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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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At least 415 records · Page 23

Identification of multivariable high performance turbofan engine dynamics from closed loop data

The multivariable instrumental variable/approximate maximum likelihood (IV/AML) method or recursive time-series analysis is used to identify the multivariable (four inputs-three outputs) dynamics of the Pratt and Whitney F100 engine. A detailed nonlinear engine simulation is used to determine linear engine model structures and parameters at an operating point using open loop data. Also, the IV/AML method is used in a direct identification mode to identify models from actual closed loop engine test data. Models identified from simulated and test data are compared to determine a final model structure and parameterization that can predict engine response for a wide class of inputs. The ability of the IV/AML algorithm to identify useful dynamic models from engine test data is assessed.

Merrill, W.↗

Identification of multivariable high performance turbofan engine dynamics from closed loop data

The multivariable instrumental variable/approximate maximum likelihood (IV/AML) method of recursive time-series analysis is used to identify the multivariable (four inputs-three outputs) dynamics of the Pratt and Whitney F100 engine. A detailed nonlinear engine simulation is used to determine linear engine model structures and parameters at an operating point using open loop data. Also, the IV/AML method is used in a direct identification made to identify models from actual closed loop engine test data. Models identified from simulated and test data are compared to determine a final model structure and parameterization that can predict engine response for a wide class of inputs. The ability of the IV/AML algorithm to identify useful dynamic models from engine test data is assessed. Previously announced in STAR as N82-20339

Merrill, W.↗

Design, Development, Implementation, and On-Orbit Performance of the Dynamic Ionosphere CubeSat Experiment Mission

Funded by the NSF CubeSat and NASA ELaNa programs, the Dynamic Ionosphere CubeSat Experiment (DICE) mission consists of two 1.5U (1.5 Unit) CubeSats which were launched into an eccentric low Earth orbit on October 28, 2011. Each identical spacecraft carries two Langmuir probes to measure ionospheric in-situ plasma densities, electric field probes to measure in-situ DC and AC electric fields, and a science grade magnetometer to measure in-situ DC and AC magnetic fields. Given the tight integration of these multiple sensors with the CubeSat platforms, each of the DICE spacecraft is effectively a sensor-sat capable of comprehensive ionospheric diagnostics. The use of two identical sensor-sats at slightly different orbiting velocities in nearly identical orbits permits the deconvolution of spatial and temporal ambiguities in the observations of the ionosphere from a moving platform. In addition to demonstrating nanosat-based constellation science, the DICE mission is advancing a number of groundbreaking CubeSat technologies including miniaturized mechanisms and high-speed downlink communications.

DICE↗

Flight Dynamics and Navigation Performance of the BioSentinel Mission

BioSentinel was one of ten CubeSats launched by the Space Launch System (SLS) as part of the Artemis I campaign on 16 November 2022. A lunar flyby gave BioSentinel the needed energy to escape the Earth-Moon system into heliocentric space. The biological payload contains yeast cells designed to measure radiation in deep space beyond the reach of Earth’s magnetosphere. This paper discusses in detail the BioSentinel flight performance, as well as challenges and lessons learned prior to, and during the mission.

BioSentinel↗

Stage-by-Stage and Parallel Flow Path Compressor Modeling for a Variable Cycle Engine

This paper covers the development of stage-by-stage and parallel flow path compressor modeling approaches for a Variable Cycle Engine. The stage-by-stage compressor modeling approach is an extension of a technique for lumped volume dynamics and performance characteristic modeling. It was developed to improve the accuracy of axial compressor dynamics over lumped volume dynamics modeling. The stage-by-stage compressor model presented here is formulated into a parallel flow path model that includes both axial and rotational dynamics. This is done to enable the study of compressor and propulsion system dynamic performance under flow distortion conditions. The approaches utilized here are generic and should be applicable for the modeling of any axial flow compressor design.

Parallel Flow Path modeling↗

Stage-by-Stage and Parallel Flow Path Compressor Modeling for a Variable Cycle Engine, NASA Advanced Air Vehicles Program - Commercial Supersonic Technology Project - AeroServoElasticity

This paper covers the development of stage-by-stage and parallel flow path compressor modeling approaches for a Variable Cycle Engine. The stage-by-stage compressor modeling approach is an extension of a technique for lumped volume dynamics and performance characteristic modeling. It was developed to improve the accuracy of axial compressor dynamics over lumped volume dynamics modeling. The stage-by-stage compressor model presented here is formulated into a parallel flow path model that includes both axial and rotational dynamics. This is done to enable the study of compressor and propulsion system dynamic performance under flow distortion conditions. The approaches utilized here are generic and should be applicable for the modeling of any axial flow compressor design accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.

Compressor Modeling Modeling↗

Enabling Large-Scale Condensed-Phase Hybrid Density Functional Theory Based Ab Initio Molecular Dynamics. 1. Theory, Algorithm, and Performance

By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semilocal density functional theory (DFT) and thereby furnish a more accurate and reliable description of the underlying electronic structure in systems throughout biology, chemistry, physics, and materials science. However, the high computational cost associated with the evaluation of all required EXX quantities has limited the applicability of hybrid DFT in the treatment of large molecules and complex condensed-phase materials. To overcome this limitation, we describe a linear-scaling approach that utilizes a local representation of the occupied orbitals (e.g., maximally localized Wannier functions (MLWFs)) to exploit the sparsity in the real-space evaluation of the quantum mechanical exchange interaction in finite-gap systems. In this work, we present a detailed description of the theoretical and algorithmic advances required to perform MLWF-based ab initio molecular dynamics (AIMD) simulations of large-scale condensed-phase systems of interest at the hybrid DFT level. We focus our theoretical discussion on the integration of this approach into the framework of Car–Parrinello AIMD, and highlight the central role played by the MLWF-product potential (i.e., the solution of Poisson’s equation for each corresponding MLWF-product density) in the evaluation of the EXX energy and wave function forces. We then provide a comprehensive description of the exx algorithm implemented in the open-source Quantum ESPRESSO program, which employs a hybrid MPI/OpenMP parallelization scheme to efficiently utilize the high-performance computing (HPC) resources available on current- and next-generation supercomputer architectures. Furthermore, this is followed by a critical assessment of the accuracy and parallel performance (e.g., strong and weak scaling) of this approach when AIMD simulations of liquid water are performed in the canonical (NVT) ensemble. With access to HPC resources, we demonstrate that exx enables hybrid DFT-based AIMD simulations of condensed-phase systems containing 500–1000 atoms (e.g., (H₂O)₂₅₆) with a wall time cost that is comparable to that of semilocal DFT. In doing so, exx takes us one step closer to routinely performing AIMD simulations of complex and large-scale condensed-phase systems for sufficiently long time scales at the hybrid DFT level of theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Closed loop performance of a brushless dc motor powered electromechanical actuator for flight control applications

A comprehensive digital model for the analysis and possible optimization of the closed loop dynamic (instantaneous) performance of a power conditioner fed, brushless dc motor powered, electromechanical actuator system (EMA) is presented. This model was developed for the simulation of the dynamic performance of an actual prototype EMA built for NASA-JSC as a possible alternative to hydraulic actuators for consideration in Space Shuttle Orbiter applications. Excellent correlation was achieved between numerical model simulation and experimental test results obtained from the actual hardware. These results include: various current and voltage waveforms in the machine-power conditioner (MPC) unit, flap position as well as other control loop variables in response to step commands of change of flap position. These results with consequent conclusions are detailed in the paper.

Demerdash, N. A.↗

Method and system for detecting a failure or performance degradation in a dynamic system such as a flight vehicle

A method and system for detecting a failure or performance degradation in a dynamic system having sensors for measuring state variables and providing corresponding output signals in response to one or more system input signals are provided. The method includes calculating estimated gains of a filter and selecting an appropriate linear model for processing the output signals based on the input signals. The step of calculating utilizes one or more models of the dynamic system to obtain estimated signals. The method further includes calculating output error residuals based on the output signals and the estimated signals. The method also includes detecting one or more hypothesized failures or performance degradations of a component or subsystem of the dynamic system based on the error residuals. The step of calculating the estimated values is performed optimally with respect to one or more of: noise, uncertainty of parameters of the models and un-modeled dynamics of the dynamic system which may be a flight vehicle or financial market or modeled financial system.

Miller, Robert H.↗