Geometry-Driven Optimization of Orifices for Multidisciplinary Engineering Applications: Optimization of Orifices for Viscous Fluids Santosh Kumar Panda, Kali Charan Rath, Balaji Kumar Choudhury Advancing Sustainable Engineering Through Next Generation Thermo Fluid Systems, 2025 Flow measurement is a critical component across numerous industrial sectors. The orifice meter has become a preferred alternative to traditional wellhead chokes, offering enhanced control and precision in measuring mass flow rate. It is suitable for fluid flow measurements, utilizing in pressure drop and the discharge coefficient. This chapter explores orifice meters in detail, focusing on the impact of various shapes, sizes, classifications, and operational parameters on their performance for high viscous fluid flow applications.This chapter considered different orifices such as sector, crescent, segmental to determine the flow charteristics on the effect of input parameters. It examines how changes in shape factor, width factor, and non-dimensional flow coefficient affect velocity, pressure drop and discharge coefficient of upside and downside of the flow. This study presents vital approaches into the more efficient design for high viscous flow application of orifice meters.
TWO-PHASE FLOW MEASUREMENT THROUGH AN ORIFICE METER WITH REGRESSION ANALYSIS Aswini Kumar Khuntia, Santosh Kumar Panda, Souren Misra International Journal of Fluid Mechanics Research, 2025 Orifice is a very simple fluid flow measuring device. Pressure drop (&#916;<i>p</i>) is vital along the cross section of the orifice for the prediction of flow rate (<i>m</i>) in relation to fluid flow problems. Flow measurement in a single phase is greatly resolved whereas multiphase flows need more experimental and numerical studies. Many correlations are developed through experimental and numerical studies, but further studies will greatly resolve the multiphase problem. The &#916;<i>p</i> along the orifice depends on the Reynolds number (Re), area ratio (AR), and volume fraction (&alpha;) of air-water mixture flow. In the present work, a numerical analysis is conducted by varying the above parameters, Re &#60; 100,000, 0.2 &#60; AR &#60; 0.7, and 0.1 &#60; &alpha; &#60; 0.9). Then the present work uses machine learning (ML) to calculate the &#916;<i>p</i> and is employed to calculate m. The ML techniques used in this analysis include gradient boosting regression, polynomial regression, and random forest regression and the support vector machine algorithm. The best possible solution is obtained with ML techniques and the same is compared with the existing database for a concentric orifice. The study will help to design the flow meter for two-phase application in an effective manner.
Heat Transfer from Blower through Bend Pipe with Machine Learning Algorithm Santosh Kumar Panda, Alok Patra, Aswini Kumar Khuntia, Suresh Kumar Mohanty, Ansuman Muduli Wseas Transactions on Heat and Mass Transfer, 2025 Forced convection is one of the modes of heat transfer. In the present paper a U-shaped bend tube is considered as a flow domain through which the air is blown for an experimental study. The heat is supplied to the bend pipe with the help of a heater and varying heat rate with voltage and current. The study will predict the heat transfer coefficient (h), temperature profile and Nusselt Number (Nu) on the variation of input heat transfer rate (Q) and the Reynolds Number (Re) of air. After collecting the data experimentally, the Machine learning (ML) based algorithms are used to predict the comparative result data. The ML method applied in the present work is Gradient boosting regression (GBR). The experimental and ML data are compared and predict a correlation. The correlation will be used to design a U-shaped bend tube used in heat exchanger applications.
POSITIVITY PRESERVING ANALYSIS OF CENTRAL SCHEMES FOR COMPRESSIBLE EULER EQUATIONS Souren Misra, Alok Patra, Santosh Kumar Panda Computational Thermal Sciences, 2024 Physical quantities like density (&rho;), pressure (p), and energy (e) are always non-negative. It is one of the essential qualities a scheme (numerical solver) to maintain the positiveness of these quantities in obtaining the solution of the Euler's equations (or diffrential equations) for inviscid fluid flow. The central solvers add explicitly numerical dissipation to obtain the solution. In this research work, the minimum amount of numerical disspation requirement is analytically obtained for 1D compressible Euler equations by enforcing the positivity criterion to have realistic density, pressure, and internal energy. The positivity analysis of explicit central solver is carried out analytically in 1D for compressible Euler equations to have realistic density, pressure, and energy under the Courant-Friedrichs-Lewy (CFL) condition with Courant number 1. The minimum numerical dissipation criterion obtained in 1D Euler's equations for an explicit solver is a function of the parameters, such as fluid velocity, flow Mach number, and specific heat ratio (&gamma;). The Lax and Friedrichs (L-F) scheme always provides real physical solutions because it has more numerical dissipation than the minimum numerical dissipation required to satisfy positivity. A new positivity-preserving numerical scheme is developed for compressible Euler's equations based on the minimum numerical dissipation in the finite volume framework and tested on the standard test cases in 1D and 2D.
