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At least 793 records · Page 44

Using XR for Improving Scientific Discovery With Numerical Weather Models

Earth science (ES) digital twins will help us understand the complex interactions and interrelationships that make up our Earth system and the impacts of earth science phenomena on it. Our work addresses two underdeveloped areas in current ES digital twin work: improving the understanding and interaction with ES model outputs by using Virtual and Mixed Reality (XR) tools and improving the non-intuitive mapping of continuous ES natural phenomena to gridded reference frames in current numerical models. Traditionally, scientists working on ES view and analyze the results of calculated or measured observables with static 1-dimensional (1D), 2D or 3D plots displayed on flat computer screens or paper. Using such limited mediums, it can be very difficult to identify, track and understand the evolution of key features due to poor viewing angles and the nature of flat computer screens. In addition, numerical models, such as the NASA Goddard Earth Observing System (GEOS) ES model, are almost exclusively formulated, visualized and analyzed in an Eulerian reference frame with fixed grid points in space and time. However, ES phenomena such as convective clouds, hurricanes and wildfire smoke plumes are visualized and analyzed in a Lagrangian reference frame: therefore it is often difficult and unnatural to understand these phenomena in relation to each other, visualized either in an Eulerian or Lagrangian context. In 3D visualizations, data generally takes one of three forms: gridded (e.g., voxelized) data, where space is divided into regions; point clouds, where data is represented as a set of points; and meshes, where objects are rendered as surfaces composed of small polygons (usually triangles). A gridded, Eulerian reference frame has been the default representation for the 2D visual analysis of atmospheric data in part because the numerical methods used to generate atmospheric model data in the first place use a gridded approach, with equations defining the relationships between the physical variables in each of a grid's cells across successive timesteps. In our work, we are particularly interested in data from GEOS. Another reason why gridded representations tend to be used for visualizing data from such models is because trajectories are difficult to interpret from representations on 2D surfaces, due to line-of-sight ambiguity. Instead of a fixed grid from GEOS, we embed a trajectory model to simulate particles' movement throughout a GEOS run. We then ingest these particle trajectories as animated point clouds with a NASA open source XR toolkit, the Mixed Reality Exploration Toolkit (MRET), and merge GEOS data with ES phenomena data onto one combined visualization that the user can intuitively interact with. Efficient rendering of arbitrarily large point clouds is an ongoing challenge being addressed by the computer science community, with the GPU-based optimizations and efficient GPU memory utilization a common theme of recent advances, especially for XR, where sustained high frame rate is mandatory to save the user from suffering due to simulation sickness. In this work, we describe and evaluate our progress in choosing and implementing appropriate methods for rendering arbitrarily large point clouds within MRET for XR. While tracking the XR headset enables the immersion of a user within a 3D scene of a data visualization, tracking of XR handheld controllers or user’s hands enables us to implement intuitive user interactions with the visualized datasets. Conventional tools require a user working with an ES visualization to conduct many interactions to commit their intended selections or manipulations with a visualized dataset; for example to specify a set of points in 3D space. Doing so in a 2D flat screen interface has traditionally required specifying a set of points in three distinct 2D coordinate systems (XY, XZ, and YZ), which is cumbersome. In other scientific domains, it has been shown that specifying or selecting a location or volume in XR using handheld controllers or tracked hands allows for greater speed and accuracy. We anticipate the same will hold true for atmospheric data, and we will share initial results of measuring the utility of such an interface. Notably, as the data being visualized is generated by GEOS as a prediction based on initial conditions, an intended application of our tool is to serve as part of an iterative feedback loop. Through XR, a scientist will review and manipulate a GEOS model run, modifying the conditions as needed to do subsequent runs of GEOS. Thereby, XR-based improvements to speed and accuracy of 3D tagging of points minimizes the effort required by both the scientist and the computer cluster conducting the necessary calculations.

Thomas Grubb↗

Cloud Computing Option for Modeling the Debris Environment

NASA’s Digital Transformation Initiative aims to promote the agency’s adoption of current and evolving digital technologies. Through agency-wide collaboration with other NASA teams, the Office of Safety and Mission Assurance (OSMA) has directed the Orbital Debris Program Office and the Meteoroid Environment Office to integrate cloud computing technologies in their publicly released software models: the Orbital Debris Engineering Model (ORDEM) and the Meteoroid Engineering Model (MEM). Decoupling the user interface from the backend processor was key for the software packages to run on a cloud computing framework. Benefits to this design include horizontal scaling of computing resources, user authentication and authorization, and automated deployment. Both models are hosted on a cloud computing platform supported by the NASA authorized IT security and compliance framework. This paper focuses on the new ORDEM web application, which includes the current features of the publicly released ORDEM software with an upgraded frontend design. The underlying ORDEM processor is run on a cloud container, allowing the user to run multiple spacecraft and telescope/radar mode simulations. Featuresexclusive to the ORDEM web application, such as importing multiple TLEs, auto-generated plotting, and the ability to check runtime progress are discussed. Comparisons between the current ORDEM software and the web application are summarized.

Andrew Vavrin↗

CFD Validation Study of a Hypersonic Cone-Slice-Flap Variable Geometry Configuration

Model validation is the process of determining the degree of accuracy between physical reality and the model. The result of model validation can either be used to improve the model through calibration or quantify the model-form uncertainty. This work focuses on providing the model-form uncertainty through an area metric for a hypersonic cone-slice-flap variable geometry configuration given uncertainty in both the simulation and experimental data. The research here compares two different turbulence models for the simulations. For a variable geometry, performing uncertainty quantification to capture the model-form uncertainty on every configuration is computationally challenging. This work lays out a procedure that can give an accurate representation of the model-form uncertainty using a small number of high-fidelity runs and many low-fidelity runs on multiple configurations. Running this comparison provides a quantifiable measurement for the accuracy of each turbulence model for this type of design. The high-fidelity CFD solver used was VULCAN-CFD and the low-fidelity results came from Cart3D. The experimental data came from the 20-Inch Mach 6 Tunnel located at NASA Langley Research Center. The present work showed that the using both the Spalart and Allamaras and Menter Shear-Stress Transport turbulence models overpredicted the drag and lift coefficient, while underpredicting the pitching moment coefficient. The model-form uncertainty estimate resulted in up to a 13.6% change in the total uncertainty for the drag coefficient, up to a 57.4% change in total uncertainty for the lift coefficient, and up to a 100% change in total uncertainty for the pitching moment coefficient.

Laura M. White↗

CFD Validation Study of a Hypersonic Cone-Slice-Flap Variable Geometry Configuration

Model validation is the process of determining the degree of accuracy between physical reality and the model. The result of model validation can either be used to improve the model through calibration or quantify the model-form uncertainty. This work focuses on providing the model-form uncertainty through an area metric for a hypersonic cone-slice-flap variable geometry configuration given uncertainty in both the simulation and experimental data. For a variable geometry, performing uncertainty quantification to capture the model-form uncertainty on every configuration is computationally challenging. This work lays out a procedure that can give an accurate representation of the model-form uncertainty using a small number of high-fidelity runs and many low-fidelity runs on multiple configurations. Running this comparison provides a quantifiable measurement for the accuracy of each turbulence model for this type of design. The high-fidelity CFD solver used was VULCAN-CFD and the low-fidelity results came from Cart3D. The experimental data came from the 20-Inch Mach 6 Tunnel located at NASA Langley Research Center. The present work showed that the turbulence simulation overpredicted the drag and lift coefficient, while underpredicting the pitching moment coefficient. The model-form uncertainty estimate resulted up to a 13.6% change in the total uncertainty for the drag coefficient, up to a 57.4% change in total uncertainty for the lift coefficient, and up to a 100% change in total uncertainty for the pitching moment coefficient.

Laura White↗

Closed Environment Air Revitalization System Based on Metal Organic Framework Adsorbents

This project utilized a systems engineering methodology to develop a vacuum swing adsorption system with full Labview automated control. The project was successful and provided students with an introduction to systems engineering and air revitalization. Specifically, two stainless steel adsorption beds were custom designed and manufactured and a sequence of computer controlled valves were used to deliver CO 2 laden, humid air, to the adsorbent where the CO 2 was removed from the air stream. Runs were completed using 13X zeolite and bed timing and switching was controlled by the computer based on the data output of a CO 2 detector. Adsorption runs using the MOF have not been completed upon the writing of this report; however, the MOF material is currently being synthesized and the runs will be completed upon receipt of the material. A follow up meeting with NASA has been tentatively planned to discuss the output of these experiments. Consistent with systems engineering practice, an end of project assessment of the class was conducted with the students and several items were realized. Specifically, the short period of performance of this grant makes it necessary to maintain a narrowly focused scope on the project such that multiple experiments after systems development (T&E) need to be limited to ensure timely completion of the proposed tasks. Also, procurement of parts may need to be moved forward in time to allow for delivery delays, and it may be necessary to request SDR, PDR, and CDR dates from NASA that are ahead of the NASA anticipated schedule. These types of lessons provided valuable to both the PI and the students and ultimately illustrate the necessity of proper systems engineering schedule risk assessment. The class met the objectives of the project and provided an introduction to systems engineering to undergraduate students. As a metric of that success, the lead engineer of the undergraduate design team acquired a job with an aerospace defense contractor, which he attributed to his knowledge of systems engineering concepts that were acquired via the X-Hab class.

T. Grant Glover↗

Transient Liquefaction on the Lunar or Martian Surface Operational Demonstration

As developments of local production of cryogenic fluids on the Lunar or Martian Surface progress, it is important to understand transient system responses to help with the balancing of process plant power and understanding system level operations. During the Cryogenic Fluid In-situ Liquefaction for Landers (CryoFILL) testing, a series of transient oxygen liquefaction tests were completed. These tests included varying liquefaction flow rate, environmental temperature, tank fill level, and effective cryocooler lift while allowing the tank pressure to respond to the input controls. An additional transient test was run at the 90% fill level to determine the impact of injecting the gaseous oxygen at the bottom of the tank, allowing the vapor to bubble up through the liquid. Tests were run in a cyclical nature varying one variable at a time. The control variable was set in a manner to increase tank pressure for a period of time and then subsequently changed in a manner to decrease the tank pressure back to its original value with multiple cycles run for all tests. Tank pressure and system temperature responses were tracked as a function of time with an emphasis on repeatability. Results indicate that of the four variables tested, the environmental temperature is the least important. As expected, the bubbling of the liquefaction gas significantly decreased the pressurization and depressurization rates in the tank at the 90% full level.

Liquefaction↗

Component Level Regression Testing in a Hierarchical Architecture

The Goddard Earth Observing System (GEOS) is an Earth system model consisting of a large suite of individual model components that can be coupled in a flexible manner to investigate a variety of Earth science issues. Specific GEOS model configurations are composed as a hierarchical collection of components based on the Earth System Modeling Framework (ESMF). Regression testing of GEOS is currently limited to (1) full system tests that are poor at isolating specific defects and (2) a suite of unit tests which have very limited coverage. As part of our approach to improve upon the current testing situation, we have prototyped the capability to perform regression tests on individual GEOS components by leveraging and extending existing checkpoint/restart capabilities. In our implementation, each ESMF component has 3 states: Import (what it needs to run), Export (which it needs to provide to other components), and Internal (the component state proper). By capturing, Import, Export and Internal states for a given component during a ull run of GEOS, a generic driver can then rerun the component offline and compare expected exports with those that have been saved. The hierarchical structure of GEOS introduces an interesting wrinkle when trying to test components that in turn drive interacting child components. To fully isolate a parent component, we use the approach of software mocks, in which the exports of children are also saved during the initial capture run of GEOS. Then when testing the parent component, the children components are replaced by a generic mock component that produces exports from the previously saved data and ensures that that all interdependencies among children components are satisfied.

Thomas Clune↗

Cloud Computing Option for Modeling the Debris Environment

NASA’s Digital Transformation Initiative aims to promote the agency’s adoption of current and evolving digital technologies. Through agency-wide collaboration with other NASA teams, the Office of Safety and Mission Assurance (OSMA) has directed the Orbital Debris Program Office and the Meteoroid Environment Office to integrate cloud computing technologies into their publicly released software models: the Orbital Debris Engineering Model (ORDEM) and the Meteoroid Engineering Model (MEM). Decoupling the user interface from the backend processor was key for the software packages to run on a cloud computing framework. Benefits to this design include horizontal scaling of computing resources, user authentication and authorization, and automated deployment. Both models are hosted on a cloud computing platform supported by the NASA authorized IT security and compliance framework. This paper focuses on the new ORDEM web application, which includes the current features of the publicly released ORDEM software with an upgraded frontend design, although parallels between ORDEM and MEM are also discussed. The underlying ORDEM processor is run on a cloud container, allowing the user to run multiple spacecraft and telescope/radar mode simulations. Features exclusive to the ORDEM web application, such as importing multiple TLEs, auto-generated plotting, and the ability to check runtime progress are discussed. Comparisons between the current ORDEM software and the web application are summarized.

Andrew Vavrin↗

Component Level Testing in a Hierarchical Architecture

The Goddard Earth Observing System (GEOS) is an Earth system model consisting of a large suite of individual model components that can be coupled in a flexible manner to investigate a variety of Earth science issues. Specific GEOS model configurations are composed as a hierarchical collection of components based on the Earth System Modeling Framework (ESMF). Regression testing of GEOS is currently limited to (1) full system tests that are poor at isolating specific defects and (2) a suite of unit tests which have very limited coverage. As part of our approach to improve upon the current testing situation, we have prototyped the capability to perform regression tests on individual GEOS components by leveraging and extending existing checkpoint/restart capabilities. In our implementation, each ESMF component has 3 states: Import (what it needs to run), Export (which it needs to provide to other components), and Internal (the component state proper). By capturing, Import, Export and Internal states for a given component during a ull run of GEOS, a generic driver can then rerun the component offline and compare expected exports with those that have been saved. The hierarchical structure of GEOS introduces an interesting wrinkle when trying to test components that in turn drive interacting child components. To fully isolate a parent component, we use the approach of software mocks, in which the exports of children are also saved during the initial capture run of GEOS. Then when testing the parent component, the children components are replaced by a generic mock component that produces exports from the previously saved data and ensures that that all interdependencies among children components are satisfied.

Tom Clune↗

Modeling and Visualization of Geomagnetic Storms at the CCMC

The Community Coordinated Modeling Center is greatly expanding activities in geospace in recent years, including the addition of new models or outputs (including WACCM-X, SAMI3-TIEGCM, HYPERS, GAMERA test runs and WAM-IPE real time outputs) that expand the range of available views or analysis activities in geospace during the upcoming Solar Maximum and Heliophysics Big Year. We are now routinely adding to a library of geomagnetic storms using anew request interface for the Space Weather Modeling Framework(SWMF). We are placing continuous run model simulation outputs as run series onto the CCMC web site where look at quick-look graphics, perform online visualization and request outputs for any day covered by the results.We demonstrate examples and results of online visualization and analysis tools that are also placed onto the cloud to support Open Science and collaborative research.

Lutz Rastaetter↗

Strategies for the GPU Implementation of the OVERFLOW CFD Code

Wondering how to port a large, computational fluid dynamics (CFD) solver, written in Fortran, to run effectively on GPUs? Join this talk to learn about the strategies NASA’s OVERFLOW CFD code has used to effectively utilize GPUs to greatly improve the time to solution compared to CPUs. OVERFLOW is an overset, structured grid, computational fluid dynamics (CFD) flow solver developed by NASA and widely used by government, US industry, and academia. It is known for its effective use of CPU hardware, but this talk will discuss recent efforts to modify the code to run efficiently on GPUs. We will describe our use of OpenACC, CUDA Fortran, and CUDA C++, discussing why and how we use each to map our problem onto NVIDIA GPUs. We will also describe structural changes we made in the code to expose enough parallelism to effectively use the GPU hardware. Finally, we will present the performance benefits from running OVERFLOW on GPUs compared to the well optimized CPU version of the code.

GPU Programming↗

High-Enthalpy Testing to Validate Simulation of an Aerosol Capture Probe

AERACEPT (Aerosol Rapid Analysis Combined Entry Probe/sonde Technology) is a developing technology enabling in-situ aerosol particle sampling and analysis in a small spacecraft mission envelope. It integrates a passive aerosol sample collection system into a probe’s thermal protection system (TPS) to remove the need for heat shield separation and active descent control (parachutes, gliders, etc.). AERACEPT is being validated against the requirements of the Nephele mission concept, which targets the middle and lower Venus cloud layers. The proposed technology employs 3D Carbon-Carbon (3D-CC) at the probe’s nose to withstand the extreme environments encountered in a Venus entry without producing pyrolysis gases that would contaminate the mission sample collection. Any shape change of this 3D-CC sample inlet will affect airflow through the sampling system, thereby impacting aerosol sample collection bias and efficiency. Accurate prediction of the nose’s material response during entry is there-fore of fundamental importance to the development and practical use of this technology. As a result, the AERACEPT project is planning a test campaign in the newly built PlasmatronX facility with a novel “Open Iso-Q” test article to validate state-of-the-art material response tools for a simulated Venus entry. The PlasmatronX is a 350 kW inductively-coupled plasma facility developed and run by the Center for Hypersonics and Entry Systems Studies at the University of Illinois at Urbana-Champaign. The facility can support ground testing for a variety of planetary destinations by simulating entry conditions in Nitrogen, Air, and Carbon Dioxide. To best simulate the Venus atmosphere and match flight-like recession, the planned AERACEPT test campaign will use Carbon Dioxide as its test gas. AERACEPT has designed two test articles for this campaign: 1) a standard test article whose curved surface approximates a constant applied heat flux (“Closed Iso-Q” model) and 2) a novel inlet test article with a through-hole at the stagnation point (“Open Iso-Q” model). Both article types consist of a 3D-CC sample bonded to a graphite fixture. All articles will be laser scanned before and after testing to estimate shape change and recession, and the “Closed Iso-Q” articles will be instrumented with thermocouples to provide temperature histories. The test article temperatures and inlet shape change will be compared against simulations run with the Porous material Analysis Toolbox based on OpenFOAM (PATO) to validate the AERACEPT 3D-CC material response model. Due to the high thermal conductivity of 3D-CC, multidimensional effects have a large influence on the test article temperature and the standard 1-D material response tools are not sufficient for test planning. The test campaign features (e.g. article design, run duration, heat fluxes) are therefore informed by a series of 3-D simulations using state-of-the-art material response tools such as PATO. The test campaign is scheduled for spring of 2024. Expected results include 1) Key drivers of selected test conditions (e.g. matching mission flight atmosphere & recession), 2) Simulation results that informed test article design, 3) Acquired test data such as recession measurements, temperature histories, and photos, and 4) Comparisons between test results and simulation predictions.

AERACEPT↗

Tracking Magnetic Perturbations, dB/dt and Geomagnetic Indices for Geospace Storms on a Routine Basis at the CCMC

The first comprehensive assessment of geospace model skill to specify magnetic perturbations (delta-B) on the ground and their time derivative (dB/dt) was performed at the Community Coordinated Modeling Center starting in 2010. This study resulted in the addition of the Space Weather Modling Framework to the suite of operational models run by the NOAA Space Weather Prediction Center (SWPC). Since then, magnetic pertubations have been made available on a larger scale for Run-on-Request simulations in geospace at the CCMC. We will demonstrate recent additions to the suite of analysis tools and model results including magnetic perturbations at more stations and on a grid of positions from both, original model outputs (SWMF using preset run configurations) and post-processed calculations using CalcDeltaB and their analysis and visualization using the open-source Kamodo data access and analysis suite and the Comprehensive Assessment of Models and Events using Library tools (CAMEL) application.

Lutz Rastaetter↗

Evaluating the Trustworthiness of Deep Neural Networks in Deployment – A Comparative Study (Replicability Study)

As deep neural networks (DNNs) are increasingly used in safety critical applications, there is a growing concern for their trustworthiness. Even highly trained, high-performant networks are not 100% accurate. However, it is very difficult to predict their behaviour during deployment without ground truth. In this paper, we provide a comparative and replicability study on recent approaches that have been proposed to evaluate the trustworthiness of DNNs. We find that it is very difficult to run and reproduce the results for these approaches on their replication packages, and it is even more difficult to run the tools on artifacts other than their own. Further, it is difficult to compare the effectiveness of the tools, due to lack of clearly defined evaluation metrics. Our results indicate that more effort is needed in our research community to obtain sound techniques for evaluating the trustworthiness of neural networks in safety-critical domains. To this end, we contribute an evaluation framework that incorporates the considered approaches and enables evaluation on common benchmarks, using common metrics. Using this framework, we run a comparative study of the three approaches.

Trustworthy AI↗

Open Science Practices at the Community Coordinated Modeling Center

Open Science is defined as “the principle and practice of making research products and processes available to all, while respecting diverse cultures, maintaining security and privacy, and fostering collaborations, reproducibility, and equity” by Federal Agencies. The CCMC has been practicing open science based on FAIR (Findable, Accessible, Interoperable and Reusable) principle by providing access to the state-of -the art space science and space weather models to users around the world through various simulation services such as Runs-on-Request, Instant Runs, Real time runs on iSWA system. The CCMC also provides a wide range of tools and framework to help users easily utilize modeled data. One of the tools is the official NASA open-sourced software called Kamodo. Kamodo allows users to work with complex space weather models and data with little or no coding experience. Additionally, to support transparent model validation efforts, the CCMC is providing an integrated and flexible framework called CAMEL. CAMEL allows users to seamlessly compare model outputs with observational data sets. Currently, we are working on a user-friendly database of the papers and research that used CCMC services, so that the future users will have open access to previously performed research by other users and its details. In this presentation, we will show the open tools and resources provided by the CCMC. Furthermore, we will share our new efforts to support open data and open science results.

Ja Soon Shim↗

High-Enthalpy Testing to Validate Simulation of an Aerosol Capture Probe

AERACEPT (Aerosol Rapid Analysis Combined Entry Probe/sonde Technology) is a developing technology enabling in-situ aerosol particle sampling and analysis in a small spacecraft mission envelope. It integrates a passive aerosol sample collection system into a probe’s thermal protection system (TPS) to remove the need for heat shield separation and active descent control (parachutes, gliders, etc.). AERACEPT is being validated against the requirements of the Nephele mission concept, which targets the middle and lower Venus cloud layers. The proposed technology employs 3D Carbon-Carbon (3D-CC) at the probe’s nose to withstand the extreme environments encountered in a Venus entry without producing pyrolysis gases that would contaminate the mission sample collection. Any shape change of this 3D-CC sample inlet will affect airflow through the sampling system, thereby impacting aerosol sample collection bias and efficiency. Accurate prediction of the nose’s material response during entry is there-fore of fundamental importance to the development and practical use of this technology. As a result, the AERACEPT project is planning a test campaign in the newly built PlasmatronX facility with a novel “Open Iso-Q” test article to validate state-of-the-art material response tools for a simulated Venus entry. The PlasmatronX is a 350 kW inductively-coupled plasma facility developed and run by the Center for Hypersonics and Entry Systems Studies at the University of Illinois at Urbana-Champaign. The facility can support ground testing for a variety of planetary destinations by simulating entry conditions in Nitrogen, Air, and Carbon Dioxide. To best simulate the Venus atmosphere and match flight-like recession, the planned AERACEPT test campaign will use Carbon Dioxide as its test gas. AERACEPT has designed two test articles for this campaign: 1) a standard test article whose curved surface approximates a constant applied heat flux (“Closed Iso-Q” model) and 2) a novel inlet test article with a through-hole at the stagnation point (“Open Iso-Q” model). Both article types consist of a 3D-CC sample bonded to a graphite fixture. All articles will be laser scanned before and after testing to estimate shape change and recession, and the “Closed Iso-Q” articles will be instrumented with thermocouples to provide temperature histories. The test article temperatures and inlet shape change will be compared against simulations run with the Porous material Analysis Toolbox based on OpenFOAM (PATO) to validate the AERACEPT 3D-CC material response model. Due to the high thermal conductivity of 3D-CC, multidimensional effects have a large influence on the test article temperature and the standard 1-D material response tools are not sufficient for test planning. The test campaign features (e.g. article design, run duration, heat fluxes) are therefore informed by a series of 3-D simulations using state-of-the-art material response tools such as PATO. The test campaign is scheduled for spring of 2024. Expected results include 1) Key drivers of selected test conditions (e.g. matching mission flight atmosphere & recession), 2) Simulation results that informed test article design, 3) Acquired test data such as recession measurements, temperature histories, and photos, and 4) Comparisons between test results and simulation predictions.

AERACEPT↗

In-Situ Ice Adhesion Testing using the Deformed Skin Adhesion Test

There exists a plethora of ice adhesion testing methods such as centrifuge-based methods, push/pull methods, and lap joint shear tests. However, these methods often cannot be done in-situ during an icing spray and require researcher handling/preparation prior to testing. Additionally, many of these methods test ice accretions that are not representative of the ice shapes that grow on airframes which can have unintended consequences such as edge or corner stress concentrations. In order to mitigate the issues present with other ice adhesion tests a novel, hands-free, in-situ test method imbedded into the leading edge of the airfoil has been developed and tested in the NASA Glenn Research Center Icing Research Tunnel. The mechanics of the new test method are discussed with finite element simulations being used to highlight the fundamental mechanics of this test method. The testing procedures used during the experimental test campaign are discussed along with the icing cloud test matrix. Analysis of the force-displacement results highlights the repeatability of the test method with regards to both sample behavior across several days of testing and different ice shapes. The results from first run of the day showed a significant discrepancy from subsequent runs and differential image analysis was used to determine differences in the interfacial bonding states between runs.

Ice Adhesion↗

Alternate Methods of Model Reduction to Avoid Dynamic Modal Truncation Error

Loads analysis is traditionally performed using dynamically reduced models, which provides the benefit to reduce run time. If the reduced model frequency cutoff is not chosen appropriately, the model will lack the dynamic content required to fully represent the response of the non-reduced model. Standard guidance for reduced model frequency content, provided in NASA-STD-5002, is to solve fixed base modes up to a minimum of 1.5x the model frequency content of interest and to employ static modal truncation methods such as residual vectors, the mode acceleration method, and the residual flexibility method to account for the truncated flexibility of the missing modes. Fixed base modes require the selection of a set of degrees of freedom to be constrained which, if not properly selected, may affect the accuracy of the reduced model by excluding some of the dynamic characteristic of the full model. In this case, the standard NASA guidance would be insufficient, but it may not be readily apparent that a portion of the reduced model response is missing. This error was encountered during an independent verification and validation (IV&V) effort, where it was observed that the resulting dynamic response was lower than the inline analysis. In this specific case, despite following the standard NASA model reduction guidelines in the selection of the frequency cutoff, the inline model still did not fully capture the necessary dynamic content. As part of the IV&V, an alternate reduction methodology was employed using an unconstrained mode acceleration method. The original model initially performed a constrained reduction to twice the frequency content of interest before doing a free-free run, employing the mode acceleration method to account for the truncated modes. In contrast in the IV&V, the unconstrained model reduced directly to the needed frequency content of the free-free run, avoiding any interactions between constraints and dynamic content. To verify the model, the original reduction methodology was used to generate a series of Hurty-Craig-Bampton reductions, each with a higher frequency cutoff than the previous. The results were shown to converge once the frequency cutoff increased past eight times the frequency content of interest. At the same frequency cutoff, the results of the Hurty-Craig-Bampton model converged with the results of the unconstrained mode acceleration model. This comparative study provided confidence that the results of the unconstrained modal acceleration reduced model were correct and that the Hurty-Craig-Bampton needed to increase its frequency cutoff to fully capture the dynamic response.

Erin Simmons↗