Effects of inclusions on the performance of a solid rocket motor

Ponti, Fabrizio De; Mini, Stefano; Fadigati, Luca; Ravaglioli, Vittorio; Annovazzi, A.; Garreffa, V.

doi:10.1016/j.actaastro.2021.08.030

Cited by 19 publications

(3 citation statements)

References 30 publications

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“…At the same time, they make it possible to detect subtle changes that could go unnoticed through traditional analysis methods. Scientific approaches published in the field of SHM depict the necessity to study uncertainties as a crucial aspect affecting the interpretation of sensor data in the route to diagnosing the structural integrity of a material; however, only a restricted number of studies explicitly refer to SRM models [83,84].…”

Section: Machine Learning As An Enabling Tool For the Cbm Of Srmsmentioning

confidence: 99%

Structural Health Monitoring of Solid Rocket Motors: From Destructive Testing to Perspectives of Photonic-Based Sensing

Korompili,

Mußbach,

Riziotis

2024

Instruments

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In the realm of space exploration, solid rocket motors (SRMs) play a pivotal role due to their reliability and high thrust-to-weight ratio. Serving as boosters in space launch vehicles and employed in military systems, and other critical & emerging applications, SRMs’ structural integrity monitoring, is of paramount importance. Traditional maintenance approaches often prove inefficient, leading to either unnecessary interventions or unexpected failures. Condition-based maintenance (CBM) emerges as a transformative strategy, incorporating advanced sensing technologies and predictive analytics. By continuously monitoring crucial parameters such as temperature, pressure, and strain, CBM enables real-time analysis, ensuring timely intervention upon detecting anomalies, thereby optimizing SRM lifecycle management. This paper critically evaluates conventional SRM health diagnosis methods and explores emerging sensing technologies. Photonic sensors and fiber-optic sensors, in particular, demonstrate exceptional promise. Their enhanced sensitivity and broad measurement range allow precise monitoring of temperature, strain, pressure, and vibration, capturing subtle changes indicative of degradation or potential failures. These sensors enable comprehensive, non-intrusive monitoring of multiple SRM locations simultaneously. Integrated with data analytics, these sensors empower predictive analysis, facilitating SRM behavior prediction and optimal maintenance planning. Ultimately, CBM, bolstered by advanced photonic sensors, promises enhanced operational availability, reduced costs, improved safety, and efficient resource allocation in SRM applications.

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Section: Machine Learning As An Enabling Tool For the Cbm Of Srmsmentioning

confidence: 99%

Structural Health Monitoring of Solid Rocket Motors: From Destructive Testing to Perspectives of Photonic-Based Sensing

Korompili,

Mußbach,

Riziotis

2024

Instruments

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“…Consequently, expensive testing is necessary to design and certify each SRM. The burning rate of the propellant plays a crucial role in predicting flight performance [2,6,7], affected by factors such as grain shape, particle orientation, air bubbles, and more [5,[8][9][10][11][12][13][14]. Manufacturing processes also impact ballistic performance [15][16][17], with macroscopic and microscopic phenomena potentially altering thrust profiles [18,19].…”

Section: Introductionmentioning

confidence: 99%

Particle migration modeling in solid propellants

Andriulli

2023

Materials Research Proceedings

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Abstract. This work presents the development of an OpenFOAM solver to predict the migration of solid particles in concentrated suspensions under non-uniform shear flow. The solver modifies the pimpleFoam solver by implementing the conservation equation for particle volume fraction. It adapts the equation of motion for non-Newtonian flows and establishes a model for the viscous field using Krieger's correlation. The code is successfully validated by the experimental results from literature.

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“…For the design control system, a dynamic simulation model of a VTSRM is required, and modeled as a nonlinear differential equation with respect to the nozzle throat area, pressure, and other system variables. However, there are also uncertainties in system parameters, such as solid fuel regression and discharge coefficient [12]. Therefore, for effective pressure and thrust control of a VTSRM, it is essential to design the control algorithms considering the nonlinearity and uncertainty [13].…”

Section: Introductionmentioning

confidence: 99%

Performance Comparison of Control Strategies for a Variable-Thrust Solid-Propellant Rocket Motor

Cha

Oliveira

2022

Aerospace

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This paper deals with a performance comparison of the control algorithm for a variable-thrust solid-propellant rocket motor (VTSRM). To do this, we develop a simulation model of a VTSRM considering characteristic changes in the combustor and design control systems for pressure and thrust. We use three types of control algorithms for the pressure control: classical PID control, feedback linearization control, and fuzzy PID control, and two control algorithms for thrust control: classical PID control and fuzzy PID control. Finally, we compare the performance of each control system through a numerical simulation using step responses. Through this work, we check that feedback linearization is better in pressure control, and fuzzy PID control is more appropriate in thrust control. Especially using fuzzy PID control, we can get fast settling with a small undershoot even if the system is a nonminimum phase system.

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Effects of inclusions on the performance of a solid rocket motor

Cited by 19 publications

References 30 publications

Structural Health Monitoring of Solid Rocket Motors: From Destructive Testing to Perspectives of Photonic-Based Sensing

Structural Health Monitoring of Solid Rocket Motors: From Destructive Testing to Perspectives of Photonic-Based Sensing

Particle migration modeling in solid propellants

Performance Comparison of Control Strategies for a Variable-Thrust Solid-Propellant Rocket Motor

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