):  
John H. Stufflebeam
Keyword(s):  
Liquid Fuel ◽  
Fluorescence Spectra ◽  
High Accuracy ◽  
Prediction Algorithm ◽  
Experimental Program ◽  
Temperature Dependent ◽  
Temperature Prediction ◽  
Flowing Liquid ◽  
Fluorescence Thermometry ◽  
Exciplex Fluorescence

An experimental program is described that investigates the application of exciplex fluorescence to the internal thermometry of flowing liquid decane in the temperature range 24–91°C. Decane is doped with pyrene and excited by laser radiation at 354.7 nm. A library of temperature-dependent, exciplex fluorescence spectra is obtained from a static, isothermal solution, and the spectral features are analyzed to produce a temperature-prediction algorithm. The solution then flows through a temperature gradient region, and the laser-induced fluorescence spectra that are recorded are used to determine the local temperature in the solution by application of the algorithm. Excellent agreement between the predicted temperatures and those measured by thermocouples in contact with the solution is realized. The experiment demonstrates the high accuracy and spatial resolution obtainable with this laser-based thermometry technique.

scholarly journals Investigation of Five Organic Dyes in Ethanol and Butanol for Two-Color Laser-Induced Fluorescence Ratio Thermometry

Optics ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Yogeshwar Nath Mishra ◽  
Ajeth Yoganantham ◽  
Matthias Koegl ◽  
Lars Zigan
Keyword(s):  
Rhodamine B ◽  
Fluorescence Spectra ◽  
Rhodamine 6G ◽  
Organic Dyes ◽  
Laser Induced Fluorescence ◽  
Eosin Y ◽  
Temperature Dependent ◽  
Spectral Bands ◽  
Sulforhodamine 101 ◽  
Fluorescence Thermometry

In this article, we compare absorption and temperature-dependent fluorescence spectra of five organic dyes for 2c-LIF (two-color laser-induced fluorescence) thermometry in ethanol and butanol. The dyes fluorescein, eosin Y, rhodamine B, rhodamine 6G, and sulforhodamine 101 individually mixed in ethanol and butanol were studied at liquid temperatures of 25–65 °C. The self-absorption spectral bands are analyzed along with intensity ratios and the respective sensitivities for one-dye and two-dye 2c-LIF thermometry are deduced. For one-dye 2c-LIF, rhodamine B showed the highest sensitivity of 2.93%/°C and 2.89%/°C in ethanol and butanol, respectively. Sulforhodamine 101 and rhodamine 6G showed the least sensitivities of 0.51%/°C and 1.24%/°C in ethanol and butanol, respectively. For two-dye 2c-LIF, rhodamine B/sulforhodamine 101 exhibited the highest temperature sensitivities of 2.39%/°C and 2.54%/°C in ethanol and butanol, respectively. The dye pair eosin Y/sulforhodamine 101 showed the least sensitivities of 0.15%/°C and 0.27%/°C in ethanol and butanol, respectively.

scholarly journals Temperature Prediction of PMSMs Using Pseudo-Siamese Nested LSTM

2021 ◽  
Vol 12 (2) ◽  
pp. 57
Author(s):  
Yongping Cai ◽  
Yuefeng Cen ◽  
Gang Cen ◽  
Xiaomin Yao ◽  
Cheng Zhao ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Simple Structure ◽  
High Accuracy ◽  
Stator Winding ◽  
High Power Density ◽  
Temperature Prediction ◽  
Permanent Magnet Synchronous Motors ◽  
Training Performance ◽  
Synchronous Motors ◽  
Better Than

Permanent Magnet Synchronous Motors (PMSMs) are widely used in electric vehicles due to their simple structure, small size, and high power-density. The research on the temperature monitoring of the PMSMs, which is one of the critical technologies to ensure the operation of PMSMs, has been the focus. A Pseudo-Siamese Nested LSTM (PSNLSTM) model is proposed to predict the temperature of the PMSMs. It takes the features closely related to the temperature of PMSMs as input and realizes the temperature prediction of stator yoke, stator tooth, and stator winding. An optimization algorithm of learning rate combined with gradual warmup and decay is proposed to accelerate the convergence during the training and improve the training performance of the model. Experimental results reveal the proposed method and Nested LSTM (NLSTM) achieves high accuracy by comparing with other intelligent prediction methods. Moreover, the proposed method is slightly better than NLSTM in temperature prediction of PMSMS.

A Novel Machine Learning Sepsis Prediction Algorithm for Intended ICU Use (NAVOY Sepsis): A Proof-of-Concept Study (Preprint)

2021 ◽  
Author(s):  
Inger Persson ◽  
Andreas Östling ◽  
Martin Arlbrandt ◽  
Joakim Söderberg ◽  
David Becedas
Keyword(s):  
Machine Learning ◽  
High Performance ◽  
Learning Algorithm ◽  
Scoring Systems ◽  
High Accuracy ◽  
Prediction Algorithm ◽  
Massachusetts Institute Of Technology ◽  
Operating Characteristics ◽  
Mortality And Morbidity ◽  
Institute Of Technology

BACKGROUND Despite decades of research, sepsis remains a leading cause of mortality and morbidity in ICUs worldwide. The key to effective management and patient outcome is early detection, where no prospectively validated machine learning prediction algorithm is available for clinical use in Europe today. OBJECTIVE To develop a high-performance machine learning sepsis prediction algorithm based on routinely collected ICU data, designed to be implemented in Europe. METHODS The machine learning algorithm is developed using Convolutional Neural Network, based on the Massachusetts Institute of Technology Lab for Computational Physiology MIMIC-III Clinical Database, focusing on ICU patients aged 18 years or older. Twenty variables are used for prediction, on an hourly basis. Onset of sepsis is defined in accordance with the international Sepsis-3 criteria. RESULTS The developed algorithm NAVOY Sepsis uses 4 hours of input and can with high accuracy predict patients with high risk of developing sepsis in the coming hours. The prediction performance is superior to that of existing sepsis early warning scoring systems, and competes well with previously published prediction algorithms designed to predict sepsis onset in accordance with the Sepsis-3 criteria, as measured by the area under the receiver operating characteristics curve (AUROC) and the area under the precision-recall curve (AUPRC). NAVOY Sepsis yields AUROC = 0.90 and AUPRC = 0.62 for predictions up to 3 hours before sepsis onset. The predictive performance is externally validated on hold-out test data, where NAVOY Sepsis is confirmed to predict sepsis with high accuracy. CONCLUSIONS An algorithm with excellent predictive properties has been developed, based on variables routinely collected at ICUs. This algorithm is to be further validated in an ongoing prospective randomized clinical trial and will be CE marked as Software as a Medical Device, designed for commercial use in European ICUs.

Exciplex Fluorescence Thermometry of Falling Hexadecane Droplets

1992 ◽  
Vol 114 (2) ◽  
pp. 450-457 ◽  
Author(s):  
T. R. Hanlon ◽  
L. A. Melton
Keyword(s):  
Droplet Radius ◽  
Droplet Volume ◽  
Sharp Rise ◽  
Optical Sampling ◽  
Fluorescence Thermometry ◽  
Exciplex Fluorescence

Exciplex fluorescence thermometry has been used to measure the temperature of 283 micron hexadecane droplets falling through a quiescent, oxygen-free, approximately 500°C ambient. After a period of negligible change, the derived droplet temperatures exhibit a sharp rise of about 100°C followed by a gentle increase to approximately 200°C. The derived temperatures, although averaged over most of the volume of the droplet, still provide some evidence of internal processes in the droplet due to the partially selective optical sampling of the droplet volume, in which fluorescence from the region between 0.50 and 0.75 of the droplet radius contributes disproportionately. At longer times, the droplet is presumed to be approximately homogeneous, and the exciplex fluorescence thermometry measurements provide accurate, interpretable temperatures for the freely falling droplets.

Systematic errors in the high-accuracy universal polarimeter: application to determining temperature-dependent optical anisotropy of KDC and KDP crystals

2000 ◽  
Vol 33 (3) ◽  
pp. 938-946 ◽  
Author(s):  
C. Hernández-Rodríguez ◽  
P. Gómez-Garrido ◽  
S. Veintemillas
Keyword(s):  
Optical Anisotropy ◽  
Experimental System ◽  
High Accuracy ◽  
Optical Quality ◽  
Temperature Dependent ◽  
Order Of Magnitude ◽  
Mechanical Elements ◽  
Kdp Crystals ◽  
Detection Unit ◽  
Good Optical Quality

The problem of removing the characteristic parasitic errors of the high-accuracy universal polarimeter method in a linearly birefringent and optically active crystal section is examined. The use of constant parasitic errors typical of each particular polarimetric system is shown to be inappropriate. The parasitics should preferably be determined in each measurement process, since the instrumental parasitics depend not only on the optical and mechanical elements of the experimental system (polarizers, rotators, detection unitetc.), but on sample quality, alignment of the system, and even in many cases on exactly where the light beam passes through the sample. Thus, measurements with different samples give different values of parasitic errors. Such instrumental parasitics can be held within the same order of magnitude for different samples (∼10−4) if they are of good optical quality. However, the parasitics are increased by an order of magnitude (∼10−3) when the samples are of moderate or bad optical quality. Optical anisotropy properties as coefficients of thermal variation of the birefringence of KDC and KDP single crystals and the optical activity of KDP at 632.8 nm wavelength are obtained, in the ranges from room temperature to 353 K and to 373 K, respectively.

Thermochromic shifts of some molecular and exciplex fluorescence spectra

1987 ◽  
Vol 139 (6) ◽  
pp. 499-502 ◽  
Author(s):  
Thomas Hagan ◽  
Denis Pilloud ◽  
Paul Suppan
Keyword(s):  
Fluorescence Spectra ◽  
Exciplex Fluorescence
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