On the shape of a rotating fluid system consisting of a gas bubble enclosed in a liquid globe
Gas bubble in liquid under surface tension, weightlessness and rotation, determining angular velocity for fluid system disintegration
Bauer, H. F.↗
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Results for “Fluid System”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Modeling of Compressible Flow with Friction and Heat Transfer Using the Generalized Fluid System Simulation Program (GFSSP)
The present paper describes the verification and validation of a quasi one-dimensional pressure based finite volume algorithm, implemented in Generalized Fluid System Simulation Program (GFSSP), for predicting compressible flow with friction, heat transfer and area change. The numerical predictions were compared with two classical solutions of compressible flow, i.e. Fanno and Rayleigh flow. Fanno flow provides an analytical solution of compressible flow in a long slender pipe where incoming subsonic flow can be choked due to friction. On the other hand, Raleigh flow provides analytical solution of frictionless compressible flow with heat transfer where incoming subsonic flow can be choked at the outlet boundary with heat addition to the control volume. Nonuniform grid distribution improves the accuracy of numerical prediction. A benchmark numerical solution of compressible flow in a converging-diverging nozzle with friction and heat transfer has been developed to verify GFSSP's numerical predictions. The numerical predictions compare favorably in all cases.
Bandyopadhyay, Alak↗
Cryogenic fluid management (base R/T): Cryogenic fluid systems, Cryogenic Orbital Nitrogen Experiment (CONE), Cryogenic Orbital Hydrogen Experiment (COHE). (Transportation focused technology)
The topics presented are covered in viewgraph form. The concluded remarks are: (1) advanced cryogenic fluid systems technology is enhancing or enabling to all known transportation scenarios for space exploration; (2) an integrated/coordinated program involving LeRC/MSFC has been formulated to address all known CFM needs - new needs should they develop, can be accommodated within available skills/facilities; (3) all required/experienced personnel and facilities are finally in place - data from initial ground-based experiments is being collected and analyzed - small scale STS experiments are nearing flight - program is beginning to yield significant results; (4) future proposed funding to primarily come from two sources; and (5) cryogenic fluid experimentation is essential to provide required technology and assure implementation in future NASA missions.
Symons, Pat↗
Introducing controlled matter into a fluid system
Device consisting of capsule holder and glass inner tube has been developed to handle controlled particulate-contamination samples. Premeasured quantity of particles can be injected into closed fluid system without contamination.
Hoffman, C. E.↗
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↗
No Vent Tank Fill and Transfer Line Chilldown Analysis by Generalized Fluid System Simulation Program (GFSSP)
The purpose of the paper is to present the analytical capability developed to model no vent chill and fill of cryogenic tank to support CPST (Cryogenic Propellant Storage and Transfer) program. Generalized Fluid System Simulation Program (GFSSP) was adapted to simulate charge‐holdvent method of Tank Chilldown. GFSSP models were developed to simulate chilldown of LH2 tank in K‐site Test Facility and numerical predictions were compared with test data. The report also describes the modeling technique of simulating the chilldown of a cryogenic transfer line and GFSSP models were developed to simulate the chilldown of a long transfer line and compared with test data.
Majumdar, Alok↗
Determination of gas volume trapped in a closed fluid system
Technique involves extracting known volume of fluid and measuring system before and after extraction, volume of entrapped gas is then computed. Formula derived from ideal gas laws is basis of this method. Technique is applicable to thermodynamic cycles and hydraulic systems.
Hunter, W. F.↗
Modeling of Cryogenic Heated-Tube Flow Boiling Experiments of Nitrogen and Methane with the Generalized Fluid System Simulation Program
Accurate modeling of cryogenic boiling heat transfer is vital for the development of extended-duration space missions. Such missions may require the transfer of cryogenic propellants from in-space storage depots or the cooling of nuclear reactors. Purdue University in collaboration with NASA has assembled a database of cryogenic flow boiling data points from heated-tube experiments dating back to 1959, which has been used to develop new flow boiling correlations specifically for cryogens. Computational models of several of these experiments have been constructed in the Generalized Fluid System Simulation Program (GFSSP), a network flow code developed at NASA’s Marshall Space Flight Center. The new Purdue-developed correlations cover the full boiling curve: onset of nucleate boiling, nucleate boiling, critical heat flux, and film boiling. These correlations have been coded into GFSSP user subroutines. The fluids modeled are methane and nitrogen. Predictions of wall temperature and heat transfer coefficient are presented and compared to the test data.
Multi-Phase Flow↗
Modeling of Cryogenic Heated-Tube Flow Boiling Experiments of Hydrogen and Helium With the Generalized Fluid System Simulation Program
Accurate modeling of cryogenic boiling heat transfer is vital for the development of extended-duration space missions. Such missions may require the transfer of cryogenic propellants from in-space storage depots or the cooling of nuclear reactors. Purdue University in collaboration with NASA has assembled a database of cryogenic flow boiling data points from heated-tube experiments dating back to 1959, which has been used to develop new flow boiling correlations specifically for cryogens. Computational models of several of these experiments have been constructed in the Generalized Fluid System Simulation Program (GFSSP), a network flow code developed at NASA’s Marshall Space Flight Center. The new Purdue-developed universal correlations cover the full boiling curve: onset of nucleate boiling, nucleate boiling, critical heat flux, and film boiling. These correlations have been coded into GFSSP user subroutines. The fluids modeled in this study are liquid hydrogen and liquid helium. Predictions of local wall temperature and pressure drop are presented and compared to the test data.
multi-phase flow↗
Development and Implementation of Non-Newtonian Rheology Into the Generalized Fluid System Simulation Program (GFSSP)
One of the goals of this program was to develop the experimental and analytical/computational tools required to predict the flow of non-Newtonian fluids through the various system components of a propulsion system: pipes, valves, pumps etc. To achieve this goal we selected to augment the capabilities of NASA's Generalized Fluid System Simulation Program (GFSSP) software. GFSSP is a general-purpose computer program designed to calculate steady state and transient pressure and flow distributions in a complex fluid network. While the current version of the GFSSP code is able to handle various systems components the implicit assumption in the code is that the fluids in the system are Newtonian. To extend the capability of the code to non-Newtonian fluids, such as silica gelled fuels and oxidizers, modifications to the momentum equations of the code have been performed. We have successfully implemented in GFSSP flow equations for fluids with power law behavior. The implementation of the power law fluid behavior into the GFSSP code depends on knowledge of the two fluid coefficients, n and K. The determination of these parameters for the silica gels used in this program was performed experimentally. The n and K parameters for silica water gels were determined experimentally at CFDRC's Special Projects Laboratory, with a constant shear rate capillary viscometer. Batches of 8:1 (by weight) water-silica gel were mixed using CFDRC s 10-gallon gelled propellant mixer. Prior to testing the gel was allowed to rest in the rheometer tank for at least twelve hours to ensure that the delicate structure of the gel had sufficient time to reform. During the tests silica gel was pressure fed and discharged through stainless steel pipes ranging from 1", to 36", in length and three diameters; 0.0237", 0.032", and 0.047". The data collected in these tests included pressure at tube entrance and volumetric flowrate. From these data the uncorrected shear rate, shear stress, residence time, and viscosity were evaluated using formulae for non-Newtonian, power law fluids. The maximum shear rates (corrected for entrance effects) obtained in the rheometer with the current setup were in the 150,000 to 170,000sec- range. GFSSP simulations were performed with a flow circuit simulating the capillary rheometer and using Power Law gel viscosity coefficients from the experimental data. The agreement between the experimental data and the simulated flow curves was within +/-4% given quality entrance effect data.
DiSalvo, Roberto↗
Design and Development of a Sub-Zero Fluid System for Demonstration of Orion's Phase Change Material Heat Exchangers on ISS
NASA's Orion Multipurpose Crew Vehicle's Exploration Mission 2 is expected to loiter in Lunar orbit for a relatively long period of time. In low Lunar orbit (LLO) the thermal environment is cyclic - extremely cold in the eclipse and relatively hot near the subsolar point. Phase change material heat exchangers (PCM HXs) are the best option for long term missions in these environments. A PCM HX allows a vehicle to store excess waste energy by thawing a phase change material such as n-pentadecane wax. During portions of the orbit that are extremely cold, the excess energy is rejected, resolidifying the wax. Due to the inherent risk of compromising the heat exchanger during multiple freeze and thaw cycles, a unique payload was designed for the International Space Station to test and demonstration the functions of a PCM HX. The payload incorporates the use of a pumped fluid system and a thermoelectric heat exchanger to promote the freezing and thawing of the PCM HX. This paper shall review the design and development undertaken to build such a system.
Sheth, Rubik B.↗
Surface cleanliness of fluid systems, specification for
This specification establishes surface cleanliness levels, test methods, cleaning and packaging requirements, and protection and inspection procedures for determining surface cleanliness. These surfaces pertain to aerospace parts, components, assemblies, subsystems, and systems in contact with any fluid medium.
Source record↗
A Finite Volume Procedure for Thermo-Fluid System Analysis in a Flow Network
This paper describes a finite volume procedure for network flow analysis in a thermofluid system. A flow network is defined as a group of inter-connected control volumes called “nodes” that are connected by “branches”. The mass and energy conservation equations are solved at the nodes and momentum conservation equations are solved at the branches. The flow network also includes solid nodes to account for fluid to solid heat transfer. The heat conduction equation is solved at the solid nodes in conjunction with the flow equations. The properties of a real fluid are calculated using a thermodynamic property program and used in the conservation equations. The system of equations describing the fluid-solid network is solved by a hybrid numerical method that is a combination of the Newton-Raphson and successive substitution method. This procedure has been incorporated into a general-purpose computer program, the Generalized Fluid System Simulation Program, GFSSP. This paper also presents the application and verification of the method by comparison with test data for several applications that include (a) internal flow in a rocket engine turbo-pump, (b) pressurization and loading of a cryogenic propellant tank, (c) fluid transient during sudden opening of valve for priming of an evacuated feed line, and (d) chill down of a cryogenic transfer line with phase change and two phase flows.
Majumdar, Alok↗
A Study of Physics-Informed Deep Learning for System Fluid Dynamics Closures
The sub-grid-scale (SGS) physics models, or so-called closure relations (CR), are essential in thermal-fluid modeling and simulation codes, ranging from large-eddy simulation to system-level thermo-fluid dynamic problems. While details vary, all thermo-fluid codes solve coupled mass-momentum-energy conservation partial differential equations (PDE). Traditionally, the analytical form of closure models has to be known, and then we calibrate the model using data from a set of applicable experiments. Characteristically, it takes long effort to gain insights and mechanistic understanding needed for developing closure models. Such a model is a compact form of data. The long time required for new model development limits the pace of model application while dealing with new geometries, new coolants or system conditions, particularly in newly designed systems. Alternative to mechanistic and semi-analytical models, it is possible to discover the pattern of closure relations by applying the modern machine learning methods to the body of relevant experimental data. Deep learning (DL) is a relatively new branch in the machine learning family, and a major breakthrough has been achieved since Hinton introduces a fast algorithm to efficiently train a feed-forward neural network (NN) with multilayer perceptrons. Generally, any NN with more than two layers is considered as deep learning, and it contains a large number of hyper-parameters to achieve pattern recognition or regression for complex datasets. Hornik shows that multilayer NN is compatible with universal approximation theorem. There is no constraint for a multilayer NN to capture the properties of any measurable information. This capability makes DL attractive for closure models in a system thermal-hydraulic code. As system geometry and/or operating conditions change, new physical experiments (increasingly sophisticated) are conducted to support evaluation and revision of closure models. Such a so-called data-driven modeling relaxes the structural form of system codes to directly assimilate data instead of hard-wiring the model to pre-calibrated correlations. The objective of this research is to enable cost-effective development of a DL-based closure that reflects the data. The previous work on applying machine learning techniques to fluid dynamics focused on statistical learning with basic NN from direct numerical simulations (DNS) dataset. In the present work, we show that DL-based closure models can cause the fluid calculation to diverge if multilayer NN is used. To address the issue, we investigate conditions by which the DL-based closure models work compatibly, stably, and effectively with PDE-constrained forward prediction problems. Optimally meeting the compatibility conditions constitutes a physics-informed deep learning (PIDL) strategy. We refer to this process as PDE-constrained machine learning or PDE-ML. To develop the technical basis for PDE-ML using DL-based fluid dynamics closure, numerical experiments are performed for manufactured problems of increasing complexity. (authors)
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Modeling Two-Phase Flow and Vapor Cycles Using the Generalized Fluid System Simulation Program
This work presents three new applications for the general purpose fluid network solver code GFSSP developed at NASA's Marshall Space Flight Center: (1) cooling tower, (2) vapor-compression refrigeration system, and (3) vapor-expansion power generation system. These systems are widely used across engineering disciplines in a variety of energy systems, and these models expand the capabilities and the use of GFSSP to include fluids and features that are not part of its present set of provided examples. GFSSP provides pressure, temperature, and species concentrations at designated locations, or nodes, within a fluid network based on a finite volume formulation of thermodynamics and conservation laws. This paper describes the theoretical basis for the construction of the models, their implementation in the current GFSSP modeling system, and a brief evaluation of the usefulness of the model results, as well as their applicability toward a broader spectrum of analytical problems in both university teaching and engineering research.
Smith, Amanda D.↗
Fluid Systems Servicing and Leak Check for the International Space Station
Fluid servicing and seal leak checking on the International Space Station will be possible on flight 5A.1 and thereafter. The equipment responsible for these startup and maintenance tasks is described.
PERFORMANCE ASSESSMENT↗
Generalized Fluid System Simulation Program (GFSSP) Training Course 05: Pre & Post Processor, Part 2
A demonstration of the Visual Thermo-fluid dynamic Analyzer for Systems and Components (VTASC) computer program designed to efficiently build flow network models for use in the GFSSP program.
LeClair, Andre↗
Generalized Fluid System Simulation Program
A general purpose program implemented on a computer analyzes steady state and transient flow in a complex fluid network, modeling phase changes, compressibility, mixture thermodynamics and external body forces such as gravity and centrifugal force. A preprocessor provides for the inter- active development of a fluid network simulation having nodes and branches. Mass, energy, and specie conservation equations are solved at the nodes, and momentum conservation equations are solved in the branches. Contained herein are subroutines for computing "real fluid" thermodynamic and thermophysical properties for 12 fluids, and a number of different source options are provided for model- ing momentum sources or sinks in the branches. The system of equations describing the fluid network is solved by a hybrid numerical method that is a combination of the Newton-Raphson and successive substitution methods. Application and verification of this invention are provided through an example problem, which demonstrates that the predictions of the present invention compare most reasonably with test data.
Alok Kumar Majumdar↗