A Modular Multiphysics Simulation Framework Using OpenMDAO
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Optimization↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Aircraft Flaps Modeling in OpenMDAO: Summer Internship Final Presentation
The goal of this project was to develop a model for a single subsystem in the aerodynamics discipline, in this case the flaps of an aircraft. This presentation details the building of the model. Additionally, this presentation discusses my goals and accomplishments as a summer intern, as a job experience and my hopes for my future at NASA as well
Aircraft Modeling↗
Mphys: Standardizing High-fidelity Optimization with OpenMDAO
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MDAO↗
Usage of ChatGPT for Engineering Design and Analysis Tool Development
ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.
Design↗
Usage of ChatGPT for Engineering Design and Analysis Tool Development
ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.
Design↗
WISDEM® v3.4.1(Wind Plant Integrated System Design and Engineering Model) [SWR-14-05]
The Wind Plant Integrated System Design and Engineering Model (WISDEM®) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM® is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM® turbine design capability. Please install all of the pre-requisites prior to installing WISDEM® by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM® development, please visit the official NREL systems engineering for wind energy website. https://www.nlr.gov/wind/systems-engineering
Dykes, Katherine↗
WISDEM® v3.15.2 2024 (Wind-Plant Integrated System Design and Engineering Model) [SWR-14-05]
The Wind-Plant Integrated System Design and Engineering Model (WISDEM®) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM® is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM® turbine design capability. Please install all of the pre-requisites prior to installing WISDEM® by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM® development, please visit the official NREL systems engineering for wind energy website. https://www.nrel.gov/wind/systems-engineering.html
Dykes, Katherine↗
Integrated System Modeling for Nuclear Thermal Propulsion (NTP)
Nuclear thermal propulsion (NTP) has long been identified as a key enabling technology for space exploration beyond LEO. From Wernher Von Braun's early concepts for crewed missions to the Moon and Mars to the current Mars Design Reference Architecture (DRA) 5.0 and recent lunar and asteroid mission studies, the high thrust and specific impulse of NTP opens up possibilities such as reusability that are just not feasible with competing approaches. Although NTP technology was proven in the Rover / NERVA projects in the early days of the space program, an integrated spacecraft using NTP has never been developed. Such a spacecraft presents a challenging multidisciplinary systems integration problem. The disciplines that must come together include not only nuclear propulsion and power, but also thermal management, power, structures, orbital dynamics, etc. Some of this integration logic was incorporated into a vehicle sizing code developed at NASA's Glenn Research Center (GRC) in the early 1990s called MOMMA, and later into an Excel-based tool called SIZER. Recently, a team at GRC has developed an open source framework for solving Multidisciplinary Design, Analysis and Optimization (MDAO) problems called OpenMDAO. A modeling approach is presented that builds on previous work in NTP vehicle sizing and mission analysis by making use of the OpenMDAO framework to enable modular and reconfigurable representations of various NTP vehicle configurations and mission scenarios. This approach is currently applied to vehicle sizing, but is extensible to optimization of vehicle and mission designs. The key features of the code will be discussed and examples of NTP transfer vehicles and candidate missions will be presented.
Systems Engineering↗
Integrated Multidisciplinary Optimization Objects
OpenMDAO is an open-source MDAO framework. It is used to develop an integrated analysis and design environment for engineering challenges. This Phase II project integrated additional modules and design tools into OpenMDAO to perform discipline-specific analysis across multiple flight regimes at varying levels of fidelity. It also showcased a refined system architecture that allows the system to be less customized to a specific configuration (i.e., system and configuration separation). By delivering a capable and validated MDAO system along with a set of example applications to be used as a template for future users, this work greatly expands NASA's high-fidelity, physics-based MDAO capabilities and enables the design of revolutionary vehicles in a cost-effective manner. This proposed work complements M4 Engineering's expertise in developing modeling and simulation toolsets that solve relevant subsonic, supersonic, and hypersonic demonstration applications.
Alston, Katherine↗
Rotorcraft Optimization Tools: Incorporating Rotorcraft Design Codes into Multi-Disciplinary Design, Analysis, and Optimization
One of the goals of NASA's Revolutionary Vertical Lift Technology Project (RVLT) is to provide validated tools for multidisciplinary design, analysis and optimization (MDAO) of vertical lift vehicles. As part of this effort, the software package, RotorCraft Optimization Tools (RCOTOOLS), is being developed to facilitate incorporating key rotorcraft conceptual design codes into optimizations using the OpenMDAO multi-disciplinary optimization framework written in Python. RCOTOOLS, also written in Python, currently supports the incorporation of the NASA Design and Analysis of RotorCraft (NDARC) vehicle sizing tool and the Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics II (CAMRAD II) analysis tool into OpenMDAO-driven optimizations. Both of these tools use detailed, file-based inputs and outputs, so RCOTOOLS provides software wrappers to update input files with new design variable values, execute these codes and then extract specific response variable values from the file outputs. These wrappers are designed to be flexible and easy to use. RCOTOOLS also provides several utilities to aid in optimization model development, including Graphical User Interface (GUI) tools for browsing input and output files in order to identify text strings that are used to identify specific variables as optimization input and response variables. This paper provides an overview of RCOTOOLS and its use
Analysi↗
Interpolant Improvements and Lessons Learned
This presentation is for the OpenMDAO workshop 2022 and updates users on recent improvements to interpolant methods. Specifically, we discuss computational improvements, visualization capabilities, and suggested best practices for using interpolants. The term interpolants is used synonymously with metamodels and surrogate models. The goal of the presentation is to increase adoption of efficient interpolant methods and increase users’ awareness to built-in features within OpenMDAO.
Multidisciplinary Design Optimization↗
Optimization of Turbine Engine Cycle Analysis with Analytic Derivatives
A new engine cycle analysis tool, called Pycycle, was built using the OpenMDAO framework. Pycycle provides analytic derivatives allowing for an efficient use of gradient-based optimization methods on engine cycle models, without requiring the use of finite difference derivative approximation methods. To demonstrate this, a gradient-based design optimization was performed on a turbofan engine model. Results demonstrate very favorable performance compared to an optimization of an identical model using finite-difference approximated derivatives.
OpenMDAO↗
Optimization of Turbine Engine Cycle Analysis with Analytic Derivatives
A new engine cycle analysis tool, called Pycycle, was recently built using the OpenMDAO framework. This tool uses equilibrium chemistry based thermodynamics, and provides analytic derivatives. This allows for stable and efficient use of gradient-based optimization and sensitivity analysis methods on engine cycle models, without requiring the use of finite difference derivative approximation methods. To demonstrate this, a gradient-based design optimization was performed on a multi-point turbofan engine model. Results demonstrate very favorable performance compared to an optimization of an identical model using finite-difference approximated derivatives.
Turbine engine↗
Aerostructural Optimization of a Flexible-Winged Aircraft Using OpenVSP
MBSAE project connecting aircraft geometry tool, OpenVSP, to opensourace aerodynamic, OpenAeroStruct, and structural, TACS, solvers using OpenMDAO.
aerostructural↗
Aviary: An Open-Source Multidisciplinary Design, Analysis, and Optimization Tool for Modeling Aircraft with Analytic Gradients
In recent years demands on aircraft design methods have begun to require higher degrees of coupling between disciplines and optimization in order to satisfy competing objectives involving large numbers of design parameters that define unconventional configurations. These expanding requirements have amplified a need for new and improved aircraft design, analysis, and optimization codes that are capable of performing coupled design and exploiting analytic gradients to perform gradient-based optimization where possible. To address this need, a new multidisciplinary design optimization and analysis tool called Aviary is presented. This tool, built on OpenMDAO, allows for tightly coupled, simultaneous aircraft and subsystem design using analytic gradients. Aviary includes methods from two NASA developed legacy aircraft analysis tools and provides native analytically differentiated calculations for five different disciplines (weights and sizing, aerodynamics, geometry, propulsion, and mission analysis), while also allowing external discipline analysis tools to be coupled, regardless of whether those tools can provide analytic gradients. Verification and preliminary examples and modeling efforts show Aviary’s ability to effectively model novel concepts and explore large and non-intuitive design spaces. Additionally, a multi-level user interface in Aviary creates an easy entry point for users with any level of multidisciplinary design, analysis, and optimization experience.
optimization↗
Aviary: An Open-Source Multidisciplinary Design, Analysis, and Optimization Tool for Modeling Aircraft with Analytic Gradients
Aviary is an open-source aircraft design, analysis, and optimization tool built on OpenMDAO and leveraging the legacy tools of FLOPS and GASP. This presentation will introduce the basics of Aviary, more details for which can be found in the paper. Specifically, this presentation will discuss an overview of why new aircraft design tools are necessary and how Aviary meets those needs, the structure and subsystems of Aviary, and the validation and interface that Aviary provides.
optimization↗
A cross-sectional aeroelastic analysis and structural optimization tool for slender composite structures
A fully open-source available framework for the parametric cross-sectional analysis and design optimization of slender composite structures, such as helicopter or wind turbine blades, is presented. The framework—Structural Optimization and Aeroelastic Analysis (SONATA)—incorporates two structural solvers, the commercial tool VABS, and the novel open-source code ANBA4. SONATA also parameterizes the design inputs, postprocesses and visualizes the results, and generates the structural inputs to a variety of aeroelastic analysis tools. It is linked to the optimization library OpenMDAO. This work presents the methodology and explains the fundamental approaches of SONATA. Structural characteristics were successfully verified for both VABS and ANBA4 using box beam examples from literature, thereby verifying the parametric approach to generating the topology and mesh in a cross section as well as the solver integration. The framework was furthermore exercised by analyzing and evaluating a fully resolved highly flexible wind turbine blade. Computed structural characteristics correlated between VABS and ANBA4, including off-diagonal terms. Stresses, strains, and deformations were recovered from loads derived through coupling with aeroelastic analysis. The framework, therefore, proves effective in accurately analyzing and optimizing slender composite structures on a high-fidelity level that is close to a three-dimensional finite element model.
42 ENGINEERING↗
RAFT (Response Amplitudes of Floating Turbines) [SWR-22-40]
RAFT is a Python code for frequency-domain analysis of floating wind turbines. RAFT works in the frequency domain to provide efficient computations of a floating wind system's response spectra accounting for platform hydrodynamics, quasi-static mooring reactions, rotor aerodynamics, and linearized control. It can be used to calculate response amplitude operators (RAO's), power spectral densities, mean/static properties, and response metrics based on mean and root-mean-square values of each output. RAFT serves as the Level 1 model in the WEIS (Wind Energy with Integrated Servo-control) toolkit, and features an OpenMDAO wrapper.
Hall, Matthew↗