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Aleksandar Jemcov
Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA

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Communication
Published: 30 July 2021 in Sensors
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An artificial neural network (ANN) was constructed and trained for predicting pressure sensitivity using an experimental dataset consisting of luminophore content and paint thickness as chemical and physical inputs. A data augmentation technique was used to increase the number of data points based on the limited experimental observations. The prediction accuracy of the trained ANN was evaluated by using a metric, mean absolute percentage error. The ANN predicted pressure sensitivity to luminophore content and to paint thickness, within confidence intervals based on experimental errors. The present approach of applying ANN and the data augmentation has the potential to predict pressure-sensitive paint (PSP) characterizations that improve the performance of PSP for global surface pressure measurements.

ACS Style

Mitsugu Hasegawa; Daiki Kurihara; Yasuhiro Egami; Hirotaka Sakaue; Aleksandar Jemcov. Predicting Pressure Sensitivity to Luminophore Content and Paint Thickness of Pressure-Sensitive Paint Using Artificial Neural Network. Sensors 2021, 21, 5188 .

AMA Style

Mitsugu Hasegawa, Daiki Kurihara, Yasuhiro Egami, Hirotaka Sakaue, Aleksandar Jemcov. Predicting Pressure Sensitivity to Luminophore Content and Paint Thickness of Pressure-Sensitive Paint Using Artificial Neural Network. Sensors. 2021; 21 (15):5188.

Chicago/Turabian Style

Mitsugu Hasegawa; Daiki Kurihara; Yasuhiro Egami; Hirotaka Sakaue; Aleksandar Jemcov. 2021. "Predicting Pressure Sensitivity to Luminophore Content and Paint Thickness of Pressure-Sensitive Paint Using Artificial Neural Network." Sensors 21, no. 15: 5188.

Review
Published: 14 July 2021 in Aerospace
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Icing on an aircraft is the cause of numerous adverse effects on aerodynamic performance. Although the issue was recognized in the 1920s, the icing problem is still an area of ongoing research due to the complexity of the icing phenomena. This review article aims to summarize current research on aircraft icing in two fundamental topics: icing physics and icing mitigation techniques. The icing physics focuses on fixed wings, rotors, and engines severely impacted by icing. The study of engine icing has recently become focused on ice-crystal icing. Icing mitigation techniques reviewed are based on active, passive, and hybrid methods. The active mitigation techniques include those based on thermal and mechanical methods, which are currently in use on aircraft. The passive mitigation techniques discussed are based on current ongoing studies in chemical coatings. The hybrid mitigation technique is reviewed as a combination of the thermal method (active) and chemical coating (passive) to lower energy consumption.

ACS Style

Masafumi Yamazaki; Aleksandar Jemcov; Hirotaka Sakaue. A Review on the Current Status of Icing Physics and Mitigation in Aviation. Aerospace 2021, 8, 188 .

AMA Style

Masafumi Yamazaki, Aleksandar Jemcov, Hirotaka Sakaue. A Review on the Current Status of Icing Physics and Mitigation in Aviation. Aerospace. 2021; 8 (7):188.

Chicago/Turabian Style

Masafumi Yamazaki; Aleksandar Jemcov; Hirotaka Sakaue. 2021. "A Review on the Current Status of Icing Physics and Mitigation in Aviation." Aerospace 8, no. 7: 188.

Journal article
Published: 12 April 2016 in Journal of Engineering for Gas Turbines and Power
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The tabulated premixed conditional moment closure (T-PCMC) method has been shown to provide the capability to model turbulent, premixed methane flames with detailed chemistry and reasonable runtimes in Reynolds-averaged Navier–Stokes (RANS) environment by Martin et al. (2013, “Modeling an Enclosed, Turbulent Reacting Methane Jet With the Premixed Conditional Moment Closure Method,” ASME Paper No. GT2013-95092). Here, the premixed conditional moment closure (PCMC) method is extended to large eddy simulation (LES). The new model is validated with the turbulent, enclosed reacting methane backward facing step data from El Banhawy et al. (1983, “Premixed, Turbulent Combustion of a Sudden-Expansion Flow,” Combust. Flame, 50, pp. 153–165). The experimental data have a rectangular test section at atmospheric pressure and temperature with an inlet velocity of 10.5 m/s and an equivalence ratio of 0.9 for two different step heights. Contours of major species, velocity, and temperature are provided. The T-PCMC model falls into the class of table lookup turbulent combustion models in which the combustion model is solved offline over a range of conditions and stored in a table that is accessed by the computational fluid dynamic (CFD) code using three controlling variables: the reaction progress variable (RPV), variance, and local scalar dissipation rate. The local scalar dissipation rate is used to account for the affects of the small-scale mixing on the reaction rates. A presumed shape beta function probability density function (PDF) is used to account for the effects of subgrid scale (SGS) turbulence on the reactions. SGS models are incorporated for the scalar dissipation and variance. The open source CFD code OpenFOAM is used with the compressible Smagorinsky LES model. Velocity, temperature, and major species are compared to the experimental data. Once validated, this low “runtime” CFD turbulent combustion model will have great utility for designing the next generation of lean premixed (LPM) gas turbine combustors.

ACS Style

Carlos Velez; Scott Martin; Aleksander Jemcov; Subith Vasu. Large Eddy Simulation of an Enclosed Turbulent Reacting Methane Jet With the Tabulated Premixed Conditional Moment Closure Method. Journal of Engineering for Gas Turbines and Power 2016, 138, 101501 .

AMA Style

Carlos Velez, Scott Martin, Aleksander Jemcov, Subith Vasu. Large Eddy Simulation of an Enclosed Turbulent Reacting Methane Jet With the Tabulated Premixed Conditional Moment Closure Method. Journal of Engineering for Gas Turbines and Power. 2016; 138 (10):101501.

Chicago/Turabian Style

Carlos Velez; Scott Martin; Aleksander Jemcov; Subith Vasu. 2016. "Large Eddy Simulation of an Enclosed Turbulent Reacting Methane Jet With the Tabulated Premixed Conditional Moment Closure Method." Journal of Engineering for Gas Turbines and Power 138, no. 10: 101501.