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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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18 records

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NASA NTRS2004

Multi-Fidelity Simulation of a Turbofan Engine With Results Zoomed Into Mini-Maps for a Zero-D Cycle Simulation

A Zero-D cycle simulation of the GE90-94B high bypass turbofan engine has been achieved utilizing mini-maps generated from a high-fidelity simulation. The simulation utilizes the Numerical Propulsion System Simulation (NPSS) thermodynamic cycle modeling system coupled to a high-fidelity full-engine model represented by a set of coupled 3D computational fluid dynamic (CFD) component models. Boundary conditions from the balanced, steady state cycle model are used to define component boundary conditions in the full-engine model. Operating characteristics of the 3D component models are integrated into the cycle model via partial performance maps generated from the CFD flow solutions using one-dimensional mean line turbomachinery programs. This paper highlights the generation of the high-pressure compressor, booster, and fan partial performance maps, as well as turbine maps for the high pressure and low pressure turbine. These are actually "mini-maps" in the sense that they are developed only for a narrow operating range of the component. Results are compared between actual cycle data at a take-off condition and the comparable condition utilizing these mini-maps. The mini-maps are also presented with comparison to actual component data where possible.

Turner, Mark G.↗

NASA NTRS2022

Multi-Fidelity CFD Simulation of the Multirotor Test Bed

The high-fidelity and reduced order CFD method's validation and analysis are presented for the Multirotor Test Bed. The reduced-order method uses a rotor-disk model in the OVERFLOW CFD code and is an important aspect of this study. A rotor-trim option loosely coupling the Comprehensive code CAMRAD II with the OVERFLOW CFD code is included in the simulation that captures rotor blade aerodynamics, blade and rotor performance, rotor-rotor, and rotor-body interactions. Detailed comparison and validation were performed for both higher-fidelity full rotor unsteady flows and reduced-order rotor-disk methods. The tunnel geometry is included in the detailed computational effort. Computations of the low-Reynolds number flows were performed for a different number of in-plane rotors as well as for a single rotor modeled inside the tunnel.

ARMD↗

NASA NTRS2006

Numerical Propulsion System Simulation

The NASA Glenn Research Center, in partnership with the aerospace industry, other government agencies, and academia, is leading the effort to develop an advanced multidisciplinary analysis environment for aerospace propulsion systems called the Numerical Propulsion System Simulation (NPSS). NPSS is a framework for performing analysis of complex systems. The initial development of NPSS focused on the analysis and design of airbreathing aircraft engines, but the resulting NPSS framework may be applied to any system, for example: aerospace, rockets, hypersonics, power and propulsion, fuel cells, ground based power, and even human system modeling. NPSS provides increased flexibility for the user, which reduces the total development time and cost. It is currently being extended to support the NASA Aeronautics Research Mission Directorate Fundamental Aeronautics Program and the Advanced Virtual Engine Test Cell (AVETeC). NPSS focuses on the integration of multiple disciplines such as aerodynamics, structure, and heat transfer with numerical zooming on component codes. Zooming is the coupling of analyses at various levels of detail. NPSS development includes capabilities to facilitate collaborative engineering. The NPSS will provide improved tools to develop custom components and to use capability for zooming to higher fidelity codes, coupling to multidiscipline codes, transmitting secure data, and distributing simulations across different platforms. These powerful capabilities extend NPSS from a zero-dimensional simulation tool to a multi-fidelity, multidiscipline system-level simulation tool for the full development life cycle.

Naiman, Cynthia↗

NASA NTRSDate not supplied

Multi-Fidelity Heating Prediction of Adaptable, Deployable Entry Placement Technology Vehicles

The objective of this work was to investigate a multi-fidelity modeling approach to accurately and efficiently predict the laminar and turbulent convective heating on adaptable, deployable entry placement technology vehicles in Mars entry. A previously developed co-Kriging based multi-fidelity modeling approach was used to model the laminar and turbulent convective heat fluxes at several surface locations along the vehicle, including the rib sections. The laminar convective heat flux multi-fidelity model was found to have a mean convective heat rate error of approximately 3% when compared to high-fidelity CFD simulations. The turbulent convective heat flux multi-fidelity model was found to have a mean convective heat rate error of approximately 8% when compared to high-fidelity CFD simulations. Compared to a single fidelity model, the multi-fidelity model required approximately one-third the number of high-fidelity model evaluations to obtain the same accuracy level. The computational cost of evaluating the multi-fidelity model was approximately five orders of magnitude less than one high-fidelity model simulation.

Mario Santos↗

NASA NTRS2006

The Airspace Concepts Evaluation System Architecture and System Plant

The Airspace Concepts Evaluation System is a simulation of the National Airspace System. It includes models of flights, airports, airspaces, air traffic controls, traffic flow managements, and airline operation centers operating throughout the United States. It is used to predict system delays in response to future capacity and demand scenarios and perform benefits assessments of current and future airspace technologies and operational concepts. Facilitation of these studies requires that the simulation architecture supports plug and play of different air traffic control, traffic flow management, and airline operation center models and multi-fidelity modeling of flights, airports, and airspaces. The simulation is divided into two parts that are named, borrowing from classical control theory terminology, control and plant. The control consists of air traffic control, traffic flow management, and airline operation center models, and the plant consists of flight, airport, and airspace models. The plant can run open loop, in the absence of the control. However, undesired affects, such as conflicts and over congestions in the airspaces and airports, can occur. Different controls are applied, "plug and played", to the plant. A particular control is evaluated by analyzing how well it managed conflicts and congestions. Furthermore, the terminal area plants consist of models of airports and terminal airspaces. Each model consists of a set of nodes and links which are connected by the user to form a network. Nodes model runways, fixes, taxi intersections, gates, and/or other points of interest, and links model taxiways, departure paths, and arrival paths. Metering, flow distribution, and sequencing functions can be applied at nodes. Different fidelity model of how a flight transits are can be used by links. The fidelity of the model can be adjusted by the user by either changing the complexity of the node/link network-or the way that the link models how the flights transit from one node to the other.

Windhorst, Robert↗

NASA NTRSDate not supplied

A Comparison of Rotor Disk Modeling and Blade-Resolved CFD Simulations for NASA's Tiltwing Air Taxi

A multi-fidelity computational fluid dynamics analysis is carried out for NASA’s tiltwing air taxi concept operating in airplane and helicopter mode. High-fidelity simulations are computationally expensive due to individual rotor blade modeling in a time-dependent computational domain with rotating grids. The mid-fidelity rotor disk option, in its source term implementation, is explored as a more affordable alternative. Computations are performed with NASA’s OVERFLOW flow solver loosely-coupled with the comprehensive code CAMRAD II for appropriate rotor trim. Detailed comparisons are shown for the trim solution, airloads, wake geometry, and rotor performance. While the rotor disk model is able to capture the flow field with satisfactory agreement in airplane mode, it faces difficulties in helicopter mode due to the three-dimensional effects of the wake. Although this study is limited to a specific vehicle geometry, it is expected that the results are somewhat generalizable to the analysis of multi-rotor configurations.

ARMD↗

NASA NTRSDate not supplied

TPSAS-NF1676L-18493-DND

The Air Traffic Operations Lab is a multi-fidelity, part-task, aircraft and air traffic operations simulation facility. Used to explore interactions between new airborne and ground-based tools in a NextGeneration ATC environment, including: - Concept-level flight operations research, looking at human decision making, situation awareness, transfer of authority/responsibility, etc. - Performance impact assessments of new operational concepts on the National Airspace System (NAS) - Rapid prototyping of new flight deck tools and automation - Concept-level safety assessments - Identification and evaluation of future communication, navigation, and surveillance (CNS) infrastructure requirements - Controller-pilot data link - Precision trajectory-based ops - Air-to-air data exchange

Michael T Palmer↗

NASA NTRS2016

Parametric Modeling Investigation of a Radially-Staged Low-Emission Aviation Combustor

Aviation gas-turbine combustion demands high efficiency, wide operability and minimal trace gas emissions. Performance critical design parameters include injector geometry, combustor layout, fuel-air mixing and engine cycle conditions. The present investigation explores these factors and their impact on a radially staged low-emission aviation combustor sized for a next-generation 24,000-lbf-thrust engine. By coupling multi-fidelity computational tools, a design exploration was performed using a parameterized annular combustor sector at projected 100% takeoff power conditions. Design objectives included nitrogen oxide emission indices and overall combustor pressure loss. From the design space, an optimal configuration was selected and simulated at 7.1, 30 and 85% part-power operation, corresponding to landing-takeoff cycle idle, approach and climb segments. All results were obtained by solution of the steady-state Reynolds-averaged Navier-Stokes equations. Species concentrations were solved directly using a reduced 19-step reaction mechanism for Jet-A. Turbulence closure was obtained using a nonlinear K-epsilon model. This research demonstrates revolutionary combustor design exploration enabled by multi-fidelity physics-based simulation.

design analysis↗

NASA NTRSDate not supplied

Uncertainty Quantification and Sensitivity Analysis in Process-Structure-Property Simulations for Laser Powder Bed Fusion Additive Manufacturing

Process variations and process-induced defects like porosity cause significant uncertainty in the microstructure and mechanical behavior of additively manufactured metals. Establishing process-structure-property (PSP) relationships and quantifying uncertainty using experiments alone is costly, especially for structural applications where mechanical allowables must be established for qualification and certification. This work presents a PSP simulation framework for laser powder bed fusion with a focus on uncertainty quantification through probabilistic calibration and multi-fidelity uncertainty propagation. Motivated by phenomenological input parameters related to grain nucleation and growth that are difficult to characterize, a global sensitivity analysis (GSA) is completed. Through GSA, the most important input parameters are identified based on their influence on the statistical distributions of microstructural metrics that influence mechanical behavior, including grain size, morphology, and crystallographic texture. The results provide insight on what experiments are necessary to quantify and control PSP uncertainties, particularly those associated with the more challenging input parameters.

additive manufacturing↗

NASA NTRS1998

Variable-Complexity Multidisciplinary Optimization on Parallel Computers

This report covers work conducted under grant NAG1-1562 for the NASA High Performance Computing and Communications Program (HPCCP) from December 7, 1993, to December 31, 1997. The objective of the research was to develop new multidisciplinary design optimization (MDO) techniques which exploit parallel computing to reduce the computational burden of aircraft MDO. The design of the High-Speed Civil Transport (HSCT) air-craft was selected as a test case to demonstrate the utility of our MDO methods. The three major tasks of this research grant included: development of parallel multipoint approximation methods for the aerodynamic design of the HSCT, use of parallel multipoint approximation methods for structural optimization of the HSCT, mathematical and algorithmic development including support in the integration of parallel computation for items (1) and (2). These tasks have been accomplished with the development of a response surface methodology that incorporates multi-fidelity models. For the aerodynamic design we were able to optimize with up to 20 design variables using hundreds of expensive Euler analyses together with thousands of inexpensive linear theory simulations. We have thereby demonstrated the application of CFD to a large aerodynamic design problem. For the predicting structural weight we were able to combine hundreds of structural optimizations of refined finite element models with thousands of optimizations based on coarse models. Computations have been carried out on the Intel Paragon with up to 128 nodes. The parallel computation allowed us to perform combined aerodynamic-structural optimization using state of the art models of a complex aircraft configurations.

Grossman, Bernard↗

NASA NTRS2004

Numerical Propulsion System Simulation Architecture

The Numerical Propulsion System Simulation (NPSS) is a framework for performing analysis of complex systems. Because the NPSS was developed using the object-oriented paradigm, the resulting architecture is an extensible and flexible framework that is currently being used by a diverse set of participants in government, academia, and the aerospace industry. NPSS is being used by over 15 different institutions to support rockets, hypersonics, power and propulsion, fuel cells, ground based power, and aerospace. Full system-level simulations as well as subsystems may be modeled using NPSS. The NPSS architecture enables the coupling of analyses at various levels of detail, which is called numerical zooming. The middleware used to enable zooming and distributed simulations is the Common Object Request Broker Architecture (CORBA). The NPSS Developer's Kit offers tools for the developer to generate CORBA-based components and wrap codes. The Developer's Kit enables distributed multi-fidelity and multi-discipline simulations, preserves proprietary and legacy codes, and facilitates addition of customized codes. The platforms supported are PC, Linux, HP, Sun, and SGI.

Naiman, Cynthia G.↗

NASA NTRSDate not supplied

Multi-Fidelity Computational Analysis of a Quiet Single-Main Rotor Helicopter for Air Taxi Operations

A multi-fidelity computational study has been conducted on NASA’s quiet single-main rotor helicopter concept for urban air mobility using computational fluid dynamics and rotorcraft comprehensive analysis tools. Two approaches have been followed in order to simulate the rotor flows: (1) a rotor disk model, which models the rotors as source terms, and (2) a high-fidelity approach using high-order accurate schemes and dual-time stepping, which simulates the rotor with its individual rotating blade grids. The delayed detached-eddy simulation model has been employed. A loose-coupling approach between the flow solver and a rotorcraft comprehensive code is utilized to include vehicle trim and motion variables. The quiet single-main rotor helicopter is one of the conceptual designs intended to focus and guide NASA’s research activities in support of aircraft development for vertical take-off and landing air taxi operations.

RVLT↗

NASA NTRSDate not supplied

The Containment Assurance Risk Framework of the Mars Sample Return Program

The Mars Sample Return campaign aims at bringing rock and atmospheric samples from Mars to Earth through a series of robotic missions. These missions would collect the samples being cached and deposited on Martian soil by the Perseverance rover, place them in a container, and launch them into Martian orbit for subsequent capture by an orbiter that would bring them back. Given there exists a non-zero probability that the samples contain biological material, precautions are being taken to design systems that would break the chain of contact between Mars and Earth. These include techniques such as sterilization of Martian particles, redundant containment vessels, and a robust reentry capsule capable of accurate landings without a parachute. Requirements exist that the probability of containment not assured of Martian-contaminated material into Earth’s biosphere be less than one in a million. To demonstrate compliance with this strict requirement, a statistical framework was developed to assess the likelihood of containment loss during each sample return phase and make a statement about the total combined mission probability of containment not assured. The work presented here describes this framework, which considers failure modes or fault conditions that can initiate failure sequences ultimately leading to containment not assured. Reliability estimates are generated from databases, design heritage, component specifications, or expert opinion in the form of probability density functions or point estimates and provided as inputs to the mathematical models that simulate the different failure sequences. The probabilistic outputs are then combined following the logic of several fault trees to compute the ultimate probability of containment not assured. Given the multidisciplinary nature of the problem and the different types of mathematical models used, the statistical tools needed for analysis are required to be computationally efficient. While standard Monte Carlo approaches are used for fast models, a multi-fidelity approach to rare event probabilities is proposed for expensive models. In this paradigm, inexpensive low-fidelity models are developed for computational acceleration purposes while the expensive high-fidelity model is kept in the loop to retain accuracy in the results. This work presents an example of end-to-end application of this framework highlighting the computational benefits of a multi-fidelity approach.

Giuseppe Cataldo↗

NASA NTRS2001

Multifunctional Collaborative Modeling and Analysis Methods in Engineering Science

Engineers are challenged to produce better designs in less time and for less cost. Hence, to investigate novel and revolutionary design concepts, accurate, high-fidelity results must be assimilated rapidly into the design, analysis, and simulation process. This assimilation should consider diverse mathematical modeling and multi-discipline interactions necessitated by concepts exploiting advanced materials and structures. Integrated high-fidelity methods with diverse engineering applications provide the enabling technologies to assimilate these high-fidelity, multi-disciplinary results rapidly at an early stage in the design. These integrated methods must be multifunctional, collaborative, and applicable to the general field of engineering science and mechanics. Multifunctional methodologies and analysis procedures are formulated for interfacing diverse subdomain idealizations including multi-fidelity modeling methods and multi-discipline analysis methods. These methods, based on the method of weighted residuals, ensure accurate compatibility of primary and secondary variables across the subdomain interfaces. Methods are developed using diverse mathematical modeling (i.e., finite difference and finite element methods) and multi-fidelity modeling among the subdomains. Several benchmark scalar-field and vector-field problems in engineering science are presented with extensions to multidisciplinary problems. Results for all problems presented are in overall good agreement with the exact analytical solution or the reference numerical solution. Based on the results, the integrated modeling approach using the finite element method for multi-fidelity discretization among the subdomains is identified as most robust. The multiple-method approach is advantageous when interfacing diverse disciplines in which each of the method's strengths are utilized. The multifunctional methodology presented provides an effective mechanism by which domains with diverse idealizations are interfaced. This capability rapidly provides the high-fidelity results needed in the early design phase. Moreover, the capability is applicable to the general field of engineering science and mechanics. Hence, it provides a collaborative capability that accounts for interactions among engineering analysis methods.

Ransom, Jonathan B.↗

NASA NTRS2020

Multi Model Monte Carlo with Python (MXMCPy)

Multi Model Monte Carlo with Python (\mxmc {}) is a software package developed as a general capability for computing the statistics of outputs from an expensive, high-fidelity model by leveraging faster, low-fidelity models for speedup. Motivated by uncertainty propagation problems where classical Monte Carlo (MC) simulation is computationally intractable, various multi-model MC approaches have recently emerged that yield unbiased estimators with significantly reduced variance relative to MC for the same cost. These existing methods include multi-level Monte Carlo (MLMC), multi-fidelity Monte Carlo (MFMC), and approximate control variates (ACV). Given a fixed computational budget and a collection of models with varying cost/accuracy, each method seeks a sample allocation strategy across the models that results in an estimator with optimal variance reduction. \mxmc {} is a versatile tool that enables convenient access to many existing multi-model MC approaches within one modular and extensible package. With \mxmc {}, users can easily compare existing methods to determine the best choice for their particular problem, while developers have a basis for implementing and sharing new variance reduction approaches. This report introduces the \mxmc {} software, providing a summary of the problem-solving workflow for users as well as a brief overview of the code layout for developers.

Geoffrey F Bomarito↗

NASA NTRSDate not supplied

The Effect of Boundary Layer Character on Stochastic Rotor Blade Vortex Shedding Noise

This work illustrates the effect of a rotor blade’s boundary layer on the broadband LBL-VS self-noise emitted from an optimum hovering rotor through experimental and multi-fidelity computational studies. Blade surface roughness effects associated with different manufacturing techniques and the effect of adding a boundary layer trip were shown to decrease LBL-VS noise by upwards of 30 dB at the frequency of maximum emission with a slight penalty in aerodynamic performance when compared with smooth rotor blades. Low-fidelity 2-D viscous flow analysis verified the presence of laminar separation bubbles on the rotor blades which are responsible for LBL-VS noise. Three high-fidelity lattice-Boltzmann simulations were conducted with different wall-functions to predict the boundary layer character correspondent to their experimental counterpart and the resultant presence or absence of LBL-VS noise. Excellent aerodynamic and aeroacoustic agreement was seen between the lattice-Boltzmann simulations and the experimental data for the cases with surface roughness and the boundary layer trip, with the broadband noise results from the simulation with fully turbulent wall-functions diverging from the experimental results above 5 kHz. The transitional wall-function simulation which emulated the smooth experimental blades underpredicted thrust by 14% and broadband noise by a minimum of 10 dB with an accurately predicted broadband noise trend.

Christopher S Thurman↗

NASA NTRSDate not supplied

An Integrated Recursive Framework for Arbitrarily Multiscale and Multi-fidelity Modeling

The NASA Multiscale Analysis Tool (NAMSAT) serves as a state-of-the-art, “plug and play,” massively multiscale modeling (M3) platform for hierarchical materials and structures. The development of NASMAT has focused on modularity, upgradability and maintainability, interoperability, and utility. Application Program Interfaces (APIs) have been developed to facilitate the integration NASMAT into other programs (commercial, research, and user-defined) as well as the integration of other codes into NASMAT. NASMAT is an integrated, recursive platform that seamlessly allows for an arbitrary number of scales, and a variety of modeling fidelity, in a single, non-linear analysis. Thus, the macroscopic response of a material can be directly linked to the behavior of the microstructure(s), including subscale defects, making it a suitable tool for integrated computational materials engineering (ICME) because . Examples using NASMAT for simulation of polycrystalline metals at elevated temperatures will be presented.

Multiscale Modeling↗

NASA NTRSDate not supplied

Uncertainty Reduction With Multi-Model Monte Carlo for Crystal Plasticity Simulations of Additively Manufactured Metals

In this work, multi-model Monte Carlo estimators are developed to reduce uncertainty in quantities of interest (QoIs) extracted from crystal plasticity simulations of additively manufactured (AM) metals. A significant concern in AM parts is uncertainty in mechanical properties caused in part by complex microstructures that arise from the AM process. Quantifying uncertainty in microstructure-sensitive behavior using experiments alone is costly, especially when mechanical allowables must be established. Quantitative relationships among microstructure, micromechanical metrics like slip accumulation, crack initiation, and failure are also difficult to capture with limited experiments. Crystal plasticity material models instead enable computational prediction of micromechanical stress and strain fields given a discretized microstructure. However, high-fidelity finely discretized crystal plasticity simulations are computationally expensive, while lower-fidelity models are less accurate and generally biased, making uncertainty quantification and reduction computationally difficult as well. Multi-model Monte Carlo methods leverage correlations between high- and low-fidelity models to produce unbiased estimators for QoIs with reduced uncertainty relative to standard Monte Carlo. Crystal plasticity QoIs considered in this work include yield strength and the mean and extreme values of micromechanical fields that are relevant to crack initiation. Multi-model Monte Carlo estimators are developed for each individual QoI and several groups of QoIs. The results of this work establish relationships among model correlations, sample allocation, and uncertainty reduction for different combinations of QoIs and demonstrate a trend of less uncertainty reduction as QoIs become more sensitive to local microstructure. Limitations from using pilot samples to estimate model covariances and train low-fidelity models are also addressed. The uncertainty reduction achieved by multi-model Monte Carlo is an important step toward using computational mechanics models to predict microstructure-sensitive crack initiation and failure in AM parts.

uncertainty quantification↗