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Usage-based Lifing of Lithium-Ion Battery with HybridPhysics-Informed Neural Networks

Lithium-ion batteries are commonly used to power unmanned aircraft vehicles (UAVs).The ability to model and forecast the remaining useful life of these batteries enables UAV reliability assurance. Building accurate models for battery state of charge and state of health based on first principles is challenging due to the complex electrochemistry that governs battery operations and computational complexity required to solve them. Therefore, reduced order models are often used due to their ability to capture the overall battery discharge. Un-fortunately, these simplifications lead to residual discrepancy between model predictions and observed data. In this paper, we present a hybrid modeling approach merging reduced-order models and neural networks. In this approach, while most of the input-output relationship is captured by Nernst and Butler-Volmer equations, data-driven kernels reduce the gap between predictions and observations. We validate our approach using data publicly available through the NASA Prognostics Center of Excellence repository. Results showed that our hybrid battery prognosis model can be successfully calibrated, even with a limited number of observations.

Lithium-ion Battery

Wave Rotor Enhanced Nuclear (WREN) Propulsion: NASA Innovative Advanced Concepts (NIAC) - Phase I Final Report

Nuclear Thermal Propulsion (NTP) is identified as one of the preferred propulsion technologies for manned missions throughout the solar system (NASA MSFC).[1, 2] The state-ofthe-art NTP cycle is based on a solid core Nuclear Engine for Rocket Vehicle Application (NERVA)[3] class technology (Fig. 1) that is envisioned to provide a specific impulse of 900 seconds doubling chemical rocket performance (450 seconds). Even with this impressive increase, the NTP NERVA designs still have issues providing adequate initial to final mass fractions for high ΔV missions.[4] Nuclear Electric Propulsion (NEP) can provide extremely high Isp (2,000 to over 10,000 seconds) but with only low thrust and limits on mass to power ratios. The need for an electric power source also adds the issue of heat rejection in space where thermal energy conversion is at best 30-40% under ideal conditions. NASA Space Technology Mission Directorate (STMD) has recently expressed interest in finding advanced nuclear propulsion technology through the NASA Go:Thrust RFI.[5, 6] A novel Wave Rotor (WR) topping cycle has been proposed for our NASA NIAC concept. It promises to deliver similar thrust as NERVA class NTP propulsion, but with Isp in the 1,200-2,000 second range. Coupled with an NEP cycle, the duty cycle Isp can further be increased (1,800-4,000 seconds) with minimal addition of dry mass. This bimodal design enables fast transit trajectories for manned missions to Mars and revolutionizes the deep space exploration of our solar system.

Nuclear Thermal Propulsion

Numerical Predictions of the Flow and Heat Transfer Characteristics in the Film Boiling Regime During Tube Quenching

Cryogenic fluid management plays a major role in refueling of spacecrafts while in space for NASA’s future human space exploration missions. Due to the low boiling points of cryogens, storage, transport and handling of these fluids becomes difficult and may result in inefficient operation of the space propulsion systems. For refueling applications in space, the cryogenic fluids have to be transported across different locations and hence, the transfer of cryogenic fluids through pipes become critical. The cryogenic chill-down process is characterized by different regimes of flow boiling, viz., film boiling, transition boiling and nucleate boiling. The prediction of these regimes in a single CFD framework available in the literature is challenging and the present work attempts to address this challenge by initially modeling the film boiling regime accurately and to incorporate an user-defined function for transition and nucleate boiling at a later stage. Hence, the aim of the present work is to numerically model and validate the film boiling regime of the chilldown curve for liquid nitrogen experiments available in the literature. The validations are carried out at different inlet mass fluxes to have a robust simulation methodology. A dispersed mixture model is used to predict the vapor-liquid interface dynamics with the phase change phenomena modeled using the Lee model.

line chilldown

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka

In-Situ Heat Rejection to the Martian Atmosphere

In order to provide in-situ heat rejection to the thin Martian atmosphere, approaches relying on forced convection and buoyancy flow are conceptualized. A convective radiator concept utilizing a fan to draw local atmosphere through an expanded metal foam heat exchanger panel is developed. To provide a pumped fluid loop interface, flow tubes are embedded in the heat exchanger panel and heat is transferred from the tubes to the foam via conduction and subsequently convectively to the environment. To forgo the use of a specialized high throughput fan, a concept utilizing a buoyant chimney tower to draw atmospheric flow through a low pressure drop heat exchanger is also considered. Both concepts may best align with moderate- to high-temperature heat loads that provide a significant delta temperature relative to the ambient atmosphere temperature. While eliminating dust accumulation on radiator surfaces, some type of serviceable filtration or screening may be required to prevent accumulation of dust inside the expanded metal foam heat exchanger for both concepts.

Heat Rejection

Electromagnetic Melt Processing: A Pathway to New Additive Manufacturing Technologies for Functional High-Performance Thermoplastics

In this study, we apply the electromagnetic (EM) melt processing of thermoplastics on an innovative EM field-driven powder bed fusion additive manufacturing (AM) concept for high-performance functional parts: Selective Microwave Melting/Sintering (SMM/SMS). This technique leverages the EM susceptibility of carbon nanotube-coated polymer micro-pellets to achieve rapid, localized heating and powder fusion. Thus, selective microwave melting (SMM) was used to fabricate multilayer specimens made of recycled polyphenylene sulfide (rPPS) and carbon nanotubes (CNTs). The resulting SMM specimens exhibited very good interlayer integrity, localized fusion at pellet boundaries, and tolerable residual porosity, indicating effective fusion and acceptable consolidation. CNT-rich interphases were retained after irradiation, generating anisotropic electrically active network pathways and enabling conductivity enhancement at low filler content. At only 1.0 wt% CNT, the specimens exhibited electrical conductivity approximately three orders of magnitude higher than neat rPPS. Dynamic mechanical analysis showed improved viscoelastic response relative to neat rPPS, while tensile testing confirmed that the SMM-processed specimens retained practical mechanical integrity despite localized voids. These results demonstrate that SMM can effectively consolidate EM susceptible thermoplastic powder beds while preserving their segregated conductive networks. This may become a scalable route for producing multifunctional thermoplastic parts with low filler loadings, tunable anisotropy, and structured materials and parts. Overall, the findings suggest that EM field-based AM can help overcome key limitations of conventional thermoplastic processing by enabling scalable, energy-efficient fabrication of nanostructured composites and expanding AM to a broader range of resins, including high-performance thermoplastics with customized functional properties.

Powder bed fusion

Time-History Statistics of Soot Formation in A Model Gas Turbine Combustor

Soot formation is a complex dynamic and intermittent process determined by properties of the fuel, combustor design, and combustor operation. Although the major steps in soot formation (i.e., formation of precursors, inception, growth and evolution) are similar for a variety of carbonaceous fuels, applications, and operating conditions, it remains unclear when the temporal transition between these steps occurs. An engineering prediction tool coupled with computational fluid physics (CFD), therefore needs to accurately model all these complex steps. To develop such a model, we propose the time-history concept for understanding the time dependency of soot formation as a function of local properties (i.e., temperature, velocity, local fuel air ratio, etc.). We continue our previous work with modeling the DLR aero-combustor [1] with our updated in-house CFD code, Open National Combustion Code (OpenNCC), that now includes a Multiple Time-Scale Flamelet Progress Variable approach and a the semi-empirical two-equation soot model. We injected massless tracer particles upstream of the injector region of the combustor to collect time-history statistics of the solution variables. The correlations between the collected statistics with respect to the experimental soot volume fraction data showed that time-history effect of certain flow variables, including turbulent kinetic energy (TKE), and multiple species is indeed important for soot formation. We then conducted a time-history based correlation analysis to determine the key species and the concentration ranges critical for soot formation (C6H5-based nucleation, acetylene-based surface growth, and oxidation with OH and O2). Based on the time-history correlation coefficient (THCC) analysis, we propose possible modifications to improve the current two-equation model.

LES

Turbo-Design: Open-Source Radial Equilibrium Turbomachinery Solver: Part I - Turbines

Advances in 3D Geometrical Designs and Cooling have played a significant role in improving the efficiency of turbomachinery. However, these advancements must be effectively translated back to the modeler. Machine learning can facilitate this transition. Specifically, machine learning–based loss models can bridge the gap between 3D and 1D designs, enabling modelers not only to predict velocity triangles but also to extract additional geometric features. Currently, the design tools used at NASA have not been updated to support such integration—until now. TurboDesign is an open-source, Python-based framework that replaces TD2 (LEW-11029-1) and AXOD2 (LEW-16323-1), both of which are radial equilibrium solvers for axial turbines. The goal of this update is to enable the integration of machine learning loss models into radial equilibrium equations. Additionally, TurboDesign is designed to support radial machines. This paper presents the governing equations, the assumptions underlying the code, the integration of legacy loss models, an example of machine learning model integration, and a validation comparison with CFD. All code, tutorials, and documentation are available at: https://www.github.com/nasa/turbo-design

Radial Equilibrium

A Parametric Battery Model for the Conceptual Design of Electric Aircraft

Electric aircraft conceptual designs usually have an assumed specific power and specific energy for the aircraft’s energy storage system that dictates the total capacity and the peak power available. The specific energy and power are inherently linked to the state-of-charge and discharge rate from which they were derived; therefore, they will not directly correspond to the diverse circumstances encountered in various aircraft missions and flight segments. These parameters turn the battery system into a black box, disregard potential electrical restrictions, and disallow the aircraft and battery to be optimized as a system. Peering into this box, this study highlights the importance of incorporating a parametric battery model into the conceptual design workflow by splitting high-level terms such as power into voltage and current and investigating their variability during the discharge process. Through the modeling of these more detailed parameters, this methodology shows the feasibility of using low states-of-charge for contingency operations, including the end of the reserve mission, expanding the amount of usable capacity for electric aircraft. Stark differences in aircraft capabilities can arise between varying fidelity battery models due to late-mission, high-power flight operations. This parametric battery model effectively captures these differences by evaluating the limitations that arise within the individual battery cells and the aircraft powertrain. This paper shows that the unusable charge of a battery is set by the balked landing power requirement and can realistically range from 5% to 44% based on assumptions. This sets the analog to unusable fuel capacity in aircraft with liquid fuel systems. Needing only aircraft- and mission-level inputs and only seconds of run time, this model is a prime fit for the fast, accurate exploration of the electric aircraft conceptual design space.

Battery

Elastic-plastic models for multi-site damage

This paper presents recent developments in advanced analysis methods for the computation of stress site damage. The method of solution is based on the p-version of the finite element method. Its implementation was designed to permit extraction of linear stress intensity factors using a superconvergent extraction method (known as the contour integral method) and evaluation of the J-integral following an elastic-plastic analysis. Coarse meshes are adequate for obtaining accurate results supported by p-convergence data. The elastic-plastic analysis is based on the deformation theory of plasticity and the von Mises yield criterion. The model problem consists of an aluminum plate with six equally spaced holes and a crack emanating from each hole. The cracks are of different sizes. The panel is subjected to a remote tensile load. Experimental results are available for the panel. The plasticity analysis provided the same limit load as the experimentally determined load. The results of elastic-plastic analysis were compared with the results of linear elastic analysis in an effort to evaluate how plastic zone sizes influence the crack growth rates. The onset of net-section yielding was determined also. The results show that crack growth rate is accelerated by the presence of adjacent damage, and the critical crack size is shorter when the effects of plasticity are taken into consideration. This work also addresses the effects of alternative stress-strain laws: The elastic-ideally-plastic material model is compared against the Ramberg-Osgood model.

Actis, Ricardo L.

Characterizing the subglacial environment of lower Thwaites Glacier using radar modeling

Understanding the spatial heterogeneity beneath Thwaites Glacier, West Antarctica, is vital to projecting its impact on future sea levels. Radar-echo sounding (RES) is commonly used to infer subglacial conditions, but these data can be challenging to interpret. We assess basal heterogeneity across Thwaites Glacier by comparing RES returns to a radar backscattering simulator for over 400 km of RES data. The modeled variations in bed returned power exhibited a strong correlation with actual RES data in 40% of our simulated flight segments, which we consider evidence for a relatively homogeneous glacier bed. Other sites (40%) demonstrated improved fit quality when hydrology or substrate transitions were introduced in the bed material model. The remaining simulated segments (20%) were diagnosed as having more complex basal heterogeneity. The spatial distribution of complex heterogeneity appears to coincide with asymmetric patterns in the RES specularity content, which has been interpreted in previous studies as a signature for channelized hydrology. Conversely, the homogeneous substrate locations coincide with areas of fast-moving ice in western Thwaites. Our simulation method can isolate power variations induced by material heterogeneity vs topography, which is an important limitation of existing RES analysis methods.

Antarctic glaciology

Bosch Carbon Catalyst Regeneration in Water I: Bosch Carbon Removal from Reacted Beads Utilizing Mechanical Agitation

The ability to recover oxygen from metabolic carbon dioxide is crucial for crewed long duration missions in which the atmosphere must be recycled. Two physiochemical methods are primarily employed for this purpose: the Bosch process and the Sabatier reaction. This paper focuses on the Bosch process. It utilizes hydrogen in the presence of a catalyst to form water and solid carbon out of metabolic carbon dioxide. The solid carbon product deposits onto the catalyst and eventually causes reactor over pressurization issues. Multiple methods are currently being investigated to regenerate the catalyst’s surface and break up the pressure causing carbon clogs. This paper explores whether water and mechanical abrasion would work to remove Bosch carbon by testing multiple washing conditions. The different washing conditions involved agitation intensity, heating, duration, and volume of water. It was found that it is possible to break up the clumps of carbon formed in the reactor through agitation with room temperature water in one hour and shows promise for completely cleaning the carbon off the beads’ surface.

Agitation

A SIMULINK Environment for Flight Dynamics and Control Analysis - Application to the DHC-2 'Beaver', Part 1. Implementation of a Model Library in SIMULINK

The design of advanced Automatic Aircraft Control Systems (AACS's) can be improved upon considerably if the designer can access all models and tools required for control system design and analysis through a graphical user-interface, from within one software environment. This MSc-thesis presents the first step in the development of such an environment, which is currently being done at the Section for Stability and Control of Delft University of Technology, Faculty of Aerospace Engineering. The environment is implemented within the commercially available software package MATLAB/SIMULINK. The report consists of two parts. Part I gives a detailed description of the AACS design environment. The heart of this environment is formed by the SIMULINK implementation of a nonlinear aircraft model in block-diagram format. The model has been worked out for the old laboratory aircraft of the Faculty, the De Havilland DHC-2 'Beaver', but due to its modular structure, it can easily be adapted for other aircraft. Part I also describes MATLAB programs which can be applied for finding steady-state trimmed-flight conditions and for linearization of the aircraft model, and it shows how the built-in simulation routines of SIMULINK have been used for open-loop analysis of the aircraft dynamics. Apart from the implementation of the models and tools, a thorough treatment of the theoretical backgrounds is presented. Part II of this report presents a part of an autopilot design process for the 'Beaver' aircraft, which clearly demonstrates the power and flexibility of the AACS design environment from part I. Evaluations of all longitudinal and lateral control laws by means of nonlinear simulations are treated in detail. The AACS design environment from part I proved to be a very useful tool for designing the control laws of the 'Beaver' autopilot within a very tight time-schedule. The autopilot design process itself will be used as a guideline for future AACS research at the Faculty of Aerospace Engineering. Flight tests of the 'Beaver' autopilot, done after evaluating the control laws in the SIMULINK package, proved to be quite successful. In the future, the AACS design package will evolve into a standardized, integrated design environment which can be applied to virtually any type of aircraft. The AACS design cycle will be shortened further by developing tools for automatically porting control laws from the MATLAB/SIMULINK environment to a piloted real-time flight simulator and the Flight Control Computers of the aircraft.

Aircraft Modelling

A Transient Hydrodynamic Model of Screen Channel Liquid Acquisition Devices for In-Space Cryogenic Propellant Management

Screen channel liquid acquisition devices (LADs) will play a crucial role in future deep space travel. It is essential that vapor-free delivery of propellants during tank-to-tank transfer is ensured to maximize yield from storage tanks and prevent potential combustion instabilities. The screen channel LAD utilizes a fine screen wire mesh that can separate phases in a low Bond number (i.e. microgravity) environment using surface tension forces. This study presents the development and verification of a new model for transient screen compliance, one of the influential factors for screen channel LAD design. Screen compliance is crucial during LAD channel outflow transients because the slight deflection of the screen can provide needed mass to satisfy rapid outflow demands and reduce the pressure difference across the screen. The model is successfully verified against CFD simulations. In addition, the characteristic speed for the governing screen compliance equations is derived which allows for numerical stability criteria to be established. As shown in this study, the transient maximum pressure difference across the screen can greatly exceed the steady state maximum pressure difference across the screen in many cases.

Hydrodynamics Simulations

Earth Observations and Integrative Models in Support of Food and Water Security

Global food production depends upon many factors that Earth observing satellites routinely measure about water, energy, weather, and ecosystems. Increasingly sophisticated, publicly-available satellite data products can improve efficiencies in resource management and provide earlier indication of environmental disruption. Satellite remote sensing provides a consistent, long-term record that can be used effectively to detect large-scale features over time, such as a developing drought. Accuracy and capabilities have increased along with the range of Earth observations and derived products that can support food security decisions with actionable information. This paper highlights major capabilities facilitated by satellite observations and physical models that have been developed and validated using remotely-sensed observations. Although we primarily focus on variables relevant to agriculture, we also include a brief description of the growing use of Earth observations in support of aquaculture and fisheries.

Water Resources

Chapter 9 - Pre-Flight Tests

Pre-flight testing is critical to the success of any flight test program. Pre-flight tests are performed to measure and evaluate the characteristics of an aircraft in a non-flying environment and to verify that these characteristics are as desired. Since aircraft systems are becoming more and more complex, conducting proper pre-flight testing to help identify system characteristics and deficiencies prior to flight is more important now than ever before. Much flight test time has been lost fixing problems that should have been found and corrected prior to flight. Accidents have occurred because pre-flight tests and verification procedures were not conducted thoroughly enough to identify the aircraft's characteristics properly or to find system discrepancies. Proper pre-flight testing helps ensure that the aircraft is ready to fly and contributes toward an efficient, productive, and safe flight test program. The reader should be aware that this Section is dedicated to the testing that should take place prior to the first flight. There are other "pre-flight" tests that take place prior to each individual flight. These latter tests are not discussed in this Section. The following paragraphs of this Section describe significant tests that are usually accomplished prior to flying a new or highly modified aircraft. Test objectives, descriptions, products, and requirements are provided in the following subsections: 9.1 Wind tunnel tests 9.2 Simulation tests 9.3 Propulsion tests 9.4 Weight and balance tests 9.5 Ground vibration tests 9.6 Structural loads tests 9.7 Gain margin tests 9.8 Verification and calibration tests 9.9 Taxi tests The specific examples given and the test facilities mentioned in this Section will illustrate the approach taken and the techniques used by the US Air Force; however, they are typical of those used by other test organizations.

Paul W Kirsten

Photophoretic Propulsion Enabling Mesosphere Exploration NIAC Phase I Final Report

This Phase I report presents a comprehensive study on photophoretic flyers—innovative, ultralight, solar-powered vehicles that harness photophoretic forces generated via Knudsen pumping to achieve sustained flight in the mesosphere (50–80 km altitude). By integrating advanced materials such as nanocardboard— characterized by its extremely low areal density (~1 g/m²) and high bending stiffness—with ultrathin light-absorbing coatings, the project converts incident solar radiation directly into a directed thrust. Extensive experimental investigations, coupled with high-fidelity computational fluid dynamics (CFD) simulations using ANSYS Fluent, validate the concept across various three-dimensional geometries, including spherical, conical, and rocket-shaped configurations. These simulations bridge the gap between free-molecular and continuum flow regimes, demonstrating that optimized designs can generate lift forces sufficient to support kilogram-scale payloads even in low-pressure environments. At the heart of this innovation is the use of Knudsen pumping, where temperature gradients across porous surfaces induce directional gas flow, creating a modest overpressure that provides lift. The report introduces an analytical framework that interpolates between the well-known low-Reynolds number drag regime and the high-Reynolds number momentum theory. This model accurately predicts lift based on design parameters such as microchannel dimensions, porous wall geometry, areal density, and nozzle exit area. For instance, simulations indicate that 10-meter-scale structures with carefully engineered porous walls can achieve the necessary pressure differential to support scientifically significant payloads (~1 kg). The study also explores a hybrid propulsion approach that combines solar buoyancy with photophoretic lift. Initially, solar heating creates a buoyant force that elevates the flyer to mesospheric altitudes. Once in the optimal pressure range, the photophoretic mechanism—powered by Knudsen pumping—takes over as the primary source of lift, ensuring stable, long-duration flight. This dual-mode operation not only facilitates the deployment of photophoretic flyers but also broadens the potential applications for mesospheric exploration. In addition to propulsion, the report investigates the integration of photophoretic thrusters for trajectory control of existing research balloons in the upper stratosphere. By dynamically adjusting the nozzle orientation and controlling the flow-through velocity, these thrusters provide precise maneuverability, enabling the flyers to counteract atmospheric disturbances and adjust their flight paths in real time. For example, a photophoretic thruster approximately 7.5 by 7.5 meters in size could be unfolded below a payload gondola of a 60 million-cubic-foot zero-pressure balloon. Such a thruster can provide horizontal speed control of approximately 1 m/s using only sunlight and no moving parts (except those needed to track the Sun and control the jet direction). Importantly, photophoretic thrusters operate more efficiently at higher altitudes, which is complementary to known trajectory control techniques, such as propellers and tethered wings, which are more effective at lower altitudes. Finally, the report identifies three scientific research thrusts where mesospheric aircraft technology can have a profound impact: atmospheric tides, characterization of gravity waves, and investigation of mesospheric instabilities. Overall, the findings of this Phase I project represent a significant advancement in photophoretic propulsion technology. By demonstrating that large-scale, ultralight structures can be powered solely by solar radiation—via carefully engineered Knudsen pumping—this work lays a robust foundation for scalable, near-space flight architectures. Future refinements in material fabrication, structural optimization, and integrated trajectory control are expected to further enhance performance, paving the way for operational demonstrations that could revolutionize atmospheric science, remote sensing, and communication networks.

Knudsen Pump

Integrated Process-Structure-Property Simulations for Additive Manufacturing Using the Open-Source Materialite Package

The microstructure and properties of additively manufactured (AM) metals are strongly dependent on process conditions. Therefore, process-structure-property (PSP) simulations are a useful tool for exploring process parameter space, studying process variations, and quantifying uncertainty in material properties. However, integrating process-structure and structure-property simulations often involves connecting multiple software packages. Each package may use unique data structures and require substantial domain knowledge. This presentation demonstrates PSP simulation capabilities of Materialite, an open-source package developed at NASA Langley Research Center. Materialite simplifies model linkages by using a common data structure and model interface, enabling straightforward simulation across a PSP model chain. Physics-based models, including kinetic Monte Carlo and crystal plasticity, are implemented within the package. The model interface is also intended to simplify implementation of new models and enable integration with external simulation tools. Example use cases include uncertainty quantification with PSP models and GPU-accelerated powder bed fusion AM process models.

additive manufacturing