Search NASA⌕ Search

SEARCH · Search NASA

Results for “Virtual models”

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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Parametric Testing of Launch Vehicle FDDR Models

For the safe operation of a complex system like a (manned) launch vehicle, real-time information about the state of the system and potential faults is extremely important. The on-board FDDR (Failure Detection, Diagnostics, and Response) system is a software system to detect and identify failures, provide real-time diagnostics, and to initiate fault recovery and mitigation. The ERIS (Evaluation of Rocket Integrated Subsystems) failure simulation is a unified Matlab/Simulink model of the Ares I Launch Vehicle with modular, hierarchical subsystems and components. With this model, the nominal flight performance characteristics can be studied. Additionally, failures can be injected to see their effects on vehicle state and on vehicle behavior. A comprehensive test and analysis of such a complicated model is virtually impossible. In this paper, we will describe, how parametric testing (PT) can be used to support testing and analysis of the ERIS failure simulation. PT uses a combination of Monte Carlo techniques with n-factor combinatorial exploration to generate a small, yet comprehensive set of parameters for the test runs. For the analysis of the high-dimensional simulation data, we are using multivariate clustering to automatically find structure in this high-dimensional data space. Our tools can generate detailed HTML reports that facilitate the analysis.

Schumann, Johann↗
NASA NTRS2016

Plasticity Tool for Predicting Shear Nonlinearity of Unidirectional Laminates Under Multiaxial Loading

This study implements a plasticity tool to predict the nonlinear shear behavior of unidirectional composite laminates under multiaxial loadings, with an intent to further develop the tool for use in composite progressive damage analysis. The steps for developing the plasticity tool include establishing a general quadratic yield function, deriving the incremental elasto-plastic stress-strain relations using the yield function with associated flow rule, and integrating the elasto-plastic stress-strain relations with a modified Euler method and a substepping scheme. Micromechanics analyses are performed to obtain normal and shear stress-strain curves that are used in determining the plasticity parameters of the yield function. By analyzing a micromechanics model, a virtual testing approach is used to replace costly experimental tests for obtaining stress-strain responses of composites under various loadings. The predicted elastic moduli and Poisson's ratios are in good agreement with experimental data. The substepping scheme for integrating the elasto-plastic stress-strain relations is suitable for working with displacement-based finite element codes. An illustration problem is solved to show that the plasticity tool can predict the nonlinear shear behavior for a unidirectional laminate subjected to multiaxial loadings.

Wang, John T.↗
NASA NTRS2016

A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit

Suboptimal suit fit is a known risk factor for crewmember shoulder injury. Suit fit assessment is however prohibitively time consuming and cannot be generalized across wide variations of body shapes and poses. In this work, we have developed a new design tool based on the statistical analysis of body shape scans. This tool is aimed at predicting the skin deformation and shape variations for any body size and shoulder pose for a target population. This new process, when incorporated with CAD software, will enable virtual suit fit assessments, predictively quantifying the contact volume, and clearance between the suit and body surface at reduced time and cost.

Kim, K. Han↗
NASA NTRSDate not supplied

Using Kamodo for CCMC ITM Output and Beyond

Kamodo is an official NASA open source python software package that functionalizes diverse datasets from models and observations in a consistent way, enabling advanced scientific analysis and visualization with simplistic syntax. Here we demonstrate this ability using several ITM models available through the Community Coordinated Modeling Center (CCMC). Users can now interact directly with model outputs, and satellites can be virtually flown through model output to allow many types of model/model and data/model comparisons. We will also provide information about significant updates and improvements to Kamodo and future plans.

Open Source Software↗
NASA NTRS2023

Loft: An Automated Mesh Generator for Stiffened-Shell Aerospace Vehicles

Loft is an automated mesh generation code designed for aerospace vehicle structures. Based on user input, it can generate meshes for wings, noses, tanks, fuselage sections, thrust structures, etc. As the mesh is generated, each element is assigned properties that mark what part of the vehicle it is associated with. This property assignment is an extremely powerful feature making possible detailed analysis tasks such as load application and sizing. Loft can save its meshes in NASTRAN bulk data deck, EDS’ I-DEAS Universal File format, Abaqus input file format, VRML 2.0 (Virtual Reality Modeling Language) and STL (Stereo Lithography) files. The property assignment scheme was designed to make sizing in Collier Research’s HyperSizer easy. Support for other mesh storage formats can be added as needed.

Structural modeling↗
DOE OSTI2014

Overhead-Aware-Best-Fit (OABF) Resource Allocation Algorithm for Minimizing VM Launching Overhead

FermiCloud is a private cloud developed in Fermi National Accelerator Laboratory to provide elastic and on-demand resources for different scientific research experiments. The design goal of the FermiCloud is to automatically allocate resources for different scientific applications so that the QoS required by these applications is met and the operational cost of the FermiCloud is minimized. Our earlier research shows that VM launching overhead has large variations. If such variations are not taken into consideration when making resource allocation decisions, it may lead to poor performance and resource waste. In this paper, we show how we may use an VM launching overhead reference model to minimize VM launching overhead. In particular, we first present a training algorithm that automatically tunes a given refer- ence model to accurately reflect FermiCloud environment. Based on the tuned reference model for virtual machine launching overhead, we develop an overhead-aware-best-fit resource allocation algorithm that decides where and when to allocate resources so that the average virtual machine launching overhead is minimized. The experimental results indicate that the developed overhead-aware-best-fit resource allocation algorithm can significantly improved the VM launching time when large number of VMs are simultaneously launched.

Wu, Hao↗
DOE OSTI2020

Demand Response Potential from the Bulk Grid Perspective

Gain insight from an exploration of the potential value of demand response (DR) in future power systems. Using hourly DR resource estimates by sub-sector, electrical end-use, and grid service, we incorporate virtual generator models of DR resources into large-scale production cost models, and analyze the grid-level impacts in terms of the ability of DR to reduce system costs and potentially help integrate renewables or reduce system emissions. Additionally, we examine the value of DR, its revenue, and how these change under different system conditions. In this panel session, we will describe our input data and modeling methods, provide an overview of the production cost models used, and summarize key results from analyses in Florida and the western United States. Findings include variations in DR value by end-use and geography, an ability to increase economic PV deployment potential in high penetration systems, and mixed emissions outcomes depending on system composition and fuel prices.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Physics Coupled Machine Learning Applications for Geological Carbon Storage

This is the conference paper accompanying a poster presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. In this paper, a physics-based method, CRM is coupled with the advanced artificial intelligence (AI)/machine learning (ML) models in virtual learning environment (VLE) for three-dimension details of reservoir responses and evaluations for a comprehensive understanding for CCS field operations and reservoir managements.

Liu, Guoxiang↗
DOE OSTI2022

Development of a water source heat pump hardware-in-the-loop (HIL) testing facility for smart building applications

Over the last decade, the global fight against climate change through electrification has led to an increase in research on building heating, ventilation, and air conditioning (HVAC) systems that utilize intelligent control algorithms to provide demand-side grid service while maintaining the thermal comfort of building occupants. As the pivotalpoint between building electricity consumption and indoor thermal comfort, high-efficiency electrical heatpumps are at the center of these emerging studies, and various grid-interactive and occupant-comfort control algorithms have been developed for them. The impact of these algorithms on the heatpump operation andperformance under different weather, building load, and grid requests calls for investigation and verification via experimental tests with actual heat pumps integrated with real-time building and grid responses. This study presents a Water-Source Heat Pump Hardware-in-The-Loop (HIL) Test Facility developed with the capability to perform such tests. The hardware configuration for this testfacility introduces a hydronic system that emulates the conditions for the heat pump water-side, and a duct system that emulates conditions for the heat pump airside. Both data acquisition and emulator control are implemented through the National Instruments (NI) LabVIEW software running on an NI PXIplatform. The HIL mechanism based on the hardware-software integration that allows the testbed to communicate with a generic simulation environment is also discussed. Currently, the test facility setup includes a single heatpump and virtual building model in EnergyPlus coupled with an occupant behavioral model in MATLAB. Preliminary test results of the current setup demonstrate the building load emulator's ability to track the simulated gone temperature with a Root Mean Square Deviation (RSME) below 0.12°C (0.216°F). An uncertainty analysis based on sensor accuracies shows that the heat pump coefficient of performance (COP) can be measured with a relative uncertainty of 10.4% in cooling and 3.7% in heating. Apartfrom the current testing on a single heat pump, the test facility also provides the flexibility to include additional heat pumps to form a heat pump cluster, as well as coupling the heat pump with active thermal storage to provide enhanced demandflexibility.

Calfa, Caleb↗
NASA NTRS1996

Tracking Virtual Trajectories

Current models of smooth pursuit eye movements assume that it is largely driven by retinal image motion. We tested this hypothesis by measuring pursuit of elliptical motion (3.2s, 0.9 Hz, 1.4 deg x 1.6 deg, 4 randomly interleaved phases) of either a small spot ("real" motion) or of a line-figure diamond viewed through apertures such that only the motion of four isolated oblique line segments was visible ("virtual" motion). Each segment moved sinusoidally along a linear trajectory yet subjects perceived a diamond moving along an elliptical path behind the aperture. We found, as expected, that real motion produced accurate tracking (N = 2) with mean gain (over horizontal and vertical) of 0.9, mean phase of -6 deg (lag), mean relative phase (H vs V) of 90 +/- 8 deg (RMS error). Virtual motion behind an X-shaped aperture (N= 4 with one naive) yielded a mean gain of 0.7, mean phase of -11 deg, mean relative phase of 87 +/- 15 deg. We also measured pursuit with the X-shaped aperture using a higher segment luminance which prevents the segments from being grouped into a coherently moving diamond while keeping the motion otherwise identical. In this incoherent case, the same four subjects no longer showed consistent elliptical tracking (RMS error in relative phase rose to 60 deg) suggesting that perceptual coherence is critical. Furthermore, to rule out tracking of the centroid, we also used vertical apertures so that all segment motion was vertical (N = 3). This stimulus still produced elliptical tracking (mean relative phase of 84 +/- 19 deg), albeit with a lower gain (0.6). These data show that humans can track moving objects reasonably accurately even when the trajectory can only be derived by spatial integration of motion signals. Models that merely seek to minimize retinal or local stimulus motion cannot explain these results.

Stone, Leland S.↗
DOE OSTI2022

Motility Analysis of T-Cell Histories in Activation (Matcha) v0.1.0

Despite advances in microscopy, imaging techniques only capture a very small spatial and temporal fraction of T cell activity within a tissue. For this reason, we have pursued the development of a virtual T cell model. Matcha's objective is to design virtual T cells that move like biological T cells. The virtual T cells will match the speed and turning angle distributions of biological cells. In addition, Matcha will also attempt to match the volume patrolled by the biological cells and the dependence on speed and turning angle on the previous speed.

Rouson, Damian↗
NASA NTRS1992

Improved two-equation k-omega turbulence models for aerodynamic flows

Two new versions of the k-omega two-equation turbulence model will be presented. The new Baseline (BSL) model is designed to give results similar to those of the original k-omega model of Wilcox, but without its strong dependency on arbitrary freestream values. The BSL model is identical to the Wilcox model in the inner 50 percent of the boundary-layer but changes gradually to the high Reynolds number Jones-Launder k-epsilon model (in a k-omega formulation) towards the boundary-layer edge. The new model is also virtually identical to the Jones-Lauder model for free shear layers. The second version of the model is called Shear-Stress Transport (SST) model. It is based on the BSL model, but has the additional ability to account for the transport of the principal shear stress in adverse pressure gradient boundary-layers. The model is based on Bradshaw's assumption that the principal shear stress is proportional to the turbulent kinetic energy, which is introduced into the definition of the eddy-viscosity. Both models are tested for a large number of different flowfields. The results of the BSL model are similar to those of the original k-omega model, but without the undesirable freestream dependency. The predictions of the SST model are also independent of the freestream values and show excellent agreement with experimental data for adverse pressure gradient boundary-layer flows.

Menter, Florian R.↗
DOE OSTI2015

Building bridges between neuroscience, cognition and education with predictive modeling

As the field of Mind, Brain, and Education seeks new ways to credibly bridge the gap between neuroscience, the cognitive sciences, and education, various connections are being developed and tested. In this article, we present a framework and offers examples of one approach, predictive modeling within a virtual educational system that can include representations from the neural level to the policy level. Researchers could calibrate, test, and question the model, potentially providing quicker, more efficient, and more responsible ways of making advances in the developing educational field. Likewise, virtual investigations using models with this sort of capability can supplement the valuable information derived from carrying out policy and instructional experiments in real educational contexts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

A bilevel multistage stochastic self-scheduling model with indivisibilities for trading in the continuous intraday electricity market

In this paper, we study the profit maximization problem of a virtual power plant trading in the continuous intraday electricity market. Our virtual power plant model is compatible with renewable, and thermal assets, covering a range of virtual power plants currently participating in energy markets. We model the trading problem as a bilevel multistage stochastic program. The upper level of the problem accounts for the profit maximization of the virtual power plant with explicit modeling of the technical constraints of the operational status of the thermal power plant including minimum start-up and shut-down times, ramp-up and ramp-down rates, and minimum generation level. The upper level also decides which continuous and indivisible (fill-or-kill) orders are submitted to the market. The lower-level problem accounts for the clearing of the continuous intraday market, i.e., matching of buy and sell orders. Because of the presence of fill-or-kill orders, the lower-level problem is mixed-integer, which prevents its direct conversion to a single-level problem using duality. In order to solve this challenging problem, we develop a convex-hull extended formulation for the lower-level problem, apply duality theory to obtain a single-level stochastic equivalent formulation, and employ McCormick envelopes to turn the problem into a multistage stochastic mixed-integer linear problem, which we solve using the stochastic dual dynamic integer programming algorithm. We conduct numerical experiments and analyze the optimal trading behavior of a virtual power plant trading in an ideal continuous market without arbitrage.

Bilevel multistage stochastic programming problem↗
DOE OSTI2017

Virtual black holes in a third quantized formalism

In this paper, we will analyse virtual black holes using the third quantization formalism. As the virtual black hole model depends critically on the assumption that the quantum fluctuations dominate the geometry of spacetime at Planck scale, we will analyse the quantum fluctuations for a black hole using third quantization. We will demonstrate that these quantum fluctuations depend on the factor ordering chosen. So, we will show that only certain values of the factor ordering parameter are consistent with virtual black holes model of spacetime foam. - Highlights: • We analyze the Wheeler–DeWitt equation using third quantization. • The quantum fluctuations of geometry is studied using this formalism. • These quantum fluctuations produce virtual black holes. • This model is consistent with only certain values of the factor ordering.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗