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NASA NTRS1980

Computer program documentation D1FLTD to drive SINDA boundary nodes: User's guide

The thermal model correlation process begins when measured thermocouple data is available from the orbital flight tests of the shuttle. For this effort, it is necessary to convert some of the system improved numerical differencing analyzer (SINDA) diffusion or arithmetic nodes to boundary nodes and then drive these boundary nodes to the temperature profile of a flight measurement. An efficient way to provide this capability within the SINDA and OFT software systems is to provide a new SINDA routine, D1FLTD, for use in VARIABLES 1 of SINDA, to access the processed (word-addressable) orbital data reduction center flight data and store the appropriate measurement temperature in the desired SINDA temperature location. The ODRC flight data that is to be used for driving the boundary nodes must be assigned a logical unit number and must reside on a word-addressable file. The user must also provide two SINDA constants for the word positions of the first and last words of the temperature record for each measurement identifier (MID), i.e. each call to D1FLTD, used in the model. D1FLTD is then called from the VARIABLES 1 block to obtain the SINDA boundary node temperature for any MID on the file at any time point.

Damico, S. J.↗

NASA NTRS1992

Running SINDA '85/FLUINT interactive on the VAX

Computer software as engineering tools are typically run in three modes: Batch, Demand, and Interactive. The first two are the most popular in the SINDA world. The third one is not so popular, due probably to the users inaccessibility to the command procedure files for running SINDA '85, or lack of familiarity with the SINDA '85 execution processes (pre-processor, processor, compilation, linking, execution and all of the file assignment, creation, deletions and de-assignments). Interactive is the mode that makes thermal analysis with SINDA '85 a real-time design tool. This paper explains a command procedure sufficient (the minimum modifications required in an existing demand command procedure) to run SINDA '85 on the VAX in an interactive mode. To exercise the procedure a sample problem is presented exemplifying the mode, plus additional programming capabilities available in SINDA '85. Following the same guidelines the process can be extended to other SINDA '85 residence computer platforms.

Simmonds, Boris↗

NASA NTRSDate not supplied

Updates and Correlation of EMU System-Level Model (SINDA EMU)

During United States Extravehicular Activity 80 (US EVA 80), water was observed in the helmet of an Extravehicular Mobility Unit (EMU) during cabin repressurization. One of the primary methods of determining the likely cause of this failure was through a comparison of EVA 80 to other historical EVAs using an analytical approach. The Systems Improved Numerical Differential Analysis EMU model (SINDA EMU) is a system-level model of the EMU that was used in this investigation. SINDA EMU was initially developed and correlated to test data in the 1980s. Since its conception, SINDA EMU has been continually adjusted based on new test data and changes to the EMU design. To support the water in the helmet investigation, SINDA EMU needed to be further updated and recorrelated to ensure accurate results. These changes included changing the primary carbon dioxide (CO2) removal technology, implementing logic to allow for re-evaporation of sweat runoff from the liquid cooling and ventilation garment (LCVG), and improving the transient modeling capabilities. To validate the implementation of these adjustments, SINDA EMU was correlated to test data from the 1990s and human-in-the-loop (HITL) testing from 2014. These updates and correlation efforts proved that SINDA EMU is an effective tool for investigating the EVA 80 water in the helmet failure event.

Noah Lial Andersen↗

NASA NTRS1992

A compressible boundary layer algorithm for use with SINDA '85

It is useful to interface a high-speed-flow solution and SINDA to analyze the thermal behavior of systems that include both conduction and high speed flows. When interfacing a high-speed-flow solution to SINDA, it may be necessary to include the viscous effects in the energy equations. Boundary layer effects of interest include heat transfer coefficients (including convection and viscous dissipation) and friction coefficients. To meet this need, a fast, uncoupled, compressible, two-dimensional, boundary layer algorithm was developed that can model flows with and without separation. This algorithm was used as a subroutine with SINDA. Given the core flow properties and the wall heat flux from SINDA, the boundary layer algorithm returns a wall temperature to SINDA and boundary layer algorithm are iterated until they predict the same wall temperature.

Sakowski, Barbara↗

NASA NTRS1973

Thermal and flow analysis subroutines for the SINDA-version 9 computer routine

Fluid flow analysis, special thermal analysis and input/output capabilities of the MOTAR routine were incorporated into the SINDA routine. All the capabilities were added in the form of user subroutines so that they may be added to different versions of SINDA with a minimum of programmer effort. Two modifications were made to the existing subroutines of SINDA/8 to incorporate the above subroutines. These were: (1) A modification to the preprocessor to permit actual values of array numbers, conductor numbers, node numbers or constant numbers supplied as array data to be converted to relative numbers. (2) Modifications to execution subroutine CNFAST to make it compatible with the radiant interchange user subroutine, RADIR. This modified version of SINDA has been designated SINDA/version 9. A detailed discussion of the methods used for the capabilities added is presented. The modifications for the SINDA subroutines are described, as well as user subroutines. All subroutines added or modified are listed.

Oren, J. A.↗

NASA NTRS1992

A simple node and conductor data generator for SINDA

This paper presents a simple, automated method to generate NODE and CONDUCTOR DATA for thermal match modes. The method uses personal computer spreadsheets to create SINDA inputs. It was developed in order to make SINDA modeling less time consuming and serves as an alternative to graphical methods. Anyone having some experience using a personal computer can easily implement this process. The user develops spreadsheets to automatically calculate capacitances and conductances based on material properties and dimensional data. The necessary node and conductor information is then taken from the spreadsheets and automatically arranged into the proper format, ready for insertion directly into the SINDA model. This technique provides a number of benefits to the SINDA user such as a reduction in the number of hand calculations, and an ability to very quickly generate a parametric set of NODE and CONDUCTOR DATA blocks. It also provides advantages over graphical thermal modeling systems by retaining the analyst's complete visibility into the thermal network, and by permitting user comments anywhere within the DATA blocks.

Gottula, Ronald R.↗

NASA NTRS1984

A SINDA modeling technique for pumped two-phase spacecraft cooling systems

The purpose of this paper is to present a modeling technique that has proven successful in simulating pumped, two-phase cooling systems. The technique uses the standard SINDA thermal-analysis program and thereby extends the capabilities of SINDA to complex, active spacecraft thermal-control systems. This paper provides sufficient detail that a current SINDA user will be able to apply the technique by reference to this paper alone.

Ollendorf, S.↗

NASA NTRS1987

SINDA-NASTRAN interfacing program theoretical description and user's manual

The task of converting SINDA finite difference thermal model temperature results into NASTRAN finite element model thermal loads can be very labor intensive if there is not one node-to-one element, or systematic node-to-element. correlation between models. This paper describes the SINDA-NASTRAN Interfacing Program (SNIP), a FORTRAN computer code that generates NASTRAN structural model thermal load cards given by SINDA (or similar thermal model) temperature results and thermal model geometric data. SNIP generates NASTRAN thermal load cards for NASTRAN plate, shell, bar, and beam elements. The paper describes the interfacing procedures used by SNIP, and discusses set-up and operation of the program. Sample cases are included to demonstrate use of the program and show its performance under a variety of conditions. SNIP can provide structural model thermal loads that accurately reflect thermal model results while reducing the time required to interface thermal and structural models when compared to other methods.

Winegar, Steven R.↗

NASA NTRS1979

Addition of a demand plotting capability to SINDA

The use of the DISSPLA plotting package to write a routine to be added to SINDA is described. This routine, DISPX1, allows the data within a SINDA execution to be plotted in the demand mode.

Damico, S. J.↗

NASA NTRS1980

Computer program documentation: Raw-to-processed SINDA program (RTOPHS) user's guide

Use of the Raw to Processed SINDA(System Improved Numerical Differencing Analyzer) Program, RTOPHS, which provides a means of making the temperature prediction data on binary HSTFLO and HISTRY units generated by SINDA available to engineers in an easy to use format, is discussed. The program accomplishes this by reading the HISTRY unit and according to user input instructions, the desired times and temperature prediction data are extracted and written to a word addressable drum file.

Damico, S. J.↗

NASA NTRS1982

Development of a CRAY 1 version of the SINDA program

The SINDA thermal analyzer program was transferred from the UNIVAC 1110 computer to a CYBER And then to a CRAY 1. Significant changes to the code of the program were required in order to execute efficiently on the CYBER and CRAY. The program was tested on the CRAY using a thermal math model of the shuttle which was too large to run on either the UNIVAC or CYBER. An effort was then begun to further modify the code of SINDA in order to make effective use of the vector capabilities of the CRAY.

Juba, S. M.↗

NASA NTRS1987

FLUINT - General fluid system analysis with SINDA '85

This paper introduces FLUINT (FLUid INTegrator), a general fluid system simulation program that works in conjunction with SINDA '85 (Systems Improved Numerical Differencing Analyzer, 1985 version). FLUINT solves arbitrary networks representing internal fluid systems while SINDA '85 simultaneously solves traditional thermal networks. This transportable program is intended to provide spacecraft thermal management engineers with the analytic tools needed to simulate single- and two-phase coolant loops. The fundamental concepts for fluid system modeling are described, and methods of modeling complex, hardware-specific components are outlined. Underlying correlations and solution methods are briefly discussed. Example analyses and comparisons to test data are provided.

Cullimore, B. A.↗

NASA NTRS1989

Systems Improved Numerical Differencing Analyzer (SINDA)

SINDA '85/FLUINT handles complex problems involving pumps, valves, heat exchangers, and resistor-capacitor networks. When combining SINDA with another classic program, TRASYS II, users tackle thermal radiation problems, including shadowing by opaque or semitransparent surfaces. Utility programs automatically convert SINDA/TRASYS output to form compatible with NASTRAN-developed structures.

Vogt, R. A.↗

NASA NTRS1990

Thermal analysis simulation for a spin-motor used in the advanced main combustion chamber vacuum plasma spray project using the SINDA computer program

One of the many design challenges of this project is predicting the thermal effects due to the environment inside the vacuum chamber on the turntable and spin motor spindle assembly. The objective of the study is to model the spin motor using the computer program System Improved Numerical Differencing Analyzer (SINDA). By formulating the appropriate input information concerning the motor's geometry, coolant flow path, material composition, and bearing and motor winding characteristics, SINDA should predict temperatures at various predefined nodes. From these temperatures, hopefully, one can predict if the coolant flow rate is sufficient or if certain mechanical elements such as bearings, O ring seals, or motor windings will exceed maximum design temperatures.

Mcdonald, Gary H.↗

NASA NTRS1992

A SINDA '85 nodal heat transfer rate calculation user subroutine

This paper describes a subroutine, GETQ, which was developed to compute the heat transfer rates through all conductors attached to a node within a SINDA '85 thermal submodel. The subroutine was written for version 2.3 of SINDA '85. Upon calling GETQ, the user supplies the submodel name and node number which the heat transfer rate computation is desired. The returned heat transfer rate values are broken down into linear, nonlinear, source and combined heat loads.

Cheston, Derrick J.↗

NASA NTRS1993

Analysis of high vacuum systems using SINDA'85

The theory, algorithms, and test data correlation analysis of a math model developed to predict performance of the Space Station Freedom Vacuum Exhaust System are presented. The theory used to predict the flow characteristics of viscous, transition, and molecular flow is presented in detail. Development of user subroutines which predict the flow characteristics in conjunction with the SINDA'85/FLUINT analysis software are discussed. The resistance-capacitance network approach with application to vacuum system analysis is demonstrated and results from the model are correlated with test data. The model was developed to predict the performance of the Space Station Freedom Vacuum Exhaust System. However, the unique use of the user subroutines developed in this model and written into the SINDA'85/FLUINT thermal analysis model provides a powerful tool that can be used to predict the transient performance of vacuum systems and gas flow in tubes of virtually any geometry. This can be accomplished using a resistance-capacitance (R-C) method very similar to the methods used to perform thermal analyses.

Spivey, R. A.↗

NASA NTRS1993

Convection equation modeling: A non-iterative direct matrix solution algorithm for use with SINDA

The determination of the boundary conditions for a component-level analysis, applying discrete finite element and finite difference modeling techniques often requires an analysis of complex coupled phenomenon that cannot be described algebraically. For example, an analysis of the temperature field of a coldplate surface with an integral fluid loop requires a solution to the parabolic heat equation and also requires the boundary conditions that describe the local fluid temperature. However, the local fluid temperature is described by a convection equation that can only be solved with the knowledge of the locally-coupled coldplate temperatures. Generally speaking, it is not computationally efficient, and sometimes, not even possible to perform a direct, coupled phenomenon analysis of the component-level and boundary condition models within a single analysis code. An alternative is to perform a disjoint analysis, but transmit the necessary information between models during the simulation to provide an indirect coupling. For this approach to be effective, the component-level model retains full detail while the boundary condition model is simplified to provide a fast, first-order prediction of the phenomenon in question. Specifically for the present study, the coldplate structure is analyzed with a discrete, numerical model (SINDA) while the fluid loop convection equation is analyzed with a discrete, analytical model (direct matrix solution). This indirect coupling allows a satisfactory prediction of the boundary condition, while not subjugating the overall computational efficiency of the component-level analysis. In the present study a discussion of the complete analysis of the derivation and direct matrix solution algorithm of the convection equation is presented. Discretization is analyzed and discussed to extend of solution accuracy, stability and computation speed. Case studies considering a pulsed and harmonic inlet disturbance to the fluid loop are analyzed to assist in the discussion of numerical dissipation and accuracy. In addition, the issues of code melding or integration with standard class solvers such as SINDA are discussed to advise the user of the potential problems to be encountered.

Schrage, Dean S.↗

NASA NTRS1992

NASA's Software Bank (SINDA 1985/FLUINT)

Astronautics Corporation uses SINDA '85/FLUINT to model designs for efficient magnetic refrigeration devices. The proposed designs are compared for relative efficiency, and the best concept is selected. SINDA is later used to develop a more complex model for predicting temperature distribution in the refrigeration.

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