Forecasting thermoacoustic instabilities in liquid propellant rocket engines using multimodal Bayesian deep learning

A complete set of equations describing the conservation of mass, momentum, and energy, and multicomponent transport and chemical reaction in a liquid propellant rocket (LPR) engine are given, along with appropriate boundary conditions. The formulation includes a detailed description of the two-phase (gas/liquid) flow in terms of a moving boundary problem, with droplets and vapor occupying time-dependent subdomains of the LPR chamber. Several sensor and actuator types are considered in detail, and their mathematical descriptions are incorporated into the differential equations and boundary conditions.

Numerical study of combustion instability in liquid propellant rocket engine is presented in the paper. Time-depending two-dimensional Navier-Stokes equations were employed to describe the fluid flow in the combust chamber and solved by finite difference method with MacCormack scheme. Turbulent viscosity was taken into consideration by the subgrid scale turbulence model. Propellant spray was treated with a lagrangian tracking method and droplet source terms were incorporated into the gas phase calculation by PSIC method. Droplet initial conditions were determined by a stochastic spray model . Spray burning rate is calculated by the classic D2 vaporization law with Ranz-Marshall correlation. The coupling of pressure disturb and burning rate variation was described with Prime's twoparameter model. The actual axisymmetric combustor was transferred into equivalent annular geometry as the references do. Combustion instability analysis was performed by imposing a bomb pressure pulse on the computed steady flow field to trigger unstable combustion. By observing the pressure wave propagation , we can asses the damping capability of the engine.The computational analysis show that numerical schemes and physical models used to describe unstable combustion are the most important factors to the success of numerical study. d NOMENCLATURE a sound velocity b annular combustor width constant pressure spcific heat CP C,, drag coefficient d droplet diameter D mass diffusivity e total energy f frequency h enthalpy 1 L~ heat of evaporation f i transverse length of the annular combstor mass flux or evaporation rate M number of computational droplet NU Nusselt number pr Prantdl number Ice Reynolds number s source terms time T lempeerature X,Y coordinates p density h coductivity P I velocity components

Fault detection and diagnosis algorithms for an open-cycle liquid propellant rocket engine using the Kalman filter and fault factor methods

The coronavirus disease 2019 (COVID-19) pandemic continues to destroy human life around the world. Almost every country throughout the globe suffered from this pandemic, forcing various governments to apply different restrictions to reduce its impact. In this study, we compare different time-series models with the neural network autoregressive model (NNAR). The study used COVID-19 data in Pakistan from February 26, 2020, to February 18, 2022, as a training and testing data set for modeling. Different models were applied and estimated on the training data set, and these models were assessed on the testing data set. Based on the mean absolute scaled error (MAE) and root mean square error (RMSE) for the training and testing data sets, the NNAR model outperformed the autoregressive integrated moving average (ARIMA) model and other competing models indicating that the NNAR model is the most appropriate for forecasting. Forecasts from the NNAR model showed that the cumulative confirmed COVID-19 cases will be 1,597,180 and cumulative confirmed COVID-19 deaths will be 32,628 on April 18, 2022. We encourage the Pakistan Government to boost its immunization policy.

Background: This study was designed to find the best statistical approach to scorpion sting predictions.Study Design: A retrospective study.Methods: Multiple regression, seasonal autoregressive integrated moving average (SARIMA), neural network autoregressive (NNAR), and hybrid SARIMA-NNAR models were developed to predict monthly scorpion sting cases in El Oued province. The root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) were used to quantitatively compare different models.Results: In general, 96909 scorpion stings were recorded in El Oued province from 2005-2020. The incidence rate experienced a gradual decrease until 2012 and since then slight fluctuations have been noted. Scorpion stings occurred throughout the year with peaks in September followed by July and August and troughs in December and January. Sting cases were not evenly distributed across demographic groups; the most affected age group was 15-49 years, and males were more likely to be stung. Of the reported deaths, more than half were in children 15 and younger. Scorpion’s activity was conditioned by climate factors, and temperature had the highest effect. The SARIMA(2,0,2)(1,1,1)12, NNAR(1,1,2)12, and SARIMA(2,0,2)(1,1,1)12-NNAR(1,1,2)12 were selected as the best-fitting models. The RMSE, MAE, and MAPE of the SARIMA and SARIMA-NNAR models were lower than those of the NNAR model in fitting and forecasting; however, the NNAR model could produce better predictive accuracy.Conclusion: The NNAR model is preferred for short-term monthly scorpion sting predictions. An in-depth understanding of the epidemiologic triad of scorpionism and the development of predictive models ought to establish enlightened, informed, better-targeted, and more effective policies.

Performance, weight, design, flexibility, engine cycles and reliability of liquid propellant rocket engines used in NASA and USAF vehicles

Non-stationary heat behaviour of liquid propellant rocket engines

Oxygen–methane rocket thrust chambers: Review of heat transfer experimental studies

This study reports univariate modelling methodologies applied to the monthly total ozone concentration (TOC) over Kolkata (22°32′, 88°20′), India, derived from the measurements made by the Earth Probe Total Ozone Mapping Spectrometer (EP/TOMS). The univariate models have been generated in two forms, namely autoregressive integrated moving average (ARIMA) and autoregressive neural network (AR-NN). Three ARIMA models in the forms of ARIMA(1,1,1), ARIMA(0,1,1) and ARIMA(0,2,2) and 11 autoregressive neural network models, AR-NN(n), have been generated for a time series. Goodness of fit of the models to the time series of monthly TOC has been assessed using prediction error, Pearson correlation coefficient and Willmott's indices. After rigorous skill assessment, the ARIMA (0,2,2) has been identified as the best predictive model for the time series under study.

The liquid-propellant rocket engine has the characteristics that allow it to deliver thrust at a high-performance level, with an efficiency and operational flexibility that enables a number of mission applications to go forward. Monopropellant and bipropellant versions of this category of engine are discussed in some detail in this chapter. Storable and cryogenic propellants are introduced, and their on-board storage requirements are discussed. Pressure-feed and turbopump-feed approaches for moving liquid propellants from their respective storage tanks to the injector head of the engine’s thrust chamber are presented. Liquid injector design considerations are discussed. Thrust chamber design issues are detailed, including dealing with combustion instability symptoms. This chapter is closed out with a discussion of thrust vector control techniques for flight control, via exploiting the main engine nozzle exhaust flow.

Blow forming technology has been used to produce glass and plastic components with easy and simple process. In order to apply this technology to metallic system, relatively high formability of material and elevated temperature are required. Since the blow forming temperature is quite high for metallic system, the main difficulty is to obtain adequate mold material which can sustain pressure difference between inside and outside of the tool. The present study demonstrates blow forming process with IN718 and steel can be applied to manufacturing of combustion chamber in liquid propellant rocket engine with complex shape. The result shows that the developed technology to process design of high temperature blow forming by the finite element method can be applied for near net shape forming of a combustion chamber of liquid rocket engine and a cone-shaped chamber extension part with cooling channels.

Purpose. This study aims to improve the accuracy of methods for determining fin efficiency. Its goal is to derive calculation relationships for finning coefficients that account for transverse temperature non-uniformity within the fin cross-section. Design / Method / Approach. The article presents the reduction of the heat conduction equation for a fin to a dimensionless form, based on dimensional analysis of the variables involved. Further development relies on analyzing the results of numerical simulations and their subsequent generalization. To this end, the gradient descent method is applied, minimizing the quadratic error function. Findings. A criterial dependence has been formulated to complement the derived heat conduction equation. Test calculations and comparisons with numerical simulations in Ansys Fluent confirm an improvement in calculation accuracy when using the proposed equation. Theoretical Implications. This paper addresses factors previously neglected in the analysis of heat transfer in fins. The results of the study thus complement existing approaches to determining finning coefficients. Practical Implications. The derived criterial relationship will enhance the accuracy of heat transfer calculations in the chambers and gas generators of liquid rocket engines. Originality / Value. The paper introduces an original criterial relationship that accounts for temperature non-uniformity across the fin cross-section. Incorporating this factor improves calculation accuracy, highlighting the practical value of the developed equation. Research Limitations / Future Research. This study focuses on rectangular fins; therefore, the proposed model is not applicable to fins with variable thickness in the ducts of liquid propellant rocket engines (LPREs). Developing a fin model without these limitations will be the objective of future research on this topic. Article Type. Applied Research. PURL: https://purl.org/cims/4.299

In the Republic of Korea, research on staged-combustion cycle liquid propellant rocket engines (LPRE) is proceeding to improve efficiency of rocket engines. Recently oxidizer-rich preburner using single triplex injector is developed in relation to the main injector development and combustion tests have been performed. This preburner is designed to operate in nominal conditions with the combustion pressure of 10 MPa, OF ratio of 60. For a stable ignition, LOx is fed in two steps. Triethylaluminum-Triethylborane (TEAB) is used as hypergolic fuel for ignition, supplied through a fuel injector. Despite the small amount of fuel flow rate and high pressure condition, the combustion pressure was stably maintained around 10 MPa as designed. As a result of Fast Fourier Transform (FFT) of the combustion chamber dynamic pressure, 1L mode frequencies related to the acoustic instability and hydraulic resistance exist in the combustion chamber. But their amplitudes are less than 1% of the combustion pressure and it does not affect the combustion. Therefore combustion test is stably completed. In the near future, coupled tests with uni-element triplex injector preburner and uni-element gas/liquid injector main combustion chamber will be carried out.

Sensing and actuation in a liquid propellant rocket engine

A linearized one-dimensional lumped-parameter model capable of predicting the occurrence of the low frequency combustion instability (chugging) experienced during preburner shutdown in the Space Shuttle Main Engines is discussed, and predictions are compared with NASA experimental results. Results from a parametric study of parameters including chamber pressure, fuel and oxygen temperatures, and the effective bulk modulus of the liquid oxidizer suggest that chugging is probably affected by conditions at shutdown through the fuel and oxidizer temperatures. It is suggested that chugging is initiated when the fuel, oxidizer, and helium temperature and flow rates pass into an unstable region, and that chugging may be terminated by decaying pressures.