Analytical Methods for Predicting Grain Regression in Tactical Solid-Rocket Motors

Practical surface-tracking methods are successfully developed to simulate the evolution of the grain geometry, which is dynamically regressing during the combustion of the solid propellant. Three methods, namely the fronttracking, emanating-ray, and least-distance methods, are proposed. The front-tracking method is based on the Lagrangian approach, whereas both the emanating-ray and the least-distance methods are formulated from the Eulerian viewpoint. Three two-dimensional test cases have been examined to compare the programming complexity, simulation accuracy, and computational efficiency of the proposed methods. It is found that the least-distance method performs superior to the other two methods in many numerical respects. The least-distance method is implemented on the tetrahedron grid system to track the outwardly regressing surface of a three-dimensional cubical propellant. Comparison between the predicted erosive volume and burning surface area with the theoretical results yields satisfactory agreement. A grain design similar to one of the Falcon Launch V cases has been employed to demonstrate the usefulness of the proposed methodology in application to a practical three-dimensional grain burnback analysis.

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“…Usually the analytical methods [2] and numerical methods [3,4] are commonly used in the grain burnback analysis.…”

Section: Surface-tracking Methods For Grain Burnback Analysismentioning

confidence: 99%

Simple Surface-Tracking Methods for Grain Burnback Analysis

Hwang

Chiang

2015

Journal of Propulsion and Power

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“…The modeling scheme for solid motors used in this study was developed by Hartfield et al 20 . The program calculates the burn perimeter and port area in terms of burn distance using a series of analytical equations described in detail in reference [20].…”

Section: A Propulsionmentioning

confidence: 99%

“…The program calculates the burn perimeter and port area in terms of burn distance using a series of analytical equations described in detail in reference [20]. A motor of uniform cross-section can be theoretically fully described using the grain length, six parameters for the cross section, the throat area, and the nozzle exit area, for a total of 9 design variables.…”

Section: A Propulsionmentioning

confidence: 99%

A Method for Optimizing Launch Vehicle Aero-Assist Including Path Optimization

Hartfield

Ahuja

Albarado

et al. 2011

AIAA Atmospheric Flight Mechanics Conference

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An efficient method for implementing the decades old concept of improving multiple stage launch vehicle performance by adding aerodynamic lifting during the first stage is presented in this work. A preliminary design for the complete vehicle including the outer mold line aerodynamic shape is matched to the most advantageous trajectory for aerodynamic assist. This paper shows that performance enhancement can be achieved by attaching wings to a rocket powered launch type vehicle design. Nomenclature݉ ௩ = Mass of the vehicle at any given point in the flight ݃ = Gravitational acceleration ߠ = Vehicle Euler angle (Pitch) ߠ ோாொ = Required Vehicle Euler angle (Pitch) ∅ = Vehicle Euler angle (Roll) ߮ ோாொ = Required Vehicle Euler angle (Yaw) ‫ݑ‬ = Velocity component along BFS-X at any given point in the flight ‫ݒ‬ = Velocity component along BFS-Y at any given point in the flight ‫ݓ‬ = Velocity component along BFS-Z at any given point in the flight ‫ݐ‬ = Time in seconds ‫ݍ‬ ா = Pitch rate in the BFS due to the Earth's rotation. ‫‬ ா = Roll rate in the BFS due to the Earth's rotation. ‫ݎ‬ ா = Yaw rate in the BFS due to the Earth's rotation. ‫ݍ‬ = Pitch rate of the vehicle ‫‬ = Roll rate of the vehicle ‫ݎ‬ = Yaw rate of the vehicle ‫ܫ‬ ௬௬ = Moment of Inertia in the YY direction ‫ܫ‬ ௫௫ = Moment of Inertia in the XX direction ‫ܫ‬ ௭௭ = Moment of Inertia in the ZZ direction α = Angle of attack of the missile β = Normalized Compressibility Coefficient

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“…For example, the grain geometry values of a solid propellant motor can be specified by the GA. From these values, the entire thrust profile of the motor is determined in the solid propellant propulsion system model. The development of this model was pioneered in the research performed by Hartfield et al [23].…”

Section: B Propulsion Modelsmentioning

confidence: 99%

Design Optimization of a Space Launch Vehicle Using a Genetic Algorithm

Bayley

Hartfield

Burkhalter

et al. 2008

Journal of Spacecraft and Rockets

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This paper describes an effort to optimize the design of an entire space launch vehicle to low Earth (circular) orbit, consisting of multiple stages using a genetic algorithm with the goal of minimizing vehicle weight and ultimately vehicle cost. The entire launch vehicle system is analyzed using various multistage configurations to reach low Earth orbit. Specifically, three-and four-stage solid propellant vehicles have been analyzed. The vehicle performance modeling requires that analysis from four separate disciplines be integrated into the design optimization process. The disciplines of propulsion characteristics, aerodynamics, mass properties, and flight dynamics have been integrated to produce a high-fidelity system model of the entire vehicle. In addition, the system model has been validated using the existing launch vehicle data. The cost model is mass based and uses extensive historical data to produce a cost estimating relationship for a solid propellant vehicle. For the design optimization, the goal is for the genetic algorithm to minimize the differences between the desired and actual orbital parameters. This ensures that the payload achieves the desired orbit. One final goal is to minimize the overall vehicle mass, thus minimizing the system cost per launch. This paper will represent the first effort of its kind to minimize the solid propellant launch vehicle cost at the preliminary design level using a genetic algorithm.

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Analytical Methods for Predicting Grain Regression in Tactical Solid-Rocket Motors

Cited by 31 publications

References 2 publications

Simple Surface-Tracking Methods for Grain Burnback Analysis

Simple Surface-Tracking Methods for Grain Burnback Analysis

A Method for Optimizing Launch Vehicle Aero-Assist Including Path Optimization

Design Optimization of a Space Launch Vehicle Using a Genetic Algorithm

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