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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Aerodynamic Characterization of a Modern Launch Vehicle

A modern launch vehicle is by necessity an extremely integrated design. The accurate characterization of its aerodynamic characteristics is essential to determine design loads, to design flight control laws, and to establish performance. The NASA Ares Aerodynamics Panel has been responsible for technical planning, execution, and vetting of the aerodynamic characterization of the Ares I vehicle. An aerodynamics team supporting the Panel consists of wind tunnel engineers, computational engineers, database engineers, and other analysts that address topics such as uncertainty quantification. The team resides at three NASA centers: Langley Research Center, Marshall Space Flight Center, and Ames Research Center. The Panel has developed strategies to synergistically combine both the wind tunnel efforts and the computational efforts with the goal of validating the computations. Selected examples highlight key flow physics and, where possible, the fidelity of the comparisons between wind tunnel results and the computations. Lessons learned summarize what has been gleaned during the project and can be useful for other vehicle development projects.

Hall, Robert M.↗
NASA NTRS2013

Mars Science Laboratory Entry, Descent, and Landing Trajectory and Atmosphere Reconstruction

On August 5th 2012, The Mars Science Laboratory entry vehicle successfully entered Mars atmosphere and landed the Curiosity rover on its surface. A Kalman filter approach has been implemented to reconstruct the entry, descent, and landing trajectory based on all available data. The data sources considered in the Kalman filtering approach include the inertial measurement unit accelerations and angular rates, the terrain descent sensor, the measured landing site, orbit determination solutions for the initial conditions, and a new set of instrumentation for planetary entry reconstruction consisting of forebody pressure sensors, known as the Mars Entry Atmospheric Data System. These pressure measurements are unique for planetary entry, descent, and landing reconstruction as they enable a reconstruction of the freestream atmospheric conditions without any prior assumptions being made on the vehicle aerodynamics. Moreover, the processing of these pressure measurements in the Kalman filter approach enables the identification of atmospheric winds, which has not been accomplished in past planetary entry reconstructions. This separation of atmosphere and aerodynamics allows for aerodynamic model reconciliation and uncertainty quantification, which directly impacts future missions. This paper describes the mathematical formulation of the Kalman filtering approach, a summary of data sources and preprocessing activities, and results of the reconstruction.

Karlgaard, Christopher D.↗
NASA NTRS2014

Learning the Task Management Space of an Aircraft Approach Model

Validating models of airspace operations is a particular challenge. These models are often aimed at finding and exploring safety violations, and aim to be accurate representations of real-world behavior. However, the rules governing the behavior are quite complex: nonlinear physics, operational modes, human behavior, and stochastic environmental concerns all determine the responses of the system. In this paper, we present a study on aircraft runway approaches as modeled in Georgia Tech's Work Models that Compute (WMC) simulation. We use a new learner, Genetic-Active Learning for Search-Based Software Engineering (GALE) to discover the Pareto frontiers defined by cognitive structures. These cognitive structures organize the prioritization and assignment of tasks of each pilot during approaches. We discuss the benefits of our approach, and also discuss future work necessary to enable uncertainty quantification.

Validation↗
NASA NTRS2013

Definition, Capabilities, and Components of a Terrestrial Carbon Monitoring System

Research efforts for effectively and consistently monitoring terrestrial carbon are increasing in number. As such, there is a need to define carbon monitoring and how it relates to carbon cycle science and carbon management. There is also a need to identify capabilities of a carbon monitoring system and the system components needed to develop the capabilities. Capabilities that enable the effective application of a carbon monitoring system for monitoring and management purposes may include: reconciling carbon stocks and fluxes, developing consistency across spatial and temporal scales, tracking horizontal movement of carbon, attribution of emissions to originating sources, cross-sectoral accounting, uncertainty quantification, redundancy and policy relevance. Focused research is needed to integrate these capabilities for sustained estimates of carbon stocks and fluxes. Additionally, if monitoring is intended to inform management decisions, management priorities should be considered prior to development of a monitoring system.

Terrestrial↗
NASA NTRS2014

An Adaptive Nonlinear Aircraft Maneuvering Envelope Estimation Approach for Online Applications

A nonlinear aircraft model is presented and used to develop an overall unified robust and adaptive approach to passive trim and maneuverability envelope estimation with uncertainty quantification. The concept of time scale separation makes this method suitable for the online characterization of altered safe maneuvering limitations after impairment. The results can be used to provide pilot feedback and/or be combined with flight planning, trajectory generation, and guidance algorithms to help maintain safe aircraft operations in both nominal and off-nominal scenarios.

nonlinearity↗
NASA NTRS2015

Ongoing Fixed Wing Research within the NASA Langley Aeroelasticity Branch

The NASA Langley Aeroelasticity Branch is involved in a number of research programs related to fixed wing aeroelasticity and aeroservoelasticity. These ongoing efforts are summarized here, and include aeroelastic tailoring of subsonic transport wing structures, experimental and numerical assessment of truss-braced wing flutter and limit cycle oscillations, and numerical modeling of high speed civil transport configurations. Efforts devoted to verification, validation, and uncertainty quantification of aeroelastic physics in a workshop setting are also discussed. The feasibility of certain future civil transport configurations will depend on the ability to understand and control complex aeroelastic phenomena, a goal that the Aeroelasticity Branch is well-positioned to contribute through these programs.

Bartels, Robert↗
NASA NTRS2015

Probabilistic Fatigue Damage Prognosis Using a Surrogate Model Trained Via 3D Finite Element Analysis

Utilizing inverse uncertainty quantification techniques, structural health monitoring can be integrated with damage progression models to form probabilistic predictions of a structure's remaining useful life. However, damage evolution in realistic structures is physically complex. Accurately representing this behavior requires high-fidelity models which are typically computationally prohibitive. In the present work, a high-fidelity finite element model is represented by a surrogate model, reducing computation times. The new approach is used with damage diagnosis data to form a probabilistic prediction of remaining useful life for a test specimen under mixed-mode conditions.

Leser, Patrick E.↗
NASA NTRS2016

Probabilistic Prognosis of Non-Planar Fatigue Crack Growth

Quantifying the uncertainty in model parameters for the purpose of damage prognosis can be accomplished utilizing Bayesian inference and damage diagnosis data from sources such as non-destructive evaluation or structural health monitoring. The number of samples required to solve the Bayesian inverse problem through common sampling techniques (e.g., Markov chain Monte Carlo) renders high-fidelity finite element-based damage growth models unusable due to prohibitive computation times. However, these types of models are often the only option when attempting to model complex damage growth in real-world structures. Here, a recently developed high-fidelity crack growth model is used which, when compared to finite element-based modeling, has demonstrated reductions in computation times of three orders of magnitude through the use of surrogate models and machine learning. The model is flexible in that only the expensive computation of the crack driving forces is replaced by the surrogate models, leaving the remaining parameters accessible for uncertainty quantification. A probabilistic prognosis framework incorporating this model is developed and demonstrated for non-planar crack growth in a modified, edge-notched, aluminum tensile specimen. Predictions of remaining useful life are made over time for five updates of the damage diagnosis data, and prognostic metrics are utilized to evaluate the performance of the prognostic framework. Challenges specific to the probabilistic prognosis of non-planar fatigue crack growth are highlighted and discussed in the context of the experimental results.

Leser, Patrick E.↗
NASA NTRS2015

Output-Based Adaptive Meshing Applied to Space Launch System Booster Separation Analysis

This paper presents details of Computational Fluid Dynamic (CFD) simulations of the Space Launch System during solid-rocket booster separation using the Cart3D inviscid code with comparisons to Overflow viscous CFD results and a wind tunnel test performed at NASA Langley Research Center's Unitary PlanWind Tunnel. The Space Launch System (SLS) launch vehicle includes two solid-rocket boosters that burn out before the primary core stage and thus must be discarded during the ascent trajectory. The main challenges for creating an aerodynamic database for this separation event are the large number of basis variables (including orientation of the core, relative position and orientation of the boosters, and rocket thrust levels) and the complex flow caused by the booster separation motors. The solid-rocket boosters are modified from their form when used with the Space Shuttle Launch Vehicle, which has a rich flight history. However, the differences between the SLS core and the Space Shuttle External Tank result in the boosters separating with much narrower clearances, and so reducing aerodynamic uncertainty is necessary to clear the integrated system for flight. This paper discusses an approach that has been developed to analyze about 6000 wind tunnel simulations and 5000 flight vehicle simulations using Cart3D in adaptive-meshing mode. In addition, a discussion is presented of Overflow viscous CFD runs used for uncertainty quantification. Finally, the article presents lessons learned and improvements that will be implemented in future separation databases.

Booster↗
NASA NTRS2017

Near Real-Time Probabilistic Damage Diagnosis Using Surrogate Modeling and High Performance Computing

This work investigates novel approaches to probabilistic damage diagnosis that utilize surrogate modeling and high performance computing (HPC) to achieve substantial computational speedup. Motivated by Digital Twin, a structural health management (SHM) paradigm that integrates vehicle-specific characteristics with continual in-situ damage diagnosis and prognosis, the methods studied herein yield near real-time damage assessments that could enable monitoring of a vehicle's health while it is operating (i.e. online SHM). High-fidelity modeling and uncertainty quantification (UQ), both critical to Digital Twin, are incorporated using finite element method simulations and Bayesian inference, respectively. The crux of the proposed Bayesian diagnosis methods, however, is the reformulation of the numerical sampling algorithms (e.g. Markov chain Monte Carlo) used to generate the resulting probabilistic damage estimates. To this end, three distinct methods are demonstrated for rapid sampling that utilize surrogate modeling and exploit various degrees of parallelism for leveraging HPC. The accuracy and computational efficiency of the methods are compared on the problem of strain-based crack identification in thin plates. While each approach has inherent problem-specific strengths and weaknesses, all approaches are shown to provide accurate probabilistic damage diagnoses and several orders of magnitude computational speedup relative to a baseline Bayesian diagnosis implementation.

Warner, James E.↗
NASA NTRS2018

Modeling-Driven Damage Tolerant Design of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composite Panels for Full-Scale Aerospace Structures

The objective of this study is to design a new nano graphenecarbon fiberpolymer hybrid composite that can be used for the NASA SLS Composite Exploration Upper Stage (CEUS) forward skirt structure. The new material will improve the resistance to open-hole compression failure of the structure relative to traditional polymer fiber composites. The material is designed rapidly and with little cost using the Integrated Computational Materials Engineering (ICME) approach. Multiscale modeling and experiments are used to synergistically optimize the material design to yield improved properties and performance by controlling key processing parameters for manufacturing nano-enhanced materials. Specifically, the nanocomposite panel showed a 22 reduction in mass relative to the traditional composite panel, while both designs are equal in terms of ease of manufacture. This potential mass savings corresponds to an estimated 45 savings in materials and manufacturing costs. The multiscale ICME workflow developed for this project can be readily applied to the development of nano-enhanced composite materials and large aerospace structures. In addition, all key aspects of ICME were employed to complete this project including multiscale modeling, experimental characterization and visualization, data management, visualization, error and uncertainty quantification, and education. The results presented herein indicate a dramatic level of success, as well as the power and potential of ICME approach and multiscale modeling for composite materials.

computational mechanics↗
NASA NTRS2019

Improving Accuracy of Structural Dynamic Modification with Augmented Residual Vectors

It is often important to perform sensitivity analysis to determine how a structural model will be impacted by design changes. Often, the structural analysts will manually make changes to the finite element model (FEM) to determine the effects. But when dealing with a large FEM with millions of degrees of freedom these manual changes can be cumbersome and calculation of the effects can computationally expensive. Therefore, it is desirable to determine the effects of model changes through approximation methods. One common technique is to determine the analytical sensitivity of the FEM model with respect to the given change. These analytical sensitivities are valid when small changes are made to the structural model, but invalid if large changes need to be assessed. Another approach is to use Structural Dynamic Modification (SDM) to create a surrogate model to analyze model changes. SDM is a widely-used sensitivity method and is used in applications of model updating, uncertainty quantification, and model design studies. SMD is valid for moderate (10-20 percent) changes in the structural model, but model approximations are often needed for large parameter changes (greater than 20 percent). Structural Dynamic Modification can be improved by using residual vectors to augment the surrogate model formulation from SDM. Adding the residual modes increases the fidelity of the surrogate model while keeping the computational cost low. This paper discusses the application and limitations of the augmented residual modes method to two structures: the Integrated Spacecraft and Payload Element (ISPE) of the Space Launch System (SLS) and the full SLS as it is configured during its Integrated Modal Test (IMT).

Stewart, Eric C.↗
NASA NTRS2017

A Model-Based, Bayesian Solution for Characterization of Complex Damage Scenarios in Aerospace Composite Structures

Ultrasonic damage detection and characterization is commonly used in nondestructive evaluation (NDE) of aerospace composite components. In recent years there has been an increased development of guided wave based methods. In real materials and structures, these dispersive waves result in complicated behavior in the presence of complex damage scenarios. Model-based characterization methods utilize accurate three dimensional finite element models (FEMs) of guided wave interaction with realistic damage scenarios to aid in defect identification and classification. This work describes an inverse solution for realistic composite damage characterization by comparing the wavenumber-frequency spectra of experimental and simulated ultrasonic inspections. The composite laminate material properties are first verified through a Bayesian solution (Markov chain Monte Carlo), enabling uncertainty quantification surrounding the characterization. A study is undertaken to assess the efficacy of the proposed damage model and comparative metrics between the experimental and simulated output. The FEM is then parameterized with a damage model capable of describing the typical complex damage created by impact events in composites. The damage is characterized through a transdimensional Markov chain Monte Carlo solution, enabling a flexible damage model capable of adapting to the complex damage geometry investigated here. The posterior probability distributions of the individual delamination petals as well as the overall envelope of the damage site are determined.

H. Reed↗
NASA NTRS2020

In-Time UAV Flight-Trajectory Estimation and Tracking Using Bayesian Filters

Rapid increase of UAV operation in the next decade in areas of on-demand delivery, medical transportation services, law enforcement, traffic surveillance and several others pose potential risks to the low altitude airspace above densely populated areas. Safety assessment of airspace demands the need for a novel UAV traffic management (UTM) framework for regulation and tracking of the vehicles. Particularly for low-altitude UAV operations, quality of GPS measurements feeding into the UAV is often compromised by loss of communication link caused by presence of trees or tall buildings in proximity to the UAV flight path. Inaccurate GPS locations may yield to unreliable monitoring and inaccurate prognosis of remaining battery life and other safety metrics which rely on future expected trajectory of the UAV. This work therefore proposes a generalized monitoring and prediction methodology for autonomous UAVs using in-time GPS measurements. Firstly, a typical 4D smooth trajectory generation technique from a series of waypoint locations with associated expected times-of-arrival based on B-spline curves is presented. Initial uncertainty in the vehicle's expected cruise velocity is quantified to compute confidence intervals along the entire flight trajectory using error interval propagation approach. Further, the generated planned trajectory is considered as the prior knowledge which is updated during its flight with incoming GPS measurements in order to estimate its current location and corresponding kinematic profiles. Estimation of position is denoted in dicrete state-space representation such that position at a future time step is derived from position and velocity at current time step and expected velocity at the future time step. A linear Bayesian filtering algorithm is employed to efficiently refine position estimation from noisy GPS measurements and update the confidence intervals. Further, a dynamic re-planning strategy is implemented to incorporate unexpected detour or delay scenarios. Finally, critical challenges related to uncertainty quantification in trajectory prognosis for autonomous vehicles are identified, and potential solutions are discussed at the end of the paper. The entire monitoring framework is demonstrated on real UAV flight experiments conducted at the NASA Langley Research Center.

Banerjee, Portia↗
NASA NTRSDate not supplied

Aerothermodynamic CFD Analysis

This presentation provides an introduction to two Computational Fluid Dynamics (CFD) codes, LAURA and FUN3D, which have been developed and widely used at NASA Langley Research Center in Entry, Descent, and Landing applications. A workflow using the LAURA and FUN3D CFD codes to predict aerodynamic and aerothermodynamic engineering quantities is presented. The presentation will cover the basics of setting up and running simulations using both CFD codes, as well as how to post-process results obtained from each code. More advanced topics will also be presented, including a state-of-the-art uncertainty quantification approach to be included in the next LAURA release, and a new geometry-based workflow used with FUN3D focused on replacing user-defined meshing with an adaptation-based approach.

Kyle B Thompson↗
NASA NTRSDate not supplied

Recent Improvements to the LAURA and HARA Codes

This paper describes recent improvements to the LAURA and HARA codes. LAURA is a CFD code for aerothermodynamics, and HARA evaluates the shock-layer radiation that provides the radiative source term for the flowfield energy equations and radiative heating to a surface. The next release of LAURA and HARA includes a variety of new capabilities. These new capabilities include an automated uncertainty quantification workflow for radiative heat transfer, options for specifying surface roughness and turbulent transition location in the algebraic turbulence models, and improved grid and solution interpolation techniques. Additionally, the computational efficiency of both LAURA and HARA have been improved. Optimization of the MPI communication routines in LAURA are shown to improve the parallel efficiency of the primary flow when running with multiple processes per block, and recent optimization of HARA leverage graphics processing unit (GPU) acceleration in the radiation calculations. Using GPU acceleration of HARA is shown to decrease the cost of the radiation line-of-sight calculation by approximately one order of magnitude for a 10.5 km/s Earth entry simulation.

LAURA HARA CFD 5.6↗
NASA NTRSDate not supplied

Summary of the NASA Semi-Span High-Lift Common Research Model Wind Tunnel Test at the QinetiQ 5-Metre Low-Speed Facility

A summary and selected results from experimental testing of the NASA 10% scale semi-span High-Lift Common Research Model (CRM-HL) at the QinetiQ 5m (5mWT) pressurized low-speed wind tunnel are presented. There were many objectives of this test, the primary being to define a set of reference configurations for dissemination and use within the CRM-HL ecosystem, one in the landing configuration and one in the takeoff configuration. A database of force, moment, pressure and surface flow visualization data was collected to support several objectives: aerodynamic sensitivity to high-lift device positioning, Reynolds number effects on configuration selection, isolation of the effects of various components of the reference configuration e.g. landing gear, nacelle, horizontal tail, etc., and limited repeatability data for uncertainty quantification assessment. Some results were compared to limited data collected at the NASA Langley Research Center 14x22 wind tunnel to assess half-model effects and facility differences. Half-model effects were further studied with use of floor blowing to change boundary layer profile and assess effects on model aerodynamics. Flow visualization data were gathered with fluorescent mini-tufts and UV oil. Finally, test time was spend working on the development of new Particle Image Velocimetry (PIV) and Model Deformation Measurement (MDM) capabilities at the 5mWT facility.

Ashley Evans↗
NASA NTRSDate not supplied

Testing of Mars Retropropulsion Concepts in the Langley Unitary Plan Wind Tunnel

Future Mars human lander missions will require using retrorockets beginning at supersonic conditions, something which has never been done before at Mars. Significant aerosciences challenges exist due to interactions between the retrorocket exhaust plumes, the freestream flow, and the vehicle that alter the aerodynamic behavior. Historical retropropulsion ground and flight data do not provide a basis for calibrating the computational uncertainties for aerodynamic interference forces and moments on proposed Mars descent vehicles, either because of insufficient data or dissimilar vehicles geometries and/or conditions. A new retropropulsion wind tunnel test was conducted in the NASA Langley Unitary Plan Wind Tunnel in order to address some of the deficiencies of previous tests and to provide a basis for computational model comparisons on relevant geometries. The test included improvements in model design and measured data. Two sub-scale model geometries derived from full-scale vehicle concepts were tested: a blunt low lift-to-drag vehicle and a more slender geometry. The first model includes variations in nozzle parameters that were estimated to have first-order effects on the measurements: location, pointing direction, size, and exit-to-throat area ratio. Both models were instrumented with discrete steady and unsteady pressure sensors on the aerodynamic and interior flow path surfaces. The heats shields of both models also were covered with pressure sensitive paint that effectively measures a steady pressure distribution in an otherwise unsteady flow field. This pressure distribution was integrated over the surface geometry in order to estimate the steady aerodynamic force and moment coefficient contribution from the painted surfaces; this approach was used as a replacement for using a flow-through balance. This paper will cover the test objectives, model design, test matrix, and available test results for each model configuration at different freestream Mach numbers, model attitude, and non-dimensional thrust magnitude. A subsequent publication will cover uncertainty quantification of the test data and comparisons to computational fluid dynamics model results.

Powered Descent↗