Search NASA⌕ Search

SEARCH · Search NASA

Results for “model complexity”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.

Chamis, Christos C.↗
NASA NTRS1980

Progress in turbulence modeling for complex flow fields including effects of compressibility

Two second-order-closure turbulence models were devised that are suitable for predicting properties of complex turbulent flow fields in both incompressible and compressible fluids. One model is of the "two-equation" variety in which closure is accomplished by introducing an eddy viscosity which depends on both a turbulent mixing energy and a dissipation rate per unit energy, that is, a specific dissipation rate. The other model is a "Reynolds stress equation" (RSE) formulation in which all components of the Reynolds stress tensor and turbulent heat-flux vector are computed directly and are scaled by the specific dissipation rate. Computations based on these models are compared with measurements for the following flow fields: (a) low speed, high Reynolds number channel flows with plane strain or uniform shear; (b) equilibrium turbulent boundary layers with and without pressure gradients or effects of compressibility; and (c) flow over a convex surface with and without a pressure gradient.

Wilcox, D. C.↗
NASA NTRSDate not supplied

Comprehensive Analysis Aeroelastic Stability Predictions for the Mars Sample Recovery Helicopters and Ingenuity

A rotorcraft comprehensive analysis was used to generate aeroelastic stability predictions for both Ingenuity and the Mars Sample Recovery Helicopters. The analysis was performed multiple times for each rotor system with sequential increases to the level of modeling complexity. Initial cases used an independent blade analysis, trim inflow distribution, no airframe degrees of freedom, and a hover condition (a time-invariant problem). The final model used all blades, dynamic inflow, airframe degrees of freedom, and a Floquet theory approach to the flutter analysis. The approach of sequentially increasing modeling complexity was employed to ensure the causes of any observed instabilities could be identified. For each case, stability results were determined across a range of air densities, tip Mach numbers, and rotor collective pitch settings. For the Sample Recovery Helicopter, a forward flight condition analysis with the highest level of modeling complexity was also performed. The aeroelastic stability predictions showed both the Ingenuity and Sample Recovery Helicopter rotor systems to be stable for all analyzed conditions. Parameter excursions of structural properties were performed to explore conditions resulting in aeroelastic instabilities.

Aeroelastic↗
NASA NTRS1982

On the automatic generation of FEM models for complex gears - A work-in-progress report

A description is presented of the development and use of a preprocessor to create a NASTRAN finite element model of a complex spur, helical, or spiral bevel gear quickly, inexpensively, and accurately. The preprocessor creates a ready to run NASTRAN input deck including the executive, case control, and bulk data sections. It generates nodes and solid elements to model spur, helical, or spiral bevel gear teeth with integral shafting. Either a complete gear shafting model or a symmetric model is created. The fundamental building block of the gear model is the base layer. The base layer is the mesh configuration of one layer of one tooth segment which is in turn duplicated, translated, and rotated to create the completed model of the gear. Once the base layer is created, the construction of the finite element model is straightforward.

Drago, R. J.↗
NASA NTRS2008

On Convergence of Development Costs and Cost Models for Complex Spaceflight Instrument Electronics

Development costs of a few recent spaceflight instrument electrical and electronics subsystems have diverged from respective heritage cost model predictions. The cost models used are Grass Roots, Price-H and Parametric Model. These cost models originated in the military and industry around 1970 and were successfully adopted and patched by NASA on a mission-by-mission basis for years. However, the complexity of new instruments recently changed rapidly by orders of magnitude. This is most obvious in the complexity of representative spaceflight instrument electronics' data system. It is now required to perform intermediate processing of digitized data apart from conventional processing of science phenomenon signals from multiple detectors. This involves on-board instrument formatting of computational operands from row data for example, images), multi-million operations per second on large volumes of data in reconfigurable hardware (in addition to processing on a general purpose imbedded or standalone instrument flight computer), as well as making decisions for on-board system adaptation and resource reconfiguration. The instrument data system is now tasked to perform more functions, such as forming packets and instrument-level data compression of more than one data stream, which are traditionally performed by the spacecraft command and data handling system. It is furthermore required that the electronics box for new complex instruments is developed for one-digit watt power consumption, small size and that it is light-weight, and delivers super-computing capabilities. The conflict between the actual development cost of newer complex instruments and its electronics components' heritage cost model predictions seems to be irreconcilable. This conflict and an approach to its resolution are addressed in this paper by determining the complexity parameters, complexity index, and their use in enhanced cost model.

Kizhner, Semion↗
NASA NTRS1997

Meta-Modeling: A Knowledge-Based Approach to Facilitating Model Construction and Reuse

In this paper, we introduce a new modeling approach called meta-modeling and illustrate its practical applicability to the construction of physically-based ecosystem process models. As a critical adjunct to modeling codes meta-modeling requires explicit specification of certain background information related to the construction and conceptual underpinnings of a model. This information formalizes the heretofore tacit relationship between the mathematical modeling code and the underlying real-world phenomena being investigated, and gives insight into the process by which the model was constructed. We show how the explicit availability of such information can make models more understandable and reusable and less subject to misinterpretation. In particular, background information enables potential users to better interpret an implemented ecosystem model without direct assistance from the model author. Additionally, we show how the discipline involved in specifying background information leads to improved management of model complexity and fewer implementation errors. We illustrate the meta-modeling approach in the context of the Scientists' Intelligent Graphical Modeling Assistant (SIGMA) a new model construction environment. As the user constructs a model using SIGMA the system adds appropriate background information that ties the executable model to the underlying physical phenomena under investigation. Not only does this information improve the understandability of the final model it also serves to reduce the overall time and programming expertise necessary to initially build and subsequently modify models. Furthermore, SIGMA's use of background knowledge helps eliminate coding errors resulting from scientific and dimensional inconsistencies that are otherwise difficult to avoid when building complex models. As a. demonstration of SIGMA's utility, the system was used to reimplement and extend a well-known forest ecosystem dynamics model: Forest-BGC.

Keller, Richard M.↗
NASA NTRS1992

Assessment of higher order turbulence models for complex two- and three-dimensional flowfields

A numerical method is presented to solve the three-dimensional Navier-Stokes equations in combination with a full Reynolds-stress turbulence model. Computations will be shown for three complex flowfields. The results of the Reynolds-stress model will be compared with those predicted by two different versions of the k-omega model. It will be shown that an improved version of the k-omega model gives as accurate results as the Reynolds-stress model.

Menter, Florian R.↗
NASA NTRS2020

Application of Extended Messinger Models to Complex Geometries

Since, ice accretion can significantly degrade the performance and the stability of an airborne vehicle, it is imperative to be able to model it accurately. While ice accretion studies have been performed on airplane wings and helicopter blades in abundance, there are few that attempt to model the process on more complex geometries such as fuselages. This paper proposes a methodology that extends an existing in-house Extended Messinger solver to complex geometries by introducing the capability to work with unstructured grids and carry out spatial surface streamwise marching. For the work presented here commercial solvers such as STAR-CCM+ and ANSYS Fluent are used for the flow field and droplet dispersed phase computations. The ice accretion is carried out using an in-house icing solver called GT-ICE. The predictions by GT-ICE are compared to available experimental data, or to predictions by other solvers such as LEWICE and STAR-CCM+. Three different cases with varying levels of complexity are presented. The first case considered is a commercial transport airfoil, followed by a three-dimensional MS(1)-317 swept wing. Finally, ice accretion calculations performed on a Robin fuselage have been discussed. Good agreement with experimental data, where applicable, is observed. Differences between the ice accretion predictions by different solvers have been discussed.

Gupta, Avani↗
NASA NTRS1990

Effects of simplifying assumptions on optimal trajectory estimation for a high-performance aircraft

When analyzing the performance of an aircraft, certain simplifying assumptions, which decrease the complexity of the problem, can often be made. The degree of accuracy required in the solution may determine the extent to which these simplifying assumptions are incorporated. A complex model may yield more accurate results if it describes the real situation more thoroughly. However, a complex model usually involves more computation time, makes the analysis more difficult, and often requires more information to do the analysis. Therefore, to choose the simplifying assumptions intelligently, it is important to know what effects the assumptions may have on the calculated performance of a vehicle. Several simplifying assumptions are examined, the effects of simplified models to those of the more complex ones are compared, and conclusions are drawn about the impact of these assumptions on flight envelope generation and optimal trajectory calculation. Models which affect an aircraft are analyzed, but the implications of simplifying the model of the aircraft itself are not studied. The examples are atmospheric models, gravitational models, different models for equations of motion, and constraint conditions.

Kern, Lura E.↗
NASA NTRS1991

Relation between the quasi-periodic oscillations and the low-frequency noise of GX 5-1 in the horizontal branch

Ginga observations of quasi-periodic oscillations (QPOs) and the low-frequency noise (LFN) from GX 5-1 in its horizontal-branch spectral state are presented. Power spectral fits were attempted using model functions based on simple oscillating shot models. A clear second-harmonic peak of QPO was detected. Variations in the powers of QPO and LFN on timescales of 8-256 s were also studied. These variations were significant for all of the timescales studied, and were uncorrelated with each other on timescales shorter than a few tens of seconds, and correlated on longer timescales. From simulations based on a simple shot model, it was found that the variation amplitude and the lack of correlation on short timescales are not inconsistent with the oscillating shot models. A more complex model is necessary to fully explain the observed properties.

Mitsuda, Kazuhisa↗
NASA NTRS1993

Nonlinear and progressive failure aspects of transport composite fuselage damage tolerance

The purpose is to provide an end-user's perspective on the state of the art in life prediction and failure analysis by focusing on subsonic transport fuselage issues being addressed in the NASA/Boeing Advanced Technology Composite Aircraft Structure (ATCAS) contract and a related task-order contract. First, some discrepancies between the ATCAS tension-fracture test database and classical prediction methods is discussed, followed by an overview of material modeling work aimed at explaining some of these discrepancies. Finally, analysis efforts associated with a pressure-box test fixture are addressed, as an illustration of modeling complexities required to model and interpret tests.

Walker, Tom↗
NASA NTRS1980

Low order equivalent models of highly augmented aircraft determined from flight data using maximum likelihood estimation

This paper presents the results of a study of the feasibility of using low order equivalent mathematical models of a highly augmented aircraft, the F-8 digital fly-by-wire (DFBW), for flying qualities research. Increasingly complex models were formulated and evaluated using flight data and maximum likelihood estimation techniques. The aircraft actuator was modeled alone first. Next the equivalent derivatives were used to model the longitudinal unaugmented F-8 DFBW aircraft dynamics. The most complex model incorporated a pure time shift of the pilot input, a first order lag, and the basic longitudinal airframe model. This same model was then implemented for the F-8 DFBW aircraft in a highly augmented mode. Excellent matching of the dynamics resulted for this model, indicating that low order equivalent models which are good representations of the highly augmented F-8 DFBW aircraft can be formulated with these methods.

Shafer, M. F.↗
NASA NTRS2024

Machine Learning for the Prediction of Local Asteroid Damages

Risk assessment studies of local asteroid hazards traditionally simulate the physics of meteors with engineering models tailored to analyze tens-of-millions of scenarios. However, these simplified approaches still need to solve time-dependent ODEs to model the entry process and the resulting ground damage. With a computational cost of O(0.01 CPU.s) per scenario, simulating these large numbers of potential entry conditions in risk assessment studies can take several days on local computers. To improve computational efficiency, we propose in this paper an orthogonal approach based on machine learning models to predict the size of damaged areas given a list of entry parameters. We train 5 machine learning methods and compare the predictions to the outputs of the PAIR model, first only with primitive entry condition variables, and then with more advanced features. We find that complex models like neural networks are well-suited to estimate blast hazards, while simpler linear models can accurately assess thermal damage. For both types of hazards, the radii of damaged areas can be predicted with around 10% average errors and a coefficient of determination (R2) of 0.99. The CPU time is decreased by a factor O(10 3 ) compared to the PAIR model, which enables the simulation of millions of scenarios in minutes, on a local computer. We then use the same machine learning approaches for a classification task where the models are trained to predict if an asteroid will produce a given level of damage. Results show that complex models like the gradient boosting classifier and the neural network can perform this task with 98% accuracy. Beyond surrogate models, we finally incorporate the machine learning algorithms to the state-of-the-art Shapley sensitivity analysis and present a ranking of the entry parameters based on their contributions to ground damages.

SMD↗
NASA NTRS1993

Turbulence modeling for complex hypersonic flows

The paper presents results of calculations for a range of 2D turbulent hypersonic flows using two-equation models. The baseline models and the model corrections required for good hypersonic-flow predictions will be illustrated. Three experimental data sets were chosen for comparison. They are: (1) the hypersonic flare flows of Kussoy and Horstman, (2) a 2D hypersonic compression corner flow of Coleman and Stollery, and (3) the ogive-cylinder impinging shock-expansion flows of Kussoy and Horstman. Comparisons with the experimental data have shown that baseline models under-predict the extent of flow separation but over-predict the heat transfer rate near flow reattachment. Modifications to the models are described which remove the above-mentioned deficiencies. Although we have restricted the discussion only to the selected baseline models in this paper, the modifications proposed are universal and can in principle be transferred to any existing two-equation model formulation.

Huang, P. G.↗
NASA NTRS2021

Development of Spaceborne SoOp Reflectometry Model for Complex Terrains

Following the launch of multiple global navigation satel-lite system (GNSS) reflectometry (GNSS-R) missions, theSignals of Opportunity (SoOp) method has proven to be apowerful tool for geophysical parameter retrieval for land ap-plications such as soil moisture. Having demonstrated thefeasibility of the SoOp techniques at P- and S-band, the devel-opment of SoOp measurements beyond the GNSS frequencyregime is highly anticipated. The SoOp Coherent Bistatic(SCoBi) model and simulator, developed in 2017 and open-sourced in 2018, has been made available to provide multi-frequency, fully polarimetric SoOp simulations for ground-based applications through the joint use of analytical wavetheory and distorted Borne approximation to evaluate landcontributions from multilayer dielectric profiles composed ofsoil moisture, vegetation, and surface roughness effects. Thispaper describes the advancement of SCoBi from a ground-and airborne-based model to a spaceborne model. This ex-tension allows for fully polarimetric, complex delay-Dopplermap (DDM) simulations through evaluation of the coherentsuperposition of electric fields emerging from a grid of ori-ented facets. The model generates a grid of facets by de-termining the geometry of contributing elements from digitalelevation models, with each element providing its contribu-tion under a flat-earth assumption. This module will enablethe analysis of fully polarimetric scattering from frequenciesavailable across the ultra-high frequency (UHF) regime.

D R Boyd↗