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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

Bond Line Thickness Estimation in Composite Structures Using Multiple Inspection Techniques

Imaging and other nondestructive evaluation techniques are commonly used for material characterization and defect recognition in safety critical aerospace applications, with data fusion providing the framework for uncertainty quantification in these contexts. Most commonly, forward physics-based modeling predicts the response conditioned on material properties and defect assumptions, and probabilistic methods are used to infer the hidden state of subject of the inspection from a combination of prior information, likelihoods, and inspection data. In this paper Bayesian methods are used to estimate bond thickness in lap joints comprised of aluminum adherends using a combination of infrared thermography, digital radiography, and ultrasound. The accuracy of the fused estimates are validated against data generated from synthetic specimens, and by comparison against high resolution X-ray computed tomography inspections of built specimens.

thermal nondestructive evaluation↗

NASA NTRSDate not supplied

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

Christopher J. Stelter↗

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 NTRS2024

Commercial Crew Program (CCP) Post-flight Reference Radiation Environments

The Nowcast of Aerospace Ionizing RAdiation System (NAIRAS) model version 3 is a coupled physics-based model that transports ionizing radiation through the heliosphere, Earth’s magnetosphere, the neutral atmosphere, and aircraft and spacecraft shielding. Ionizing radiation sources included in the model are: 1) galactic cosmic rays, 2) solar energetic particles including protons and heavy ions, and 3) the inner radiation belt trapped protons and electrons. NAIRAS predicts dosimetric quantities and differential and integral flux and fluence quantities for assessing human radiation exposure and single event effects in vehicle electronic systems from the Earth’s surface to the space environment.

Christopher J Mertens↗

NASA NTRSDate not supplied

Development of Computational Materials Workflows for Additively Manufactured Metallic Materials to Enable Accelerated Prediction of Fatigue Performance

The maturation of computational materials approaches for fatigue performance prediction in a qualification and certification process is stifled by the ability to validate complex, microstructure-based simulations. Such a validation strategy bears immediate challenges including generating accurate virtual microstructures, efficiently solving physics-based mechanical simulations over relevant spatial and temporal scales, and acquiring high-fidelity calibration and validation data at the appropriate length scale. This presentation will overview these common challenges and present a case study to demonstrate a computational materials workflow for additively manufactured metallic materials. In this study, process-specific defects are characterized using segmented X-Ray micro-computed tomography measurements and overlaid on virtual microstructures. Accelerated crystal plasticity-based fatigue simulations are performed to demonstrate cyclic evolution and localization of mechanical fields in the vicinity of defects in response to their precise spatial configuration. An example of how this computational materials workflow may support next-generation qualification is discussed.

computational materials↗

NASA NTRSDate not supplied

Towards Surrogate Modeling of Subgrid Turbulent Transport for 3D Radiative Hydrodynamic Simulations of the Quiet Sun

In this work, we investigate the use of deep learn-ing techniques as surrogate models, to enhance the estimationof effects of subgrid turbulent transport for 3D radiatuve hy-drodynamic simulations of the quiet Sun. We develop two dis-tinct 3D Convolutional Neural Networks (3DCNNs) to capturespatio-temporal dependencies in 3D velocity fields, leveragingdifferent activation functions and architectural designs. Thesemodels integrate both averaged velocity vector components andscalar features such as plasma density to enhance predictionaccuracy. Additionally, a Multilayer Perceptron (MLP) modelis employed to approximate complex nonlinear relationships,offering a comparison in performance between convolutionaland fully connected architectures. Logarithmic transformationis applied to the targets to handle heavily skewed data, im-proving model performance. All models are compared againsta physics-based Gradient Model. Results show that the 3DCNNmodels excel at approximating Reynolds stress tensors, makingthem a candidate for assisting in producing reduced resolutionsimulations, and thereby reducing computational overheadwhile maintaining higher accuracy than the baseline. Thesefindings demonstrate the potential of deep learning, particu-larly CNNs, to advance scalable and accurate simulations ofsolar dynamics, offering a promising alternative to traditionalturbulence models.

Heliophysics↗

NASA NTRSDate not supplied

Evaluation of the Recent Improvements of the Nowcast of Aerospace Ionizing Radiation System (NAIRAS)

The Nowcast of Aerospace Ionizing Radiation System (NAIRAS) model is a real-time, global, physics-based model used to assess radiation exposure now running in real-time and in run on request (RoR) mode at NASA Goddard’s Community Coordinated Modeling Center. NAIRAS was recently updated to extend the galactic cosmic ray (GCR) model to include ultra-heavy nuclei (Z=29-92, A=64-238) for single event effects assessment from high linear energy transfer processes, to expand the geomagnetic cutoff rigidity model to use the either the TS05 (Tsyganenko and Sitnov, 2005), T89 (Tsyganenko, 1989), or the International Geomagnetic Reference Field model (IGRF) magnetic field models, and to improve the solar energetic particle (SEP) proton spectral fitting to better represent relativist protons during ground level enhancements. Here, we evaluate the recent NAIRAS improvements for a range of conditions. First, we demonstrate the effect of choice in magnetic field model to the NAIRAS computed dosimetric quantities for a United States domestic flight and a transatlantic flight during the May 11, 2024 SEP event. Second, the effect of ultra-heavy ions on SEP dose rate is examined for two different flight trajectories during the top SEP events. Lastly, the effect of ultra-heavy ions on NAIRAS computed GCR dose rates at solar minimum and maximum is demonstrated.

Daniel B Phoenix↗

NASA NTRS2024

Stellar Occultation Observations to Constrain the Stratosphere of Uranus for Aerocapture

Background on Uranus: Voyager 2 (V2) UV stellar and solar occultations at Uranus detected a warm stratosphere and extremely hot thermosphere [1, 2], far in excess of solar irradiance [3, 4] and internal heating [5, 6]. New theories to explain similar heating at Jupiter [7] and Saturn [8] cannot be tested at Uranus due to a dearth of reliable measurements. In [9, 10], we reprocessed 26 archival Earth-based stellar occultations by Uranus (1977-1996), finding stratospheric temperatures (~200 K) warmer than the original (~100 K), but in stark tension with V2 (~300-500 K). In [10], we built a physics-based, 1-D atmospheric model (see Fig 1) that finds a nearly isothermal stratosphere and a dynamic heat sink in the lower thermosphere. Aerocapture: Aerocapture is spacecraft maneuver that uses a single deep dip to enter orbit. It could decrease cruise time and launch mass for a Uranus mission, but the greatest impediment is uncertain stratospheric densities of Uranus [11]. Aims: 1) Observe and process many high S/N Uranus stellar occultations in the next decade; 2) constrain stratospheric densities for aerocapture; 3) better understand the energy balance; 4) determine stratospheric changes since 1996. Upcoming Occultations: We will present our observing plan for the 2025 April Uranus occultation (K mag 8) and discuss the best-in-a-century 2031 event (K mag 4). We will discuss other events in the early 2030s [12] [13], predicted constraints on density, and simulations of aerocapture for UOP. We will discuss the Shadow Chaser, a small satellite concept for observing occultations from Earth orbit [12]. Conclusions: New stellar occultations can vastly improve profiles of the stratosphere of Uranus; this is critical for understanding energy circulation and constraining densities for using aerocapture on UOP. References: [1] Herbert, F. et al. (1987). JGR. [2] Stevens, M. et al. (1993). Icarus. [3] Marley, M. & McKay, C. (1999). Icarus, [4] Li, C. et al. (2018). JQRST. [5] Pearl, J. et al. (1990). Icarus. [6] Melin, H (2020). Nat Astron. [7] O’Donoghue, J. et al. (2021) Nature. [8] Mueller-Wodarg, I. et al. (2019) GRL. [9] Saunders, W. et al. (2023). PSJ. [10] Saunders, W. et al. (2024). PSJ. [11] Report of the Aerocapture Demonstration Relevance Assessment Team (2023). [12] Saunders, W. et al. (2022). P&SS. [13] French, R. & Souami, D. (2023) PSJ.

William Saunders↗

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↗

NASA NTRS2024

Storm-Time Variability of Terrestrial Hydrogen Exosphere: Kinetic Simulation Results

Recent studies of TWINS Lyman-α observations have reported an increase in geocoronal column brightness during geomagnetic storms, indicating enhanced exospheric hydrogen atom density (NH). This suggests a complex role of exospheric neutrals in determining storm-time magnetosphere dynamics and their energy release through charge-exchange processes. We developed a Model for Analyzing Terrestrial Exosphere (MATE) to investigate storm-time exospheric behaviors and their physical drivers. MATE traces test hydrogen atoms backward in time from locations in the exosphere to a nominal exobase altitude of 500 km, employing Newtonian mechanics with gravitational force. The model then calculates the phase-space densities (PSDs) of test hydrogen atoms at the exobase using the Maxwellian distribution with physics-based exobase conditions from the TIMEGCM upper atmosphere model. MATE maps PSDs at the exobase to the exosphere using Liouville’s Theorem under collisionless assumptions and derives NH by integrating the PSDs across velocity space. We conducted MATE simulation before, during, and after a minor geomagnetic storm from 12 to 18 June 2008, and compared the model results with NH estimates from the TWINS geocorona data. MATE reproduces storm-time density enhancements soon after the minimum Dst is reached, matching well with a general trend of TWINS NH estimates. The results suggest that upper atmospheric heating during a geomagnetic storm increases the number of ballistic and escaping hydrogen atoms entering the exosphere from the exobase, thereby boosting NH. However, the magnitude of modeled NH mismatches the TWINS NH estimates. The potential mechanisms of this density discrepancy include the physics excluded in the MATE model — such as neutralneutral collisions, neutral-plasma charge exchange, solar radiation pressure, and photoionization — as well as the higher exobase hydrogen density of TIMEGCM compared to typical empirical values, which will be addressed in future.

Hyunju K Connor↗

NASA NTRS2024

Control Effectiveness: Metric Development and Application to Resilient Lunar Habitat Design

System safety engineering in its bare essence involves identifying, assessing, and mitigating, or controlling, hazards. Appropriate safety controls are selected using hazard reduction precedence principles, prior experience, or by assessing their impact on residual risk (together with other factors like cost). We propose a control effectiveness metric as one way to systematically and consistently evaluate potential safety controls individually and thereby facilitate selecting a shortlist of potential controls for subsequent integrated evaluation. The control effectiveness metric considers a safety control’s availability when needed, the probability that its design is adequate in addressing the targeted hazard, the probability that the design will be implemented as intended, and the relationship between the time it takes for the safety control to address its target hazard and the time before the hazard propagates. We demonstrated the use of our metric on a lunar habitat design using a physics-based habitat simulator. High control effectiveness and safety controls result in a habitat with high resilience, while low control effectiveness results in lower resilience.

Rashi Jain↗