SEARCH · Search NASA

Results for “Physics-Based”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27

All sources NASA NTRS DOE OSTI

NASA NTRS2023

Harnessing the Digital Transformation for Development of Electrified Aircraft Propulsion Control Systems

Hybrid electric aircraft propulsion is an emerging technology that presents a variety of potential benefits along with technical integration challenges. Developing these new propulsion architectures with their complex control systems, and ultimately proving their benefit, is a multistep process. This process includes concept development and analysis, dynamic simulation, hardware-in-the-loop testing, full-scale testing, and so on. This effort is being revolutionized and indeed enabled by new digital tools that support increasing the technology readiness level throughout the maturation process. As part of this Digital Transformation, NASA has developed a suite of publicly available digital tools that facilitate the path from concept to implementation. This paper describes the NASA-developed tools and puts them in the context of control system development for hybrid electric aircraft propulsion. The three MATLAB®-based software packages are the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS), the Electrical Modeling and Thermal Analysis Toolbox (EMTAT), and the Thermal Systems Analysis Toolbox (TSAT). These tools are interactive, complementary, and compatible with each other. T-MATS is a modular thermodynamic modeling framework designed for creating custom component level models of jet engines. EMTAT is a modeling framework used to simulate a variety of power electronic devices, using both physics-based and power flow calculations. TSAT is a framework for modeling and analysis of dynamic heat transfer. These packages all consist of graphical, drag-and-drop, parameterizable building blocks representing various components of the system to be modeled, e.g., compressors, turbines, motors, energy storage devices, etc. They are designed to enable the user to model and simulate the end-to-end dynamic operation of a hybrid electric gas turbine engine powertrain at the timescale of the turbomachinery, capturing mechanical, electrical, and thermal interactions. This paper demonstrates through multiple examples how these tools have been used successfully in a variety of applications, including several of the early stages of hybrid electric gas turbine engine propulsion system development, from the initial system modeling to real-time interactive pilot-in-the-loop simulation to physical hardware-in-the-loop testing, each step bringing the technology closer to fruition.

hybrid electric propulsion↗

NASA NTRSDate not supplied

Real World Applications of AI/ML in Optimizing Airspace Operations

As National Airspace System (NAS) is going through the Digital Transformation journey, data science and analytics methods can significantly contribute to improving the traditional physics-based decision-making tools. The adoption of AI/ML methods will not only help accelerate Federal Aviation Administration (FAA)’s vision of Info-centric NAS but also contribute to the overall objective of sustainable aviation. AI/ML can improve the ground and airspace operations by enhancing the accuracy of current decision-making tools used by the airlines and the FAA to manage traffic on the ground and in the air. Huge amount of data that gets collected during a flight. AI/ML methods can extract information from this data and provide valuable insights to make better operational decisions. NASA has partnered with the FAA and commercial airlines such as American and Southwest Airlines on this effort and has successfully demonstrated the benefits of using ML in real world environment by reducing delays and optimizing ground operations at the US airports. In 2022 itself, NASA demonstrated real-world benefits (over 24K lbs. of fuel savings, over 76.6K lbs. CO2 emission savings, and several hours of delay savings) by deploying ML based prediction models to optimize ground operations at Dallas/Fort Worth International and Dallas Love Field Airports in Texas. These tools are being deployed on the cloud for broader deployment, adaptability, and scalability. NASA is developed a reference implementation of the cloud-based platform to significantly lower the bar to development and distribution of these digital services for aviation. In this talk, I will share information about the Digital Information Platform project, the novel AI/ML based approaches used for optimizing ground operations and the opportunities to partner with NASA on these demonstrations.

air traffic management↗

NASA NTRSDate not supplied

Thermal Data-driven Model Reduction for Enhanced Battery Health Monitoring

Electric aviation faces a major challenge of avoiding potentially catastrophic consequences of the battery’s thermal runaway while keeping the weight of the battery low. Detection of early warning signals of battery failures requires accurate monitoring of the battery’s health throughout its lifespan. However, identifying the parameters of the battery from field data is notoriously difficult. We investigate this problem within the framework of modeling the temperature dynamics of a Li-ion cell during tests simulating loading in electric aircraft flights. It is found that the parameters of a higher-fidelity physics-based thermal model cannot be identified from the simulated flight data. To resolve this issue, we reduce the higher-fidelity thermal model to a model with fewer parameters. The resulting reduced-order model can predict temperature dynamics accurately and is identifiable throughout the cell’s lifespan which allows using the model’s parameters to monitor the state-of-health of the aging cell and detect anomalies in thermal behavior.

Li ion batteries↗

NASA NTRSDate not supplied

Pre-Flight Hazardous Gas Assessment Methodology for the Space Launch System

The complexity of the Artemis I liquid rocket propulsion systems produces many sources of hazards during the operation of the vehicle. Pre-flight hazardous gas leakages pose fire and explosion risks to rocket that could potentially lead to loss of the vehicle, mission, and crew. The National Aeronautics and Space Administration (NASA) uses a probability risk assessment strategy to assess the likelihood of the hazard and the consequence should the hazardous situation occur. For high probability hazards that pose a potentially catastrophic consequence to the vehicle, the most effective strategy for reducing the risk is accomplished by engineering and implementing systems that actively mitigate the hazard. A hazards analysis is completed to determine the likelihood and severity of each hazard. These hazard analyses are informed using relevant empirical data and physics-based analytical models. Time-accurate Computational Fluid Dynamics models used to quantify and understand the risks posed to Artemis I due to expulsions of hazardous gas near the vehicle. Several sources of hazardous gas that posed a risk to Artemis I during nominal pre-flight operations are analyzed in this work. The results of the analyses were used to develop flight rationale and make risk acceptance decisions for the Artemis I launch.

Brian R. Richardson↗

NASA NTRSDate not supplied

Comparison of the Nowcast of Aerospace Ionizing Radiation System (NAIRAS) With ISS Measurements

The Nowcast of Aerospace Ionizing Radiation System (NAIRAS) is a sophisticated physics-based model that has been providing real-time global predictions of cosmic radiation exposure, pertinent to both galactic and solar sources, to air travelers for a decade. The utility of NAIRAS, however, extends beyond the atmospheric ionizing radiation environment. The recently developed NAIRAS 3.0 version demonstrates an expansion of its domain to the space radiation environment. This extension incorporates an additional trapped inner belt proton source, coupled with altitude-dependent and rigidity-dependent geomagnetic shielding for galactic cosmic rays (GCR) and solar energetic particle (SEP) protons. The latest version of NAIRAS operates in two modes: real-time global predictions of the atmospheric radiation environment and a user-specified run-on-request service for global dosimetric calculations or predictions of dosimetric and particle flux quantities along user-uploaded flight path. It is available to the public at the Community Coordinated Modeling Center (CCMC). In this work, we present the validation exercises that have been conducted using the Automated Radiation Measurements for Aerospace Safety (ARMAS) onboard the International Space Station (ISS), thereby establishing NAIRAS's efficacy in predicting space radiation exposure. As such, NAIRAS 3.0 holds significant potential for human safety and technological advancement in aerospace travel and exploration.

Daniel Phoenix↗

NASA NTRSDate not supplied

Boundary Layer Data Assimilation and Interaction with Parameterizations in the NASA GEOS Model

The NASA Global Modeling and Assimilation Office develops the Goddard Earth Observing System (GEOS), which assimilates a wide range of observations to support medium range and seasonal forecasts and production of reanalyses like MERRA-2. In this talk we report on recent efforts to assimilate boundary layer (PBL) height observations derived from radiosondes, GNSS radio occultation, space-based lidar (CALIPSO, CATS, IceSat-2) and ground-based lidar (MPLNET). A novel component of this project includes examining the influence of model parameterizations on PBL profile estimates. We will discuss physics-based parameterizations of the PBL and how they may benefit or distort representation of PBL profiles in data assimilation. In particular, we consider the tendency of PBL parameterizations to compensate for analysis updates of state variables, effectively reducing the information retained from observations. We will present efforts to reduce this compensation in GEOS by using the PBL height analysis to adjust length scales used in the model PBL parameterizations.

Nathan P. Arnold↗

NASA NTRS2024

Considerations for Qualifying Reliable Eddy Current Array Technique for Detection of Backwall Cracks

A reliable nondestructive evaluation (NDE) technique provides minimum 90% probability of detection(POD) with 95% confidence for detection of cracklike flaws of a qualified size. In this case, the flaws are on backside of material. Eddy current array (ECA) probe or a single sensor eddy current probe in c-scanning mode is used for the flaw detection. Here, two geometries are considered for the test specimens. The two geometries are, a flat plate, and tube or pipe. The probe is assumed to be on outer diameter (OD)surface and the flaw is assumed to be at the inner diameter (ID) surface for tube inspection. The flaw and probe are on opposite side of wall thickness for inspection of plate material. The application may be used for acreage inspection or just for inspection of butt weld and heat affected zone (HAZ) in a tube, cylinder, or plate. The proposed approach is based on developing an instrument standardization or calibration procedure. Decision threshold of inspection procedure is determined using empirical qualification and noise data. The work explores essential parameters that are required to meet certain conditions to ensure reliable flaw detection. Physics-based simulation of eddy current array flaw detection is used to understand effect of essential parameters on signal response (amplitude and phase),and therefore flaw detectability. Simulation data is used to justify choice of calibration reference standard requirements and the qualification approach. An ECA technique qualification model is provided. The paper gives brief description of tasks to be completed for qualifying ECA technique for reliable detection of cracklike flaws.

Eddy current array inspection, nondestructive eval↗

NASA NTRSDate not supplied

The Effect of a SEP Event on Astronauts Doing a Spacewalk As Computed By the Nowcast of Aerospace Ionizing Radiation System (NAIRAS)

The Nowcast of Aerospace Ionizing Radiation System (NAIRAS) is a sophisticated physics-based model that has been providing real-time global predictions of cosmic radiation exposure, pertinent to both galactic and solar sources, to air travelers for a decade. The utility of NAIRAS, however, extends beyond the atmospheric ionizing radiation environment. The recently developed NAIRAS 3.0 version demonstrates an expansion of its domain to the space radiation environment. This extension incorporates an additional trapped inner belt proton source, coupled with altitude-dependent and rigidity-dependent geomagnetic shielding for galactic cosmic rays (GCR) and solar energetic particle (SEP) protons. The latest version of NAIRAS operates in two modes: real-time global predictions of the atmospheric radiation environment and a user-specified run-on-request service for global dosimetric calculations or predictions of dosimetric and particle flux quantities along user-uploaded flight path. It is available to the public at the Community Coordinated Modeling Center (CCMC). In this work, we present the computations of the dose in the ISS vicinity during the SEP event of August 8, 2023; which happened a day before a scheduled spacewalk. We demonstrate that astronauts would not have suffered a dose equivalent in excess of 1 mSv if the event happened a day later. As such, NAIRAS 3.0 holds significant potential for human safety and technological advancement in aerospace travel and exploration.

Guillaume Gronoff↗

NASA NTRS2024

Prediction of Concentrated Vortex Aerodynamics: Current CFD Capability Survey

Concentrated vortex flows contribute to the aerodynamic performance of aircraft at elevated load conditions. For military interests, the vortex flows are exploited at maneuver conditions of combat aircraft and missiles. For transport interests, the vortex flows are exploited at takeoff and landing conditions as well as at select transonic conditions. Aircraft applications of these vortex flows are reviewed with a historical perspective followed by a discussion of the underlying physics of a concentrated vortex flow. A hierarchy of computational fluid dynamics simulation technology is then presented followed by findings from a capability survey for predicting concentrated vortex flows with computational fluid dynamics. Results are focused on military and civil aircraft; only limited results are included for missiles. Opportunities for predictive capability advancement are then reported with comments related to digital transformation interests. A hierarchical approach that merges a physics-based perspective of the concentrated vortex flows with a systems engineering viewpoint of the air vehicle is also used to frame much of the discussion.

vortex flow↗

NASA NTRSDate not supplied

Thermal Modelling of the in-Situ Consolidation of Automated Fiber Placement of Thermoplastic Composites

NASA is developing carbon fiber reinforced thermoplastic composites processing methods under the Hi-rate Composites Aircraft Manufacturing (HiCAM) project. The in-situ consolidation automated fiber placement (AFP) of thermoplastics (ICAT) process has high potential to increase manufacturing throughput and lower costs as it combines the repeatability and fast lay down rates of AFP with the thermoformability of thermoplastic materials to achieve part consolidation out of the autoclave. Physics-based process models are employed in the ICAT process development to understand, fundamentally, the thermal response of the carbon fiber (CF)/polyaryletherketone (PAEK) material during the rapid heating and cooling associated with laser-assisted AFP. A one-dimensional (1-D) closed-form model was developed capable of predicting the temperature profile through-the-thickness of the tape material. In addition, a two-dimensional (2-D) model was developed to predict the heat transfer through-the-thickness and in the laydown x-direction of the AFP head motion. The solution of the Fourier heat-transfer equations in the 2-D model is approximated using the explicit finite difference numerical method. The temperature profile during placement of PAEK slit-tape materials at various laser target temperatures and placement speeds were measured during ICAT process development trials at Electroimpact®, Inc. †† and the resulting experimental data is compared with the predictions of the 1-D and 2-D models.

Thermoplastics↗

NASA NTRSDate not supplied

Immersive Technologies for Human-in-the-Loop Lunar Surface Simulations

NASA, the National Aeronautics and Space Administration, continually seeks innovative solutions to enhance its operations, particularly in the realms of testing, evaluation, and training for future missions. Immersive technologies, such as virtual, augmented, and mixed reality have proven to be powerful tools for immersing users in realistic, interactive, and engaging environments. This paper explores how the Simulation and Graphics Branch at NASA’s Johnson Space Center (JSC) leverages immersive technology, modern commercial rendering engines, and physics-based systems simulations to develop human-in-the-loop systems for humanity’s return to the Moon through the Artemis program. When NASA returns to the Moon, astronauts will travel to the Moon’s South Pole where lighting conditions will cause a more complex operational environment. Human-in-the-loop simulations play a crucial role in NASA’s mission planning, spacecraft and space systems development, and evaluation of operational scenarios. The development of immersive environments such as a lunar rover mockup at a video wall enables engineers and astronauts to simulate and experience mission scenarios, integrated spacecraft systems, and operational procedures in a relevant environment before deployment. By integrating realistic virtual environments, immersive technology allows for the visualization and interaction with virtual spacecraft models, mission landscapes, and complex operational tasks. This approach helps identify potential design flaws, operational challenges, and safety considerations. It also provides valuable insights for risk reduction and helps improve mission efficiency and effectiveness. With advanced motion tracking systems and custom virtual environments, data can be gathered and evaluated to help NASA refine training protocols, develop specialized training procedures, and optimize human-robotic interactions for future space missions. Furthermore, immersive technology offers opportunities for future training initiatives at NASA. The Virtual Reality Laboratory at JSC has pioneered training with Virtual Reality (VR) since the Hubble Space Telescope repair missions in the early 1990’s. Extended Reality (XR) simulations enable astronauts to rehearse complex spacewalks, spacecraft maneuvers, and extravehicular activities in a safe and controlled environment. By replicating the physical and cognitive challenges of space missions, immersive training experiences enhance astronauts’ situational awareness, decision-making abilities, and adaptability to unexpected scenarios. Additionally, immersive technology facilitates collaborative training, allowing geographically dispersed crew and mission control personnel to engage in synchronized simulations, fostering teamwork and effective communication. The adoption of immersive technology in NASA’s testing, evaluation, and future training programs has yielded significant benefits. By incorporating human-in-the-loop simulations for studies involving Extra Vehicular Activities (EVA), surface mobility and landing systems, NASA can identify and mitigate risks, optimize operational procedures, and enhance mission success. Ultimately, immersive simulation experiences can empower astronauts to better navigate the complexities of space missions, ensuring their safety, productivity, and success in the dynamic and challenging environments they will experience at the Lunar South Pole.

HITL↗

NASA NTRS2022

Shape Servoing of Deformable Objects using Adaptive Deformation Model Estimation

In this paper, we propose an adaptive shape servoing method to deform a soft object into a desired 3-D shape. The high dimensional representation and the unknown deformation properties of the soft object pose a challenge to actively manipulate its shape. To address this issue, we develop a method to compute the deformation Jacobian matrix in real-time. The Jacobian is estimated using a set of basis functions and its corresponding parameters to capture the dynamics of the system and relate the applied input motion to changes in the soft object's shape. An integral concurrent learning (ICL) based adaptive update law is derived using Lyapunov analysis to estimate the deformation parameters and prove its convergence. A physics-based simulation is used to validate the proposed method and controller by performing manipulation tasks with different desired configurations. The performance is compared with a standard gradient update law to demonstrate the accuracy and robustness of our approach.

Vrithik Raj Guthikonda↗

NASA NTRSDate not supplied

Laser Angle of Incidence Effects on in-Situ Consolidation of Automated Fiber Placement of Polyaryletherketone Composites

NASA and Electroimpact, Inc. ® in conjunction with other U.S. industry partners are performing research as a part of the NASA High-rate Composites for Aircraft Manufacturing (HiCAM) Project to fabricate thermoplastic panels using automated fiber placement (AFP) to increase manufacturing rates of aircraft structural composites. This work focuses on evaluating the in-situ consolidation AFP of thermoplastics (ICAT) process. Previous studies of the ICAT process using semi-crystalline, polyaryletherketone (PAEK) slit-tape have resulted in an adequate degree of intimate contact between plies; however, the resulting interlaminar strength have been less than laminates fabricated in an autoclave. To improve these properties, the effect of reducing the laser angle of incidence (AoI) during placement to increase the degree of auto-hesion was evaluated. The AoI of the laser assisted AFP head was varied between 12° and 16° to fabricate multiple quasi-isotropic and unidirectional test panels. Physics-based thermal models developed at the NASA Langley Research Center were utilized to predict the temperature profile. Laminate processing temperature was measured experimentally, and panel quality was evaluated by both non-destructive evaluation (NDE) as well as destructively by photo-microscopy. The effect on interlaminar strength was determined by short beam strength testing. Test results of carbon fiber laminates fabricated by ICAT using polyetheretherketone (PEEK), polyetherketoneketone (PEKK), and low-melt polyaryletherketone (LM-PAEK) at various laser angles of incidence, placement temperatures and placement speeds are presented.

Thermoplastic Composites↗

NASA NTRSDate not supplied

Evaluation of Finite Impulse Response Filters for Turbulence Effects on Sonic Booms

Turbulence effects on sonic booms lead to random variability of sonic boom waveforms measured on the ground, complicating the prediction of such waveforms using sonic boom propagation codes that do not account for turbulence effects. The NASA PCBoom software is one such code shown to accurately predict sonic booms above the atmospheric boundary layer but not those on the ground. Analyses of measured sonic booms show that, on average, the turbulence effects result in sonic boom loudness reduction, on average, that increases with propagation distance and turbulence strength. To efficiently account for such effects, a signal processing-based approach has been developed at NASA using finite impulse response filters derived from predicted waveforms by solving a nonlinear parabolic equation. Analyses indicate that the mean loudness reduction obtained using the filters does not increase with propagation distance or with increasing turbulence strength, in disagreement with flight test data. An alternative approach to the filters is currently under development employing the multiple scattering theory (MST) of wave propagation. Available results from the physics-based MST approach are used to evaluate the predictive capability of the filters, suggesting that the filters can severely underestimate the prediction of the MST approach.

sonic booms↗

NASA NTRSDate not supplied

Role of PHM in Autonomous Decision-Making: Aerospace applications

There is an increased need for onboard decision-making capabilities in cyber-physical systems be it in energy, automotive, aviation, space, or other industries as they aim for increased efficiency, resiliency, and mission assurance capabilities. Emerging next-gen technologies such as multi-rover planetary missions, distributed satellites, unmanned ground and aerial vehicle operations and smart grid systems rely on in-time risk assessment and autonomous decision-making. One critical piece of the autonomy puzzle is reliable prediction of system behavior under time-varying and potentially uncertain environmental conditions. Further, if agent states change during operation such as initiation of faults or degradation, reliable diagnostic tools need to be investigated. In this tutorial, we will revise approaches that integrates existing physics-based and data-driven models of agents interacting with probability models of the environment and component operation state. Role of existing PHM methodologies as they feed into decision-making under uncertainty will be studied. Balancing critical trade-offs between high-fidelity prognostic models, prediction time-horizons and the computational requirements for in-time cost-effective decision-making will be discussed through the implementation of surrogate models. Finally, the audience will be introduced to a real-time application of in-time trajectory planning of an unmanned aerial system (UAS) based on its PHM assessments under uncertain and varying wind conditions.

decision-making↗

NASA NTRSDate not supplied

Evaluation of Finite Impulse Response Filters for Turbulence Effects on Sonic Booms

sonic booms↗

NASA NTRSDate not supplied

Investigating Material Behavior in Atmospheric Entry Conditions: Arc-Jet Testing Insights from Meteorite Ablation to High-Temperature Coatings.

Arc-jet testing is an indispensable tool in elucidating the complex interactions materials undergo when subjected to the extreme thermal and mechanical stresses of atmospheric entry. By replicating these harsh conditions, arc-jets enable researchers to explore critical phenomena such as ablation, melting, and spallation, generating invaluable data that informs the development of sophisticated, physics-based models. These models are pivotal not only in predicting material performance for spacecraft re-entry systems but also in assessing the threat posed by celestial bodies as they encounter Earth’s atmosphere. One of the leading facilities for such investigations is the Hypersonic Materials Environmental Test System (HyMETS) at NASA’s Langley Research Center. A pioneering test campaign conducted at HyMETS focused on unraveling the ablation mechanisms of an ordinary chondrite meteorite (Tamdakht H5) and a terrestrial analog (basalt). These studies unveiled distinct material behaviors: Tamdakht demonstrated a remarkably stable melt flow, with mass loss primarily driven by the volatilization of elements such as iron and sodium, whereas basalt exhibited more aggressive surface degradation due to the rapid decomposition of hydrated minerals, culminating in significant spallation and surface material ejection. Beyond meteorite analysis, HyMETS has also been integral in the exploration of advanced Thermal Protection Systems (TPS) such as Phenolic Impregnated Carbon Ablator (PICA), a material with extensive flight heritage in missions like Stardust, Mars Science Laboratory, Mars 2020, and Osiris-REx. PICA, when coated with NuSil CV-1144-0—a polysiloxane resin designed to prevent particle shedding—undergoes a remarkable transformation upon heating. The resin pyrolyzes to form a thin, oxidation-resistant silicon oxycarbide layer that profoundly influences the material’s thermal response through a sophisticated four-stage process. Initially, the silicon oxycarbide acts as a formidable barrier, impeding reactive interactions with the PICA char and effectively suppressing surface temperature rise and material recession. However, as the heating persists, the protective layer decomposes via carbothermal reduction, exposing the underlying char, which in turn leads to a dramatic spike in surface temperature and accelerated material erosion. In the final stage, equilibrium is reached, with recession rates aligning with those of the virgin material. This intricate understanding of PICA-NuSil behavior under extreme conditions offers valuable insights, enhancing material response models and advancing the development of next-generation TPS for space exploration.

Chemistry↗

NASA NTRSDate not supplied

Surrogate Modeling of Subgrid Turbulent Transport Based on 3D Radiative Hydrodynamic Simulations of the Quiet Sun

Turbulent Transport: Plays a critical role in astrophysical plasmas, such as the solar interior, spanning multiple scales and challenging traditional modeling approaches. Objective: Develop machine learning (ML) models—MLP and CNN—to predict subgrid Reynolds stress tensors from StellarBox 3D simulations of the solar atmosphere. Benchmarking: Compare ML-driven models against physics-based Gradient and Smagorinsky approaches.

SMD↗