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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2019

Modeling Turboshaft Engines for the Revolutionary Vertical Lift Technology Project

Turboshaft engine performance and weight models were developed to support conceptual propulsion and vehicle mission design and performance under the Revolutionary Vertical Lift Technology (RVLT) Project. These models were developed using open data sources, assuming current and advanced technology levels, and range from 650 to 7,500 shaft output horsepower (485 to 5,600 kW). Documenting the methodology, assumptions, and resulting performance realizes important benefits NASA and the aviation community. NASA concept vehicle efforts using these propulsion models can be more readily shared among the government, industry and university community as common baselines to support current and future work. Assessing the benefits of advanced technologies and new configurations can be facilitated using these models, which helps guide technology investment. As the various modeling conceptual vehicle and mission analysis environments advanced, these models can be used directly for broader systems analysis studies, including optimization within the propulsion model itself. To perform this effort, the turboshaft engine is briefly discussed, highlighting the specific components and their expected performance characteristics over the power range and technology levels considered. Engine configurations will also be discussed as they will vary based on power output and assumed technology level. Engine performance, such as airflow, power output and weight will be reported, noting trends that are important for system studies. The effect of advanced propulsion technologies on RVLT concept vehicles are also reported. Finally, potential future propulsion modeling work will be proposed.

Snyder, Christopher A.↗
NASA NTRS2019

Modeling Turboshaft Engines for the Revolutionary Vertical Lift Technology Project

Turboshaft engine performance and weight models were developed to support conceptual propulsion and vehicle mission design in support of the National Aeronautics and Space Administration's (NASA) Aeronautics Mission Research Directorate's (ARMD) Revolutionary Vertical Lift Technology (RVLT) Project. These models were developed using open data sources, assuming current and advanced technology levels, and range from 650 to 7,500 shaft output horsepower (485 to 5,600 kilowatts). Documenting the methodology, assumptions, and resulting performance realizes important benefits for NASA and the aviation community. NASA concept vehicle efforts using these propulsion models can more readily shared among the government, industry and university community as common baselines to support current and future work. Assessing the benefits of advanced technologies and new configurations can be facilitated using these models, which helps guide technology investment. As the various modeling conceptual vehicle and mission analysis environments advance, these models can be used directly for broader systems analysis studies, including optimization within the propulsion model itself. To perform this effort, the turboshaft engine is briefly discussed, highlighting the specific components and their expected performance characteristics over the power range and technology levels considered. Engine configurations will also be discussed as they will vary based on power output and assumed technology level. Engine performance, such as airflow, power output and weight will be reported, noting trends that are important for system studies. The effect of advanced propulsion technologies on RVLT-concept vehicles are also reported. Finally, potential future propulsion modeling work will be proposed.

Snyder, Christopher A.↗
NASA NTRS2003

Engineering-Level Model Atmospheres for Titan and Neptune

Engineering-level atmospheric models for Titan and Neptune have been developed for use in NASA s systems analysis studies of aerocapture applications in missions to the outer planets. Analogous to highly successful Global Reference Atmospheric Models for Earth (GRAM, Justus et al., 2000) and Mars (Mars-GRAM, Justus and Johnson, 2001, Justus et al., 2002) the new models are called Titan-GRAM and Neptune-GRAM. Like GRAM and Mars-GRAM, an important feature of Titan-GRAM and Neptune-GRAM is their ability to simulate quasi-random perturbations for Monte- Carlo analyses in developing guidance, navigation and control algorithms, and for thermal systems design.

Justus, C. G.↗
NASA NTRS2011

Development of the Transport Class Model (TCM) Aircraft Simulation From a Sub-Scale Generic Transport Model (GTM) Simulation

A six degree-of-freedom, flat-earth dynamics, non-linear, and non-proprietary aircraft simulation was developed that is representative of a generic mid-sized twin-jet transport aircraft. The simulation was developed from a non-proprietary, publicly available, subscale twin-jet transport aircraft simulation using scaling relationships and a modified aerodynamic database. The simulation has an extended aerodynamics database with aero data outside the normal transport-operating envelope (large angle-of-attack and sideslip values). The simulation has representative transport aircraft surface actuator models with variable rate-limits and generally fixed position limits. The simulation contains a generic 40,000 lb sea level thrust engine model. The engine model is a first order dynamic model with a variable time constant that changes according to simulation conditions. The simulation provides a means for interfacing a flight control system to use the simulation sensor variables and to command the surface actuators and throttle position of the engine model.

Hueschen, Richard M.↗
NASA NTRS1992

Identification of the Space Shuttle Main Engine dynamic models from firing data

A multi-input multi-output system identification technique is used to obtain linearized point models of the Space Shuttle Main Engine (SSME) at five different operating conditions (power levels) from the engine firing data. This study demonstrates that the open-loop dynamics of the SSME can be successfully modeled from the engine firing data. The identified linear models may be used for fault detection studies and control system design and development.

Saravanan, N.↗
NASA NTRSDate not supplied

An Updated Secondary Lunar Meteoroid Ejecta Model for Engineering Design

Introduction: The surface of the Moon is constantly being bombarded by a flux of meteoroids of various sizes. Impacts due to these meteoroids produce secondary ejecta material at much lower speeds but with a total mass larger than the original impactor. Details about the secondary ejecta are important for planning missions on the lunar surface. In this work, an updated ejecta model is presented called the Meteoroid Model of Secondary Ejecta (MeMoSeE), to re-place the Apollo-era ejecta model, NASA SP-8013 [1], in the SLS-SPEC 159 Design Specification for Natural Environments (DSNE) [2]. The model pro-duces secondary ejecta flux environments for a user-specified location on the lunar surface, and sorts the incoming secondary flux by angular direction and speed. Methods: MeMoSeE is separated into three parts: the inputs, the conversion step, and the integration of fluxes. Inputs to the model include the primary meteoroid fluxes and the primary near-Earth object (NEO) fluxes. Meteoroid fluxes, both asteroidal and cometary, are calculated using the Meteoroid Engineering Model (MEM3) [3] for different locations on the Moon. For each surface location, an ephemeris is generated using the JPL HORIZONS System [4] that feeds into MEM3. The NEO fluxes are approximated by the high-density population of MEM3 (i.e., only the directionality), where the speed distribution of the NEO fluxes is renormalized to match observations [5]. The regolith properties are used as defined in the DSNE [2]. The conversion step utilizes scaling laws given by Housen & Holsapple 2011 [6] to convert the primary impactor flux to the total mass of secondary ejecta. The ejecta distribution, at the point-of-impact (POI), is separated into a zenith angle and azimuthal angle distribution. The zenith angle distribution follows a beta distribution where the peak depends on the impact altitude angle and the impact azimuth [7]. We employ an ejecta azimuth distribution that is based on Rival & Mandeville 1999 [8] which focuses ejecta in the downstream direction for more oblique impacts. Finally, during the integration step, we sum secondary ejecta number fluxes at a particular region-of-interest (ROI) that originated from many POI locations over the entire surface of the Moon. We keep track of both altitude and azimuth angle bins as well as a range of speed bins, following the igloo gridding as done in MEM3 [9]. The ejecta particle size distribution and density is assumed to be the same as the lunar regolith [10, 2]. Results: The primary fluxes are computed for one Metonic cycle (19 years) for various locations over the lunar surface with a fixed orientation. Both the angular and speed distributions of the primary fluxes are dependent on the latitude and longitude. The over-all primary fluxes show a roughly 13% increase from the eastern limb to the western limb. In general, the speed distribution of the secondary fluxes span from a user-defined minimum speed to the escape speed of the Moon (2.38 km/s), roughly following a power-law relation [6]. Different parts of the speed distribution come from different primary impact locations on the Moon. The secondary ejecta is dominated by the slowest speeds, where these particles originate nearby the ROI. For speeds around 71% of the escape speed, the secondary ejecta originates from locations near the antipodal point. On the other hand, for secondary ejecta speeds that exceed roughly 90% the escape speed, the ejecta particles come from all over the lunar surface to the ROI. Comparing the secondary ejecta fluxes from MeMoSeE with NASA SP-8013 [1], there is a reduction by about 2-3 orders of magnitude for secondary ejecta particles greater than 1 µg. These estimates agree with recent findings from Bjorkman & Christiansen 2019 [11]. The secondary ejecta fluxes are also compared with the primary fluxes, where the ejecta fluxes are roughly an order of magnitude greater than the primary fluxes. References: [1] Cour-Palais, B. G., (1969) NASA SP-8013. [2] NASA SLS-SPEC-159 Rev. H (2020). [3] Moorhead, A. V., et al. (2019) JS&R, 1-17. [4] Giorgini, J. D., (2015) IAUGA, 29, 2256293. [5] Moorhead, A. V., (2020) Memo OSMA/MEO/Lunar-001. [6] Housen, K. R., and Holsapple, K. A., (2011) Icarus, 211(1), 856-875. [7] Gault, D. E., and Wedekind, J. A., (1978) L&PSCP, 9, 3843-3875. [8] Rival, M., and Mandeville, J., (1999) Space Debris, 1(1), 45-57. [9] Moorhead, A. V., (2019) MEM3 User Guide. [10] Carrier, W. D., (1973) The Moon, 6(3-4), 250-263. [11] Bjorkman, M. D. & Christiansen, E. L., (2019) ODC

impacts↗
NASA NTRS2017

A Dynamic Model for the Evaluation of Aircraft Engine Icing Detection and Control-Based Mitigation Strategies

Aircraft flying in regions of high ice crystal concentrations are susceptible to the buildup of ice within the compression system of their gas turbine engines. This ice buildup can restrict engine airflow and cause an uncommanded loss of thrust, also known as engine rollback, which poses a potential safety hazard. The aviation community is conducting research to understand this phenomena, and to identify avoidance and mitigation strategies to address the concern. To support this research, a dynamic turbofan engine model has been created to enable the development and evaluation of engine icing detection and control-based mitigation strategies. This model captures the dynamic engine response due to high ice water ingestion and the buildup of ice blockage in the engines low pressure compressor. It includes a fuel control system allowing engine closed-loop control effects during engine icing events to be emulated. The model also includes bleed air valve and horsepower extraction actuators that, when modulated, change overall engine operating performance. This system-level model has been developed and compared against test data acquired from an aircraft turbofan engine undergoing engine icing studies in an altitude test facility and also against outputs from the manufacturers customer deck. This paper will describe the model and show results of its dynamic response under open-loop and closed-loop control operating scenarios in the presence of ice blockage buildup compared against engine test cell data. Planned follow-on use of the model for the development and evaluation of icing detection and control-based mitigation strategies will also be discussed. The intent is to combine the model and control mitigation logic with an engine icing risk calculation tool capable of predicting the risk of engine icing based on current operating conditions. Upon detection of an operating region of risk for engine icing events, the control mitigation logic will seek to change the engines operating point to a region of lower risk through the modulation of available control actuators while maintaining the desired engine thrust output. Follow-on work will assess the feasibility and effectiveness of such control-based mitigation strategies.

engine control↗
NASA NTRS2017

A Dynamic Model for the Evaluation of Aircraft Engine Icing Detection and Control-Based Mitigation Strategies

Aircraft flying in regions of high ice crystal concentrations are susceptible to the buildup of ice within the compression system of their gas turbine engines. This ice buildup can restrict engine airflow and cause an uncommanded loss of thrust, also known as engine rollback, which poses a potential safety hazard. The aviation community is conducting research to understand this phenomena, and to identify avoidance and mitigation strategies to address the concern. To support this research, a dynamic turbofan engine model has been created to enable the development and evaluation of engine icing detection and control-based mitigation strategies. This model captures the dynamic engine response due to high ice water ingestion and the buildup of ice blockage in the engines low pressure compressor. It includes a fuel control system allowing engine closed-loop control effects during engine icing events to be emulated. The model also includes bleed air valve and horsepower extraction actuators that, when modulated, change overall engine operating performance. This system-level model has been developed and compared against test data acquired from an aircraft turbofan engine undergoing engine icing studies in an altitude test facility and also against outputs from the manufacturers customer deck. This paper will describe the model and show results of its dynamic response under open-loop and closed-loop control operating scenarios in the presence of ice blockage buildup compared against engine test cell data. Planned follow-on use of the model for the development and evaluation of icing detection and control-based mitigation strategies will also be discussed. The intent is to combine the model and control mitigation logic with an engine icing risk calculation tool capable of predicting the risk of engine icing based on current operating conditions. Upon detection of an operating region of risk for engine icing events, the control mitigation logic will seek to change the engines operating point to a region of lower risk through the modulation of available control actuators while maintaining the desired engine thrust output. Follow-on work will assess the feasibility and effectiveness of such control-based mitigation strategies.

engine control↗
NASA NTRS1978

Alternatives for jet engine control

General goals of the research were classified into two categories. The first category involves the use of modern multivariable frequency domain methods for control of engine models in the neighborhood of a quiescent point. The second category involves the use of nonlinear modelling and optimization techniques for control of engine models over a more extensive part of the flight envelope. In the frequency domain category, works were published in the areas of low-interaction design, polynomial design, and multiple setpoint studies. A number of these ideas progressed to the point at which they are starting to attract practical interest. In the nonlinear category, advances were made both in engine modelling and in the details associated with software for determination of time optimal controls. Nonlinear models for a two spool turbofan engine were expanded and refined; and a promising new approach to automatic model generation was placed under study. A two time scale scheme was developed to do two-dimensional dynamic programming, and an outward spiral sweep technique has greatly speeded convergence times in time optimal calculations.

Leake, R. J.↗
NASA NTRS2023

Modeling Turboshaft Engines for the Revolutionary Vertical Lift Technology Project, Expanded

Turboshaft engine performance and weight models were developed to support conceptual propulsion and vehicle mission design and performance under the Revolutionary Vertical Lift Technology (RVLT) Project in 2019 by Snyder in Reference 7. These models were developed using open data sources, assuming present and future technology levels, and range from 650 to 5,000 output shaft horsepower (485 to 3,730 kW). This paper expands on the previous research, extending the power ranges from 200 to 15000 output shaft horsepower (150 to 11,200 kW) and documenting the methodology, assumptions, and engine performance realizes important benefits for NASA and the aviation community. NASA concept-vehicle study efforts using these baseline propulsion models can be more readily shared among the government, industry, and university community to support present and future work. Assessing the benefits of advanced technologies and new configurations can be facilitated using these models, which helps guide technology investment. As the various conceptual vehicle and mission analysis simulations are developed, these models can be used directly for broader systems analysis studies, including optimization within the propulsion model itself. To expand on the previous effort, the turboshaft engine is briefly discussed, highlighting the specific components, and expected performance characteristics over the updated power range and technology levels considered. Additional engine configurations will also be discussed as they vary based on power output and assumed technology level. Engine performance, such as airflow, power output and weight are updated, noting important trends for system studies. Finally, the effect of advanced propulsion technologies on public reference models including RVLT concept vehicles are reported along with the tools and software methods used to complete the analysis.

VTOL↗
NASA NTRSDate not supplied

Modeling Turboshaft Engines for the Revolutionary Vertical Lift Technology Project, Expanded

Turboshaft engine performance and weight models were developed to support conceptual propulsion and vehicle mission design and performance under the Revolutionary Vertical Lift Technology (RVLT) Project in 2019 by Snyder in Ref. 1. These models were developed using open data sources, assuming present and future technology levels, and range from 650 to 5,000 output shaft horsepower (485 to 3,730 kW). This paper expands on the previous research, extending the power ranges from 200 to 15000 output shaft horsepower (150 to 11,200 kW) and documenting the methodology, assumptions, and engine performance realizes important benefits for NASA and the aviation community. NASA concept vehicle study efforts using these baseline propulsion models can be more readily shared among the government, industry, and university community to support present and future work. Assessing the benefits of advanced technologies and new configurations can be facilitated using these models, which helps guide technology investment. As the various modeling conceptual vehicle and mission analysis environments advance, these models can be used directly for broader systems analysis studies, including optimization within the propulsion model itself. To expand on the previous effort, the turboshaft engine is briefly discussed, highlighting the specific components, and expected performance characteristics over the updated power range and technology levels considered. Additional engine configurations will also be discussed as they vary based on power output and assumed technology level. Engine performance, such as airflow, power output and weight will be updated, noting trends that are important for system studies. Finally, the effect of advanced propulsion technologies on RVLT concept vehicles are also reported along with the tools and software methods used to complete the analysis.

VTOL↗
NASA NTRSDate not supplied

Modeling Turboshaft Engines for the Revolutionary Vertical Lift Technology Project, Expanded

Turboshaft engine performance and weight models were developed to support conceptual propulsion and vehicle mission design and performance under the Revolutionary Vertical Lift Technology (RVLT) Project in 2019 by Snyder in Ref. 1. These models were developed using open data sources, assuming present and future technology levels, and range from 650 to 5,000 output shaft horsepower (485 to 3,730 kW). This paper expands on the previous research, extending the power ranges from 200 to 15000 output shaft horsepower (150 to 11,200 kW) and documenting the methodology, assumptions, and engine performance realizes important benefits for NASA and the aviation community. NASA concept-vehicle study efforts using these baseline propulsion models can be more readily shared among the government, industry, and university community to support present and future work. Assessing the benefits of advanced technologies and new configurations can be facilitated using these models, which helps guide technology investment. As the various modeling conceptual vehicle and mission analysis environments advance, these models can be used directly for broader systems analysis studies, including optimization within the propulsion model itself. To expand on the previous effort, the turboshaft engine is briefly discussed, highlighting the specific components, and expected performance characteristics over the updated power range and technology levels considered. Additional engine configurations will also be discussed as they vary based on power output and assumed technology level. Engine performance, such as airflow, power output and weight will be updated, noting trends that are important for system studies. Finally, the effect of advanced propulsion technologies on RVLT concept vehicles are also reported along with the tools and software methods used to complete the analysis

VTOL↗
NASA NTRS1979

Alternatives for jet engine control

The research is classified in two categories: (1) the use of modern multivariable frequency domain methods for control of engine models in the neighborhood of a set-point, and (2) the use of nonlinear modelling and optimization techniques for control of engine models over a more extensive part of the flight envelope. Progress in the first category included the extension of CARDIAD (Complex Acceptability Region for Diagonal Dominance) methods developed with the help of the grant to the case of engine models with four inputs and four outputs. A suitable bounding procedure for the dominance function was determined. Progress in the second category had its principal focus on automatic nonlinear model generation. Simulations of models produced satisfactory results where compared with the NASA DYNGEN digital engine deck.

Sain, M. K.↗
NASA NTRS2002

NASA Marshall Engineering Thermosphere Model

This Technical Memorandum describes the NASA Marshall Engineering Thermosphere Model-Version 2.0 (MET-V 2.0) and contains an explanation on the use of the computer program along with an example of the MET-V 2.0 model products. The MET-V 2.0 provides an update to the 1988 version of the model. It provides information on the total mass density, temperature, and individual species number densities for any altitude between 90 and 2,500 km as a function of latitude, longitude, time, and solar and geomagnetic activity. A description is given for use of estimated future 13-mo smoothed solar flux and geomagnetic index values as input to the model. Address technical questions on the MET-V 2.0 and associated computer program to Jerry K. Owens, Spaceflight Experiments Group, Marshall Space Flight Center, Huntsville, AL 35812 (256-961-7576; e-mail Jerry.Owens@msfc.nasa.gov).

Owens, J. K.↗
NASA NTRS2003

Engineering-Level Model Atmospheres For Titan and Mars

An engineering-level atmospheric model for Titan has been developed for use in NASA s systems analysis studies of aerocapture and entry, descent and landing (EDL) applications in potential missions to Titan. Analogous to highly successful Global Reference Atmospheric Models for Earth (GRAM) and Mars (Mars-GRAM), the new model is called Titan-GRAM. Like GRAM and Mars-GRAM, an important feature of Titan-GRAM is its ability to simulate quasi-random perturbations for Monte-Carlo analyses in developing guidance, navigation and control algorithms, and for thermal systems design. Titan-GRAM features and sample results will be presented. Features of Mars-GRAM especially related to EDL applications will also be presented and illustrated.

Justus, C. G.↗
NASA NTRS2006

Next-generation concurrent engineering: developing models to complement point designs

Concurrent Engineering Design teams have made routine the rapid development of point designs for space missions. The Jet Propulsion Laboratory's Team X is now evolving into a next generation CED; nin addition to a point design, the team develops a model of the local trade space. The process is a balance between the power of model-developing tools and the creativity of human experts, enabling the development of a variety of trade models for any space mission.

trade space exploration↗
NASA NTRS1982

Computer program for a four-cylinder-Stirling-engine controls simulation

A four cylinder Stirling engine, transient engine simulation computer program is presented. The program is intended for controls analysis. The associated engine model was simplified to shorten computer calculation time. The model includes engine mechanical drive dynamics and vehicle load effects. The computer program also includes subroutines that allow: (1) acceleration of the engine by addition of hydrogen to the system, and (2) braking of the engine by short circuiting of the working spaces. Subroutines to calculate degraded engine performance (e.g., due to piston ring and piston rod leakage) are provided. Input data required to run the program are described and flow charts are provided. The program is modular to allow easy modification of individual routines. Examples of steady state and transient results are presented.

Daniels, C. J.↗