Academic literature on the topic 'Solid propellant rockets Combustion'

The aim of this work is to eliminate the explosion possibility of a rocket engine that operates on a fast-burning solid propellant. The problem is considered by analogy with experiments conducted earlier. Various ways to increase the propellant combustion rate are presented. Examples of how the solid propellant combustion rate depends on the metal fuel and the oxidizer particle size are given. It is shown that unstable combustion of a solid propellant at high combustion chamber pressures is due to unstable combustion of the gas phase in the vicinity of the bifurcation point. Zeldovich’s theory of nonstationary powder combustion is applied to analyzing the explosion dynamics of the Hrim-2 missile’s solid-propellant sustainer engine. This method of analysis has not been used before. The suggested version that this phenomenon is related to the aluminum particle size allows one to increase the combustion rate in the combustion chamber of a liquid-propellant engine, thus avoiding the vicinity of the bifurcation point. The combustion of solid propellants differing in aluminum particle size is considered. The metal fuel and the oxidizer particle sizes most optimal in terms of explosion elimination are determined and substantiated. The use of submicron aluminum enhances the evaporation of ammonium perchlorate due to the infrared radiation of aluminum particles heated to an appropriate radiation temperature. This increases the gas inflow into the charge channel, thus impeding the suppression of ammonium perchlorate sublimation by a high pressure, which is important in the case where the engine body materials cannot withstand a high pressure in the charge channel. This increases the stability and rate of solid propellant combustion. It is shown that the Hrim-2 missile’s solid propellant cannot be used in the Hran missile. The combustion rate is suggested to be increased by using fine-dispersed aluminum in the solid propellant.

Several industrial- and research – type fuel rich solid rocket propellants containing nano-metric aluminum metal particles, featuring the same nominal composition, were prepared and experimentally analyzed. The effects of nano-sized aluminum (nAl) on the rheological properties of metal/HTPB slurries and fuel rich solid propellant slurries were investigated. The energetic properties (heat of combustion and density) and the hazardous properties (impact sensitivity and friction sensitivity) of propellants prepared were analyzed and the properties mentioned above compared to those of a conventional aluminized (micro-Al, mAl) propellant. The strand burning rate and the associated combustion fl ame structure of propellants were also determined. The results show that nAl powder is nearly “round” or “ellipse” shaped, which is different from the tested micrometric Al used as a reference metal fuel. Two kinds of Al (nAl and mAl) powder can be dispersed in HTPB binder suffi ciently. The density of propellant decreases with increasing mass fraction of nAl powder; the measured heat of combustion, friction sensitivity, and impact sensitivity of propellants increase with increasing mass fraction of nAl powder in the formulation. The burning rates of fuel rich propellant increase with increasing pressure, and the burning rate of the propellant loaded with 20% mass fraction of nAl powder increases 77.2% at 1 MPa, the pressure exponent of propellant increase a little with increasing mass fraction of nAl powder in the explored pressure ranges.

Ammonium perchlorate (AP) based solid propellant is a modern solid rocket propellant used in various applications. The combustion characteristics of AP based composite propellants were extensively studied by many research scholars to gain higher thrust. The amount of thrust and the thrust profile, which may be obtained from a specific grain design, is mainly determined by the propellant composition and the manufacturing process that produces the solid propellant. This article is intended to review and discuss several aspects of the composition and preparation of the solid rocket propellant. The analysis covers the main ingredients of AP based propellants such as the binder, oxidizer, metal fuel, and plasticizers. The main conclusions are derived from each of its components with specific methods of good manufacturing practices. In conclusion, the AP based solid propellant, like other composite propellants is highly influenced by its composition. However, the quality of the finished grain is mainly due to the manufacturing process.

To describe the acoustic instabilities in the combustion chambers of laterally burning solid propellant rockets the interaction of the mean flow with the acoustic waves is analysed, using multiple scale techniques, for realistic cases in which the combustion chamber is slender and the nozzle area is small compared with the cross-sectional area of the chamber. Associated with the longitudinal acoustic oscillations we find vorticity and entropy waves, with a wavelength typically small compared with the radius of the chamber, penetrating deeply into the chamber. We obtain a set of differential equations to calculate the radial and axial dependence of the amplitude of these waves. The boundary conditions are provided by the acoustic admittance of the propellant surface, given by an existing analysis of the thin gas-phase reaction layer adjacent to the solid–gas interface, and of the nozzle, accounting here for the possible effect of the vorticity and entropy waves. The equations are integrated in closed form and the results provide the growth rate of the disturbances, which we use to determine the conditions for instability of the longitudinal oscillations.

Erosive burning usually refers to the increase in the propellant burning rate caused by high velocity combustion gasses flowing over the propellant surface. It may seriously affect the performance of solid-propellant rocket motors [1]. A series of experiments had been made to study the effects of length to the diameter ratio in a single tubular propellant grain on the erosive burning phenomenon. In the same combustion pressure and different grain geometries, the burning pattern ofAP1based propellantwere recorded. Furthermore, pressure-time curve for each condition was obtained. The mean velocity gradient is obtained by some thermo-gas-dynamical analysis on experimental data. The results can be used for preliminary design ofAPbased tubular propellant rocket motors. This method may be used for other types of tubular solid propellants which defer in chemical formulation.

The asphalt propellant for rockets has been investigated since 1960. This material has been developed with the variation of fuels, oxidizer, binders, metal elements and additives. As solid propellant, it has some advantages and disadvantages during the implementation. At present, Extracted Buton asphalt has been studied as an alternative propellant fuels. It is a natural asphalt, extracted from Buton island asphalt rock. When the extract of buton asphalt is mixed with oxidizer, binder, and metal powder, it can be functioned as propellant which is able to release high intensity of energy, have strong thrust and power to fly the rocket. This optimization study of solid propellant was conducted by mixing the Buton asphalt as fuel, oxidizer, metal element and other additives to form a solid propellant. The oxidizer consisted of potassium nitrate (KNO3) and potassium perchlorate (KClO4). The variations of KClO4/KNO3, propellant density and the ratio of the nozzle diameter were also conducted in order to find the best propellant composition and the optimum operating conditions to produce enough power while maintain the integrity of the rocket. The main parameters such as the propellant’s thrust (F) and the specific impulse (Isp) were examined. The results showed that higher composition of KClO4/KNO3 gave the higher value of the thrust and the specific impulse. KClO4/KNO3 levels above the 1:1 ratio produced an explosive properties at the time of ignition. The tendency of propellant to explode during ignition process was also observed. The optimum condition was obtained at the KClO4/KNO3 ratio of 1:1 , the propellant density was 1.900 gram/cm3 and Ae/A* was 3.33. These conditions generated impulse value that last for 277.07 seconds, average thrust of 14.082 N, and average rate of combustion of 0,24 cm/second. Therefore, it can be concluded that propellant with fuel from extracted of Buton asphalt can be used as an alternative propellant for rocket.

This study is a mathematical model to obtain the characteristics performance of magnesium metal (powder) and carbon on a potassium nitrate-sucrose (KNSU) solid propellant formulation. Characterization of propellant is, as a general rule, important to determine its performance before it can be suitable for use for a rocket flight or any mission. Method of ballistic load cell evaluation was used to validate results and a mathematical model using the combustion exhaust products was solved to obtain the characteristics performance parameters of the propellant. The carbon constituent which acts as an opacifier and coolant was kept constant at 2% in order to arrest some of the heat during the combustion process and helped to lower the combustion temperature, because high combustion temperature could lead to combustion chamber rupture or failure. The effect of addition of magnesium which was optimized for 3% in the formulation contributed significantly in improving the overall performance of the propellant. The utilization of magnesium in KNSU propellant provided higher values parameters and better performance compared to when not included. This was confirmed with the model equations. The propellant combustion products equation was used to model and obtain the characteristics performance parameters. This gave propellant specific impulse (122.9s), combustion temperature (1821K), heat ratio (1.1592), molecular weight (36.89g/mole), propellant density (1912.5kg/m3) and characteristics velocity (1000m/s) result while maintaining the same chamber pressure.

This research work aimed at investigating the effects of magnesium metal (powder) and carbon on a potassium nitrate-sucrose (KNSU) solid propellant formulation. Characterization of propellant is very important to determine its performance before it can be suitable for use for a rocket flight or any mission. Ballistic loadcell method was used. The ballistic load cell instrumentation measured the thrust generated by the propellant, the propellant burn time and the exit temperature of the burning hot propellant gases. The carbon constituent which acts as an opacifier and coolant was kept constant at 2% in order to arrest some of the heat during the combustion process and helped to lower the combustion temperature, because high combustion temperature could lead to combustion chamber rupture or failure. Also, carbon was not increased beyond 2%, so as not to make the propellant excessively smoky because of presence of magnesium oxide and other solids in the combustion products that can cause air pollution, and could be harmful to human lives and the environment. The propellant specific impulse (117.9s), combustion temperature (1818K), heat ratio (1.1508), propellant molecular weight (38.88g/mole), propellant density (1874.6kg/m3), characteristics velocity (997.2m/s) and burn rate (0.00906m/s) were obtained. The effect of addition of magnesium which was optimized for 3% in the formulation contributed significantly in improving the overall performance of the propellant as parameters such as the specific impulse, chamber temperature, characteristics velocity and heat ratio were found to have higher values as compare to the KNSU propellant when magnesium was not present in the formulation. Basically, higher values of these parameters suggest better propellant performance. Also, in this case, when carbon was increased beyond 2%, the propellant was excessively smoky because of presence of magnesium oxide and other solids in the combustion products that can cause air pollution, and could be harmful to human lives and the environment.

The paper describes an influence of high explosives: hexogene (RDX), octogene (HMX), and dinitro-diaminoethene (FOX-7) on the properties of heterogeneous solid rocket propellant (HSRP) prepared on the base of Hydroxy Terminated Polybutadiene (HTPB) in which ammonium perchlorate (AP) was partially replaced by sodium nitrate (SN). It reduced the content of HCl in combustion products. Theoretical values of thermochemical and thermodynamic properties such as isochoric combustion heat (Q), specific impulse (Isp) and contents of combustion products in motor combustion chamber and nozzle have been identified by using the ICT-Code program. The rheological properties (virtual viscosity) of the propellant slurry during curing process, the sensitivity to mechanical stimuli (impact, friction), decomposition temperature, calorific value and hardness of propellants containing explosive materials were tested by instruments and ballistic properties were investigated by laboratory rocket motor (LRM).

A dual-frequency microwave bum rate measurement system for solid rocket motors has been developed and is described. The system operates in the X-band (8.2-12.4 Ghz) and uses two independent frequencies operating simultaneously to measure the instantaneous bum rate in a solid rocket motor. Modeling of the two frequency system was performed to determine its effectiveness in limiting errors caused by secondary reflections and errors in the estimates of certain material properties, particularly the microwave wavelength in the propellant. Computer simulations based upon the modeling were performed and are presented. Limited laboratory testing of the system was also conducted to determine its ability perform as modeled.

Simulations showed that the frequency ratio and the initial motor geometry (propellant thickness and combustion chamber diameter) determined the effectiveness of the system in reducing secondary reflections. Results presented show that higher frequency ratios provided better error reduction. Overall, the simulations showed that a dual frequency system can provide up to a 75% reduction in burn rate error over that returned by a single frequency system. The hardware and software for dual frequency measurements was developed and tested, however, further instrumentation work is required to increase the rate at which data is acquired using the methods presented here. The system presents some advantages over the single frequency method but further work needs to be done to realize its full potential.

Master of Science

A method for developing an erosive burning model for use in solid propellant design-and-analysis interior ballistics codes is described and evaluated. Using Direct Numerical Simulation, the primary mechanisms controlling erosive burning (turbulent heat transfer, and finite rate reactions) have been studied independently through the development of models using finite rate chemistry, and infinite rate chemistry. Both approaches are calibrated to strand burn rate data by modeling the propellant burning in an environment with no cross-flow, and adjusting thermophysical properties until the predicted regression rate matches test data. Subsequent runs are conducted where the cross-flow is increased from M=0.0 up to M=0.8. The resulting relationship of burn rate increase versus Mach Number is used in an interior ballistics analysis to compute the chamber pressure of an existing solid rocket motor. The resulting predictions are compared to static test data. Both the infinite rate model and the finite rate model show good agreement when compared to test data. The propellant considered is an AP/HTPB with an average AP particle size of 37 microns. The finite rate model shows that as the cross-flow increases, near wall vorticity increases due to the lifting of the boundary caused by the side injection of gases from the burning propellant surface. The point of maximum vorticity corresponds to the outer edge of the APd-binder flame. As the cross-flow increases, the APd-binder flame thickness becomes thinner; however, the point of highest reaction rate moves only slightly closer to the propellant surface. As such, the net increase of heat transfer to the propellant surface due to finite rate chemistry affects is small. This leads to the conclusion that augmentation of thermal transport properties and the resulting heat transfer increase due to turbulence dominates over combustion chemistry in the erosive burning problem. This conclusion is advantageous in the development of future models that can be calibrated to heat transfer conditions without the necessity for finite rate chemistry. These results are considered applicable for propellants with small, evenly distributed AP particles where the assumption of premixed APd-binder gases is reasonable.

Thesis (MScIng)--University of Stellenbosch, 2003.
ENGLISH ABSTRACT: It was shown in an earlier study that it is possible to predict the spectral radiance of rocket combustion plumes directly from the propellant composition and motor parameters. Little is published in the open literature on this subject, but the current trend is to use determinative methods like computational fluid dynamics and statistical techniques to simulate wide band radiance based on blackbody temperature assumptions. A limitation of these methods is the fact that they are computationally expensive and rather complex to implement. An alternative modeling approach was used which did not rely on solving all the nonlinearities and complex relationships applicable to a fundamental model. A multilayer perceptron based Neural Network was used to develop a parametric functional mapping between the propellant chemical composition and the motor design and the resulting spectral irradiance measured in a section of the plume. This functional mapping effectively models the relationship between the rocket design and the plume spectral radiance. Two datasets were available for use in this study: Emission spectra from solid propellant rockets and flare emission spectra. In the case of the solid rocket propellants, the input to the network consisted of the chemical composition of the fuels and four motor parameters, with the output of the network consisting of 146 scaled emission spectra points in the waveband from 2-5 microns. The four motor parameters were derived from equations describing the mass flow characteristics of rocket motors. The mass flow through the rocket motor does have an effect on the shape of the plume of combustion gases, which in turn has an effect on the infrared signature of the plume. The characteristics of the mass flow through the nozzle of the rocket motor determine the thermodynamic properties of the combustion process. This then influences the kind of chemical species found in the plume and also at what temperature these species are radiating energy.The resultant function describing the plume signature is: Plume signature f {p T A fuel composition} t , , , , 1 1 = ε It was demonstrated that this approach yielded very useful results. Using only 18 basic variables, the spectra were predicted properly for variations in all these parameters. The model also predicted spectra that agree with the underlying physical situation when changing the composition as a whole. By decreasing the Potassium content for example, the model demonstrated the effect of a flame suppressant on the radiance in this wavelength band by increasing the predicted output. Lowering the temperature, which drives the process of molecular vibration and translation, resulted in the expected lower output across the spectral band. In general, it was shown that only a small section of the large space of 2 propellant classes had to be measured in order to successfully generate a model that could predict emission spectra for other designs in those classes. The same principal was then applied to predicting the infrared spectral emission of a burning flare. The brick type flare considered in this study will ignite and the solid fuel will burn on all surfaces. Since there are no physical parameters influencing the plume as in the case of the rocket nozzles it was required to search for parameters that could influence the flare plume. It was possible to calculate thermodynamic properties for the flare combustion process. These parameters were then reduced to 4 parameters, namely: the oxidant-fuel ratio, equilibrium temperature, the molar mass and the maximum combustion temperature. The input variables for the flares thus consisted of the chemical composition and 4 thermodynamic parameters described above. The network proposed previously was improved and optimised for a minimum number of variables in the system. The optimised network marginally improved on the pevious results (with the same data), but the training time involved was cut substantially. The same approach to the optimization of the network was again followed to determine the optimal network structure for predicting the flare emission spectra. The optimisation involved starting out with the simplest possible network construction and continuouslyincreasing the variables in the system until the solution predicted by the network was satisfactory. Once the structure of the network was determined it was possible to optimise the training algorithms to further improve the solution. In the case of the solid rocket propellant emission data it was felt that it would be important to be able to predict the chemical composition of the fuel and the motor parameters using the infrared emission spectra as input. This was done by simply reversing the optimised network and exchanging the inputs with the outputs. The results obtained from the reversed network accurately predicted the chemical composition and motor parameters on two different test sets. The predicted spectra of some of the solid propellant rocket test sets and flare test sets did not compare well with the expected values. This was due to the fact that these test sets were in a sparsely populated area of the variable space. These outliers are normally removed from training data, but in this case there wasn’t enough data to remove outliers. To obtain an indication of the strength of the correlation between the predicted and measured line spectra two parameters were used to test the correlation between two line spectra. The first parameter is the Pearson product moment of coefficient of correlation and gives an indication of how good the predicted line spectra followed the trend of the measured spectral lines. The second parameter measures the relative distance between a target and predicted spectral point. For both the solid propellants and the flares the correlation values was very close to 1, indicating a very good solution. Values for the two correlation parameters of a test set of the flares were 0.998 and 0.992. In order to verify the model it was necessary to prove that the solution yielded by the model is better than the average of the variable space. Three statistical tests were done consisting of the mean-squared-error test, T-test and Wilcoxon ranksum test. In all three cases the average of the variable space (static model) and the predicted values (Neural Network model) were compared to the measured values. For both the T-test and the Wilcoxon ranksum test the null hypothesis is rejected when t < -tα = 1.645 and then thealternative hypothesis is accepted, which states that the error of the NN model will be smaller than that of the static model. The mean squared error for the static model was 0.102 compared to the 0.0167 of the neural net, for a solid propellant rocket test set. A ttest was done on the same test set, yielding a value of –2.71, which is smaller than – 1.645, indicating that the NN model outperforms the static model. The Z value for this test set is Z = -11.9886, which is a much smaller than –1.645. The results from these statistical tests confirm that neural network is a valid conceptual model and the solutions yielded are unique.
AFRIKAANSE OPSOMMING: In ‘n vroeër studie is bewys hoe dit moontlik is om die spektrale irradiansie van ‘n vuurpyl se verbrandingspluim te voorspel vanaf slegs die dryfmiddelsamestelling en vuurpylmotoreienskappe. In die literatuur is daar min gepubliseer oor hierdie onderwerp. Dit wil voorkom asof meer deterministiese metodes gebruik word om die probleem op te los. Metodes soos CFD simulasies en statistiese analises word tans verkies om wyeband radiansie te voorspel gebaseer op perfekte swart ligaam teorie. ‘n Groot beperking van hierdie metodes is die feit dat die berekeninge kompleks is en baie lank neem om te voltooi. ‘n Alternatiewe benadering is gebruik, wat nie poog om al die nie-liniêre en komplekse verbande uit eerste beginsels op te los nie. ‘n Neurale netwerk is gebruik om ‘n funksionele verband te skep tussen die chemiese samestelling van die dryfmiddel, vuurpylmotor ontwerp en die spektrale irradiansie van die vuurpyl se pluim. Die funksionele verband kan nou effektief die afhanklikheid van die dryfmiddelsamestelling, vuurpylmotor ontwerp en die spektrale uitset modelleer. Twee datastelle was beskikbaar vir analise: Emissie spektra van vaste dryfmiddel vuurpyle en ook van vaste dryfmiddel fakkels. Die invoer tot die neurale netwerk van die vuurpyle het bestaan uit die chemiese samestelling van die dryfmiddel en 4 vuurpylmotor eienskappe. Die uitvoer van die netwerk het weer bestaan uit 146 spektrale irradiansie waardes in die golflengte band van 2-5μm. Die 4 vuurpylmotor eienskappe is afgelei uit massavloei teorie vir vuurpyl motors, aangesien die uitvloei van die produkgasse ‘n invloed op die pluim van die motor sal hê. Die massavloei het weer ‘n effek op die spektrale handtekening van die pluim. Die eienskappe van die massavloei deur die mondstuk van die vuurpylmotor bepaal die termodinamiese eienskappe van die verbrandingsproses. Die invloed op die verbrandingsproses bepaal weer watter tipe produkte gevorm word en by watter temperatuur hulle energie uitstraal. Die gevolg is dat ‘n funksie gedefinieer kan word wat die pluim beskryf.Pluim handtekening = f{, temperatuur, mondstuk keël grootte, vernouings verhouding van mondstuk, dryfmiddelsamestelling} Deur net 18 invoer nodes te gebruik kon die netwerk die irradiansie suksesvol voorspel met ‘n variansie in al die invoer waardes. Deur byvoorbeeld die Kalium inhoud van die dryfmiddel samestelling te verminder het die model die vermindering van ‘n vlam onderdrukker suksesvol nageboots deurdat die irradiansie ‘n hoër uitset gehad het. Die sensitiwiteit van die model is verder getoets deur die temperatuur in die verbrandingskamer te verlaag, met ‘n korrekte laer irradiansie uitset, as gevolg van die feit dat die temperatuur die molekulêre vibrasie en translasie beweging beheer. Dieselfde benadering is gebruik om die model te bou vir die voorspelling van die fakkels se infrarooi irradiansie. Anders as die vuurpylmotors vind die verbranding in die geval van die fakkels in die atmosfeer plaas. Dit was dus ook nodig om na die termodinamiese eienskappe van die fakkel verbranding te kyk. Verskeie parameters is bereken, maar 4 parameters, naamlik die brandstof-suurstof verhouding, temperatuur, molêre massa en die maksimum verbrandingstemperatuur, tesame met die dryfmiddel samestelling kon die irradiansie van die fakkels suskesvol voorspel. Die bestaande netwerk struktuur vir die vuurpylmotors is verbeter en geoptimiseer vir ‘n minimum hoeveelheid veranderlikes in die stelsel. Die geoptimiseerde netwerk het ‘n klein verbetering in die voorspellings getoon, maar die oplei het drasties afgeneem. Dieselfde benadering is gebruik om die optimale netwerk vir die fakkels te bepaal. Optimisering van die netwerk struktuur is bereik deur met die eenvoudigste struktuur te begin en die hoeveelheid veranderlikes te vermeerder totdat ‘n bevredigende oplossing gevind is. Na die struktuur van die netwerk bevestig is, kon die oordragfunksies op die nodes verder geoptimiseer word om die model verder te verbeter. Dit het verder geblyk dat dit moonlik is om die netwerk vir die vuurpylmotors om te draai sodat die irradiansie gebruik word om die dryfmiddel samestelling en motor eienskappe te voorspel. Die netwerk is eenvoudig omgedraai en die insette het die uitsette geword.Die resultate van die omgekeerde netwerk het bevestig dat dit wel moontlik is om die dryfmiddel samestelling en motor eienskappe te voorspel vanaf die irradiansie. Die voorspelde spektra van beide die vuurpylmotors en die fakkels het nie altyd goed gekorreleer met die gemete data nie. Van die spektra kom voor in ‘n lae digtheidsdeel van die veranderlike ruimte. Dit het tot gevolg gehad dat daar nie genoeg data vir opleiding van die netwerk in die omgewing van die toetsdata was nie. Hierdie data is eintlik uitlopers en moet verwyder word van die opleidingsdata, maar daar is alreeds nie genoeg data beskikbaar om die uitlopers te verwyder nie. Dit is nodig om te bepaal hoe goed die voorspelde data vergelyk met die gemete data. Twee parameters is gebruik om te bepaal hoe goed die data korreleer. Die eerste is die “Pearson product moment of coefficient of correlation”, wat ‘n goeie aanduiding gee van hoe goed die voorspelde waardes die gemete waardes se profiel volg. Die tweede parameter meet die relatiewe afstand tussen die teiken en die voorspelde waardes. Vir beide die vuurpylmotors en die fakkels het die toetsstelle ‘n korrelasiewaarde van baie na aan 1 gegee, wat ‘n goeie korrelasie is. Die waardes van die twee parameters vir een van die fakkel toetstelle was onderskeidelik 0.998 en 0.992. Die model is geverifieer deur te bepaal of die model ‘n beter oplossing bied as die gemiddeld van die veranderlike ruimte. Drie statistiese toetse is gedoen: “Mean-squarederror” toets, T-toets en ‘n “Wilcoxon ranksum” toets. In al drie gevalle word die gemiddelde van die veranderlike ruimte (statiese model) en die voorspelde waardes (Neurale netwerk model) teen die gemete waardes getoets. Vir beide die T-toets en die “Wilcoxon ranksum” toets word die nul hipotese verwerp indien t < ta = 1.645 en dan word die alternatiewe hipotese aanvaar, wat bepaal dat die fout van die neurale netwerk model kleiner is as die van die statiese model. Die “mean-squared-error” van die statiese model was 0.102, in vergelyking met 0.0167 van die neurale netwerk model vir ‘n vuurpylmotor toetsstel. ‘n T-toets is gedoen vir dieselfde toetsstel, met ‘n resultaat van-2.71, wat kleiner is as –1.645 en aandui dat die neurale netwerk model weereens beter presteer as die statiese model. Die Z waarde uit die “Wilcoxon ranksum” toets is Z=- 11.9886, wat baie kleiner is as –1.645. Die resultate van die statitiese toetse toon dat die neurale netwerk ‘n geldige model is en die oplossings van die model ook uniek is.

Thesis (MScIng)--University of Stellenbosch, 2003.
ENGLISH ABSTRACT: The emission spectrum measured in the middle infrared (IR) band from the plume of a rocket can be used to identify rockets and track inbound missiles. It is useful to test the stealth properties of the IR fingerprint of a rocket during its design phase without needing to spend excessive amounts of money on field trials. The modelled predictions of the IR spectra from selected rocket motor design parameters therefore bear significant benefits in reducing the development costs. In a recent doctorate study it was found that a fundamental approach including quantum-mechanical and computational fluid dynamics (CFD) models was not feasible. This is first of all due to the complexity of the systems and secondly due to the inadequate calculation speeds of even the most sophisticated modern computers. A solution was subsequently investigated by use of the ‘black-box’ model of a multi-layer perceptron feed-forward neural network with a single hidden layer consisting of 146 nodes. The input layer of the neural network consists of 18 rocket motor design parameters and the output layer consists of 146 IR absorbance variables in the range from 2 to 5 μm wavelengths. The results appeared promising for future investigations. The available data consist of only 18 different types of rocket motors due to the high costs of generating the data. The 18 rocket motor types fall into two different design classes, the double base (DB) and composite (C) propellant types. The sparseness of the data is a constraint in building adequate models of such a multivariate nature. The IR irradiance spectra data set consists of numerous repeat measurements made per rocket motor type. The repeat measurements form the pure error component of the data, which adds stability to training and provides lack-of-fit ANOVA capabilities. The emphasis in this dissertation is on comparing the feed-forward neural network model to the linear and neural network partial least squares (PLS) modelling techniques. The objective is to find a possibly more intuitive and more accurate model that effectively generalises the input-output relationships of the data. PLS models are known to be robust due to the exclusion of redundant information from projections made to primary latent variables, similarly to principal components (PCA) regression. The neural network PLS techniques include feed-forward sigmoidal neural network PLS (NNPLS) and radial-basis functions PLS (RBFPLS). The NNPLS and RBFPLS algorithms make use of neural networks to find non-linear functional relationships for the inner PLS models of the NIPALS algorithm. Error-based neural network PLS (EBNNPLS) and radial-basis function network PLS (EBRBFPLS) are also briefly investigated, as these techniques make use of non-linear projections to latent variables. A modification to the orthogonal least squares (OLS) training algorithm of radial-basis functions is developed and applied. The adaptive spread OLS algorithm (ASOLS) allows for the iterative adaptation of the Gaussian spread parameters found in the radial-basis transfer functions. Over-fitting from over-parameterisation is controlled by making use of leaveone- out cross-validation and the calculation of pseudo-degrees of freedom. After cross-validation the overall model is built by training on the entire data set. This is done by making use of the optimum parameterisation obtained from cross-validation. Cross-validation also gives an indication of how well a model can predict data unseen during training. The reverse problem of modelling the rocket propellant chemical compositions and the rocket physical design parameters from the IR irradiance spectra is also investigated. This problem bears familiarity to the field of spectral multivariate calibration. The applications in this field readily make use of PLS and neural network modelling. The reverse problem is investigated with the same modelling techniques applied to the forward modelling problem. The forward modelling results (IR spectrum predictions) show that the feedforward neural network complexity can be reduced to two hidden nodes in a single hidden layer. The NNPLS model with eleven latent dimensions outperforms all the other models with a maximum average R2-value of 0.75 across all output variables for unseen data from cross-validation. The explained variance for the output data of the overall model is 94.34%. The corresponding explained variance of the input data is 99.8%. The RBFPLS models built using the ASOLS training algorithm for the training of the radialbasis function inner models outperforms those using K-means and OLS training algorithms. The lack-of-fit ANOVA tests show that there is reason to doubt the adequacy of the NNPLS model. The modelling results however show promise for future development on larger, more representative data sets. The reverse modelling results show that the feed-forward neural network model, NNPLS and RBFPLS models produce similar results superior to the linear PLS model. The RBFPLS model with ASOLS inner model training and 5 latent dimensions stands out slightly as the best model. It is found that it is feasible to separately find the optimum model complexity (number of latent dimensions) for each output variable. The average R2-value across all output variables for unseen data is 0.43. The average R2-value for the overall model is 0.68. There are output variables with R2-values of over 0.8. The forward and reverse modelling results further show that dimensional reduction in the case of PLS does produce the best models. It is found that the input-output relationships are not highly non-linear. The non-linearities are largely responsible for the compensation of both the DB- and C-class rocket motor designs predictions within the overall model predictions. For this reason it is suggested that future models can be developed by making use of a simpler, more linear model for each rocket class after a class identification step. This approach however requires additional data that must be acquired.
AFRIKAANSE OPSOMMING: Die emissiespektra van die uitlaatpluime van vuurpyle in die middel-infrarooi (IR) band kan gebruik word om die vuurpyle te herken en om inkomende vuurpyle op te spoor. Dit is nuttig om die uitstralingseienskappe van ‘n vuurpyl se IR afdruk te toets, sonder om groot bedrae geld op veldtoetse te spandeer. Die gemodelleerde IR spektrale voorspellings vir ‘n bepaalde stel vuurpylmotor ontwerpsparameters kan dus grootliks bydra om motorontwikkelingskostes te bemoei. In ‘n onlangse doktorale studie is gevind dat ‘n fundamentele benadering van kwantum-meganiese en vloeidinamika-modelle nie lewensvatbaar is nie. Dit is hoofsaaklik as gevolg van die onvoldoende vermoë van selfs die mees gesofistikeerde moderne rekenaars. ‘n Moontlike oplossing tot die probleem is ondersoek deur gebruik te maak van ‘n multilaag perseptron voorwaartse neurale netwerk met 146 nodes in ‘n enkele versteekte laag. Die laag van invoer veranderlikes bestaan uit agtien vuurpylmotor ontwerpsparameters en die uitvoerlaag bestaan uit 146 IR-absorbansie veranderlikes in die reeks golflengtes vanaf 2 tot 5 μm. Dit het voorgekom dat die resultate belowend lyk vir toekomstige ondersoeke. Weens die hoë kostes om die data te genereer bestaan die beskikbare data uit slegs agtien verskillende tipes vuurpylmotors. Die agtien vuurpyl tipes val verder binne twee ontwerpsklasse, naamlik die dubbelbasis (DB) en saamgestelde (C) dryfmiddeltipes. Die yl data bemoeilik die bou van doeltreffende multiveranderlike modelle. Die datastel van IR uitstralingspektra bestaan uit herhaalde metings per vuurpyltipe. Die herhaalde metings vorm die suiwer fout komponent van die data. Dit verskaf stabilitieit tot die opleiding op die data en verder die vermoë om ‘n analise van variansie (ANOVA) op die data uit te voer. In hierdie tesis lê die klem op die vergelyking tussen die voorwaartse neurale netwerk en die lineêre en neurale netwerk parsiële kleinste kwadrate (PLS) modelleringstegnieke. Die doel is om ‘n moontlik meer insiggewende en akkurate model te vind wat effektief die in- en uitvoer verhoudings kan veralgemeen. Dit is bekend dat PLS modelle meer robuus kan wees weens die weglating van oortollige inligting deur projeksies op hoof latente veranderlikes. Dit is analoog aan hoofkomponente (PCA) regressie. Die neurale netwerk PLS-tegnieke sluit in voorwaartse sigmoïdale neurale netwerk PLS (NNPLS) en radiale-basis funksies PLS (RBFPLS). Die NNPLS en RBFPLS algoritmes maak gebruik van die neurale netwerke om nie-lineêre funksionele verbande te kry vir die binne PLS-modelle van die nie-lineêre iteratiewe parsiële kleinste kwadrate (NIPALS) algoritme. Die fout-gebaseerde neurale netwerk PLS (EBNNPLS) en radiale-basis funksies PLS (EBRBFPLS) is ook weens hulle nie-lineêre projeksies na latente veranderlikes kortiliks ondersoek. ‘n Aanpassing tot die ortogonale kleinste kwadrate (OLS) opleidingsalgoritme vir radiale-basis funksies is ontwikkel en toegepas. Die aangepaste algoritme (ASOLS) behels die iteratiewe aanpassing van die verspreidingsparameters binne die Gauss-funksies van die radiale-basis transformasie funksies. Die oormatige parameterisering van ‘n model word beheer deur kruisvalidering met enkele weglatings en die berekening van pseudo-vryheidsgrade. Na kruisvalidering word die algehele model gebou deur opleiding op die volledige datastel. Dit word gedoen deur van die optimale parameterisering gebruik te maak wat deur kruisvalidering bepaal is. Kruisvalidering gee ook ‘n goeie aanduiding van hoe goed ‘n model ongesiende data kan voorspel. Die modellering van die vuurpyle se chemiese en fisiese ontwerpsparameters (omgekeerde probleem) is ook ondersoek. Hierdie probleem is verwant aan die veld van spektrale multiveranderlike kalibrasie. Die toepassings in die veld maak gebruik van PLS en neurale netwerk modelle. Die omgekeerde probleem word dus ondersoek met dieselfde modelleringstegnieke wat gebruik is vir die voorwaartse probleem. Die voorwaartse modelleringsresultate (IR voorspellings) toon dat die kompleksiteit van die voorwaartse neurale netwerk tot twee versteekte nodes in ‘n enkele versteekte laag gereduseer kan word. Die NNPLS model met elf latente dimensies vaar die beste van alle modelle, met ‘n maksimum R2-waarde van 0.75 oor alle uitvoer veranderlikes vir die ongesiende data (kruisvalidering). Die verklaarde variansie vir die uitvoer data vanaf die algehele model is 94.34%. Die verklaarde variansie van die ooreenstemmende invoer data is 99.8%. Die RBFPLS modelle wat gebou is deur van die ASOLS algoritme gebruik te maak om die PLS binne modelle op te lei, vaar beter in vergelyking met die K-gemiddeldes en OLS opleidingsalgoritmes. Die toetse wat ‘n ‘tekort-aan-passing’ ANOVA behels, toon dat daar rede is om die geskiktheid van die NNPLS model te wantrou. Die modelleringsresultate lyk egter belowend vir die toekomstige ontwikkeling van modelle op groter, meer verteenwoordigde datastelle. Die omgekeerde modellering toon dat die voorwaartse neurale netwerk, NNPLS en RBFPLS modelle soortgelyke resultate produseer wat die lineêre PLS model s’n oortref. Die RBFPLS model met ASOLS opleiding van die PLS binne modelle word beskou as die beste model. Dit is lewensvatbaar om die optimale modelkompleksiteite van elke uitvoerveranderlike individueel te bepaal. Die gemiddelde R2-waarde oor alle uitvoerveranderlikes vir ongesiende data is 0.43. Die gemiddelde R2-waarde vir die algehele model is 0.68. Daar is van die uitvoer veranderlikes wat R2-waardes van 0.8 oortref. Die voor- en terugwaartse modelleringsresultate toon verder dat dimensionele reduksie in die geval van PLS die beste modelle lewer. Daar is ook gevind dat die nie-lineêriteite grootliks vergoed vir die voorspellings van beide DB- en Ctipe vuurpylmotors binne die algehele model. Om die rede word voorgestel dat toekomstige modelle ontwikkel kan word deur gebruik te maak van eenvoudiger, meer lineêre modelle vir elke vuurpylklas nadat ‘n klasidentifikasiestap uitgevoer is. Die benadering benodig egter addisionele praktiese data wat verkry moet word.

This thesis presents the results and analyses of computational studies on certain problems of combustion instability in solid propellants. Specifically, effects of relaxing certain assumptions made in previous models of unsteady burning of solid propellants are investigated. Knowledge of unsteady burning of solid propellants is essential in studying the phenomenon of combustion instability in solid propellant rocket motors. In Chapter 1, an introduction to different types of unsteady combustion investigated in this thesis, such as 1) intrinsic instability, 2) pressure-driven dynamic burning, 3) extinction by depressurization, and 4) L* -instability, is given. Also, a review of previous experimental and theoretical studies of these phenomena is presented. From this review it is concluded that all the previous studies, which investigated the unsteady combustion of solid propellants, made one or more of the following assumptions: 1) quasi-steady gas-phase (QSG), 2) quasi-steady condensed phase reaction zone (QSC), 3) small perturbations, and 4) unity Lewis number. These assumptions limit the validity of the results obtained with such models to: 1) relatively low frequencies (< 1 kHz) of pressure oscillations and 2) small deviations in pressure from its steady state or mean values. The objectives of the present thesis are formulated based on the above conclusions. These are: 1) to develop a nonlinear numerical model of unsteady solid propellant combustion, 2) to relax the assumptions of QSG and QSC, 3) to study the consequent effects on the intrinsic instability and pressure-driven dynamic burning, and 4) to investigate the L* -instability in solid propellant rocket motors. In Chapter 2, a nonlinear numerical model, which relaxes the QSG and QSC assumptions, is set up. The transformation and nondimensionalization of the governing equations are presented. The numerical technique based on the method of operator-splitting, used to solve the governing equations is described. In Chapter 3, the effect of relaxing the QSG assumption on the intrinsic instability is investigated. The stable and unstable solutions are obtained for parameters corresponding to a typical composite propellant. The stability boundary, in terms of the nondimensional parameters identified by Denison and Baum (1961), is predicted using the present model. This is compared with the stability boundary obtained by previous linear stability theories, based on activation energy asymptotics in the gas-phase, which employed QSC and/or QSG assumptions. It is found that in the limit of large activation energy and low frequencies, present result approaches the previous theoretical results. This serves as a validation of the present method of solution. It is confirmed that relaxing the QSG assumption widens the stable region. However, it is found that a distributed reaction in the gas-phase destabilizes the burning. The effect of non-unity Lewis number on the stability boundary is also investigated. It is found that at parametric values corresponding to low pressures and large flame stand-off distances, small amplitude, high frequency (at frequencies near the characteristic frequency of the gas-phase) oscillations in burning rate appear when the Lewis number is greater than one. In Chapter 4, the effect of relaxing the QSG assumption is further investigated with respect to the pressure-driven dynamic burning. Comparison of the pressure-driven frequency response function, Rp, obtained with the present model, both in the QSG and non-QSG framework, with those obtained with previous linear stability theories invoking QSG and QSC assumptions are made. As the frequency of pressure oscillations approaches zero, |RP| predicted using present models approached the value obtained by previous theoretical studies. Also, it is confirmed that the effect of relaxing QSG is to decrease the |Rp| at frequencies near the first resonant frequency. Moreover, relaxing QSG assumption produces a second resonant peak in |Rp| at a frequency near the characteristic frequency of the gas-phase. Further, Rp calculated using the present model is compared with that obtained by a previous linear theory which relaxed the QSG assumption. The two models predicted the same resonant frequencies in the limit of small amplitudes of pressure oscillations. Finally, it is found that the effect of large amplitude of pressure oscillations is to introduce higher harmonics in the burning rate and to reduce the mean burning rate. In Chapter 5, first the present non-QSC model is validated by comparing its results with that of a previous non-QSC model for radiation-driven burning. The model is further validated for steady burning results by comparing with experimental data for a double base propellant (DBP). Then, the effect of relaxing the QSC assumption on steady state solution is investigated. It is found that, even in the presence of a strong gas-phase heat feedback, QSC assumption is valid for moderately large values of condensed phase Zel'dovich number, as far as steady state solution is concerned. However, for pressure-driven dynamic burning, relaxing the QSC assumption is found to increase |RP| at all frequencies. The error due to QSC assumption is found to become significant, either when |Rp| is large or as the driving frequency approaches the characteristic frequency of the condensed phase reaction zone. The predicted real part of the response function is quantitatively compared with experimental data for DBP. The comparison seems to be better with a value of condensed phase activation energy higher than that suggested by Zenin (1992). In Chapter 6, burning rate transients for a DBP during exponential depressurization are computed using non-QSG and non-QSC models. Salient features of extinction and combustion recovery are predicted. The predicted critical initial depressurization rate, (dp/dt)i, is found to decrease markedly when the QSC assumption is relaxed. The effect of initial pressure level on critical (dp/dt)i is studied. It is found that the critical (dp/dt)i decreases with the initial pressure. Also, the overshoot of burning rate during combustion recovery is found to be relatively large with low initial pressures. However as the initial pressure approached the final pressure, the reduction in initial pressure causes a large increase in the critical (dp/dt)i. No extinction is found to occur when the initial pressure is very close to the final pressure. In Chapter 7, a numerical model is developed to simulate the L* -instability in solid propellant motors. This model includes a) the propellant burning model that takes into account nonlinear pressure oscillations and that takes into account an unsteady gas- and condensed phase, and b) a combustor model that allows pressure and temperature oscillations of finite amplitude. Various regimes of L* -burning of a motor, with a typical composite propellant, namely 1) steady burning, 2) oscillatory burning leading to steady state, 3) oscillatory burning leading to extinction, 4) reignition and 5) chuffing are predicted. The predicted dependence of frequency of L* -oscillations on mean pressure is compared with one set of available experimental data. It is found that proper modeling of the radiation heat flux from the chamber walls to the burning surface may be important to predict the re-ignition. In Chapter 8, the main conclusions of the present study are summarized. Certain suggestions for possible future studies to enhance the understanding of dynamic combustion of solid propellants are also given.

The application of emission spectroscopy to monitor combustion products of solid rocket propellant combustion can potentially yield valuable data about reactions occurring within the volatile environment of a strand burner. This information can be applied in the solid rocket propellant industry. The current study details the implementation of a compact spectrometer and fiber optic cable to investigate the visible emission generated from three variations of solid propellants. The grating was blazed for a wavelength range from 200 to 800 nm, and the spectrometer system provides time resolutions on the order of 1 millisecond. One propellant formula contained a fine aluminum powder, acting as a fuel, mixed with ammonium perchlorate (AP), an oxidizer. The powders were held together with Hydroxyl-Terminated-Polybutadiene (HTPB), a hydrocarbon polymer that is solidified using a curative after all components are homogeneously mixed. The other two propellants did not contain aluminum, but rather relied on the HTPB as a fuel source. The propellants without aluminum differed in that one contained a bimodal mix of AP. Utilizing smaller particle sizes within solid propellants yields greater surface area contact between oxidizer and fuel, which ultimately promotes faster burning. Each propellant was combusted in a controlled, non-reactive environment at a range of pressures between 250 and 2000 psi. The data allow for accurate burning rate calculations as well as an opportunity to analyze the combustion region through the emission spectroscopy diagnostic. It is shown that the new diagnostic identifies the differences between the aluminized and non-aluminized propellants through the appearance of aluminum oxide emission bands. Anomalies during a burn are also verified through the optical emission spectral data collected.
M.S.M.E.
Department of Mechanical, Materials and Aerospace Engineering;
Engineering and Computer Science
Mechanical Engineering

Solid rocket motors (SRM)s commonly use aluminized composite propellants. The combustion of aluminum composite propellants in SRM chambers lead to high temperature and pressure conditions resulting in the liquid alumina as a combustion product. The presence of liquid alumina in the flow presents problems such as; chemical erosion of propellant, and mechanical erosion of nozzle. One method of solving the problem of liquid alumina in flow is to change the SRM geometry to induce liquid breakup and suspend the alumina in the flow thus avoiding erosive behavior. To validate numerical simulation methods for geometric breakup induction simulation models of alumina flow can be compared to air and liquid water flows, and the air-liquid water flow models then compared to water-air experimental results. This study investigates experimental geometric induced liquid breakup behavior for the implementation of the alumina flow and nozzle geometry simulation in SRM design. A rectangular chamber was considered for experimental and simulation to explore the air-water flow behavior. The suspension of water was induced with a triangular shaped jump. The resulting two phase flow was examined using photography technique. Significant incitement in the air-water behavior was observed due to geometry modification. Replication of experimental results was simulated with some accuracy.

Abstract It has been a challenge to investigate how to trace particles in a solid rocket motor (SRM) using aluminized composite solid propellant and submerged nozzle. In using CFD simulations, the boundary conditions for the ejecting particles constrain their trajectories, hence these affect the two-phase flow calculations, and thus significantly affect the evaluation of the slag accumulation. The RTR (X-ray Real-time Radiography) technique is a new method to detect the particles in a firing SRM. A method was developed to simulate the particle ejection from the propellant surface. The moving trajectories of metal particles in a firing combustion chamber were measured by using the RTR high-speed motion analyzer. Numerical simulations with different propellant-surface boundary conditions were performed to calculate particle trajectories. Through this study an appropriate surface velocity condition on the propellant surface was discovered. The method developed here can be used for the future CRM research.