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Alok Majumdar

Publications and source records attributed to Alok Majumdar.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2026

CFD-Assisted Nodal Modeling of Sloshing in a Cryogenic Propellant Tank

During autogenous pressurization, tank sloshing causes a significant increase in pressurant consumption to maintain constant ullage pressure during draining of the tank. This increase in pressurant consumption is caused by a significant increase in condensation at the liquid-vapor interface. Sloshing strongly affects the liquid side heat transfer coefficient and thereby the condensation rate. Traditionally, sloshing is modeled by CFD code using the VOF (Volume of Fluid) method to track the liquid vapor interface during sloshing. CFD calculations require a very fine grid to accurately compute the heat and mass transfer at the interface. Therefore, computations are time consuming and prohibit performing many parametric studies often needed during the design of a new system. This paper describes an alternative approach by developing a CFD-assisted nodal model to predict system parameters more economically with reasonable accuracy. In this approach, a multi-node model of tank pressurization was developed using GFSSP. A multi-node model was needed to account for stratification. The model computes heat and mass transfer at the interface to calculate the condensation rate. The liquid side heat transfer is computed using the parameters of sloshing dynamics such as frequency, wave amplitude, and interface area. The parameters of sloshing dynamics are computed by the CFD code LOCI-Stream. The model predictions were compared with test data for several cases.

Cryogenic Tank Sloshing↗
NASA NTRS2024

Nodal Modeling of Liquid Propellant Feed and Pressurization System

Nodal or network flow modeling plays an important role in the design and operation of the feed and pressurization system of a liquid rocket engine. Model development and execution time is relatively short for nodal codes in comparison to the Navier-Stokes based CFD codes. Nodal models also allow the inclusion of several components into one model to predict the behavior of a larger system. Unlike CFD models, the nodal models do not need very fine discretization of the flow field because they use empirical correlations to model fluid friction and heat transfer. This paper presents several applications of nodal modeling of liquid propellant feed and pressurization systems using the Generalized Fluid System Simulation Program (GFSSP), a nodal code developed at NASA/ Marshall Space Flight Center. GFSSP discretizes the flow field into nodes which are connected by branches. The mass and energy conservation equations and the equation of state are solved to calculate pressure, temperature, and resident mass at the nodes. The momentum equations are solved at the branches to calculate flow rates. Applications include a) tank pressurization by inert gas as well as autogenous pressurization by gaseous propellant, b) submerged pressurization by helium, c) self-pressurization due to boil-off of cryogenic propellant, d) chilldown of a transfer line of a cryogenic propellant feed system, and e) chilldown and filling of a cryogenic tank. Each of the above-mentioned models was verified and validated by comparing with test data.

Nodal Model↗
NASA NTRS2024

Nodal Modeling of Liquid Propellant Feed and Pressurization System

Nodal or network flow modeling plays an important role in the design and operation of the feed and pressurization system of a liquid rocket engine. Model development and execution time is relatively short for nodal codes in comparison to the Navier-Stokes based CFD codes. Nodal models also allow the inclusion of several components into one model to predict the behavior of a larger system. Unlike CFD models, the nodal models do not need very fine discretization of the flow field because they use empirical correlations to model fluid friction and heat transfer. This paper presents several applications of nodal modeling of liquid propellant feed and pressurization systems using the Generalized Fluid System Simulation Program (GFSSP), a nodal code developed at NASA/ Marshall Space Flight Center. GFSSP discretizes the flow field into nodes which are connected by branches. The mass and energy conservation equations and the equation of state are solved to calculate pressure, temperature, and resident mass at the nodes. The momentum equations are solved at the branches to calculate flow rates. Applications include a) tank pressurization by inert gas as well as autogenous pressurization by gaseous propellant, b) submerged pressurization by helium, c) self-pressurization due to boil-off of cryogenic propellant, d) chilldown of a transfer line of a cryogenic propellant feed system, and e) chilldown and filling of a cryogenic tank. Each of the above-mentioned models was verified and validated by comparing with test data.

Nodal Model↗
NASA NTRS2023

Two-Dimensional Network Flow Modeling of No-Vent Tank Filling of A Cryogenic Tank With Thermo-Dynamic Vent System Assisted Injector

A finite volume-based network flow modeling tool, Generalized Fluid System Simulation Program (GFSSP), was used to simulate the no-vent filling of a cryogenic tank with a thermodynamic vent system assisted injector. The tank was discretized into nodes in the radial and axial directions to calculate two-dimensional axisymmetric flow with heat transfer between the solid wall and fluid. The nodes are connected by branches where momentum equations are solved to calculate the flowrates. The mass and energy conservation equations and the equation of state are solved to calculate pressure, temperature, and resident mass at the nodes. The energy conservation equations at the solid nodes were solved to calculate the temperature of the solid wall. The system of equations was solved by a combination of successive substitution and simultaneous Newton-Raphson method. The numerical model accounts for a) different regimes of pool boiling heat transfer, b) condensation of vapor around the spray droplets, c) condensation of vapor at the interface of the cooled injector and ullage, and d) condensation at the liquid-vapor interphase. The numerical predictions of tank pressure, filling rate, and wall temperatures were compared with the test data. The paper also presents the effect of nodal discretization by comparing the results of the 1D and 2D models and examines the effect of the droplet diameter on tank filling.

Nodal Model↗
NASA NTRS2023

Critical Heat Flux of Liquid Hydrogen, Liquid Methane, and Liquid Oxygen: A Review of Available Data and Predictive Tools

Available experimental data dealing with critical heat flux (CHF) of liquid hydrogen (LH2), liquid methane (LCH4), and liquid oxygen (LO2) in pool and flow boiling are compiled. The compiled data are compared with widely used correlations. Experimental pool boiling CHF data for the aforementioned cryogens are scarce. Based on only 25 data points found in five independent sources, the correlation of Sun and Lienhard (1970) is recommended for predicting the pool CHF of LH2. Only two experiments with useful CHF data for the pool boiling of LCH4 could be found. Four different correlations including the correlation of Lurie and Noyes (1964) can predict the pool boiling CHF of LCH4 within a factor of two for more than 70% of the data. Furthermore, based on the 19 data points taken from only two available sources, the correlation of Sun and Lienhard (1970) is recommended for the prediction of pool CHF of LO2. Flow boiling CHF data for LH2 could be found in seven experimental studies, five of them from the same source. Based on the 91 data points, it is suggested that the correlation of Katto and Ohno (1984) be used to predict the flow CHF of LH2. No useful data could be found for flow boiling CHF of LCH4 or LO2. The available databases for flow boiling of LCH4 and LO2 are generally deficient in all boiling regimes. This deficiency is particularly serious with respect to flow boiling.

Multi-Phase Flow↗
NASA NTRS2023

Modeling of Condensation in the Presence of Noncondensables in GFSSP

The Generalized Fluid System Simulation Program (GFSSP) computer code is enhanced with the capability to model condensation in the presence of noncondensable gases. Condensation in the presence of noncondensables is modeled using the Couette flow film (stagnant film) model. Experimental data on the condensation of water vapor in downward flow of air-water vapor and helium-water vapor mixtures in vertical tubes are compared with the predictions of GFSSP. The comparisons show that GFSSP can predict the experimental data well.

heat transfer↗
NASA NTRS2023

Analysis of Cryogenic Propellant Liquefaction Rates in Cooled Constant-Wall-TemperatureTanks

NASA has been focused on developing technology that would allow the production of cryogenic propellants on the Lunar and Martian surfaces. Utilizing Lunar/Martian resources, the produced gaseous propellants must first be liquefied and stored prior to use on the Moon or Mars ascent vehicle. Liquefaction of cryogenic propellant is a necessary technical development to enable NASA’s future spaceflight goals. This paper presents an overview of the effect of spacecraft propellant system parameters on cryogenic propellant liquefaction rates. The propellant system was assumed to be a receiver of a gas from an In-Situ Resource Utilization (ISRU) harvester and condensed the gas by cooling the tank walls. First, the general thermodynamic principles pertinent to condensation are summarized, followed by an overview of the model which performed the analysis, including a summary of the Fortran implementation. Comparisons between the model results and test data are discussed, as well as sensitivity of the condensation rate to various parameters.

cryogenics↗
NASA NTRS2022

Test data analysis of the thermodynamic vent system-augmented top spray injector liquid nitrogen transfer experiments

Traditionally, a cryogenic tank must be pre-chilled to some “target” temperature before the main vent valve can be closed to attempt a non-vented fill (NVF) of cryogenic liquid propellant. This methodology is particularly attractive for performing in-space transfer of cryogens due to the unknown location of the liquid/vapor interface in microgravity and the high likelihood of venting liquid if the vent valve is opened during transfer. This paper presents in-depth test data analysis of a Thermodynamic Vent System (TVS) augmented injector used for cryogenic tank chilldown and fill experiments of a thin-walled Titanium tank. Eight tests were conducted using liquid nitrogen across a range of inlet conditions and boundary conditions, and three different chilldown/fill methods. For four of the tests, the injector sprays liquid into the tank as normal, but also uses a TVS heat exchanger to cool the metallic injector itself as well as the main incoming liquid stream. Results show that using the TVS augmented injector simplifies transfer operation via enhanced condensation at the injector surface at the cost of sacrificing only a small amount of propellant.

No-vent Fill↗
NASA NTRSDate not supplied

Numerical Modeling of No Vent Filling of a Cryogenic Tank

This paper presents a multi-node finite volume model of the chilling and filling of a cryogenic tank using the Generalized Fluid System Simulation Program (GFSSP), a general purpose flow network code. Vented Chill and No Vent Fill (VCNVF) tests were conducted at Marshall Space Flight Center where a flight-like tank was filled with liquid nitrogen from a supply tank. In the VCNVF tests, the tank was partially chilled while the vent valve was open. After the partial chilling, the vent valve was closed and the tank was filled without any venting. An integrated numerical model of the test set up was developed. The model included the transfer line from the supply tank, the target tank with the spray nozzle and solid walls, and the discharge line with the vent valve. The tank was discretized into multiple fluid nodes and branches to represent the ullage and liquid nitrogen and multiple solid nodes to represent the tank wall and structure. The heat transfer between solid to fluid was calculated from pool boiling correlations which include film, transition, and nucleate boiling, as well as natural convection during pre- and post-boiling. The model also accounts for the condensation of vapor in the tank when it comes in contact with the liquid spray. The predicted pressure, resident mass, wall and ullage temperature in the tank were compared with the test data.

Alok Majumdar↗
NASA NTRSDate not supplied

Numerical Modeling of No Vent Filling of a Cryogenic Tank

This paper presents a multi-node finite volume model of the chilling and filling of a cryogenic tank using the Generalized Fluid System Simulation Program (GFSSP), a general purpose flow network code. Vented Chill and No Vent Fill (VCNVF) tests were conducted at Marshall Space Flight Center where a flight-like tank was filled with liquid nitrogen from a supply tank. In the VCNVF tests, the tank was partially chilled while the vent valve was open. After the partial chilling, the vent valve was closed and the tank was filled without any venting. An integrated numerical model of the test set up was developed. The model included the transfer line from the supply tank, the target tank with the spray nozzle and solid walls, and the discharge line with the vent valve. The tank was discretized into multiple fluid nodes and branches to represent the ullage and liquid nitrogen and multiple solid nodes to represent the tank wall and structure. The heat transfer between solid to fluid was calculated from pool boiling correlations which include film, transition, and nucleate boiling, as well as natural convection during pre- and post-boiling. The model also accounts for the condensation of vapor in the tank when it comes in contact with the liquid spray. The predicted pressure, resident mass, wall and ullage temperature in the tank were compared with the test data.

Alok Majumdar↗
NASA NTRSDate not supplied

GFSSP Software Demo

A one hour demonstration of the Generalized Fluid System Simulation Program.

Andre Leclair↗
NASA NTRSDate not supplied

Numerical Modeling of No Vent Filling of a Cryogenic Tank with Thermo-dynamic Vent System Assisted Injector

This paper presents a multi-node finite volume model of No Vent Filling (NVF) of a cryogenic tank with Thermo-dynamic Vent System (TVS) assisted injector, using the Generalized Fluid System Simulation Program (GFSSP), a general purpose flow network code. NVF tests were conducted in a CRYOgenic Orbital Testbed (CRYOTE) tank which was filled by liquid nitrogen using a TVS assisted injector with vent valve closed during the entire filling process. In TVS assisted injector, the liquid flow splits into two streams: one stream is routed to a Joule-Thomson (J-T) orifice where the flow immediately flashes from liquid to vapor or two phase mixture because the downstream to J-T leg is maintained at vacuum level.; the other stream is injected into the tank after being cooled by cold vapor of J-T leg in a heat exchanger. The flow through J-T leg is also used to cool the outer metal matrix of the injector which in turn cools the vapor in the tank ullage. The cooling of vapor in the ullage by cold injector surface reduces ullage pressure that allows liquid to enter and fill the tank. An integrated numerical model of the test set up was developed. The model included the dual lines of TVS assisted injector, tank and tank wall. The tank was discretized into multiple fluid nodes and branches to represent the ullage and liquid nitrogen and multiple solid nodes to represent the tank wall and structure. The heat transfer between solid to fluid was calculated from pool boiling correlations which include film, transition, and nucleate boiling, as well as natural convection during pre- and post-boiling. The model also accounts for the condensation of vapor at ullage-injector interface and when it comes in contact with the liquid spray. The predicted pressure, resident mass, wall temperature in the tank were compared with the test data.

Alok Majumdar↗
NASA NTRSDate not supplied

Axisymmetric Two-Dimensional Modeling of No Vent Filling of a Cryogenic Tank using Generalized Fluid System Simulation Program

Filling a tank with cryogenic fluid is more challenging than filling a tank with water or any other fluid that is in liquid state at atmospheric condition. Filling a tank with cryogenic fluid is a two-step process. First the tank and the transfer line mustbe chilled. Liquid cryogens start flowing into the tank only after the tank and transfer lines are chilled to the fluid saturation temperature. In normal gravity, cryogenic tanks are usually filled from the bottom at nearly atmospheric pressure. The vapor, caused by heat transfer from the warm tank walls, is allowed to vent from the top of the tank while the tank is being filled. Filling a cryogenic tank in the absence of gravity is more challenging because in a non-stratified environment liquid propellantmay not settle at the tank bottom as it does on earth. There is a strong possibility that liquid propellant may exit through the vent valve, which is typically located at the top of the tank to vent propellant vapor. There are several methodsof filling atank in space: Charge-Hold-Vent method [1], Vented-Chill / No-Vent-Fill (VCNVF)[2],and No Vent Fill with TVS assisted injector [3].This paper addressesnumerical modelingofthe No Vent Fill (NVF) processwhere a TVS (Thermodynamic Vent System) augmented injector was used with the vent valve closed during the entire filling process. NVF tests were conducted in the CRYOgenic Orbital Testbed (CRYOTE) tankat NASA/Marshall Space Flight Centerin 2018.The Generalized Fluid System Simulation Program (GFSSP), a general-purpose flow network code [4] was used to simulate the chilland fill process.

Cryogenics↗
NASA NTRSDate not supplied

Evaluation of Heat Transfer Coefficient from Velocity Distribution in Boundary Layer

This paper describes a method of evaluating heat transfer coefficient from a velocity distribution in the boundary layer. The power law velocity profile and universal velocity distribution in a smooth pipe have been used to evaluate the wall shear stress, and the heat transfer coefficient was evaluated from the wall shear stress using the Chilton-Colburn analogy. The predicted pressure drop was compared with the pressure drop computed by the Colebrook equation, and the predicted heat transfer coefficient was compared with the heat transfer coefficient calculated by the Dittus-Boelter equation. The accuracy of pressure drop prediction was within 1%, and the accuracy of heat transfer coefficient prediction was within 8%. This method has the potential to use a Navier-Stokes based CFD solution to evaluate the heat transfer coefficient in nodal or network flow codes.

Heat Transfer Coefficient↗
NASA NTRSDate not supplied

Evaluation of Heat Transfer Coefficient from Velocity Distribution in Boundary Layer

This paper describes a method of evaluating heat transfer coefficient from a velocity distribution in the boundary layer. The power law velocity profile and universal velocity distribution in a smooth pipe have been used to evaluate the wall shear stress, and the heat transfer coefficient was evaluated from the wall shear stress using the Chilton-Colburn analogy. The predicted pressure drop was compared with the pressure drop computed by the Colebrook equation, and the predicted heat transfer coefficient was compared with the heat transfer coefficient calculated by the Dittus-Boelter equation. The accuracy of pressure drop prediction was within 1%, and the accuracy of heat transfer coefficient prediction was within 8%. This method has the potential to use a Navier-Stokes based CFD solution to evaluate the heat transfer coefficient in nodal or network flow codes.

Heat Transfer Coefficient↗
NASA NTRSDate not supplied

Analysis of Cryogenic Propellant Liquefaction Rates in Cooled Constant-Wall-Temperature Tanks

NASA has been focused on developing technology that would allow the production of cryogenic propellants on the Lunar and Martian surfaces. Utilizing Lunar/Martian resources, the produced gaseous propellants must first be liquefied and stored prior to use on the Moon or Mars ascent vehicle. Liquefaction of cryogenic propellant is a necessary technical development to enable NASA’s future spaceflight goals. This paper presents an overview of the effect of spacecraft propellant system parameters on cryogenic propellant liquefaction rates. The propellant system was assumed to be a receiver of a gas from an In-Situ Resource Utilization (ISRU) harvester and condensed the gas by cooling the tank walls. First, the general thermodynamic principles pertinent to condensation are summarized, followed by an overview of the model which performed the analysis, including a summary of the Fortran implementation. Comparisons between the model results and test data are discussed, as well as sensitivity of the condensation rate to various parameters.

Anson Koch↗
NASA NTRSDate not supplied

Analysis of Cryogenic Propellant Liquefaction Rates in Cooled Constant-Wall-Temperature Tanks

NASA has been focused on developing technology that would allow the production of cryogenic propellants on the Lunar and Martian surfaces. Utilizing Lunar/Martian resources, the produced gaseous propellants must first be liquefied and stored prior to use on the Moon or Mars ascent vehicle. Liquefaction of cryogenic propellants is a necessary technical development to enable NASA’s future spaceflight goals. This paper presents an overview of a proposed model for a propellant liquefaction system, and the effect of tank wall temperatures on cryogenic propellant liquefaction rates. The propellant system was assumed to be a receiver of a gas from an In-Situ Resource Utilization (ISRU) harvester and condensed the gas by cooling the tank walls. First, the heat transfer principles pertinent to condensation are summarized, followed by an overview of the model which performed the analysis, including a summary of the Fortran algorithm implementation. The sensitivity of the condensation rate relative to varying tank wall temperatures is also discussed.

Anson Koch↗