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At least 1,621 records · Page 90

Exergy-based Sensitivity Analysis of the Generic Hypersonic Vehicle using FUN3D

In this paper, the implementation of an exergy-based objective function and its adjoint gradient into NASA’s FUN3D solver is discussed and verified. In order to verify that the exergy-based functional is properly implemented, it is used to predict the drag of the Generic Hypersonic Vehicle (GHV), which is then compared to more traditional force-based drag predictions. In addition to the functional implementation, FUN3D’s adjoint capability was extended to obtain sensitivities. Results were verified using FUN3D’s native complex step method for di↵erentiation using a generic wing configuration. The complex and adjoint gradients yielded discrete agreement demonstrating correct implementation and that the functional can be used for gradient-based multidisciplinary analysis and optimization. Next, various trade studies are conducted on the GHV to understand the design space of the vehicle. Finally, an inverse design problem is solved to verify the utilized design optimization framework which is ready to be deployed for exergy-based optimizations in future work.

Neal L. Novotny↗

Towards a More Realistic Representation of NASA CERES-derived Surface Radiative Fluxes during Polar Night: A Comparison with the MOSAiC Field Campaign

The Arctic is one of the most sensitive regions of Earth to climate change, and yet remains one of the more difficult regions to both observe and simulate. The remoteness of the Arctic from most of civilization makes large volumes of in situ observations difficult to collect, and so satellite observations are a critical tool for observing the region, such as those from Clouds and the Earth’s Radiant Energy System (CERES). But validating the satellite radiative flux estimates is difficult because of the lack of in situ measurements. A useful remedy is utilizing measurements from field campaigns, such as the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition during 2019-2020. The extensive high-quality surface radiative flux and meteorological measurements collected from MOSAiC provide a useful check on flux retrievals from CERES instruments. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020. As this time period is mostly during polar night and twilight, the focus of the study is on longwave surface fluxes. To better understand the reasons for errors in CERES fluxes, we use the large set of meteorological measurements also collected by MOSAiC, including surface temperature, thermodynamic vertical profiles, surface turbulent fluxes, and cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. An overestimate of low cloud amount yielded an underestimate of the downwelling flux on the order of tens of W m2. Continuing this work, we test other meteorological properties such as the vertical thermodynamic profile and surface turbulent fluxes. In addition, we examine different estimates of surface fluxes derived from CERES measurements. Previous work used the SYN1deg product, which had the limitation of having a 1º x 1 º horizontal resolution. A newer product estimates the surface fluxes at the CERES footprint resolution, which allows a more precise colocation, and thus a representative flux estimate, with the MOSAiC site.

J Brant Dodson↗

Orbital Debris Shape Effect Investigations for Mitigating Risk

NASA’s Orbital Debris Program Office (ODPO) and Hypervelocity Impact Technology (HVIT) team have coordinated to better understand the risks to upper stages and spacecraft from non-spherical orbital debris. It is well understood that fragmentation (collision or explosion) events in orbit produce fragments of various materials, sizes, and shapes. To further characterize these parameters, the ODPO is developing the next-generation Orbital Debris Engineering Model (ORDEM) version 4.0 to include orbital debris shape distributions. Ground-based assets, such as radar and optical sensors, can provide size estimates and some insight into material based on radar return or optical filter photometry/spectroscopy, respectively. Characterizing an object’s shape requires more laboratory analyses to infer how shape affects these measurements. More importantly, in addition to size and material/density, the shape of fragments in orbit will alter the ballistic limit equations used in orbital debris risk assessments with NASA’s Bumper Code. The ODPO plans to release ORDEM 4.0 in the coming years. Performing ground-based laboratory impact tests on high-fidelity spacecraft mockups provides the means to directly measure size, mass, material/density, and shape of fragments, all key parameters needed to characterize real-world break up events. The DebriSat test, the results of which are provided, showcases the details of this type of experiment. The goal of this collaborative research between the ODPO and the HVIT team is to include a shape parameter in the environmental and breakup models used to assess risk for various space structures. This paper examines ground-based laboratory impact tests and the associated fragment shape categories. Provided these defined shapes, the approach is simplified by assuming a right circular cylinder (RCC) approximation with varying length-to-diameter ratios. Highlights of impact tests conducted by the HVIT team using non-spherical projectiles based on the RCC approximation are presented. Hydrocode simulations have also been performed to expand on the complexity of variations with non-spherical projectiles. Lastly, ray-tracing simulations of various RCCs of known material are provided to support the ongoing research on optical reflectance distributions with known shapes and to highlight how this may modify the current optical size estimation model. The status and plan forward are outlined for NASA's orbital debris shape effect investigation using a multidisciplinary approach by the ODPO and the HVIT team.

Heather Cowardin↗

NDARC - NASA Design and Analysis of Rotorcraft: Theory - Appendix A

The NASA Design and Analysis of Rotorcraft (NDARC) software is an aircraft system analysis tool that supports both conceptual design efforts and technology impact assessments. The principal tasks are to design (or size) a rotorcraft to meet specified requirements, including vertical takeoff and landing(VTOL) operation, and then analyze the performance of the aircraft for a set of conditions. For broad and lasting utility, it is important that the code have the capability to model general rotorcraft configurations, and estimate the performance and weights of advanced rotor concepts. The architecture of the NDARC code accommodates configuration flexibility, a hierarchy of models, and ultimately multidisciplinary design, analysis, and optimization. Initially the software is implemented with low-fidelity models, typically appropriate for the conceptual design environment. An NDARC job consists of one or more cases, each case optionally performing design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance calculation, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. For analysis tasks, the aircraft description can come from the sizing task, from a previous case or a previous NDARC job, or be independently generated (typically the description of an existing aircraft). The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. For each component, attributes such as performance, drag, and weight can be calculated; and the aircraft attributes are obtained from the sum of the component attributes. Description and analysis of conventional rotorcraft configurations is facilitated, while retaining the capability to model novel and advanced concepts. Specific rotorcraft configurations considered are single-main-rotor and tail-rotor helicopter, tandem helicopter, coaxial helicopter, and tiltrotor. The architecture of the code accommodates addition of new or higher-fidelity attribute models for a component, as well as addition of new components.

NDARC↗

Modeling and Simulation of a Parallel Hybrid Electric Regional Aircraft for the Electrified Powertrain Flight Demonstration (EPFD) Program

This paper presents a parametric modeling and integrated aircraft sizing and synthesis approach for a charge depleting parallel hybrid electric architecture. The developed models are integrated within the baseline thin-haul and regional aircraft. In addition to the physical architecture, different modes of operation enabled by propulsion system electrification are also modeled parametrically. The modes of operation presented in this paper are the peak power shaving, climb power electric boost, in-flight battery recharging, and electric taxi. The sizing of the powertrain and the aircraft are performed within the multidisciplinary analysis and optimization environment, E-PASS. The consideration of the physical system and its operation together provides a holistic approach where the propulsion system and the airframe are designed under an optimized power and energy management strategy. The parametric nature of the work enables the design space exploration for electrification and lays the groundwork for future technology projection and uncertainty quantification studies. The developed capability is generic and can be applied on other aircraft classes. The work is done as part of the Electrified Powertrain Flight Demonstration program.

electrified powertrain flight demonstration↗

High Fidelity Adaptively Refined CFD and Reduced Order Models of a High Aspect Ratio Aeroelastic Wing Wind-Tunnel Model

The NASA Advanced Air Transport Technology (AATT) goal of reduced fuel burn for transport aircraft has led to the NASA N+3 High Aspect Ratio Wing (HARW) subproject. This project requires identifying, developing, and demonstrating key technologies and integrated multidisciplinary solutions to enable a safe, high performance, aeroelastic wing. Since this aircraft will have a high aspect ratio wing, aeroelasticity is expected to be a major issue in the design. In this paper high fidelity computational fluid dynamics (CFD) is performed with flow adapted meshes. A system identification of the aerodynamics is developed using both a multi-modal multi-sine time-marching and a multi-mode linear frequency domain method. GLA, MLA and flutter suppression simulations will be performed.

Robert Bartels↗

The Containment Assurance Risk Framework of the Mars Sample Return Program

The Mars Sample Return campaign aims at bringing rock and atmospheric samples from Mars to Earth through a series of robotic missions. These missions would collect the samples being cached and deposited on Martian soil by the Perseverance rover, place them in a container, and launch them into Martian orbit for subsequent capture by an orbiter that would bring them back. Given there exists a non-zero probability that the samples contain biological material, precautions are being taken to design systems that would break the chain of contact between Mars and Earth. These include techniques such as sterilization of Martian particles, redundant containment vessels, and a robust reentry capsule capable of accurate landings without a parachute. Requirements exist that the probability of containment not assured of Martian-contaminated material into Earth’s biosphere be less than one in a million. To demonstrate compliance with this strict requirement, a statistical framework was developed to assess the likelihood of containment loss during each sample return phase and make a statement about the total combined mission probability of containment not assured. The work presented here describes this framework, which considers failure modes or fault conditions that can initiate failure sequences ultimately leading to containment not assured. Reliability estimates are generated from databases, design heritage, component specifications, or expert opinion in the form of probability density functions or point estimates and provided as inputs to the mathematical models that simulate the different failure sequences. The probabilistic outputs are then combined following the logic of several fault trees to compute the ultimate probability of containment not assured. Given the multidisciplinary nature of the problem and the different types of mathematical models used, the statistical tools needed for analysis are required to be computationally efficient. While standard Monte Carlo approaches are used for fast models, a multi-fidelity approach to rare event probabilities is proposed for expensive models. In this paradigm, inexpensive low-fidelity models are developed for computational acceleration purposes while the expensive high-fidelity model is kept in the loop to retain accuracy in the results. This work presents an example of end-to-end application of this framework highlighting the computational benefits of a multi-fidelity approach.

Giuseppe Cataldo↗

Sea Ice Drift Tracks From Autonomous Buoys in the MOSAiC Distributed Network

A network of autonomous, ice-tethered buoys was deployed around the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) experiment in late September 2019 for a year-long drift in the Arctic Transpolar Drift Stream. The buoys were deployed as part of the MOSAiC distributed network (DN) which included 12 multi-instrumented ice stations and an additional 116 GPS buoys distributed primarily within a 40 km radius of the MOSAiC Central Observatory. Buoy coverage within the DN was maintained with additional deployments throughout the year-long drift allowing for collection of data over a full sea ice growth and melt cycle. All GPS position data from buoys deployed within the DN have been assembled and processed into the collection of 216 quality-controlled buoy drift tracks presented in this dataset covering the period 26 September 2019 – 23 May 2021. The drift tracks in this collection are ideal for studies of dynamic sea ice motion around the MOSAiC experiment at cascading spatial scales ranging from 100s of meters to 100s of km.

Angela C. Bliss↗

NASA Aeronautics Research Mission Directorate System Security Engineering Approaches

System security engineering (SSE) is a set of formal engineering methods and is considered a subset of systems engineering. It is a relatively new development in systems engineering with the initial NIST (National Institute of Standards) standard published in November of 2016 with updates in 2018, and 2022. The guiding principles in our methodology are based in NIST Special Publication 800-160 Vol. 1 “Systems Security Engineering: Considerations For A Multidisciplinary Approach In The Engineering Of Trustworthy Secure Systems” and integrate methodologies from common IT (Information Technology) threat modeling approaches utilizing MBSE (Model-Based Systems Engineering). The presentation will discuss how our teams utilize SSE and MBSE (Model-Based Systems Engineering) to develop secure architectures for systems under development in our NASA aeronautics research environment. This includes the activities to develop Protection Needs (PN) that, in turn result in security requirements in the design context and policies for the future state operational context for system protection. The process of applying SSE to analyze project architectures and ConOps (Concept of Operations) is intended to ensure the transferred research is both secure and securable in a “real-world” setting.

Systems Security Engineering↗

IMPACTing Medical System Design with a Risk Analysis Tool [“IMPACT” sur la Conception du Système Médical avec un Outil d'Analyse des Risques]

Background: Following the success of Artemis I, NASA is preparing for human extended duration missions. Ongoing efforts are focused on mitigating mission-related risks, including those affecting crew health and performance. Communication latency, logistics of resupply and time frame of medical evacuation are barriers to provision of healthcare for these missions, especially with respect to constraints in mass, volume, and crew training. An in-depth assessment of medical risks, capabilities and resources for a specific mission design is necessary to determine an optimal balance that maximizes likelihood of mission success. Overview: IMPACT (Informed Mission Planning via Analysis of Complex Tradespaces) is a dynamic tool designed to estimate medical risk and outcomes for a specific mission design. In its current iteration, a list of medical conditions selected based on likelihood of occurrence and/or consequence was linked to a set of clinical capabilities and resources necessary for diagnosis and management. A probabilistic risk analysis tool was then used to identify and estimate the likelihood and consequence of risks through the following outcome metrics: loss of crew life (inflight mortality due to medical conditions), need for medical evacuation (return to definitive care), and crew disability (task time affected based on how medical conditions influence the ability to perform specific exploration mission crew tasks). Finally, the model’s optimization algorithm provides recommendations for medical capabilities that maximize risk mitigation relative to mass and volume constraints. In the Spring of 2023, IMPACT was utilized to estimate outcome metrics for a design reference mission that would be representative of an extended duration Artemis mission. Notional data generated were then used to determine a recommended set of medical capabilities and resources relative to user-defined mass and volume constraints. A multidisciplinary team has also been updating IMPACT to strengthen the model’s fidelity. Figure 1 shows how updates to outcome metric inputs for the conditions resulted in different capability and resource allocation recommendations. Discussion: This presentation will discuss the IMPACT tool and share the latest data generated for a representative extended duration Artemis mission. Efforts to improve the fidelity of data generated by the model’s algorithm will also be discussed.

K A Shair↗

Propulsion-Airframe Integration for Conceptual Redesign of a Low-Boom Supersonic Transport

A low-boom supersonic transport was generated in a previous low-boom multidisciplinary optimization (MDO) study that used computational fluid dynamics (CFD) off-body pressure to compute the undertrack sonic boom ground signature and calibrated low-fidelity aerodynamics analyses to compute the mission performance metrics. This low-boom aircraft, referred to as the Mach 1.7 40-PAX concept, can carry 40 passengers for a low-boom overland mission with cruise Mach 1.7 for the airport pairs over the continental US and has the potential to achieve an undertrack sonic boom ground noise level below 70 perceived level of decibels at the start of overland cruise (SOC). The engine for the Mach 1.7 40-PAX concept was designed using the Numerical Propulsion System Simulation (NPSS) for the mission analysis and modeled as a flow-through nacelle for CFD-based sonic boom analysis. To understand how the engine plume affects the undertrack ground signature, the Mach 1.7 40-PAX concept is redesigned in this paper after replacing the flow-through nacelles by CFD engines for sonic boom analysis using aeropropulsive CFD simulation. A process is developed for approximation of the NPSS engine at SOC by a CFD engine for aeropropulsive CFD simulation. The generated CFD engine has the identical nozzle boundary conditions and approximately the same mass flow and thrust as those of the NPSS engine at SOC. Then, the outer mold line of the configuration with the CFD engines is redesigned to approximately restore the low-boom characteristics of the Mach 1.7 40-PAX concept at SOC. Finally, the CFD simulation data for the redesigned concept with the CFD engines is used to calibrate the low-fidelity aerodynamic analyses for mission analysis of this concept. The cyclic dependency of the involved disciplinary analyses is resolved using an iteration method for a consistent coupling of the mission analysis, NPSS engine analysis, and low-boom redesign using the aeropropulsive CFD simulation. This low-boom redesign study is used as an example to demonstrate how the propulsion-airframe integration could be implemented for conceptual design of supersonic transports that satisfy both the low-boom and mission performance requirements.

Low-boom supersonic transport↗

Gateway Induced Environments Overview

Gateway will be a long duration space station orbiting the Moon in support of NASA’s Artemis campaign. Over its lifetime, Gateway will be exposed to a variety of induced environments, including materials outgassing, chemical and electric thruster plumes, vacuum vents, and lunar dust transport (from the Human Lander System, HLS). Induced Environments can impact vehicle performance and mission success. The multidisciplinary Gateway Induced Environments Team has developed requirements and methodologies to address the complex challenge of integrating multiple elements and visiting vehicles while maintaining the Gateway induced environments within prescribed limits. The Gateway Induced Environments requirements are summarized along with the integration / verification process and preliminary system analysis results.

Gateway↗

Gateway Induced Environments Overview

Gateway will be a long duration space station orbiting the Moon in support of NASA’s Artemis campaign. Over its lifetime, Gateway will be exposed to a variety of induced environments, including materials outgassing, chemical and electric thruster plumes, vacuum vents, and lunar dust transport (from the Human Lander System, HLS). Induced Environments can impact vehicle performance and mission success. The multidisciplinary Gateway Induced Environments Team has developed requirements and methodologies to address the complex challenge of integrating multiple elements and visiting vehicles while maintaining the Gateway induced environments within prescribed limits. The Gateway Induced Environments requirements are summarized along with the integration / verification process and preliminary system analysis results.

Gateway↗

Orbital Debris Shape Effect Investigations for Mitigating Risk

NASA’s Orbital Debris Program Office (ODPO) and Hypervelocity Impact Technology (HVIT) team have coordinated to better understand the risks to upper stages and spacecraft from non-spherical orbital debris. It is well understood that fragmentation (collision or explosion) events in orbit produce fragments of various materials, sizes, and shapes. To further characterize these parameters, the ODPO is developing the next-generation Orbital Debris Engineering Model (ORDEM) version 4.0 to include orbital debris shape distributions. Ground-based assets, such as radar and optical sensors, can provide size estimates and some insight into material based on radar return or optical filter photometry/spectroscopy, respectively. Characterizing an object’s shape requires more laboratory analyses to infer how shape affects these measurements. More importantly, in addition to size and material/density, the shape of fragments in orbit will alter the ballistic limit equations used in orbital debris risk assessments with NASA’s Bumper Code. The ODPO plans to release ORDEM 4.0 in the coming years. Performing ground-based laboratory impact tests on high-fidelity spacecraft mockups provides the means to directly measure size, mass, material/density, and shape of fragments, all key parameters needed to characterize real-world break up events. The DebriSat test, the results of which are provided, showcases the details of this type of experiment. The goal of this collaborative research between the ODPO and the HVIT team is to include a shape parameter in the environmental and breakup models used to assess risk for various space structures. This paper examines ground-based laboratory impact tests and the associated fragment shape categories. Provided these defined shapes, the approach is simplified by assuming a right circular cylinder (RCC) approximation with varying length-to-diameter ratios. Highlights of impact tests conducted by the HVIT team using non-spherical projectiles based on the RCC approximation are presented. Hydrocode simulations have also been performed to expand on the complexity of variations with non-spherical projectiles. Lastly, ray-tracing simulations of various RCCs of known material are provided to support the ongoing research on optical reflectance distributions with known shapes and to highlight how this may modify the current optical size estimation model. The status and plan forward are outlined for NASA's orbital debris shape effect investigation using a multidisciplinary approach by the ODPO and the HVIT team.

Heather Cowardin↗

Earth-Independent Medical Operations (EIMO) Concept of Operations

Compared to the current paradigm for crew health in low-Earth orbit and Lunar missions that rely on constant communication with Mission Control, there is an anticipated shift in medical operations for deep-space exploration missions. This shift stems from mission constraints imposed by the considerable distance from Earth, which include resource limitations due to a lack of resupply, mass, power, volume, and data limitations, challenges imposed by communication latency and the inability to evacuate in case of emergencies. To transition towards a more self-reliant medical approach, a comprehensive strategy is essential to progressively enable crew autonomy and mitigate mission success risks in the challenging environment of space. This transformative shift is collectively referred to as "Earth-Independent Medical Operations" (EIMO), signifying the gradual transfer of medical care and decision-making from terrestrial resources to space-based assets. This transition is aimed at bolstering astronaut health and performance while simultaneously reducing the overall risks associated with space missions. The constraints related to EIMO necessitate an integrated development of medical systems, featuring interoperability with mission planning, vehicle design, spacesuit design, and data architecture. This integration is vital in establishing a robust medical infrastructure that not only supports the well-being of astronauts but also ensures the success of the mission as a whole. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has developed a model-based Concept of Operations (ConOps) outlining an initial vision for EIMO. Within this ConOps, a comprehensive view is presented, encompassing stakeholder needs, system objectives, and system goals associated with EIMO. Additionally, it provides illustrative examples of the various activities (scenarios) for which the system will be employed during missions. The selection of these activities has been meticulous, aiming to encompass a wide spectrum of medical conditions, including those falling under different risk categories, such as low-likelihood-low-consequence, low-likelihood-high-consequence, and high-likelihood-low-consequence. The selection of these activities (scenarios) effectively encompasses the wide range of medical events situated within an assumed probability-consequence bell curve. In each scenario, at least one of the five main EIMO components identified is captured. Those EIMO components are: Pre-mission Planning, Acute and Emergent Management Decision Making, Prolonged Medical Management Decision Making, Supplies and Resource Management, and Task Load Management. The ConOps was developed by a multidisciplinary team consisting of systems engineers, scientists, and clinicians across NASA and aims to serve as an initial recommendation to gradually and safely enabling crew autonomy for Mars missions and beyond.

Earth Independent Medical Operations↗

IMPACTing Medical System Design with a Risk Analysis Tool

Background: Following the success of Artemis I, NASA is preparing for human extended duration missions. Ongoing efforts are focused on mitigating mission-related risks, including those affecting crew health and performance. Communication latency, logistics of resupply and time frame of medical evacuation are barriers to provision of healthcare for these missions, especially with respect to constraints in mass, volume, and crew training. An in-depth assessment of medical risks, capabilities and resources for a specific mission design is necessary to determine an optimal balance that maximizes likelihood of mission success. Overview: IMPACT (Informed Mission Planning via Analysis of Complex Tradespaces) is a dynamic tool designed to estimate medical risk and outcomes for a specific mission design. In its current iteration, a list of medical conditions selected based on likelihood of occurrence and/or consequence was linked to a set of clinical capabilities and resources necessary for diagnosis and management. A probabilistic risk analysis tool was then used to identify and estimate the likelihood and consequence of risks through the following outcome metrics: loss of crew life (inflight mortality due to medical conditions), need for medical evacuation (return to definitive care), and crew disability (task time affected based on how medical conditions influence the ability to perform specific exploration mission crew tasks). Finally, the model’s optimization algorithm provides recommendations for medical capabilities that maximize risk mitigation relative to mass and volume constraints. In the Spring of 2023, IMPACT was utilized to estimate outcome metrics for a design reference mission that would be representative of an extended duration Artemis mission. Notional data generated were then used to determine a recommended set of medical capabilities and resources relative to user-defined mass and volume constraints. A multidisciplinary team has also been updating IMPACT to strengthen the model’s fidelity. Figure 1 shows how updates to outcome metric inputs for the conditions resulted in different capability and resource allocation recommendations. Discussion: This presentation will discuss the IMPACT tool and share the latest data generated for a representative extended duration Artemis mission. Efforts to improve the fidelity of data generated by the model’s algorithm will also be discussed.

K A Shair↗

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↗

Linearized Frequency-Domain Gust Analysis and Adjoint-Based Sensitivities

Gust analysis is added to a linearized frequency-domain method in FUN3D, a NASA computational fluid dynamics solver. The method linearizes about a nonlinear static equilibrium condition and is therefore appropriate for problems with small perturbations such as transonic stochastic gust analysis. In addition to the gust analysis, adjoint-based sensitivities of stochastic gust constraints are implemented for multidisciplinary design optimization. The linearized frequency-domain gust model and adjoint-based sensitivities are described and verified. The method is applied to an optimization for mass minimization of the AGARD 445.6 wing subject to a stochastic gust constraint limiting the displacement of the wing tip.

Aeroelasticity↗