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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Hybrid Approaches to Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Systems Health Management↗
NASA NTRSDate not supplied

Volumetric Assessment of UPRITE Exercises From Marker-Based Motion Capture

BACKGROUND Lack of volumetric data on full-body movement of exercises presents a challenge to ensuring the fit of crew member’s full range of motion on the International Space Station (ISS). The Upright Proprioception Retention via In-flight Training and Evaluation (UPRITE) is a sensorimotor countermeasure device designed for maintaining crew members’ proprioception in a microgravity environment. A footplate—attached to a static base—rotates in two degrees of freedom (pitch and roll) up to a 20 deg angle. An initial volumetric assessment assuming an upright standing posture produced a cone-like shape with a narrow bottom and wide top. Such general volumetric assessments risk creating an overly conservative volume estimate, taking up more space than is necessary on the already limited interior space of the ISS, and neglecting necessary volume due to oversimplifying assumptions. Rather, higher-fidelity volumetric assessments offer more comprehensive insights in an environment where every area counts. The main objective of this work is to provide the spatial parameters of exercises on the UPRITE such that it is placed on the ISS according to its volumetric demands or that usage is adjusted to fit the available space. METHODS In 2023, a data collection was performed originally to inform loads and dynamics of system use and was recently leveraged for volumetric assessment. Three human subjects representing different body types (~63-76 inches in stature) performed a variety of board manipulations using UPRITE with body weight offload. The test collected the 3D positional data of a modified full-body Plug-in Gait marker set [1] via a 16-camera OptiTrack MoCap system. After processing – filling marker gaps and trimming data – in OptiTrack Motive, the recorded marker location data, which included device markers, was exported to a readable trajectory file. To accurately represent the full volume defining landmarks, additional markers were digitally added to an unscaled Modified Full Body Model [2]. The model was then scaled according to its subject parameters upon which an inverse kinematics analysis was performed. A custom plugin yielded model marker location data files. Volumetric analyses were performed on the recorded trajectory and model trajectory files using a custom Python-built tool that extracted the marker location data and plotted it in a 3D space. Concerned with only the maximum volume of the motion, a 3D convex hull analysis was applied to the plot, extracting the vertices or external points of the eventual 3D CAD output, dubbed aptly as a “volume shell”. This overall approach was based on guidance in a NASA-STD-3001 Technical Brief [3]. RESULTS AND DISCUSSION Batch volumetric assessment on the exercises for each subject was performed, producing high-fidelity volume shells in minimal time. Preliminary results highlighted the value in higher-fidelity volumes based on collected data when possible. For example, revolving a single posture in the cone assessment would not have sufficiently captured a single leg stance; rather, it would need to involve swinging the leg both forward and back. Additional observations and the maximal dimensions of the volumes, including those based on scaled data for ISS anthropometric requirements, will be presented at the Human Research Program Investigator’s Workshop. CONCLUSIONS While this work’s primary objective was for the UPRITE-to-ISS integration, the tool built to conduct this analysis has wide applications for future exercise systems as an informational tool for optimal device placement. The tool and its findings also have implications for exercise device design and spacecraft interior considerations on Gateway, the Lunar Pressurized Rover, and beyond. REFERENCES [1] Bell, C. A., et al. (2023) Recent Improvements and Verification of a Full Body Model in OpenSim. NASA Human Research Program Investigator’s Workshop. https://ntrs.nasa.gov/citations/20230001080 [2] Lostroscio, K., et al (2023) The Digital Astronaut Simulation. AHFE International Conference on Human Factors in Design, Engineering, and Computing for All. [3] Exercise Overview. (2023) NASA-STD-3001 Technical Brief. https://www.nasa.gov/wp-content/uploads/2023/12/ochmo-tb-031-exercise-overview.pdf?emrc=9d454c?emrc=9d454c

L D Quinto↗
DOE OSTI2022

Woven ceramic matrix composite surrogate model based on physics-informed recurrent neural network

A recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear constitutive behavior of woven ceramic matrix composites (CMCs) driven by matrix damage at multiple length scales. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the multiscale generalized method of cells (MSGMC) approach coupled with a matrix damage model. This coupling permits simulating the nonlinear behavior of woven CMCs based on constituent response at the micro-, meso-, and macroscales. The multiscale repeating unit cell is loaded under non-monotonic conditions including multiple load / unload cycles and tension / compression. The fiber volume fraction as well as the intra- and intertow void volume fractions are also varied in the generation of training data. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input strain sequence and fiber and void volume fractions, the resulting stress versus strain response while satisfying physical constraints such as positive semi-definiteness of the tangent stiffness matrix and linear elastic unloading. Further, the trained surrogate model effectively matches the stress versus strain response and successfully predicts the tangent modulus throughout the loading regime. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex architectures, nonlinear multiaxial material response, and under non-monotonic loading conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

A Scalable Multi-Modal Framework for High-Fidelity Distributed Human Mobility Simulations

The development of data-driven models for human mobility in urban settings requires access to substantial and diverse real-world data. However, existing historical data often presents challenges such as limited volume, variety, and veracity, as well as missing data and privacy preservation concerns. Also, urban mobility modeling is inherently time-variant, complex, and multi-modal, encompassing everything from individual walking and running to private road travel and large-scale public transportation. These challenges call for innovative solutions to overcome data limitations and compute needs to model mobility behaviors accurately. To address these challenges, we propose a distributed, co-simulation-based architecture DURMOSim that integrates real-world data with scalable, high-fidelity simulations, demonstrating distributed co-simulation feasibility with existing mobility models. DURMOSim underpins a modular integration that would enable using any available mobility simulators for greater extensibility and scalability in performing various urban scenarios. In this paper, we present the design, implementation, and performance evaluation of DURMOSim, highlighting its capability to model population-scale mobility patterns. Our initial results show its ability to dynamically synchronize multiple simulation models at runtime with negligible computational overhead. We believe DURMOSim could be a robust tool for advancing urban mobility research and intelligent transportation systems.

Yoginath, Srikanth [ORNL] (ORCID:0000000184236050)↗
NASA NTRS2016

Ground-Level Digital Terrain Model (DTM) Construction from Tandem-X InSAR Data and Worldview Stereo-Photogrammetric Images

The ground-level digital elevation model (DEM) or digital terrain model (DTM) information are invaluable for environmental modeling, such as water dynamics in forests, canopy height, forest biomass, carbon estimation, etc. We propose to extract the DTM over forested areas from the combination of interferometric complex coherence from single-pass TanDEM-X (TDX) data at HH polarization and Digital Surface Model (DSM) derived from high-resolution WorldView (WV) image pair by means of random volume over ground (RVoG) model. The RVoG model is a widely and successfully used model for polarimetric SAR interferometry (Pol-InSAR) technique for vertical forest structure parameter retrieval [1][2][3][4]. The ground-level DEM have been obtained by complex volume decorrelation in the RVoG model with the DSM using stereo-photogrammetric technique. Finally, the airborne lidar data were used to validate the ground-level DEM and forest canopy height results.

Lee, Seung-Kuk↗
DOE OSTI2023

Assessment of Mechanical Draft Cooling Tower Thermal Emissions from Visual Images of Plumes

Using a one-dimensional code, we computed the power (enthalpy discharge rate) of a twelve-cell mechanical draft cooling tower (MDCT) using over two hundred visible condensed water vapor plume volume measurements derived from images, weather data, and tower operating conditions. The plume images were simultaneously captured by multiple stationary digital cameras surrounding the cooling tower. An analysis technique combining structure from motion (SfM), a neural-network-based image segmentation algorithm, and space carving was used to quantify the volumes. Afterwards, the power output was computed using novel techniques in the one-dimensional code that included cooling tower exhaust plume adjacency effects implemented with a modified version of the entrainment function, weather data averaged from eleven stations, and fan operations at the times when plume volumes were measured. The model was then compared with the averaged observed power output, and it validated well with an average error ranging from 6 to 12%, depending on the meteorological data used in the simulations. This methodology can possibly determine power plant fuel consumption rates by applying visible imagery.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1989

Test of a geometric model for the modification stage of simple impact crater development

This paper presents a geometric model describing the geometry of the transient cavity of an impact crater and the subsequent collapse of its walls to form a crater filled by an interior breccia lens. The model is tested by comparing the volume of slump material calculated from known dimensional parameters with the volume of the breccia lens estimated on the basis of observational data. Results obtained from the model were found to be consistent with observational data, particularly in view of the highly sensitive nature of the model to input parameters.

Grieve, R. A. F.↗
NASA NTRSDate not supplied

Additional Metadata Guidelines to Improve the Structure and Usability of HDF and NetCDF Files

The Hierarchical Data Format (HDF) and Network Common Data Form (NetCDF) are data file formats created to aid users in the creation or use of scientific data. These file formats are useful for handling large data volumes and hosting extensive metadata as global attributes or variables and are popular with the modeling community. HDF and NetCDF files are largely used with remote sensing data and have been used to support measurements from numerous campaigns, from satellite to aircraft or ground and mobile based measurements. The files from airborne field studies, however, vary greatly in terms of the file structure and the amount and content of metadata. Information relevant to the file that can be useful to the user such as the data producer, location where data was taken, variable descriptions, or information about the instrument might not be included in the file. This metadata might be present in another file in the dataset containing the same data using the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) format. Recently, the Aerosols, Clouds, and their Interactions for Earth System Models (MACIE) group started a grassroots effort to develop a set of requirements for the HDF and NetCDF files for field studies, aiming to make the data products more interoperable and usable. Particularly, these requirements seek to make the files more compliant to Climate and Forecast (CF) metadata conventions and to standardize the file structure and the global and variable attributes. These requirements would help to ensure that HDF and NetCDF files contain adequate metadata to better support their use for research, e.g., the modeling community, and to enhance the usability and interoperability of data for research communities at large. To be presented are the details of the MACIE requirements as well as examples of the implementation of these requirements for merge files and lidar observation data files.

Sean Leavor↗
DOE OSTI2026

Near-Real-Time Material Tracking: Combining Vis–NIR Spectroscopy with Flow Sensing for Accurate Nd(III) Quantification

A fiber-optic visible–near-infrared (vis–NIR) absorption spectroscopy and flow sensor system has been developed for near-real-time tracking of Nd mass in the effluent stream from a column in a fume hood. The approach leverages two unique data streams and a partial least-squares regression (PLSR) model trained on vis–NIR absorption spectra of Nd(III) (0–1.5 M) in 1 M HNO 3 . In-line volumetric flow rate and vis–NIR spectra are measured in sequence after a chromatography column. The time stamps from each data stream are then synchronized, which allows integrated volumes to be combined with Nd(III) molarities predicted by a PLSR model to accurately calculate the Nd mass flowing through the column. This integrated measurement provides instantaneous mass flow and accumulates these data over time to obtain the total mass processed. The methodology developed in this study contributes critical technical infrastructure to improve monitoring capabilities to support chemical separations and the production of strategic materials and isotopes.

Irvine, Sawyer B. [Oak Ridge National Laboratory (↗
NASA NTRSDate not supplied

Artemis 1 Radiation Modeling and Analysis Using Operational Methods

The successful completion of the Artemis 1 mission has provided NASA with a significant volume of space radiation dosimetry data that can be used to verify the accuracy of current operational SRAG dose computation models and methods for Beyond LEO missions. High-Fidelity CAD models of the Artemis 1 MPCV Orion were raytraced in 10,000 directions per sensor location, including the location of Artemis HERA sensors, Artemis RAMs (TLDs), and the crew active dosimetry (CADs). The full Artemis 1 mission was modelled using the as-flown trajectory, Ap9-Ae9 IRENE providing the VAB trapped proton and electron environment, and the Badhwar-O’Neill 2020 model providing the freespace GCR environment. IGRF 12 was used to compute cutoff rigidities for the GCR environment in LEO. 1DHZETRN was used to estimate point doses at each sensor position. Computed RAM doses were within 5% of measured values. The computed VAB transit and freespace GCR dose rates showed good qualitative agreement with measured HERA values. An estimate of normalized mean effective dose for a hypothetical male crew member on Artemis 1 using current standard operational methods was computed to be 22.3 mSv.

Artemis 1↗
NASA NTRS1974

Effects of air breathing engine plumes on SSV orbiter subsonic wing pressure distribution (OA57B), volume 1

Data were obtained during wind tunnel tests of a 0.0405-scale model of the ferry configuration of the space shuttle vehicle orbiter conducted in a low speed wind tunnel during the time period of September 18 to September 23, 1973. The primary test objective was to investigate orbiter wing pressure distributions resulting from nacelle plumes above and below the wing. Three six-engine nacelle configurations were tested. One configuration had a twin-podded nacelle mounted above each wing and the others had one mounted below each wing. Both had a centerline twin-podded nacelle mounted below the wing. Wing pressure distribution was determined by locating static pressure bugs on the upper and lower surfaces of the left wing. Pressure bugs were also located on the upper and lower surfaces of the body flap and on the B12 afterbody fairing when it was installed. Base and balance cavity pressures were recorded and a strain gage instrumented beam in the right wing measured elevon hinge moments and normal forces.

Soard, T.↗
NASA NTRS2000

Climatology of the Finite-Volume CCM and Sensitivity Studies

A new model has been developed in the Data Assimilation Office at NASA Goddard Space Flight Center. It is intended for data assimilation and general circulation modeling, including representations of radiatively active trace gases such as stratospheric ozone. The model is based on the flux-form semi-Lagrangian' dynamical core, developed by Lin and Rood. In collaboration with the National Center for Atmospheric Research, the physical parametrization package from the Community Climate model, Version 3, has been included. This paper will discuss the climatology of a multi-year integration of the model, with observed boundary conditions (sea-surface temperature, sea ice, and incoming solar radiation). The standard model version has a resolution of 2.5 degrees longitude, 2 degrees latitude and has 55 levels between the surface and 80km. The mean climate and interannual variability of this model will be discussed, with emphasis on the middle atmosphere. The sensitivity to horizontal resolution will be examined, as will the impact of increasing and decreasing the vertical resolution. Changes which differ significantly from the interannual variations of the control run will be highlighted. Impacts of using long-term mean boundary conditions or values which vary from year to year will be discussed. Changes in the tropospheric circulation induced by lowering the upper boundary of the model will be discussed. The emphasis of the paper is on the climatology of the middle atmosphere and its impacts on the troposphere, with particular attention given to the climatologically important region near the tropopause.

Pawson, Steven↗
NASA NTRS2017

MPCV Exercise Operational Volume Analysis

In order to minimize the loss of bone and muscle mass during spaceflight, the Multi-purpose Crew Vehicle (MPCV) will include an exercise device and enough free space within the cabin for astronauts to use the device effectively. The NASA Digital Astronaut Project (DAP) has been tasked with using computational modeling to aid in determining whether or not the available operational volume is sufficient for in-flight exercise.Motion capture data was acquired using a 12-camera Smart DX system (BTS Bioengineering, Brooklyn, NY), while exercisers performed 9 resistive exercises without volume restrictions in a 1g environment. Data were collected from two male subjects, one being in the 99th percentile of height and the other in the 50th percentile of height, using between 25 and 60 motion capture markers. Motion capture data was also recorded as a third subject, also near the 50th percentile in height, performed aerobic rowing during a parabolic flight. A motion capture system and algorithms developed previously and presented at last years HRP-IWS were utilized to collect and process the data from the parabolic flight [1]. These motions were applied to a scaled version of a biomechanical model within the biomechanical modeling software OpenSim [2], and the volume sweeps of the motions were visually assessed against an imported CAD model of the operational volume. Further numerical analysis was performed using Matlab (Mathworks, Natick, MA) and the OpenSim API. This analysis determined the location of every marker in space over the duration of the exercise motion, and the distance of each marker to the nearest surface of the volume. Containment of the exercise motions within the operational volume was determined on a per-exercise and per-subject basis. The orientation of the exerciser and the angle of the footplate were two important factors upon which containment was dependent. Regions where the exercise motion exceeds the bounds of the operational volume have been identified by determining which markers from the motion capture exceed the operational volume and by how much. A credibility assessment of this analysis was performed in accordance with NASA-STD-7009 prior to delivery to the MPCV program.

mathematical models↗
DOE OSTI2022

Technoeconomic Analysis of Infrastructure Buildout Scenarios

The success of CCUS deployment in the southeast will depend on the optimized pipeline network from CO 2 point sources to geologic sinks for CO 2 storage. An optimal pipeline framework will reduce both environmental impacts and pipeline building cost. However, finding an optimal pipeline/transport infrastructure design is a non-trivial task and requires simultaneous usage of large volumes of data, computational resources, and a state-of-the-art simulator. Such a transport infrastructure model must consider point sources for CO 2 capture and associated volumes, sinks for CO 2 storage, and transportation from source to sink via pipeline networks. These considerations must be addressed simultaneously and systemically in an optimization process, in which a defined objective function (i.e., capital, variable CO 2 capture, transport, and storage cost function) is required to be minimized with the consideration of practical constraints (e.g., CO 2 flow through pipelines is less than the maximum capacity). Although optimization has been widely used in subsurface resources production and CO 2 storage, its application in large scale CCUS infrastructure design is rarely reported in the literature. SimCCS, developed by Los Alamos National Laboratory, is an open-source CCUS pipeline infrastructure design toolset that facilitates the optimization of pipeline infrastructure networks.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Assessing Effects of Climate Change on Legacy Waste at the Enewetak Atoll

The Republic of the Marshall Islands (RMI) is in the central Pacific Ocean ~4,500 km west of Hawaii. The Enewetak Atoll, located in the northwest part of the RMI, was the site for 43 nuclear weapon tests between 1948 and 1958. Fallout and deposition from the tests contaminated the island surfaces, lagoon waters and sediment, and nearby ocean waters at the atoll. In the 1970s, a cleanup effort collected radioactive waste and placed it in the Cactus Crater on Runit Island (also called the Runit Dome). In December 2021, Congress directed the U.S. Department of Energy to study the impacts of climate change on the Runit Dome nuclear waste disposal site. Pacific Northwest National Laboratory (PNNL) assembled a multidisciplinary team of climate scientists, ocean modelers, environmental scientists, and health physicists to assess the likely effects of remaining radionuclides at the Enewetak Atoll. PNNL’s approach focused on effects of tropical cyclones that were postulated to mobilize and transport contaminated lagoon sediments and result in human and biota exposure. PNNL’s study estimated (1) the radionuclide source term, (2) the effects of climate change on severe storms, (3) mobilization and transport of radionuclides, and (4) radiation dose to humans and biota. Radionuclides in the lagoon and/or ocean waters of the Enewetak Atoll were characterized by the U.S. Atomic Energy Commission (AEC) in 1972, Woods Hole Oceanographic Institution in 2015, and Lawrence Livermore National Laboratory in 2018. The RMI Nationwide Radiological Study was conducted in the early 1990s for radionuclides remaining in island soils. The 1972 AEC survey remains the most comprehensive source of radionuclide data on lagoon sediments. Climate change modeling at a regional scale in the central Pacific Ocean is limited. PNNL climate scientists simulated severe historical storms postulated to occur both in a recent climate (2015) and in the future (2090) using the Advanced Research Weather Research and Forecasting (WRF-ARW) model, employing a pseudo-global-warming technique. A postulated complete, future failure of the Runit Dome was also considered. PNNL developed a high-resolution regional ocean hydrodynamics model covering the entire RMI extended economic zone using the Finite Volume Coastal Ocean Model (FVCOM). The FVCOM model was run using global reanalysis data for current climate and WRF-ARW simulation for the future climate. PNNL also developed a radionuclide fate and transport model using the FVCOM Integrated Compartment Model (FVCOM-ICM) to simulate the current and future mobilization and transport of radionuclides sorbed to lagoon sediments and the exchange of radionuclides between the water and sediment. FVCOM-ICM-predicted radionuclide concentrations were then used to estimate radiation dose to humans and biota at all islands of the Enewetak Atoll. Under current climate conditions, annual radiation exposures for the southern islands including Enewetak (Fred) and Medren (Elmer) were below the current U.S. standards. Radiation doses were somewhat elevated starting at Runit Island northward and westward to Enjebi Island (Janet). The islands in the northwest quadrant, particularly Bokoluo (Alice) and Bokombako (Belle), remain relatively contaminated. The islands in the southwestern quadrant have low contamination. The highest contribution to radiation doses comes from consumption of locally grown foods. Two radionuclides, 90Sr and 137Cs, contributed the greatest fraction for most terrestrial foods. In current climate conditions, the storms temporarily increased radionuclide concentrations in the lagoon waters, increasing the radiation dose slightly. In future conditions, doses are expected to be smaller, primarily because of the radioactive decay of the shorter-lived radioisotopes of 90Sr and 137Cs. This could make all islands in the far northwest of the atoll – except Bokombako (Belle) and perhaps Bokoluo (Alice) – suitable for residency. For the f

Prasad, Rajiv↗
NASA NTRS1984

A kinetic energy analysis of the meso beta-scale severe storm environment

Analyses are performed of the meso beta-scale (20-200 km wavelengths and several hours to one-day periods) severe storm kinetic energy balance on the fifth day of the AVE SESAME campaign of May 1979. A 24-hr interval covering the antecedent, active and post-convective outbreak activity over Oklahoma are considered. Use is made of the kinetic energy budget equation (KEBE) for a finite volume in an isobaric coordinate system. Rawindsonde data with 75 km resolution were treated. The KEBE model covered changes in kinetic energy due to the cross contour flows, horizontal and vertical components of flux divergence, and volumic mass changes on synoptic and subsynoptic scales. The greatest variability was concentrated above 400 mb height and over the most intense storm activity. Energy was generated at the highest rates in divergence and decreased the most in convection. The meso beta-scale lacked sufficient resolution for analyzing mesoscale activity.

Fuelberg, H. E.↗
NASA NTRS1999

Hot Gas Testing Results of Stagnant Volume Filling Through a Back-Filled RSRM Nozzle Joint

Silicone rubber is back-filled into RSW nozzle joints after assembly. A possible artifact of this process is the formation of small pathways through this filter leading to sensitive sealing materials within the joint. At motor ignition, hot gases fill the stagnant volumes within the joint through this path. A series of 14 test has been completed studying this scenario and providing anchoring data for thermal/flow models. Parameters such as gas path cross section, gas path length, gas path materials, fill volume size, and post path gas spreading prior to unpingement on seal material, have been investigated. Tests were accomplished using geometry similar to RSRM nozzle joint 4 with attached volumes replicating the free volume and flow friction in the actual hardware. The test hardware simulated 8 inches of the full-scale circumference. Testing has pointed to changes required in model boundary condition assumptions and gas dynamics corrections for gas paths of this size and geometry. Areas ,where this date has provided improvement in analysis models will be covered as well as model inadequacies that require separate specialized efforts. Questions remaining after this testing and a possible direction for future testing will be suggested.

Prince, Andrew S.↗