Kamodo: A Model-Agnostic Tool for Model-Model and Model-Data Comparisons
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software↗
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Results for “PYTHON”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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New Software Capabilities Using Kamodo at CCMC
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software↗
Structural Sizing of a Composite Transonic Truss-Braced Wing
Accurate finite element modeling (FEM) is a vital part of the modern aircraft design process. As aircraft become increasingly complex, the time-consuming nature of detailed FEM approaches comes at a significant cost to program timeline and budget. In an effort produce modeling efforts that are sufficiently accurate and minimally costly, a proposed FEM approach and optimization scheme for a composite aircraft is explored, including a discussion of the manufacturing constraints of a highly tailored composite panel design. A high-fidelity structural model of a transonic truss-braced wing (TTBW) is generated, and the components are sized by structural optimization to satisfy buckling and strength constraints while subjected to critical maneuver loads. The structural modeling approaches and sizing of a TTBW are discussed, including details for FEM approaches, verification of an approximated FEM approach, a sizing optimization using the optimization software LS-OPT, and a manufacturing trial of integrally stiffened composite panels conducted to explore the validity of highly tailored composites as a design consideration. The results of study discussed herein indicate that the proposed FEM approach is suitable for modeling composite-construction aircraft and for use in sizing optimization. Further efforts regarding integrally stiffened composite panels will indicate the suitability of this method for the integration of highly tailored composite panels into the design and optimization process, given the manufacturability of such panels as shown here.
Finite Element↗
Structural Sizing of a Transonic Truss-Braced Wing
Accurate finite element modeling (FEM) is a vital part of the modern aircraft design process. As aircraft become increasingly complex, the time-consuming nature of detailed FEM approaches comes at a significant cost to program timeline and budget. In an effort produce modeling efforts that are sufficiently accurate and minimally costly, a proposed FEM approach and optimization scheme for a composite aircraft is explored, including a discussion of the manufacturing constraints of a highly tailored composite panel design. A high-fidelity structural model of a transonic truss-braced wing (TTBW) is generated, and the components are sized by structural optimization to satisfy buckling and strength constraints while subjected to critical maneuver loads. The structural modeling approaches and sizing of a TTBW are discussed, including details for FEM approaches, verification of an approximated FEM approach, a sizing optimization using the optimization software LS-OPT, and a manufacturing trial of integrally stiffened composite panels conducted to explore the validity of highly tailored composites as a design consideration. The results of study discussed herein indicate that the proposed FEM approach is suitable for modeling composite-construction aircraft and for use in sizing optimization. Further efforts regarding integrally stiffened composite panels will indicate the suitability of this method for the integration of highly tailored composite panels into the design and optimization process, given the manufacturability of such panels as shown here.
Finite Element↗
Kamodo: Simplifying Model Data Access and Utilization
To address the lack of user-friendly software needed to simplify the utilization of model data across Heliophysics, the Community Coordinated Modeling Center (CCMC) at NASA’s Goddard Space Flight Center has developed a model-agnostic method via Kamodo for users to easily access and utilize model data in their workflows. By abstracting away the broad range of file formats and the intricacies of interpolation on specialized grids, this approach significantly lowers the barrier to model data access and utilization for the community while adding exciting new capabilities to their tool boxes. This paper describes the direct interfaces to the model data, called model readers, and a basic introduction on how to use them. Additionally, we detail the planned approach for including custom interpolation codes, and include current progress on specialized visualization developments. The CCMC is maintaining Kamodo as an official NASA open-sourced software to enable and encourage community collaboration.
Heliophysics↗
Mshpy23: A User-Friendly, Parameterized Model of Magnetosheath Conditions
Lunar Environment heliospheric X-ray Imager (LEXI) and Solar wind – Magnetosphere - Ionosphere Link Explorer (SMILE) will observe magnetosheath and its boundary motion in soft X-rays for understanding magnetopause reconnection modes under varioussolar wind conditions after their respective launches in 2024 and 2025. Magnetosheath conditions, namely, plasma density, velocity, and temperature, are key parameters for predicting and analyzing soft X-ray images from the LEXI and SMILE missions. We developed a user-friendly model of magnetosheath that parameterizes number density, velocity, temperature, and magnetic field by utilizing the global Magnetohydrodynamics (MHD) model as well as the pre-existing gas-dynamic and analytic models. Using this parameterized magnetosheath model, scientists can easily reconstruct expected soft X-ray images and utilize them for analysis of observed images of LEXI and SMILE without simulating the complicated global magnetosphere models. First, we created an MHD based magnetosheath model by running a total of 14 OpenGGCM global MHD simulations under 7 solar wind densities (1, 5, 10, 15, 20, 25, and 30cm−3) and 2 interplanetary magnetic field BZ components (± 4nT), and then parameterizing the results in new magnetosheath conditions. We compared the magnetosheath model result with THEMIS statistical data and it showed good agreement with a weighted Pearson correlation coefficient greater than 0.77, especially for plasma density and plasma velocity. Second, we compiled a suite of magnetosheath models incorporating previous magnetosheath models (gas-dynamic, analytic), and did two case studies to test the performance. The MHD based model was comparable to or better than the previous models while providing self consistency among the magnetosheath parameters. Third, we constructed a tool to calculate a soft X-ray image from any given vantage point, which can support the planning and data analysis of the aforementioned LEXI and SMILE missions. A release of the code has been uploaded to a Github repository.
Magnetosheath↗
Simplified Applied Loads of a Transonic Truss-Braced Wing Derived from Computational Fluid Dynamics
The transonic truss-braced wing (TTBW) concept is under consideration by the NASA Advanced Air Transport Technology (AATT) project due to its potential to reduce fuel consumption of transport aircraft. To properly evaluate the TTBW concept, detailed structural modeling and subsequent test planning is underway, which requires a simplified set of discrete applied loads that simulate the distributed aerodynamic pressures. Given the unique architecture of the TTBW and its intended operation in the transonic regime, computational fluid dynamics (CFD) is the ideal approach to employ to ensure the aerodynamics of this configuration are sufficiently captured. To convert aerodynamic results into input for structural models, application of a data transfer tool, Discrete Data Transfer Between Dissimilar Meshes (DDTBDM), is presented to resolve aerodynamic pressures from CFD into single load vectors at hardpoints along both the wing and the strut. Evaluation of mapping the aerodynamic forces to hardpoints at rib and spar intersections in a structural model is performed, and the results are also compared with a linear static aeroelastic analysis. The structural responses indicate that distributing forces along only the wing and strut forward spars is insufficient for simulating the distributed aerodynamic loads. Adding moments along the forward spars improved the global response of the wing, but the point moments created unrealistic local rotations within the structure. When distributing loads along both the forward and aft spars of the wing and strut, the global response was less sensitive to the inclusion of point moments, which indicated the arrangement of point forces alone was sufficient input for structural design work and testing and provided a more continuous loading profile.
Finite Element↗
Simplified Applied Loads of a Transonic Truss-Braced Wing Derived from Computational Fluid Dynamic
The transonic truss-braced wing (TTBW) concept is under consideration by the NASA Advanced Air Transport Technology (AATT) project due to its potential to reduce fuel consumption of transport aircraft. To properly evaluate the TTBW concept, detailed structural modeling and subsequent test planning is underway, which requires a simplified set of discrete applied loads that simulate the distributed aerodynamic pressures. Given the unique architecture of the TTBW and its intended operation in the transonic regime, computational fluid dynamics (CFD) is the ideal approach to employ to ensure the aerodynamics of this configuration are sufficiently captured. To convert aerodynamic results into input for structural models, application of a data transfer tool, Discrete Data Transfer Between Dissimilar Meshes (DDTBDM), is presented to resolve aerodynamic pressures from CFD into single load vectors at hardpoints along both the wing and the strut. Evaluation of mapping the aerodynamic forces to hardpoints at rib and spar intersections in a structural model is performed, and the results are also compared with a linear static aeroelastic analysis. The structural responses indicate that distributing forces along only the wing and strut forward spars is insufficient for simulating the distributed aerodynamic loads. Adding moments along the forward spars improved the global response of the wing, but the point moments created unrealistic local rotations within the structure. When distributing loads along both the forward and aft spars of the wing and strut, the global response was less sensitive to the inclusion of point moments, which indicated the arrangement of point forces alone was sufficient input for structural design work and testing and provided a more continuous loading profile.
Finite Element↗
Parahydrogen Thermophysical Properties V05 Final Report
The NASA Space Nuclear Propulsion (SNP) Program works to mature both nuclear electric and nuclear thermal propulsion capabilities. The nuclear thermal propulsion (NTP) sub-effort focuses on development of technologies enabling human exploration of Mars – with a nominal performance target of 900 second vacuum specific impulse (Ivac). This Ivac target demands a hydrogen (molecular hydrogen, or dihydrogen) monopropellant NTP engine system, as other propellant choices fall well short of this target for realistically attainable reactor system temperatures (< 3000 K).
Parahydrogen↗
The Development and Deployment of Machine Learning Models for Aircraft Engine Concept Assessment
In today's competitive landscape, the effective development and utilization of machine-learning (ML) applications have become crucial across diverse economic sectors. This study presents an outline of the procedure involved in creating and implementing ML models for conceptualizing and evaluating aircraft engines. These models leverage supervised deep-learning algorithms to analyze patterns within an open-source repository containing data on both production and research conventional turbofan engines. The main areas of focus encompass crucial engine parameters like thrust-specific fuel consumption (TSFC), engine weight, engine diameter, and turbomachinery stage counts. While the creation of ML models is fundamental for their utilization, ensuring their seamless deployment holds equal significance. To address this aspect, a conversational AI chatbot that specifically focuses on propulsion has been developed. Leveraging natural language processing (NLP) techniques, this chatbot simplifies the deployment of machine learning (ML) models. The comprehensive workflow encompasses several key stages: gathering and enhancing engine data, training and cross validating the ML models, testing and evaluating their performance, and finally, deploying, monitoring, and updating the ML models. By following this systematic approach, the aim is to streamline the development and deployment process of ML models tailored for aircraft engine assessment.
AI Chatbot↗
Search for Displaced Supersymmetry in Events with an Electron and a Muon with Large Impact Parameters
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V. Khachatryan↗