Chemical Kinetics of the TPS and Base Bleeding During Flight Test

The present research deals with thermal degradation of polyurethane foam (PUF) during flight test. Model of thermal decomposition was developed that accounts for polyurethane kinetics parameters extracted from thermogravimetric analyses and radial heat losses to the surrounding environment. The model predicts mass loss of foam, the temperature and kinetic of release of the exhaust gases and char as function of heat and radiation loads. When PUF is heated, urethane bond break into polyol and isocyanate. In the first stage, isocyanate pyrolyses and oxidizes. As a result, the thermo-char and oil droplets (yellow smoke) are released. In the second decomposition stage, pyrolysis and oxidization of liquid polyol occur. Next, the kinetics of chemical compound release and the information about the reactions occurring in the base area are coupled to the CFD simulations of the base flow in a single first stage motor vertically stacked vehicle configuration. The CFD simulations are performed to estimate the contribution of the hot out-gassing, chemical reactions, and char oxidation to the temperature rise of the base flow. The results of simulations are compared with the flight test data

Physics based model for online fault detection in autonomous cryogenic loading system

We report the progress in the development of the chilldown model for a rapid cryogenic loading system developed at NASA-Kennedy Space Center. The nontrivial characteristic feature of the analyzed chilldown regime is its active control by dump valves. The two-phase flow model of the chilldown is approximated as one-dimensional homogeneous fluid flow with no slip condition for the interphase velocity. The model is built using commercial SINDA/FLUINT software. The results of numerical predictions are in good agreement with the experimental time traces. The obtained results pave the way to the application of the SINDA/FLUINT model as a verification tool for the design and algorithm development required for autonomous loading operation

Optimization of cryogenic chilldown and loading operation using SINDA/FLUINT

A cryogenic advanced propellant loading system is currently being developed at NASA. A wide range of applications and variety of loading regimes call for the development of computer assisted design and optimization methods that will reduce time and cost and improve the reliability of the APL performance. A key aspect of development of such methods is modeling and optimization of non-equilibrium two-phase cryogenic flow in the transfer line. Here we report on the development of such optimization methods using commercial SINDA/FLUINT software. The model is based on the solution of two-phase flow conservation equations in one dimension and a full set of correlations for flow patterns, losses, and heat transfer in the pipes, valves, and other system components. We validate this model using experimental data obtained from chilldown and loading of a cryogenic testbed at NASA Kennedy Space Center. We analyze sensitivity of this model with respect to the variation of the key control parameters including pressure in the tanks, openings of the control and dump valves, and insulation. We discuss the formulation of multi-objective optimization problem and provide an example of the solution of such problem

Hierarchy of two-phase flow models for autonomous control of cryogenic loading operation

We report on the development of a hierarchy of models of cryogenic two-phase flow motivated by NASA plans to develop and maturate technology of cryogenic propellant loading on the ground and in space. The solution of this problem requires models that are fast and accurate enough to identify flow conditions, detect faults, and to propose optimal recovery strategy. The hierarchy of models described in this presentation is ranging from homogeneous moving- front approximation to separated non-equilibrium two-phase cryogenic flow. We compare model predictions with experimental data and discuss possible application of these models to on-line integrated health management and control of cryogenic loading operation

d-matrix based fault modeling for cryogenic loading systems

The study is motivated by NASA plans to develop technology for an autonomous cryogenic loading operation including online fault diagnostics as a part of Integrated Health Management system. For years, the diagnostic modeling effort is performed in many paradigms. None of these paradigms independently can provide a complete set of efficiency metrics: better diagnostics, lower run-time, etc. D-matrix, a causal 0-1 relationship between faults and tests, is proposed as a single representation between different model-based diagnostic methods for comparison and communication. This framework is suitable to create a common platform for communication via D-matrix for systems engineering process. The knowledge transfer between modeling techniques is done via D-matrix. In addition, D-matrix provides a common paradigm to compare the embedded knowledge and performance of heterogeneous diagnostic systems. D-matrix is generated from physics models to be used with faster run-time performance D-matrix based diagnostic algorithms. Additionally, we will also investigate if the derived D-matrix and thereby the physics model is sufficient and accurate for efficient diagnostics via iDME tool