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Revolutionizing Investigation of Unsteady Flow with Pressure-Sensitive Paint

NASA and its Stakeholders are developing increasingly advanced aerospace vehicles. Performing a ground test is a standard method to quantify the loads a vehicle will experience during flight. In order to efficiently design these new advanced aerospace vehicles, more advanced tools are required. A new state-of-the-art technique to measure unsteady aerodynamics is currently being developed using pressure-sensitive paint (PSP), high-speed cameras, and advanced image processing methods. This new technique is capable of acquiring fluctuating pressures up to 20 kHz with continuous spatial resolution which enables direct calculation of unsteady loads. To successfully develop a new capability, a systems perspective must be taken. Recently, a connection was established between the Unitary Plan Wind Tunnel and the NASA Advanced Supercomputer, both located at NASA Ames Research Center. The rapid transfer, processing, and display of high-speed PSP data from the wind tunnel demonstrated the ability to make real-time decisions in order to decrease design cycle time.

PSP

Visualizing UPSP Data with Python

The Unsteady Pressure-Sensitive Paint (uPSP) projects uses Pressure-Sensitive paint applied over aerospace models during wind tunnel testing to collect pressure data with high spatial and temporal resolution in order to inform unsteady aerodynamics studies. For each of the 800+ experimental runs, four cameras generate up to 50 GB of video data, which must then be processed, analyzed, and visualized on the NASA Advanced Supercomputing system (NAS) to assess the result. One of the final data analysis products is the dynamic modal decomposition (DMD) results, which decomposes the pressure reading signals by their frequency component. The goal of this project is to visualize the DMD results over a 3D rendering of the model, using efficient and parallelized python routines. The software uses the pytecplot library, a high-level API that connects python scripting to a Tecplot 360 engine. Tecplot is an industry standard high-performance visualization tool that can handle large datasets and workflow. Various animation, rendering, and image-combination techniques were investigated to generate the final videos using OpenCV on the NAS. The final result is a software tool that takes in data products from the uPSP processing chain and generates high resolution visualization videos in parallel for every data file, allowing researchers to view their results efficiently and at an unprecedentedly detailed level.

Emma Dolores McMillian

Launch Vehicle Loads Analysis Using Pressure-Sensitive Paint

Pressure transducers have been the instrumentation of choice for measuring unsteady flow phenomena. With recent advances in high-speed cameras, high-powered LEDs, and fast-response, pressure-sensitive paint, the unsteady pressure-sensitive paint (uPSP) technique has become a valuable alternative for production wind tunnel facilities, enabling time-resolved measurements of unsteady pressure fluctuations over a dense spatial grid on a wind tunnel model. Launch vehicle ground tests have proven to be a particularly well-matched application for uPSP due to the high signal level relative to tunnel background acoustics, relatively simple camera optical access, and rigidity of the model in wind-on test conditions. This presentation will highlight recent advances in data reduction of uPSP measurement data from recent launch vehicle wind tunnel tests at the NASA Ames Unitary Plan Wind Tunnel Complex (UPWT). The system can provide both localized surface pressure spectra as well as regional or zonal estimates of turbulence correlation model parameters. In addition, integrated vehicle-scale loads can be provided for buffet analysis. Data is reduced at the on-premise NASA Advanced Supercomputer (NAS) Division for just-in-time delivery of results during an ongoing wind tunnel test.

Pressure-Sensitive Paint

Implementation of an Unsteady PSP System in the NASA Transonic Dynamics Tunnel

An unsteady pressure-sensitive paint (uPSP) system has been developed to provide time-resolved pressure measurements in the NASA Langley Transonic Dynamics Tunnel (TDT). Obtaining these measurements necessitated the development of environmental enclosures to protect the high-speed camera and ultraviolet lights required for uPSP from the harsh environment present during tunnel operation. Since the facility main drive was non-functioning during the testing window, performance of the uPSP system was demonstrated using an impinging jet with a passive oscillator attachment to provide unsteady flow with a known frequency independent of amplitude. Measurements were obtained for tunnel pressures ranging from 565 to 2116 psf, and model angles of attack between -4 degrees and 4 degrees. Results indicate that the system is capable of measuring surface pressure differentials on the order of 0.01 psi at full scale with a camera frame rate of at least 10 kHz. Spectral analysis shows that the fundamental frequency of the oscillating jet is captured by the uPSP system, as are the second and third harmonics. Dynamic mode decomposition highlights the dominant coherent spatial structures of the surface pressure, along with the associated frequency and growth rate of each mode, allowing for a de-noised reconstruction of the uPSP measurements. The experimental campaign outlined within this report also confirmed compatibility of the uPSP system with the TDT facility data acquisition system, and verified the successful integration with existing processing capabilities within the NASA advanced supercomputing environment.

unsteady pressure-sensitive paint

Implementation of an Unsteady PSP System in the NASA Transonic Dynamics Tunnel

An unsteady pressure-sensitive paint (uPSP) system has been developed to provide time-resolved pressure measurements in the NASA Langley Transonic Dynamics Tunnel (TDT). Obtaining these measurements necessitated the development of environmental enclosures to protect the high-speed camera and ultraviolet lights required for uPSP from the harsh environment present during tunnel operation. Since the facility main drive was non-functioning during the testing window, performance of the uPSP system was demonstrated using an impinging jet with a passive oscillator attachment to provide unsteady flow with a known frequency independent of amplitude. Measurements were obtained for tunnel pressures ranging from 565 to 2116 psf, and model angles of attack between -4 degrees and 4 degrees. Results indicate that the system is capable of measuring surface pressure differentials on the order of 0.01 psi at full scale with a camera frame rate of at least 10 kHz. Spectral analysis shows that the fundamental frequency of the oscillating jet is captured by the uPSP system, as are the second and third harmonics. Dynamic mode decomposition highlights the dominant coherent spatial structures of the surface pressure, along with the associated frequency and growth rate of each mode, allowing for a de-noised reconstruction of the uPSP measurements. The experimental campaign outlined within this report also confirmed compatibility of the uPSP system with the TDT facility data acquisition system, and verified the successful integration with existing processing capabilities within the NASA advanced supercomputing environment.

unsteady pressure-sensitive paint

Implementation of an Unsteady PSP System in the NASA TDT

An unsteady pressure-sensitive paint (uPSP) system has been developed to provide time-resolved pressure measurements in the NASA Langley Transonic Dynamics Tunnel (TDT). Obtaining these measurements necessitated the development of environmental enclosures to protect the high-speed camera and ultraviolet lights required for uPSP from the harsh environment present during tunnel operation. Since the facility main drive was non-functioning during the testing window, performance of the uPSP system was demonstrated using an impinging jet with a passive oscillator attachment to provide unsteady flow with a known frequency independent of amplitude. Measurements were obtained for tunnel pressures ranging from 565 to 2116 psf, and model angles of attack between -4 degrees and 4 degrees. Results indicate that the system is capable of measuring surface pressure differentials on the order of 0.01 psi at full scale with a camera frame rate of at least 10 kHz. Spectral analysis shows that the fundamental frequency of the oscillating jet is captured by the uPSP system, as are the second and third harmonics. Dynamic mode decomposition highlights the dominant coherent spatial structures of the surface pressure, along with the associated frequency and growth rate of each mode, allowing for a de-noised reconstruction of the uPSP measurements. The experimental campaign outlined within this report also confirmed compatibility of the uPSP system with the TDT facility data acquisition system, and verified the successful integration with existing processing capabilities within the NASA advanced supercomputing environment. Note: this presentation is an MP4 video with sound, color with a run time of 10 minutes 37 seconds.

unsteady pressure-sensitive paint

2022 Spring Internship Exit Presentation

As efforts of the National Aeronautics and Space Administration (NASA) and the Federal Aviation Administration (FAA) continue to digitize the air traffic management (ATM) domain, there is countless times of need for downstream natural language processing (NLP) tasks such as named entity recognition, text summarization, classification, and more. Although there are a plethora of open-sourced pre-trained transformer models in the NLP field such as BERT, RoBERTa, XLNet, and GPT-3, these models are trained on general corpora and perform poorly on domain-specific terminology and phraseology seen in ATM documents such as Notice to Airmen (NOTAMs) and Letters of Agreement (LoA). Our proposed research objective will be to first gather a large corpus of air traffic management related documents, orders, notices, books, technical papers, conference papers, articles, and other miscellaneous sources of text data from the FAA, NASA, and accredited conference and publication societies. After gathering this data, many steps will have to be taken to collate and preprocess the data into a format understandable by our test transformer models. Thirdly, we will set up training pipelines to train the RoBERTa model on its unsupervised training task masked language modelling (MLM) using resources provided by the NASA Advanced Supercomputing (NAS) facilities. Finally, these fine-tuned transformer models will be evaluated on their performance on down-stream NLP tasks as mentioned above, to show whether they will be effective when working with ATM related data or not. Once complete, this model could be made open-sourced on the HuggingFace website, where the rest of the ATM community can access and utilize this tool.

NLP

Launch Vehicle Loads Analysis Using Pressure-Sensitive Paint

Pressure transducers have been the instrumentation of choice for measuring unsteady flow phenomena. With recent advances in high-speed cameras, high-powered LEDs, and fast-response, pressure-sensitive paint, the unsteady pressure-sensitive paint (uPSP) technique has become a valuable alternative for production wind tunnel facilities, enabling time-resolved measurements of unsteady pressure fluctuations over a dense spatial grid on a wind tunnel model. Launch vehicle ground tests have proven to be a particularly well-matched application for uPSP due to the high signal level relative to tunnel background acoustics, relatively simple camera optical access, and rigidity of the model in wind-on test conditions. This presentation will highlight recent advances in data reduction of uPSP measurement data from recent launch vehicle wind tunnel tests at the NASA Ames Unitary Plan Wind Tunnel Complex (UPWT). The system can provide both localized surface pressure spectra as well as regional or zonal estimates of turbulence correlation model parameters. In addition, integrated vehicle-scale loads can be provided for buffet analysis. Data is reduced at the on-premise NASA Advanced Supercomputer (NAS) Division for just-in-time delivery of results during an ongoing wind tunnel test.

pressure-sensitive paint

NASA’s Unsteady Pressure-Sensitive Paint Phase I Development Overview

Since 2019, a group out of NASA Ames Research Center(ARC)has been focused on implementing systematic updates to make unsteady pressure-sensitive paint (uPSP) a more viable capability for production wind tunnel testing. Focusing on the general categories of data acquisition, data transfer, data processing, and data visualization, the uPSP Development Team has made several improvements to increase data quality and innovate a more workable system that would provide valuable surface pressure data to customers. As a result of the COVID-19 pandemic and several initial demonstration tests prior to the formal start of the development effort, the decision was made to focus on launch vehicles as the test article. To-date this development has focused on implementation in the ARC Unitary Plan Wind Tunnel 11-by11-footTransonic Wind Tunnel due to the large optical access of the test section and that the NASA Advanced Supercomputer is located at ARC. This paper summarizes the project origins and the results of four years of development effort, which will all culminate in a final demonstration test in the first half of2024.

unsteady pressure-sensitive paint

Invited: uPSP Launch Vehicle Demonstration Test at NASA Ames Research Center

The Unsteady Pressure-Sensitive Paint (uPSP) Development Team outof NASA Ames Research Center (ARC) has spent the past five yearsimproving the systems and processes to advance the uPSP technology for production-level wind tunnel testing. Already considered turnkey for small-scale and research applications, development in acquisition, calibration, data transfer, and data processing were needed to be useful to customers testing at NASA wind tunnels. This development focused at ARC at the Unitary Plan Wind Tunnel (UPWT) 11-by 11-ft Transonic Wind Tunnel due to the large optical access of the test section and the NASA Advanced Supercomputer(NAS), also located at ARC. A Launch Vehicle Demonstration Test (LVDT) at the UPWT represents a milestone of this initial phase of development where several new improvements were demonstrated in a production wind tunnel environment for the first time. LVDT was conducted in April 2024 and used a 4% forebody Space Launch System (SLS) Block 1B model as the test article. Both a crew and cargo configuration were tested, with varying Mach numbers, pressures, model positions, and camera magnifications. This paper summarizes the details of the test and is part of a collection with four additional papers that provide greater detail on: high-speed lifetime methodology, spectral proper orthogonal decomposition analysis, quality of high-resolution data compared to Corcos model, and data quality, calibration, and uncertainty.

SLS

Investigation of Lunar-Inspired Geopolymer Concrete Formulations Mixed and Cured in Microgravity on the International Space Station (ISS)

The research outlined in this presentation investigates the use of various lunar regolith simulants in geopolymer lunar concrete mixes mixed and cured on the International Space Station (ISS). The motivation for this work is to study the effects of gravity on the microstructure of alkali-activated materials cured with heat, and to develop materials for the construction of long-term infrastructure on the lunar surface with in-situ resource utilization (ISRU). ISRU for construction materials reduces the cost and mass of payloads related to lunar construction. The advantage of geopolymer concrete as opposed to traditional portland cement concrete is that water acts as a medium for the polymerization reaction and leaves the system throughout the process, reducing its demand. Twelve samples of lunar regolith simulant and a solution composed of sodium hydroxide and sodium silicate were sent to the ISS. The three simulants were OPRH2N, OPRL2N, and JSC-1AF, using only particles less than 53 µm in diameter to increase reactivity of the simulant. Simulant to solution ratios were determined by workability while mixing. The simulant and solution were sealed Burst Pouches® along with 2 other sealed bags to prevent material from leaking. Crew member F-14 conducted testing on the ISS by introducing the solution to the simulant in the Burst Pouch®, mixing the sample with a spatula, and then clamping the specimen in the fresh state to prevent flow inside the Burst Pouch®. These specimens were then put in a thermos heated to 80C via sealed drinking water bags to cure for 24 hours with a temperature logger. The cured specimens remained in microgravity for at least 28 days and were returned from the ISS in February 2025. The specimens were then brought to the NASA Marshall Space Flight Center (MSFC) to analyze. Material characterization consisted of conducting Micro-CT tests of entire samples in their sealed apparatus to a resolution of 25µm. 2D image slices were saved in each orthogonal direction of each specimen at a 0.03 mm step size from the 3D model to conduct analytical porosity calculations. Representative samples from each specimen were sampled to perform helium gas pycnometery and were then mounted in resin for SEM imaging, EDS, and nanoindentation. Porosity was analyzed analytically using micromechanics modelling with the assistance of the NASA Multiscale Analysis Tool (NASMAT), as well as the NASA Advanced Supercomputing (NAS) servers (V. Saseendran & N. Yamamoto, 2024). Density was measured using helium gas pycnometery and was then compared to the theoretical density for experimental porosity calculation. Due to the samples’ non-uniform shape being cured in a pouch, traditional compression and tensile strength testing could not be performed. Nanoindentation was conducted at Clarkson University to determine the microhardness and reduced modulus of elasticity. Results from flight samples can be compared to ground samples currently in DLR’s possession to determine the effect on microstructure from being mixed and cured in microgravity. This study gives further insight and understanding of geopolymer lunar concrete and its viability as a lunar construction material with ISRU.

Adam Johnson

Advancing Quantum Many-Body GW Calculations on Exascale Supercomputing Platforms

Advanced ab initio materials simulations face growing challenges as increasing systems and phenomena complexity requires higher accuracy, driving up computational demands. Quantum many-body GW methods are state-of-the-art for treating electronic excited states and couplings but often hindered due to the costly numerical complexity. Here, we present innovative implementations of advanced GW methods within the BerkeleyGW package, enabling large-scale simulations on Frontier and Aurora exascale platforms. Our approach demonstrates exceptional versatility for complex heterogeneous systems with up to 17,574 atoms, along with achieving true performance portability across GPU architectures. We demonstrate excellent strong and weak scaling to thousands of nodes, reaching double-precision core-kernel performance of 1.069 ExaFLOP/s on Frontier (9,408 nodes) and 707.52 PetaFLOP/s on Aurora (9,600 nodes), corresponding to 59.45% and 48.79% of peak, respectively. Our work demonstrates a breakthrough in utilizing exascale computing for quantum materials simulations, delivering unprecedented predictive capabilities for rational designs of future quantum technologies.

Zhang, Benran [University of Southern California,

Status and projections of the NAS program

NASA's Numerical Aerodynamic Simulation (NAS) Program has completed development of the initial operating configuration of the NAS Processing System Network (NPSN). This is the first milestone in the continuing and pathfinding effort to provide state-of-the-art supercomputing for aeronautics research and development. The NPSN, available to a nation-wide community of remote users, provides a uniform UNIX environment over a network of host computers ranging from the Cray-2 supercomputer to advanced scientific workstations. This system, coupled with a vendor-independent base of common user interface and network software, presents a new paradigm for supercomputing environments. Background leading to the NAS program, its programmatic goals and strategies, technical goals and objectives, and the development activities leading to the current NPSN configuration are presented. Program status, near-term plans, and plans for the next major milestone, the extended operating configuration, are also discussed.

Bailey, Frank R.

Status and projections of the NAS Program

NASA's Numerical Aerodynamic Simulation (NAS) Program has completed development of the initial operating configuration of the NAS Processing System Network (NPSN). This is the first milestone in the continuing and pathfinding effort to provide state-of-the-art supercomputing for aeronautics research and development. The NPSN, available to a nation-wide community of remote users, provides a uniform UNIX environment over a network of host computers ranging from the new Cray-2 supercomputer to advanced scientific workstations. This system, coupled with a vendor-independent base of common user interface and network software, presents a new paradigm for supercomputing environments. Presented here is the background leading to the NAS Program, its programmatic goals and strategies, technical goals and objectives, and the development activities leading to the current NPSN configuration. Program status, near-term plans and plans for the next major milestone, the extended operating configuration, are also discussed.

Bailey, F. R.

Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit

Turbulence plays a crucial role in multiphysics applications, including aerodynamics, fusion, and combustion. Accurately capturing turbulence's multiscale characteristics is essential for reliable predictions of multiphysics interactions, but remains a grand challenge even for exascale supercomputers and advanced deep learning models. The extreme-resolution data required to represent turbulence, ranging from billions to trillions of grid points, pose prohibitive computational costs for models based on architectures like vision transformers. To address this challenge, we introduce a multiscale hierarchical Turbulence Transformer that reduces sequence length from billions to a few millions and a novel RingX sequence parallelism approach that enables scalable long-context learning. We perform scaling and science runs on the Frontier supercomputer. Our approach demonstrates excellent performance up to 1.1 EFLOPS on 32,768 AMD GPUs, with a scaling efficiency of 94\%. To our knowledge, this is the first AI model for turbulence that can capture small-scale eddies down to the dissipative range in three-dimensional turbulence at high Reynolds numbers.

Yin, Junqi [ORNL] (ORCID:0000000338435520)

Brochure on the 2024 ASCR Workshop on Energy-Efficient Computing for Science

Large-scale computing has enabled numerous scientific discoveries, including ground-breaking achievements facilitated by the US Department of Energy (DOE) supercomputers and advances in applied mathematics and computer science. While important advances were made in energy efficiency to enable exascale computing, continued efforts are needed to dramatically improve the energy efficiency of the next generation of high-performance computing (HPC) systems and, more broadly, AI data centers. Without substantial improvements in energy efficiency, the energy consumption associated with computing could become a limiting factor for future scientific discovery, national security, and technological advancement.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Volumetric visualization of 3D data

In recent years, there has been a rapid growth in the ability to obtain detailed data on large complex structures in three dimensions. This development occurred first in the medical field, with CAT (computer aided tomography) scans and now magnetic resonance imaging, and in seismological exploration. With the advances in supercomputing and computational fluid dynamics, and in experimental techniques in fluid dynamics, there is now the ability to produce similar large data fields representing 3D structures and phenomena in these disciplines. These developments have produced a situation in which currently there is access to data which is too complex to be understood using the tools available for data reduction and presentation. Researchers in these areas are becoming limited by their ability to visualize and comprehend the 3D systems they are measuring and simulating.

Russell, Gregory

Supercomputer optimizations for stochastic optimal control applications

Supercomputer optimizations for a computational method of solving stochastic, multibody, dynamic programming problems are presented. The computational method is valid for a general class of optimal control problems that are nonlinear, multibody dynamical systems, perturbed by general Markov noise in continuous time, i.e., nonsmooth Gaussian as well as jump Poisson random white noise. Optimization techniques for vector multiprocessors or vectorizing supercomputers include advanced data structures, loop restructuring, loop collapsing, blocking, and compiler directives. These advanced computing techniques and superconducting hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations, by permitting the solution of large multibody problems. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random aerospace fluctuations.

Chung, Siu-Leung