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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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Virtual Diagnostics Interface (ViDI) for Planning Laser-Based Wind Tunnel Experiments

Virtual Diagnostics Interface (ViDI), originally introduced by Richard Schwartz in 2004 and described again by Alderfer, et. al., in 2007, is an interactive 3D software tool developed at NASA Langley Research Center to serve three main purposes: assist in pre-test planning, enhance post-test image analysis and visualization, and serve as a central location for data storage and distribution.1,2 ViDI is composed of custom-developed software and Autodesk® 3ds Max® as it incorporates Computer Aided Design (CAD) models with the results obtained from optical diagnostics.3 This software tool has proven useful in the field of optical diagnostics where pre-test planning of beam paths, optical elements, and test articles must be carried out to avoid interference, ensure spatial resolution is sufficient, and the camera Field of View (FoV) is adequate for the field of interest. Typically, practical considerations such as the distance a camera is from the region of interest, the angles at which the camera is oriented and issues such as the size of the camera and its sensor and size and focal length lens as well as the path of the laser need to be taken into account to predict a successful measurement. An example application of ViDI is shown in Fig.1 where an experiment to investigate flow separation over the wing of the High Lift Common Research Model (HL-CRM) is currently being planned in the National Transonic Facility (NTF) at NASA Langley Research Center.

virtual diagnostics interface↗
NASA NTRS2009

Virtual Diagnostic Interface: Aerospace Experimentation in the Synthetic Environment

The Virtual Diagnostics Interface (ViDI) methodology combines two-dimensional image processing and three-dimensional computer modeling to provide comprehensive in-situ visualizations commonly utilized for in-depth planning of wind tunnel and flight testing, real time data visualization of experimental data, and unique merging of experimental and computational data sets in both real-time and post-test analysis. The preparation of such visualizations encompasses the realm of interactive three-dimensional environments, traditional and state of the art image processing techniques, database management and development of toolsets with user friendly graphical user interfaces. ViDI has been under development at the NASA Langley Research Center for over 15 years, and has a long track record of providing unique and insightful solutions to a wide variety of experimental testing techniques and validation of computational simulations. This report will address the various aspects of ViDI and how it has been applied to test programs as varied as NASCAR race car testing in NASA wind tunnels to real-time operations concerning Space Shuttle aerodynamic flight testing. In addition, future trends and applications will be outlined in the paper.

Schwartz, Richard J.↗
NASA NTRS2010

Virtual Diagnostic Interface: Aerospace Experimentation in the Synthetic Environment

The Virtual Diagnostics Interface (ViDI) methodology combines two-dimensional image processing and three-dimensional computer modeling to provide comprehensive in-situ visualizations commonly utilized for in-depth planning of wind tunnel and flight testing, real time data visualization of experimental data, and unique merging of experimental and computational data sets in both real-time and post-test analysis. The preparation of such visualizations encompasses the realm of interactive three-dimensional environments, traditional and state of the art image processing techniques, database management and development of toolsets with user friendly graphical user interfaces. ViDI has been under development at the NASA Langley Research Center for over 15 years, and has a long track record of providing unique and insightful solutions to a wide variety of experimental testing techniques and validation of computational simulations. This report will address the various aspects of ViDI and how it has been applied to test programs as varied as NASCAR race car testing in NASA wind tunnels to real-time operations concerning Space Shuttle aerodynamic flight testing. In addition, future trends and applications will be outlined in the paper.

Schwartz, Richard J.↗
NASA NTRS2007

Virtual Diagnostics Interface: Real Time Comparison of Experimental Data and CFD Predictions for a NASA Ares I-Like Vehicle

Virtual Diagnostics Interface technology, or ViDI, is a suite of techniques utilizing image processing, data handling and three-dimensional computer graphics. These techniques aid in the design, implementation, and analysis of complex aerospace experiments. LiveView3D is a software application component of ViDI used to display experimental wind tunnel data in real-time within an interactive, three-dimensional virtual environment. The LiveView3D software application was under development at NASA Langley Research Center (LaRC) for nearly three years. LiveView3D recently was upgraded to perform real-time (as well as post-test) comparisons of experimental data with pre-computed Computational Fluid Dynamics (CFD) predictions. This capability was utilized to compare experimental measurements with CFD predictions of the surface pressure distribution of the NASA Ares I Crew Launch Vehicle (CLV) - like vehicle when tested in the NASA LaRC Unitary Plan Wind Tunnel (UPWT) in December 2006 - January 2007 timeframe. The wind tunnel tests were conducted to develop a database of experimentally-measured aerodynamic performance of the CLV-like configuration for validation of CFD predictive codes.

Schwartz, Richard J.↗
NASA NTRS2007

Virtual Diagnostics Interface: Real Time Comparison of Experimental Data and CFD Predictions for a NASA Ares I-Like Vehicle

Virtual Diagnostics Interface technology, or ViDI, is a suite of techniques utilizing image processing, data handling and three-dimensional computer graphics. These techniques aid in the design, implementation, and analysis of complex aerospace experiments. LiveView3D is a software application component of ViDI used to display experimental wind tunnel data in real-time within an interactive, three-dimensional virtual environment. The LiveView3D software application was under development at NASA Langley Research Center (LaRC) for nearly three years. LiveView3D recently was upgraded to perform real-time (as well as post-test) comparisons of experimental data with pre-computed Computational Fluid Dynamics (CFD) predictions. This capability was utilized to compare experimental measurements with CFD predictions of the surface pressure distribution of the NASA Ares I Crew Launch Vehicle (CLV) - like vehicle when tested in the NASA LaRC Unitary Plan Wind Tunnel (UPWT) in December 2006 - January 2007 timeframe. The wind tunnel tests were conducted to develop a database of experimentally-measured aerodynamic performance of the CLV-like configuration for validation of CFD predictive codes.

Schwartz, Richard J.↗
NASA NTRS2003

Rapid Technology Assessment via Unified Deployment of Global Optical and Virtual Diagnostics

This paper discusses recent developments in rapid technology assessment resulting from an active collaboration between researchers at the Air Force Research Laboratory (AFRL) at Wright Patterson Air Force Base (WPAFB) and the NASA Langley Research Center (LaRC). This program targets the unified development and deployment of global measurement technologies coupled with a virtual diagnostic interface to enable the comparative evaluation of experimental and computational results. Continuing efforts focus on the development of seamless data translation methods to enable integration of data sets of disparate file format in a common platform. Results from a successful low-speed wind tunnel test at WPAFB in which global surface pressure distributions were acquired simultaneously with model deformation and geometry measurements are discussed and comparatively evaluated with numerical simulations. Intensity- and lifetime-based pressure-sensitive paint (PSP) and projection moire interferometry (PMI) results are presented within the context of rapid technology assessment to enable simulation-based R&D.

Jordan, Jeffrey D.↗
NASA NTRS2004

ViDI: Virtual Diagnostics Interface: The Future of Wind Tunnel Testing - Volume 1

The quality of data acquired in a given test facility ultimately resides within the fidelity and implementation of the instrumentation systems. Over the last decade, the emergence of robust optical techniques has vastly expanded the envelope of measurement possibilities. At the same time the capabilities for data processing, data archiving and data visualization required to extract the highest level of knowledge from these global, on and off body measurement techniques have equally expanded. Yet today, while the instrumentation has matured to the production stage, an optimized solution for gaining knowledge from the gigabytes of data acquired per test (or even per test point) is lacking. A technological void has to be filled in order to possess a mechanism for near-real time knowledge extraction during wind tunnel experiments. Under these auspices, the Virtual Diagnostics Interface, or ViDI, was developed.

Fleming, Gary A.↗
NASA NTRS2004

ViDI: Virtual Diagnostics Interface: Unified File Format and Web Services as Applied to Seamless Data Transfer - Volume 2

The desire to revolutionize the aircraft design cycle from its currently lethargic pace to a fast turn-around operation enabling the optimization of non-traditional configurations is a critical challenge facing the aeronautics industry. In response, a large scale effort is underway to not only advance the state of the art in wind tunnel testing, computational modeling, and information technology, but to unify these often disparate elements into a cohesive design resource. This paper will address Seamless Data Transfer, the critical central nervous system that will enable a wide variety of varied components to work together.

Fleming, Gary A.↗
DOE OSTI2023

Prediction on X-ray output of free electron laser based on artificial neural networks

Abstract Knowledge of x-ray free electron lasers’ (XFELs) pulse characteristics delivered to a sample is crucial for ensuring high-quality x-rays for scientific experiments. XFELs’ self-amplified spontaneous emission process causes spatial and spectral variations in x-ray pulses entering a sample, which leads to measurement uncertainties for experiments relying on multiple XFEL pulses. Accurate in-situ measurements of x-ray wavefront and energy spectrum incident upon a sample poses challenges. Here we address this by developing a virtual diagnostics framework using an artificial neural network (ANN) to predict x-ray photon beam properties from electron beam properties. We recorded XFEL electron parameters while adjusting the accelerator’s configurations and measured the resulting x-ray wavefront and energy spectrum shot-to-shot. Training the ANN with this data enables effective prediction of single-shot or average x-ray beam output based on XFEL undulator and electron parameters. This demonstrates the potential of utilizing ANNs for virtual diagnostics linking XFEL electron and photon beam properties.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Physics-constrained superresolution diffusion for six-dimensional phase space diagnostics

Adaptive physics-constrained superresolution diffusion is developed for noninvasive virtual diagnostics of the six-dimensional (6D) phase space density of charged particle beams. An adaptive variational autoencoder embeds initial beam condition images and scalar measurements to a low-dimensional latent space from which a 32 6 pixel 6D tensor representation of the beam's 6D phase space density is generated. Projecting from a 6D tensor generates physically consistent two-dimensional projections. Physics-guided superresolution diffusion transforms low-resolution images of the 6D density to high resolution 256 × 256 pixel images. Unsupervised adaptive latent space tuning enables tracking of time-varying beams without knowledge of time-varying initial conditions. The method is demonstrated with experimental data and multiparticle simulations at the HiRES UED. The general approach is applicable to a wide range of complex dynamic systems evolving in high-dimensional phase space. The method is shown to be robust to distribution shift without retraining. Published by the American Physical Society 2025

43 PARTICLE ACCELERATORS↗
NASA NTRS2007

Testing of the Crew Exploration Vehicle in NASA Langley's Unitary Plan Wind Tunnel

As part of a strategic, multi-facility test program, subscale testing of NASA s Crew Exploration Vehicle was conducted in both legs of NASA Langley s Unitary Plan Wind Tunnel. The objectives of these tests were to generate aerodynamic and surface pressure data over a range of supersonic Mach numbers and reentry angles of attack for experimental and computational validation and aerodynamic database development. To provide initial information on boundary layer transition at supersonic test conditions, transition studies were conducted using temperature sensitive paint and infrared thermography optical techniques. To support implementation of these optical diagnostics in the Unitary Wind Tunnel, the experiment was first modeled using the Virtual Diagnostics Interface software. For reentry orientations of 140 to 170 degrees (heat shield forward), windward surface flow was entirely laminar for freestream unit Reynolds numbers equal to or less than 3 million per foot. Optical techniques showed qualitative evidence of forced transition on the windward heat shield with application of both distributed grit and discreet trip dots. Longitudinal static force and moment data showed the largest differences with Mach number and angle of attack variations. Differences associated with Reynolds number variation and/or laminar versus turbulent flow on the heat shield were very small. Static surface pressure data supported the aforementioned trends with Mach number, Reynolds number, and angle of attack.

Murphy, Kelly J.↗
DOE OSTI2024

Conditional guided generative diffusion for particle accelerator beam diagnostics

Abstract Advanced accelerator-based light sources such as free electron lasers (FEL) accelerate highly relativistic electron beams to generate incredibly short (10s of femtoseconds) coherent flashes of light for dynamic imaging, whose brightness exceeds that of traditional synchrotron-based light sources by orders of magnitude. FEL operation requires precise control of the shape and energy of the extremely short electron bunches whose characteristics directly translate into the properties of the produced light. Control of short intense beams is difficult due to beam characteristics drifting with time and complex collective effects such as space charge and coherent synchrotron radiation. Detailed diagnostics of beam properties are therefore essential for precise beam control. Such measurements typically rely on a destructive approach based on a combination of a transverse deflecting resonant cavity followed by a dipole magnet in order to measure a beam’s 2D time vs energy longitudinal phase-space distribution. In this paper, we develop a non-invasive virtual diagnostic of an electron beam’s longitudinal phase space at megapixel resolution (1024 × 1024) based on a generative conditional diffusion model. We demonstrate the model’s generative ability on experimental data from the European X-ray FEL.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Solving the Orszag–Tang vortex magnetohydrodynamics problem with physics-constrained convolutional neural networks

We study the 2D Orszag–Tang vortex magnetohydrodynamics (MHD) problem through the use of physics-constrained convolutional neural networks (PCNNs) for forecasting the density, ρ, and the magnetic field, B, as well as the prediction of B given the velocity field v of the fluid. In addition to translation equivariance from the convolutional architecture, other physics constraints were embedded: absence of magnetic monopoles, non-negativity of ρ, use of only relevant variables, and the periodic boundary conditions of the problem. The use of only relevant variables and the hard constraint of non-negative ρ were found to facilitate learning greatly. The divergenceless condition ∇·B=0 was implemented as a hard constraint up to machine precision through the use of a magnetic potential to define B=∇×A. Residual networks and data augmentation were also used to improve performance. This allowed for some of the residual models to function as surrogate models and provide reasonably accurate simulations. For the prediction task, the PCNNs were evaluated against a physics-informed neural network, which had the ideal MHD induction equation as a soft constraint. Several models were able to generate highly accurate fields, which are visually almost indistinguishable and have low mean squared error. Only methods with built-in hard constraints produced physical fields with ∇·B=0. The use of PCNNs for MHD has the potential to produce physically consistent real-time simulations to serve as virtual diagnostics in cases where inferences must be made with limited observables.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Dynamic evolution of ultracold electron beams from nanostructured cathodes

Dynamic Coulomb expansion of dense, nonuniform particle beamlets can lead to causticlike formations in the charge density profile of the resultant beam. Such features only occur for cold beams where thermal diffusion of the particles is minimized. These phenomena have been observed experimentally for select cases with ion beams but not yet for electron beams as the electron dynamics occur over far faster timescales. We simulate the interaction of electron bunches while varying the initial transverse temperature and density profiles to determine the thresholds that characterize this pattern formation. Furthermore, we extend the simulations to geometric arrangements that are more pertinent to the nanotip cathode application and consider the effects of asymmetries and the impact of a low-density halo on the overall process. The simulations are conducted using a previously documented high-fidelity algorithm for collisional particle dynamics. These studies identify the temperature and density thresholds required for caustic formation and provide guidance for optimizing the design of nanoscale structured cathodes. We also demonstrate that the correlation between the final density patterns and the underlying beam parameters enables a virtual diagnostic tool for measuring ultralow emittance beams solely based on a transverse charge density profile.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Machine learning surrogate for charged particle beam dynamics with space charge based on a recurrent neural network with aleatoric uncertainty

In this work, we develop a machine learning (ML) model with aleatoric uncertainty for the low energy beam transport (LEBT) region of the LANSCE linear accelerator in which we model the transport of a space-charge-dominated 750 keV proton beam through a lattice of 22 quadrupole magnets. Our ML model is developed based on data generated by a Kapchinsky–Vladimirsky (KV) envelope model of beam transport. We show that a recurrent neural network can be used as a dynamical surrogate model for fast prediction of the LEBT beam envelope. Furthermore, we endow the model with the prediction of aleatoric uncertainty and compare three different approaches. We demonstrate that the ML-based uncertainty quantification models are well calibrated and produce good estimates of the regions where the model is less certain about its predictions. This ML framework is a necessary step in the development of a real-time virtual diagnostic tool with uncertainty quantification that can be integrated into more complex downstream tasks (e.g., adaptive control or learning flexible control policies via reinforcement learning) for improved efficiency in beam operations. In future work, we plan to expand on this preliminary study by considering more realistic envelope models that include longitudinal momentum spread and dispersive effects in bending magnets, as well as particle tracking codes with 3D space charge (such as and ). Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗
NASA NTRS2006

Visualization of a Capsule Entry Vehicle Reaction-Control System (RCS) Thruster

Planar laser-induced fluorescence (PLIF) was used to visualize the reaction control system (RCS) jet flow emanating from the aft-body of an Apollo-geometry capsule test article in the NASA Langley Research Center 31-Inch Mach 10 Air wind tunnel. The RCS jet was oriented normal to the aft surface of the model and had a nominal Mach number of 2.94. The composition of the jet gas by mass was 95% nitrogen (N2) and 5% nitric oxide (NO). The RCS jet flowrate varied between zero and 0.5 standard liters per minute and the angle of attack and tunnel stagnation pressure were also varied. PLIF was used to excite the NO molecules for flow visualization. These flow visualization images were processed to determine the trajectory and to quantify the flapping of the RCS jet. The spatial resolution of the jet trajectory measurement was about 1 mm and the single-shot precision of the measurement was estimated to be 0.02 mm in the far field of the jet plume. The jet flapping, measured by the standard deviation of the jet centerline position was as large as 0.9 mm, while the jet was 1.5-4 mm in diameter (full width at half maximum). Schlieren flow visualization images were obtained for comparison with the PLIF. Surface pressures were also measured and presented. Virtual Diagnostics Interface (VIDI) technology developed at NASA Langley was used to superimpose and visualize the data sets. The measurements demonstrate some of the capabilities of the PLIF method while providing a test case for computational fluid dynamics (CFD) validation.

Danehy, P. M.↗
NASA NTRS2006

Planar laser-induced fluorescence (PLIF) investigation of hypersonic flowfields in a Mach 10 wind tunnel

Planar laser-induced fluorescence (PLIF) of nitric oxide (NO) was used to visualize four different hypersonic flowfields in the NASA Langley Research Center 31-Inch Mach 10 Air wind tunnel. The four configurations were: (1) the wake flowfield of a fuselage-only X-33 lifting body, (2) flow over a flat plate containing a rectangular cavity, (3) flow over a 70deg blunted cone with a cylindrical afterbody, formerly studied by an AGARD working group, and (4) an Apollo-geometry entry capsule - relevant to the Crew Exploration Vehicle currently being developed by NASA. In all cases, NO was seeded into the flowfield through tubes inside or attached to the model sting and strut. PLIF was used to visualize the NO in the flowfield. In some cases pure NO was seeded into the flow while in other cases a 5% NO, 95% N2 mix was injected. Several parameters were varied including seeding method and location, seeding mass flow rate, model angle of attack and tunnel stagnation pressure, which varies the unit Reynolds number. The location of the laser sheet was as also varied to provide three dimensional flow information. Virtual Diagnostics Interface (ViDI) technology developed at NASA Langley was used to visualize the data sets in post processing. The measurements demonstrate some of the capabilities of the PLIF method for studying hypersonic flows.

Danehy, Paul M.↗