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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Aerospace applications of SINDA/FLUINT at the Johnson Space Center

SINDA/FLUINT has been found to be a versatile code for modeling aerospace systems involving single or two-phase fluid flow and all modes of heat transfer. Several applications of SINDA/FLUINT are described in this paper. SINDA/FLUINT is being used extensively to model the single phase water loops and the two-phase ammonia loops of the Space Station Freedom active thermal control system (ATCS). These models range from large integrated system models with multiple submodels to very detailed subsystem models. An integrated Space Station ATCS model has been created with ten submodels representing five water loops, three ammonia loops, a Freon loop and a thermal submodel representing the air loop. The model, which has approximately 800 FLUINT lumps and 300 thermal nodes, is used to determine the interaction between the multiple fluid loops which comprise the Space Station ATCS. Several detailed models of the flow-through radiator subsystem of the Space Station ATCS have been developed. One model, which has approximately 70 FLUINT lumps and 340 thermal nodes, provides a representation of the ATCS low temperature radiator array with two fluid loops connected only by conduction through the radiator face sheet. The detailed models are used to determine parameters such as radiator fluid return temperature, fin efficiency, flow distribution and total heat rejection for the baseline design as well as proposed alternate designs. SINDA/FLUINT has also been used as a design tool for several systems using pressurized gasses. One model examined the pressurization and depressurization of the Space Station airlock under a variety of operating conditions including convection with the side walls and internal cooling. Another model predicted the performance of a new generation of manned maneuvering units. This model included high pressure gas depressurization, internal heat transfer and supersonic thruster equations. The results of both models were used to size components, such as the heaters and gas bottles and also to point to areas where hardware testing was needed.

Ewert, Michael K.↗
NASA NTRS2018

Validation of Heat Transfer Correlations in Line Chill-Down Tests of Cryogenic Fluid in SINDA/FLUINT

Line Chill-down heat transfer was modelled using SINDA/FLUINT. Multiple chill-down tests were modelled using the heat transfer correlations that are available in SINDA/FLUINT, as well as incorporating heat transfer empiricisms developed by the University of Florida1 based on a series of liquid nitrogen chill-down tests. The chill-down tests that were modelled were the liquid nitrogen tests conducted by the University of Florida1 as well as liquid hydrogen tests conducted by NASA Glenn Research Center2. The liquid nitrogen tests included horizontal flow, upward flow, and downward flow with the liquid Reynolds Numbers ranging 850 - 231,000. The liquid hydrogen test was vertical upward flow at a Reynolds Number range of 18,400 - 433,000. Both the University of Florida's heat transfer correlations and SINDA/FLUINT's internal correlations faired similarly to wall temperature test data. They were acceptable although improvements could be made to the University of Florida correlations as well and SINDA/FLUINT's internal correlations.

cryogenic modeling↗
NASA NTRS1993

Features of a SINDA/FLUINT model of a liquid oxygen supply line

The modeling features used in a steady-state heat transfer problem using SINDA/FLUINT are described. The problem modeled is a 125 feet long, 3 inch diameter pipe, filled with liquid oxygen flow driven by a given pressure gradient. The pipe is fully insulated in five sections. Three sections of 1 inch thick spray-on foam and two sections of vacuum jacket. The model evaluates friction, turns losses and convection heat transfer between the fluid and the pipe wall. There is conduction through the foam insulation with temperature dependent thermal conductivity. The vacuum space is modeled with radiation and gas molecular conduction, if present, in the annular gap. Heat is transferred between the outer surface and surrounding ambient by natural convection and radiation; and, by axial conduction along the pipe and through the vacuum jacket spacers and welded seal flanges. The model makes extensive use of SINDA/FLUINT basic capabilities such as the GEN option for nodes and conductors (to generate groups of nodes or conductors), the SIV option (to generate single, temperature varying conductors), the SIM option (for multiple, temperature varying conductors) and the M HX macros for fluids (to generate strings of lumps, paths, and ties representing a diabatic duct). It calls subroutine CONTRN (returns the relative location in the G-array of a network conductor, given an actual conductor number) enabling an extensive manipulation of conductor (calculates an assignment of their values) with DO loops. Models like this illustrate to the new and even to the old SINDA/FLUINT user, features of the program that are not so obvious or known, and that are extremely handy when trying to take advantage of both, the automation of the DATA headers and make surgical modifications to specific parameters of the thermal or fluid elements in the OPERATIONS portion of the model.

Simmonds, Boris G.↗
NASA NTRS1995

Validation of the SINDA/FLUINT code using several analytical solutions

The Systems Improved Numerical Differencing Analyzer and Fluid Integrator (SINDA/FLUINT) code has often been used to determine the transient and steady-state response of various thermal and fluid flow networks. While this code is an often used design and analysis tool, the validation of this program has been limited to a few simple studies. For the current study, the SINDA/FLUINT code was compared to four different analytical solutions. The thermal analyzer portion of the code (conduction and radiative heat transfer, SINDA portion) was first compared to two separate solutions. The first comparison examined a semi-infinite slab with a periodic surface temperature boundary condition. Next, a small, uniform temperature object (lumped capacitance) was allowed to radiate to a fixed temperature sink. The fluid portion of the code (FLUINT) was also compared to two different analytical solutions. The first study examined a tank filling process by an ideal gas in which there is both control volume work and heat transfer. The final comparison considered the flow in a pipe joining two infinite reservoirs of pressure. The results of all these studies showed that for the situations examined here, the SINDA/FLUINT code was able to match the results of the analytical solutions.

Keller, John R.↗
NASA NTRS1992

Development status of SINDA/FLUINT and SINAPS

SINDA/FLUINT (Systems Improved Numerical Differencing Analyzer/Fluid Integrator, formerly SINDA '85) is a computer code used to analyze thermal/fluid systems that can be represented in lumped parameter form. In addition to conduction and radiation heat transfer, the code is capable of modeling both single- and two-phase flow networks, their associated hardware, and their heat transfer processes. In this paper, recent improvements to SINDA/FLUINT are described, as are those in progress that will be available in the fall of 1992 in Version 2.5. Also, a preview of planned enhancements is provided. This paper also introduces SINAPS (SINDA Application Programming System), a powerful graphical pre- and postprocessor that will also be available in the fall of 1992.

Cullimore, Brent A.↗
NASA NTRS2002

Solving Problems With SINDA/FLUINT

SINDA/FLUINT, the NASA standard software system for thermohydraulic analysis, provides computational simulation of interacting thermal and fluid effects in designs modeled as heat transfer and fluid flow networks. The product saves time and money by making the user's design process faster and easier, and allowing the user to gain a better understanding of complex systems. The code is completely extensible, allowing the user to choose the features, accuracy and approximation levels, and outputs. Users can also add their own customizations as needed to handle unique design tasks or to automate repetitive tasks. Applications for SINDA/FLUINT include the pharmaceutical, petrochemical, biomedical, electronics, and energy industries. The system has been used to simulate nuclear reactors, windshield wipers, and human windpipes. In the automotive industry, it simulates the transient liquid/vapor flows within air conditioning systems.

Source record↗
NASA NTRS2014

Sinda/Fluint Stratfied Tank Modeling

A general purpose SINDA/FLUINT (S/F) stratified tank model was created and used to simulate the Ksite1 LH2 liquid self-pressurization tests as well as axial jet mixing within the liquid region of the tank. The S/F model employed the use of stratified layers, i.e. S/F lumps, in the vapor ullage as well as in the liquid region. The model was constructed to analyze a general purpose stratified tank that could incorporate the following features: Multiple or singular lumps in the liquid and vapor regions of the tank, Real gases (also mixtures) and compressible liquids, Venting, pressurizing, and draining, Condensation and evaporation/boiling, Wall heat transfer, Elliptical, cylindrical, and spherical tank geometries. Extensive user logic was used to allow for tailoring of the above features to specific cases. Most of the code input for a specific case could be done through the Registers Data Block.

Sinda/Fluint↗
NASA NTRS2014

SINDA/FLUINT Stratified Tank Modeling for Cryrogenic Propellant Tanks

A general purpose SINDA/FLUINT (S/F) stratified tank model was created to simulate self-pressurization and axial jet TVS; Stratified layers in the vapor and liquid are modeled using S/F lumps.; The stratified tank model was constructed to permit incorporating the following additional features:, Multiple or singular lumps in the liquid and vapor regions of the tank, Real gases (also mixtures) and compressible liquids, Venting, pressurizing, and draining, Condensation and evaporation/boiling, Wall heat transfer, Elliptical, cylindrical, and spherical tank geometries; Extensive user logic is used to allow detailed tailoring - Don't have to rebuilt everything from scratch!!; Most code input for a specific case is done through the Registers Data Block:, Lump volumes are determined through user input:; Geometric tank dimensions (height, width, etc); Liquid level could be input as either a volume percentage of fill level or actual liquid level height

Axial Jet↗
NASA NTRS1992

Modeling and analysis of the Space Station Freedom Active Thermal Control System radiators using SINDA/FLUINT

Detailed SINDA/FLUINT models have been developed to assess the adequacy of the Space Station Freedom External Thermal Control System's radiator design, as well as to simulate the effects of various operational scenarios. Design margins can be deduced by quantifying such real-world effects as flow maldistribution due to line-pressure drop and uneven heat loads. The factor which most reduced the heat-rejection capacity is an uneven heat load split between the two low temperature loops.

Andish, Kambiz K.↗
NASA NTRS2012

Advanced Stirling Radioisotope Generator Thermal Power Model in Thermal Desktop SINDA/FLUINT Analyzer

This paper presents a three-dimensional Advanced Stirling Radioisotope Generator (ASRG) thermal power model that was built using the Thermal Desktop SINDA/FLUINT thermal analyzer. The model was correlated with ASRG engineering unit (EU) test data and ASRG flight unit predictions from Lockheed Martin's Ideas TMG thermal model. ASRG performance under (1) ASC hot-end temperatures, (2) ambient temperatures, and (3) years of mission for the general purpose heat source fuel decay was predicted using this model for the flight unit. The results were compared with those reported by Lockheed Martin and showed good agreement. In addition, the model was used to study the performance of the ASRG flight unit for operations on the ground and on the surface of Titan, and the concept of using gold film to reduce thermal loss through insulation was investigated.

Wang, Xiao-Yen↗
NASA NTRS2018

Validation of Heat Transfer Correlations in Line Chill-Down Tests of Cryogenic Fluid in SINDA/FLUINT

Line chill-down is an important process in cryogenic tank propellant management, storage, and usage Complex flow dynamics during these processes: boiling heat transfer (film, transition, and nucleate) Understanding boiling phenomena can lead to efficient line chill-down systems that use less propellant, propellant stored, reducing cost for space missions Line Chill-down heat transfer was modelled using SINDA/FLUINT version 5.8 (SF) Multiple chill-down tests were modelled using: heat transfer correlations readily available in SF using HTN/HTC TIES heat transfer empiricisms developed by the University of Florida (UF) based on a series of liquid nitrogen chill-down tests using SF HTU TIES Chill-down tests modelled: liquid nitrogen tests conducted by the University of Florida horizontal flow, upward flow, and downward flow (Reynolds Numbers ranging 850-231,000)liquid hydrogen tests conducted by NASA Glenn Research Center vertical upward flow (Reynolds Number range of 18,400 - 433,000)The flow rate was measured far downstream of the test section, near the system exit. Where to set the flow rate? SF was highly sensitive, and sometime unstable, setting the test flow rate downstream (the outlet) of the test section model and setting the test pressure upstream (the inlet) of the test section model higher flow rate oscillations at the entrance of the model's test section SF was more stable setting the test flow rate upstream (than the downstream flow rate set case)test pressure was used as an inlet (SF plenum) to set the thermodynamic state (temperature and quality) coming into the system setting the appropriate downstream pressure was the unknown. The pressure drops predicted by SF for the downstream set flow rate boundary condition were much smaller than test section measured pressure drops. The multiphase pressure drop correlations used internally in SF may need to be adjusted. Models with an upstream flow rate set assumed a pressure drop that was small

cryogenic modeling↗
NASA NTRS2019

SINDA/FLUINT and Thermal Desktop Multi-Node Settled and Unsettled Propellant Tank Modeling of Zero Boil Off Test

Cryogenic propellant storage tank self-pressurization involves complex physical phenomena which are usually analytically modelled via complex multidimensional CFD (Computational Fluid Dynamics) codes. Unfortunately these codes, even when modelling axisymmetric domains, may take weeks or longer to obtain transient pressure and temperature information for relatively short periods of time (several seconds to several hours). Propellant tank storage end-to-end mission simulations can last a duration of days to weeks to months. Multi-node modelling of propellant tanks is a viable alternative to traditional CFD modelling and presents the advantage of greatly reduced run times on the order of hours and days compared to the weeks or longer for CFD codes. A multi-node model represents the fluid within the storage tank, as well as the storage tank itself, as a fluid-thermal network. This type of setup is not necessarily geometrically based. This can be accomplished using a commercial generalized fluid-thermal network code, such as SINDA/FLUINT (SF). The advantage of using a fluid-thermal network code like SF lies in its extensive ability to model the external environment of the storage tank through the graphical user interface, Thermal Desktop (TD). The total heat load into the tank may be a function of heaters and a complex radiative environment as well. Thermal Desktop may be used to address the detailed radiative environment of the tank as well as building a geometrically accurate depiction of the storage tank itself.

Thermal Desktop↗
NASA NTRS2019

SINDA/FLUINT and Thermal Desktop Multi-Node Settled and Unsettled Propellant Tank Modeling of Zero Boil Off Test

Cryogenic propellant storage tank self-pressurization involves complex physical phenomena which are usually analytically modelled via complex multidimensional CFD codes. Unfortunately these codes, even when modelling axisymmetric domains, may takes weeks or longer to obtain transient pressure and temperature information for relatively short periods of time (several seconds to several hours). Propellant tank storage end-to-end mission simulations can last a duration of days to weeks to months. Multi-node modelling of propellant tanks is a viable alternative to traditional CFD modelling and presents the advantage of greatly reduced run times on the order of hours and days compared to the weeks or longer for CFD codes. A multi-node model represents the fluid within the storage tank, as well as the storage tank itself, as a fluid-thermal network. This type of setup is not necessarily geometrically based. This can be accomplished using a commercial generalized fluid-thermal network code, such as SINDA/FLUINT (SF). The advantage of using a fluid-thermal network code like SF lies in its extensive ability to model the external environment of the storage tank through the graphical user interface, Thermal Desktop (TD). The total heat load into the tank may be a function of heaters and a complex radiative environment as well. Thermal Desktop may be used to address the detailed radiative environment of the tank as well as building a geometrically accurate depiction of the storage tank itself.

Sakowski, Barbara↗
NASA NTRS2006

Upper Stage Tank Thermodynamic Modeling Using SINDA/FLUINT

Modeling to predict the condition of cryogenic propellants in an upper stage of a launch vehicle is necessary for mission planning and successful execution. Traditionally, this effort was performed using custom, in-house proprietary codes, limiting accessibility and application. Phenomena responsible for influencing the thermodynamic state of the propellant have been characterized as distinct events whose sequence defines a mission. These events include thermal stratification, passive thermal control roll (rotation), slosh, and engine firing. This paper demonstrates the use of an off the shelf, commercially available, thermal/fluid-network code to predict the thermodynamic state of propellant during the coast phase between engine firings, i.e. the first three of the above identified events. Results of this effort will also be presented.

Schallhorn, Paul↗
NASA NTRS2014

One Dimensional Analysis Model of a Condensing Spray Chamber Including Rocket Exhaust Using SINDA/FLUINT and CEA

Modeling droplet condensation via CFD codes can be very tedious, time consuming, and inaccurate. CFD codes may be tedious and time consuming in terms of using Lagrangian particle tracking approaches or particle sizing bins. Also since many codes ignore conduction through the droplet and or the degradating effect of heat and mass transfer if noncondensible species are present, the solutions may be inaccurate. The modeling of a condensing spray chamber where the significant size of the water droplets and the time and distance these droplets take to fall, can make the effect of droplet conduction a physical factor that needs to be considered in the model. Furthermore the presence of even a relatively small amount of noncondensible has been shown to reduce the amount of condensation. It is desirable then to create a modeling tool that addresses these issues. The path taken to create such a tool is illustrated. The application of this tool and subsequent results are based on the spray chamber in the Spacecraft Propulsion Research Facility (B2) located at NASA's Plum Brook Station that tested an RL-10 engine. The platform upon which the condensation physics is modeled is SINDAFLUINT. The use of SINDAFLUINT enables the ability to model various aspects of the entire testing facility, including the rocket exhaust duct flow and heat transfer to the exhaust duct wall. The ejector pumping system of the spray chamber is also easily implemented via SINDAFLUINT. The goal is to create a transient one dimensional flow and heat transfer model beginning at the rocket, continuing through the condensing spray chamber, and finally ending with the ejector pumping system. However the model of the condensing spray chamber may be run independently of the rocket and ejector systems detail, with only appropriate mass flow boundary conditions placed at the entrance and exit of the condensing spray chamber model. The model of the condensing spray chamber takes into account droplet conduction as well as the degrading effect of mass and heat transfer due to the presence of noncondensibles. The one dimension model of the condensing spray chamber makes no presupposition on the pressure profile within the chamber, allowing the implemented droplet physics of heat and mass transfer coupled to the SINDAFLUINT solver to determine a transient pressure profile of the condensing spray chamber. Model results compare well to the RL-10 engine pressure test data.

Chemical Equilibrium↗
NASA NTRS2014

One Dimensional Analysis Model of a Condensing Spray Chamber Including Rocket Exhaust Using SINDA/FLUINT and CEA

Modeling droplet condensation via CFD codes can be very tedious, time consuming, and inaccurate. CFD codes may be tedious and time consuming in terms of using Lagrangian particle tracking approaches or particle sizing bins. Also since many codes ignore conduction through the droplet and or the degradating effect of heat and mass transfer if noncondensible species are present, the solutions may be inaccurate. The modeling of a condensing spray chamber where the significant size of the water droplets and the time and distance these droplets take to fall, can make the effect of droplet conduction a physical factor that needs to be considered in the model. Furthermore the presence of even a relatively small amount of noncondensible has been shown to reduce the amount of condensation [Ref 1]. It is desirable then to create a modeling tool that addresses these issues. The path taken to create such a tool is illustrated. The application of this tool and subsequent results are based on the spray chamber in the Spacecraft Propulsion Research Facility (B2) located at NASA's Plum Brook Station that tested an RL-10 engine. The platform upon which the condensation physics is modeled is SINDAFLUINT. The use of SINDAFLUINT enables the ability to model various aspects of the entire testing facility, including the rocket exhaust duct flow and heat transfer to the exhaust duct wall. The ejector pumping system of the spray chamber is also easily implemented via SINDAFLUINT. The goal is to create a transient one dimensional flow and heat transfer model beginning at the rocket, continuing through the condensing spray chamber, and finally ending with the ejector pumping system. However the model of the condensing spray chamber may be run independently of the rocket and ejector systems detail, with only appropriate mass flow boundary conditions placed at the entrance and exit of the condensing spray chamber model. The model of the condensing spray chamber takes into account droplet conduction as well as the degrading effect of mass and heat transfer due to the presence of noncondensibles. The one dimension model of the condensing spray chamber makes no presupposition on the pressure profile within the chamber, allowing the implemented droplet physics of heat and mass transfer coupled to the SINDAFLUINT solver to determine a transient pressure profile of the condensing spray chamber. Model results compare well to the RL-10 engine pressure test data.

Condensing Spray Model↗
NASA NTRS2009

System Modeling of Metabolic Heat Regenerated Temperature Swing Adsorption (MTSA) Subassembly for Prototype Design

This paper describes modeling methods for the three core components of a Metabolic heat regenerated Temperature Swing Adsorption (MTSA) subassembly: the sorbent bed, a sublimation (cooling) heat exchanger (SHX), and a condensing icing (warming) heat exchanger (CIHX). The primary function of the MTSA, removing carbon dioxide from a ventilation loop, is performed via the sorbent bed. The CIHX is used to heat the sorbent bed for desorption and to remove moisture from the ventilation loop while the SHX is alternately employed to cool the sorbent bed via sublimation of a spray of water at low pressure to prepare the reconditioned bed for the next cycle. This paper describes a system level model of the MTSA as developed in Thermal Desktop and SINDA/FLUINT including assumptions on geometry and physical phenomena, modeling methodology and relevant pa ra mete rizatio ns. Several areas of particular modeling interest are discussed. In the sorbent bed, capture of the translating CO2 saturation front and associated local energy and mass balance in both adsorbing and desorbing modes is covered. The CIHX poses particular challenges for modeling in SINDA/FLUINT as accounting for solids states in fluid submodels are not a native capability. Methods for capturing phase change and latent heat of ice as well as the transport properties across a layer of low density accreted frost are developed. This extended modeling capacity is applicable to temperatures greater than 258 K. To extend applicability to the minimum device temperature of 235 K, a method for a mapped transformation of temperatures from below the limit temperatures to some value above is given along with descriptions for associated material property transformations and the resulting impacts to total heat and mass transfer. Similar considerations are shown for the SHX along with assumptions for flow mechanics and resulting model methods for sublimation in a flow.

Bower, Chad↗
NASA NTRS2010

Orion Active Thermal Control System Dynamic Modeling Using Simulink/MATLAB

This paper presents dynamic modeling of the crew exploration vehicle (Orion) active thermal control system (ATCS) using Simulink (Simulink, developed by The MathWorks). The model includes major components in ATCS, such as heat exchangers and radiator panels. The mathematical models of the heat exchanger and radiator are described first. Four different orbits were used to validate the radiator model. The current model results were compared with an independent Thermal Desktop (TD) (Thermal Desktop, PC/CAD-based thermal model builder, developed in Cullimore & Ring (C&R) Technologies) model results and showed good agreement for all orbits. In addition, the Orion ATCS performance was presented for three orbits and the current model results were compared with three sets of solutions- FloCAD (FloCAD, PC/CAD-based thermal/fluid model builder, developed in C&R Technologies) model results, SINDA/FLUINT (SINDA/FLUINT, a generalized thermal/fluid network-style solver ) model results, and independent Simulink model results. For each case, the fluid temperatures at every component on both the crew module and service module sides were plotted and compared. The overall agreement is reasonable for all orbits, with similar behavior and trends for the system. Some discrepancies exist because the control algorithm might vary from model to model. Finally, the ATCS performance for a 45-hr nominal mission timeline was simulated to demonstrate the capability of the model. The results show that the ATCS performs as expected and approximately 2.3 lb water was consumed in the sublimator within the 45 hr timeline before Orion docked at the International Space Station.

Wang, Xiao-Yen J.↗