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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Computational Aerodynamic Analysis of Three-Dimensional Ice Shapes on a NACA 23012 Airfoil

The present study identifies a process for performing computational fluid dynamic calculations of the flow over full three-dimensional (3D) representations of complex ice shapes deposited on aircraft surfaces. Rime and glaze icing geometries formed on a NACA23012 airfoil were obtained during testing in the NASA Glenn Research Center's Icing Research Tunnel (IRT). The ice shape geometries were scanned as a cloud of data points using a 3D laser scanner. The data point clouds were meshed using Geomagic software to create highly accurate models of the ice surface. The surface data was imported into Pointwise grid generation software to create the CFD surface and volume grids. It was determined that generating grids in Pointwise for complex 3D icing geometries was possible using various techniques that depended on the ice shape. Computations of the flow fields over these ice shapes were performed using the NASA National Combustion Code (NCC). Results for a rime ice shape for angle of attack conditions ranging from 0 to 10 degrees and for freestream Mach numbers of 0.10 and 0.18 are presented. For validation of the computational results, comparisons were made to test results from rapid-prototype models of the selected ice accretion shapes, obtained from a separate study in a subsonic wind tunnel at the University of Illinois at Urbana-Champaign. The computational and experimental results were compared for values of pressure coefficient and lift. Initial results show fairly good agreement for rime ice accretion simulations across the range of conditions examined. The glaze ice results are promising but require some further examination.

Aerodynamics↗
NASA NTRS2014

Computational Aerodynamic Analysis of Three-Dimensional Ice Shapes on a NACA 23012 Airfoil

The present study identifies a process for performing computational fluid dynamic calculations of the flow over full three-dimensional (3D) representations of complex ice shapes deposited on aircraft surfaces. Rime and glaze icing geometries formed on a NACA23012 airfoil were obtained during testing in the NASA Glenn Research Centers Icing Research Tunnel (IRT). The ice shape geometries were scanned as a cloud of data points using a 3D laser scanner. The data point clouds were meshed using Geomagic software to create highly accurate models of the ice surface. The surface data was imported into Pointwise grid generation software to create the CFD surface and volume grids. It was determined that generating grids in Pointwise for complex 3D icing geometries was possible using various techniques that depended on the ice shape. Computations of the flow fields over these ice shapes were performed using the NASA National Combustion Code (NCC). Results for a rime ice shape for angle of attack conditions ranging from 0 to 10 degrees and for freestream Mach numbers of 0.10 and 0.18 are presented. For validation of the computational results, comparisons were made to test results from rapid-prototype models of the selected ice accretion shapes, obtained from a separate study in a subsonic wind tunnel at the University of Illinois at Urbana-Champaign. The computational and experimental results were compared for values of pressure coefficient and lift. Initial results show fairly good agreement for rime ice accretion simulations across the range of conditions examined. The glaze ice results are promising but require some further examination.

Aerodynamics↗
NASA NTRSDate not supplied

Summary of the First AIAA Stability and Control Prediction Workshop

Results from the First AIAA Stability and Control Prediction Workshop are summarized in this paper. The workshop series was developed in support of three primary objectives: (1) to establish best practices for the prediction of stability and control derivatives using industry-standard Computational Fluid Dynamics (CFD) solvers, (2) to provide an impartial forum for evaluating the effectiveness of Reynolds-averaged-Navier-Stokes- and Detached-Eddy-Simulation-based modeling techniques, and (3) to identify areas in need of additional research and development. To address these objectives, the inaugural workshop focused on generating computational aerodynamic predictions for the ONERA version of the NASA/Boeing Common Research Model. The configuration includes the wing, body, horizontal tail, and a vertical tail designed by ONERA. While longitudinal wind tunnel test data for the model had been previously documented, unpublished lateral test data at small sideslip angles provided a unique opportunity for participants to generate blind computational predictions for wind tunnel data comparisons. Additional test cases included assessments of the Mach number effect on static lateral/directional stability and the impact of the wind tunnel sting on longitudinal stability. Participants were invited to generate solutions using two workshop-provided series of structured overset and unstructured grids, in addition to any participant custom grids of interest. Total and component-level breakdowns for the force and moment coefficients for each test case are presented, as well as sectional pressure distribution data on the wing and tail components, to assess the agreement between several different Reynolds-averaged Navier-Stokes CFD solvers.

CFD↗
NASA NTRS2018

Airframe Noise Simulations of a Full-Scale Aircraft

Computational results for a full-scale simulation of a Gulfstream G-III aircraft are presented. In support of a NASA airframe noise flight test campaign, Exa Corporation’s lattice Boltzmann PowerFLOW® solver was used to perform time-accurate simulations of the flow around a highly detailed, full-scale aircraft model. Free-air boundary conditions were used at a Mach number of 0.23 and a Reynolds number of 10.5 × 10(exp 6) based on mean aerodynamic chord. This paper documents the simulation campaign for the baseline aircraft configuration at several flight conditions, including multiple flap deflections and main landing gear deployed or retracted. The high-fidelity, synthetic data were post-processed using a Ffowcs-Williams and Hawkings integral approach to estimate farfield acoustic behavior, with pressures on the model solid surface or a permeable surface enveloping the acoustic near field used as input. The numerical approach, simulation attributes, and the effects of grid resolution, gear deployment, and multiple flap deflections, are discussed as well.

Appelbaum, Jason↗
DOE OSTI2023

Factors Influencing Building Demand Flexibility

The U.S. Department of Energy’s National Roadmap for Grid-interactive Efficient Buildings (GEB) acknowledged that building demand flexibility (DF) is both an important strategy to decarbonizing the buildings sector and an important resource for meeting the changing needs of the electrical grid such as improving grid reliability. However, understanding the complexity and uncertainties in real building field performance of DF strategies is a large gap hindering stakeholders on both grid and buildings side to make investments on deploying such strategies. The research work in this report intended to advance understanding of the variability and influential factors in building demand flexibility. Adding such knowledge based on lab testing results and measured performance data from real buildings is an important contribution. The report uses standardized metrics and methods to quantify DF performance from field-measured DF datasets of two significant building groups of big-box retail and medium office buildings to present the challenge of building DF variability in multiple dimensions. The report presents findings related to how several key factors influence building demand flexibility from implementing a common, cost-effective DF control strategy (i.e., adjusting zone temperatures). The findings are supported by full-scale lab testing, field data analysis and simulation research. The authors also provided application-oriented recommendations to stakeholders such as building aggregators, utility program design professionals, sophisticated building portfolio owners, and more.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2001

An Inviscid Computational Study of Three '07 Mars Lander Aeroshell Configurations Over a Mach Number Range of 2.3 to 4.5

This report documents the results of a study conducted to compute the inviscid longitudinal aerodynamic characteristics of three aeroshell configurations of the proposed '07 Mars lander. This was done in support of the activity to design a smart lander for the proposed '07 Mars mission. In addition to the three configurations with tabs designated as the shelf, the canted, and the Ames, the baseline configuration (without tab) was also studied. The unstructured grid inviscid CFD software FELISA was used, and the longitudinal aerodynamic characteristics of the four configurations were computed for Mach number of 2.3, 2.7, 3.5, and 4.5, and for an angle of attack range of -4 to 20 degrees. Wind tunnel tests had been conducted on scale models of these four configurations in the Unitary Plan Wind Tunnel, NASA Langley Research Center. Present computational results are compared with the data from these tests. Some differences are noticed between the two results, particularly at the lower Mach numbers. These differences are attributed to the pressures acting on the aft body. Most of the present computations were done on the forebody only. Additional computations were done on the full body (forebody and afterbody) for the baseline and the Shelf configurations. Results of some computations done (to simulate flight conditions) with the Mars gas option and with an effective gamma are also included.

Prabhu, Ramadas K.↗
NASA NTRS1988

A numerical simulation of the full two-dimensional electrothermal de-icer pad

The ability to predict the time-temperature history of electrothermal de-icer pads is important in the subsequent design of improved and more efficient versions. These de-icer pads are installed near the surface of aircraft components, for the specific purpose of removing accreted ice. The proposed numerical model can incorporate the full 2-D geometry through a section of a region (i.e., section of an airfoil), that current 1-D numerical codes are unable to do. Thus, the effects of irregular layers, curvature, etc., can now be accounted for in the thermal transients. Each layer in the actual geometry is mapped via a body-fitted coordinate transformation into uniform, rectangular computational grids. The relevant heat transfer equations are transformed and discretized. To model the phase change that might occur in any accreted ice, in an enthalpy formulation the phase change equations are likewise transformed and discretized. The code developed was tested against numerous classical numerical solutions, as well as against experimental de-icing data on a UH1H rotor blade obtained from the NASA Lewis Research Center. The excellent comparisons obtained show that this code can be a useful tool in predicting the performance of current de-icer models, as well as in the designing of future models.

Masiulaniec, Konstanty C.↗
DOE OSTI2022

Dendrite-resolved, full-melt-pool phase-field simulations to reveal non-steady-state effects and to test an approximate model

In this report we study the epitaxial, columnar growth of (multiply oriented) dendrites/cells for a spot melt in a polycrystalline Al–Cu substrate using two-dimensional, phase-field, direct numerical simulations (DNS) at the full-melt-pool scale. Our main objective is to compare the expensive DNS model to a much cheaper but approximate “line” model in which a single-crystal phase-field simulation is confined to a narrow rectangular geometry. To perform this comparison, we develop algorithms that automatically extract quantities of interest (QoIs) from both DNS and line models. These QoIs allow us to quantitatively assess the assumptions in the line model and help us analyze its discrepancy with the DNS model. We consider four sets of heat source parameters, mimicking welding and additive manufacturing conditions, that create a combination shallow and deep melt pools. Our largest DNS simulation used 16K x 14K grid points in space. Our main findings can be summarized as follows. Under AM conditions, the QoIs of line models are in excellent agreement with the full DNS results for both shallow and deep melt pools. Under welding conditions, the primary spacing of the DNS model is smaller than the prediction of line model. We identify a geometric crowding effect that accounts for the discrepancies between the DNS and line models. We propose two potential mechanisms that determine the response of the microstructure to geometric crowding.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Computational Bayesian Framework for Quantification and Reduction of Predictive Uncertainty in Subsurface Environmental Modeling

Subsurface environmental systems are open and complex, in which intricate hydrologic, microbiologic, and geochemical processes occur and interact at multiple scales. Understanding and predicting system responses to natural forces (e.g., climate changes) and human activities (e.g., contaminant remediation and CO 2 sequestration) is indispensable for managing water resources, cleaning subsurface contamination at many sites of the Department of Energy (DOE), and providing expert analysis to inform policy-making on long-term stewardship of nuclear waste disposal and CO 2 storage sites. Groundwater reactive transport modeling is necessary for understanding and predicting the complex subsurface environmental system. However, as complex systems are never completely predictable, model predictions of the subsurface system are inherently uncertain, and uncertainty is one of the greatest obstacles in simulating the subsurface environment. Quantifying predictive uncertainty of the complex system is critical to test model predictive power, support decision-making, and guide experimental design and data collection for uncertainty reduction. This project tackled two major obstacles to efficient and effective quantification and reduction of predictive uncertainty in simulating the complex subsurface environment. One obstacle is that existing methods of uncertainty quantification are too fragmented and incomplete for understanding and predicting the complex subsurface environment as a whole. The other obstacle is that existing methods of uncertainty quantification are computationally demanding and may not be applicable to groundwater reactive transport modeling that is always computationally expensive. The above two obstacles to uncertainty quantification directly affect the design of data collection schemes for uncertainty reduction. In this project, we developed a comprehensive Bayesian framework to remove the first obstacle. The second obstacle was tackled by using the sparse grid methods, which were originally developed and analyzed for numerical integration in the field of applied mathematics. We integrated the sparse grid methods into the Bayesian framework seamlessly, which led to a sparse-grid-based method of Bayesian uncertainty analysis. The developed computational Bayesian framework has been applied to a number of subsurface environmental problems through collaborating with scientists at the Pacific Northwest National Laboratory and Oak Ridge National Laboratory. The applications demonstrated that the computational Bayesian framework is general and compatible with any models and numerical codes of subsurface modeling. It is thus can be applied to gain insights for subsurface environmental modeling. This project helped the PI achieve his career goal to advance the state-of-the-art computational methods in uncertainty quantification for subsurface environmental modeling. This project supported two doctoral students, two master students, and one post-doc. The two doctoral students, after their graduation, worked as post-docs at the Pacific Northwest National Laboratory and the Oak Ridge National Laboratory. The project produced a total of 29 journal articles (four under review), one book chapter, and a number of conference proceedings and abstracts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

Tropospheric Wind Observations with Doppler Lidars

Simpson Weather Associates has continued its efforts on the tools which operate the DLSM's s line-of-sight output products file. Due to the long model run times which were revealed in last month's benchmark tests, four model options for the LSM's atmospheric inputs are now included in the LSM. The user can choose to either spatially and/or temporally interpolate the inputs or use inputs closest to the DWL shot. A problem in the terrain assignment from the GADS was corrected. A database conversion tool was added to convert DWL line-of-sight ASCII files into database format for the graphic display models. Efforts have continued in simulating DWL horizontal wind components using the DAO ficcm Nature Run. Experiments 2 and 3 (40 days worth) were completed and sent to the DAO for their use in bracketing OSSE experiments. In addition, in order to investigate differences in the way regional (MM5) and global scale (ECMWF T213) models treat features such as clouds and subgrid scale variability, a gridded Mesoscale Atmospheric Data Set (MADS) was created and ready to be incorporated into simulation experiments.

Source record↗
NASA NTRS2012

Advances in Rotor Performance and Turbulent Wake Simulation Using DES and Adaptive Mesh Refinement

Time-dependent Navier-Stokes simulations have been carried out for a rigid V22 rotor in hover, and a flexible UH-60A rotor in forward flight. Emphasis is placed on understanding and characterizing the effects of high-order spatial differencing, grid resolution, and Spalart-Allmaras (SA) detached eddy simulation (DES) in predicting the rotor figure of merit (FM) and resolving the turbulent rotor wake. The FM was accurately predicted within experimental error using SA-DES. Moreover, a new adaptive mesh refinement (AMR) procedure revealed a complex and more realistic turbulent rotor wake, including the formation of turbulent structures resembling vortical worms. Time-dependent flow visualization played a crucial role in understanding the physical mechanisms involved in these complex viscous flows. The predicted vortex core growth with wake age was in good agreement with experiment. High-resolution wakes for the UH-60A in forward flight exhibited complex turbulent interactions and turbulent worms, similar to the V22. The normal force and pitching moment coefficients were in good agreement with flight-test data.

Chaderjian, Neal M.↗
DOE OSTI2026

A cell-centered AMR-ALE framework for 3D multi-material hydrodynamics. Part I: Lagrangian and indirect Euler AMR algorithms

Many applications of physics and engineering involve wide ranges of time and spatial scales. The numerical simulation of localized small scales such as shock waves and material interfaces requires a large number of computational cells in these regions. For these applications, Lagrangian and Arbitrary-Lagrangian-Eulerian (ALE) related methods are engaging since the moving mesh feature naturally brings mesh cells on shock discontinuities and material interfaces are carefully captured. In addition, Adaptive-Mesh-Refinement (AMR) strategies aim to optimize computational resources by concentrating finer mesh cells only in areas of interest while using coarser cells elsewhere. A key but challenging AMR requirement consists in efficiently distributing the computational effort to achieve high accuracy without the prohibitive computational costs associated with uniformly fine grids. Here, in this document, the coupling of the p4est AMR library with a cell-centered Lagrangian scheme is presented with the goal to perform reliable 3D Lagrangian-AMR and indirect Euler-AMR multi-material simulations. In particular, it is shown that starting from a 3D indirect ALE code, the memory management and load balancing requirements can be delegated to an external library (here the p4est library) to unlock ALE-AMR capabilities. First, we present a strategy to transcribe the octant-based connectivity of the 3D AMR framework with that of an unstructured mesh of polygonal cells used in Lagrangian hydrodynamics. Then, we show how refinement and coarsening operations must be adapted to the particular Lagrangian framework to ensure the conservation of volume during those steps. Finally, several numerical test cases are presented that demonstrate the capabilities of the Lagrangian-AMR and indirect Euler-AMR algorithms.

3D cell-centered Lagrangian numerical scheme↗
DOE OSTI2025

Algorithmic Advancements for High-Order Self-Gravitating Hydrodynamics

Self-gravity plays a key role in the formation and evolution of many astronomical objects. Though gravity is often dominant at large scales, other forces (e.g., gas pressure gradients, radiation, and/or magnetic fields) often compete. It is therefore essential for numerical simulations to evaluate their interplay accurately and robustly. Hanawa & Mullen derived a 4th-order accurate finite volume scheme to solve the equations of self-gravitating hydrodynamics on a uniform Cartesian grid. In this work, we supply improvements to the algorithm that (1) mitigate spurious gravitational circulation and (2) greatly simplify the evaluation of the high order corrections. The proposed algorithm provides the gravitational acceleration (ρg) and the gravitational energy release (ρv · g) as source terms for the hydrodynamic equations, all while preserving conservation of linear momentum. Spurious heating and/or cooling associated with truncation error in the numerical evaluation of the gravitational energy release decreases in proportion to the fourth power of the cell width. We demonstrate fourth order convergence on smooth problems (e.g., 3D inclined sound wave propagation and 3D equilibria). An application test tracks the spherical collapse of a polytrope by an imposed, sudden decrease of the central gas pressure; a bounce and second collapse (associated with a spherical accretion shock) are robustly captured by the high order algorithm.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Dynamically Learning Incentives for Load Control

As electrical generation becomes more distributed and volatile, and loads become more uncertain, controllability of distributed energy resources (DERs), regardless of their ownership status, will be necessary for grid reliability. Grid operators lack direct control over end-users' grid interactions, such as energy usage, but incentives can influence behavior -- for example, an end-user that receives a grid-driven incentive may adjust their consumption or expose relevant control variables in response. A key challenge in studying such incentives is the lack of data about human behavior, which usually motivates strong assumptions, such as distributional assumptions on compliance or rational utility-maximization. In this paper, we propose a general incentive mechanism in the form of a constrained optimization problem -- our approach is distinguished from prior work by modeling human behavior (e.g., reactions to an incentive) as an arbitrary unknown function. We propose feedback-based optimization algorithms to solve this problem that each leverage different amounts of information and/or measurements. We show that each converges to an asymptotically stable incentive with (near)-optimality guarantees given mild assumptions on the problem. Finally, we evaluate our proposed techniques in voltage regulation simulations on standard test beds. We test a variety of settings, including those that break assumptions required for theoretical convergence (e.g., convexity, smoothness) to capture realistic settings. In this evaluation, our proposed algorithms are able to find near-optimal incentives even when the reaction to an incentive is modeled by a theoretically difficult (yet realistic) function.

demand response↗
DOE OSTI2022

Decarbonizing the grid: Utilizing demand-side flexibility for carbon emission reduction through locational marginal emissions in distribution networks

Decarbonization of the electric grid has become an important world-wide priority and is actively happening in many ways by introducing innovations and new technologies from the generation sectors to the demand sectors. In particular, one promising pathway toward such net-zero carbon emissions is to utilize the demand-side flexibility with the increasing number of flexible loads in distribution networks. In this paper, we explore a load shifting strategy with the emerging concept of location marginal emissions (LMEs) to reduce carbon emissions. LMEs measure the impact of carbon emissions including the locational aspect in more granular way and thus provide a novel mechanism for the system operator and load aggregators to design the LME-based load shifting strategy, which can efficiently guide consumers and thus adjust their consumption behaviors. Simulation case studies on the IEEE test networks are performed to validate the capability of the proposed load shifting method to reduce carbon emissions. We also compare this with other relevant strategies to discuss multiple scenarios and corresponding results. Finally, while each provides a different level of flexibility, all the explored strategies tested have led to solutions that have lower carbon emissions, indicating the great potential of demand-side flexibility in reducing carbon emissions for future distribution networks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Adaptive mesh refinement for steady flows in Nek5000

Adaptive mesh refinement is performed in the framework of the spectral element method augmented by approaches to error estimation and control. The h-refinement technique is used for adapting the mesh, where selected grid elements are split by a quadtree (2D) or octree (3D) structure. Continuity between parent-child elements is enforced by high-order interpolation of the solution across the common faces. Parallel mesh partitioning and grid management respectively, are taken care of by the external libraries ParMETIS and p4est. Two methods are considered for estimating and controlling the error of the solution. The first error estimate is local and based on the spectral properties of the solution on each element. This method gives a local measure of the L-2-norm of the solution over the entire computational domain. The second error estimate uses the dual-weighted residuals method - it is based on and takes into account both the local properties of the solution and the global dependence of the error in the solution via an adjoint problem. The objective of this second approach is to optimize the computation of a given functional of physical interest. The simulations are performed by using the code Nek5000 and three steady-state test cases are studied: a two-dimensional lid-driven cavity at Re = 7, 500, a two-dimensional flow past a cylinder at Re = 40, and a three-dimensional lid-driven cavity at Re = 2,000 with a moving lid tilted by an angle of 30 degrees. Finally, the efficiency of both error estimators is compared in terms of refinement patterns and accuracy on the functional of interest. In the case of the adjoint error estimators, the trend on the error of the functional is shown to be correctly represented up to a multiplicative constant.

42 ENGINEERING↗
DOE OSTI2021

Review of Design Elements within Power Infrastructure Cyber–Physical Test Beds as Threat Analysis Environments

Cyber–physical systems (CPSs) are an integral part of modern society; thus, enhancing these systems’ reliability and resilience is paramount. Cyber–physical testbeds (CPTs) are a safe way to test and explore the interplay between the cyber and physical domains and to cost-effectively enhance the reliability and resilience of CPSs. Here a review of CPT elements, broken down into physical components (simulators, emulators, and physical hardware), soft components (communication protocols, network timing protocols), and user interfaces (visualization-dashboard design considerations) is presented. Various methods used to validate CPS performance are reviewed and evaluated for potential applications in CPT performance validation. Last, initial simulated results for a CPT design, based on the IEEE 33 bus system, are presented, along with a brief discussion on how model-based testing and fault–injection-based testing (using scaling and ramp-type attacks) may be used to help validate CPT performance.

14 SOLAR ENERGY↗