Search NASA⌕ Search

SEARCH · Search NASA

Results for “aerospace robotics”

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.

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

At least 199 records · Page 11

Advanced EVA Capabilities: A Study for NASA's Revolutionary Aerospace Systems Concept Program

This report documents the results of a study carried out as part of NASA s Revolutionary Aerospace Systems Concepts Program examining the future technology needs of extravehicular activities (EVAs). The intent of this study is to produce a comprehensive report that identifies various design concepts for human-related advanced EVA systems necessary to achieve the goals of supporting future space exploration and development customers in free space and on planetary surfaces for space missions in the post-2020 timeframe. The design concepts studied and evaluated are not limited to anthropomorphic space suits, but include a wide range of human-enhancing EVA technologies as well as consideration of coordination and integration with advanced robotics. The goal of the study effort is to establish a baseline technology "road map" that identifies and describes an investment and technical development strategy, including recommendations that will lead to future enhanced synergistic human/robot EVA operations. The eventual use of this study effort is to focus evolving performance capabilities of various EVA system elements toward the goal of providing high performance human operational capabilities for a multitude of future space applications and destinations. The data collected for this study indicate a rich and diverse history of systems that have been developed to perform a variety of EVA tasks, indicating what is possible. However, the data gathered for this study also indicate a paucity of new concepts and technologies for advanced EVA missions - at least any that researchers are willing to discuss in this type of forum.

Hoffman, Stephen J.↗

Research and test facilities

A description is given of each of the following Langley research and test facilities: 0.3-Meter Transonic Cryogenic Tunnel, 7-by 10-Foot High Speed Tunnel, 8-Foot Transonic Pressure Tunnel, 13-Inch Magnetic Suspension & Balance System, 14-by 22-Foot Subsonic Tunnel, 16-Foot Transonic Tunnel, 16-by 24-Inch Water Tunnel, 20-Foot Vertical Spin Tunnel, 30-by 60-Foot Wind Tunnel, Advanced Civil Transport Simulator (ACTS), Advanced Technology Research Laboratory, Aerospace Controls Research Laboratory (ACRL), Aerothermal Loads Complex, Aircraft Landing Dynamics Facility (ALDF), Avionics Integration Research Laboratory, Basic Aerodynamics Research Tunnel (BART), Compact Range Test Facility, Differential Maneuvering Simulator (DMS), Enhanced/Synthetic Vision & Spatial Displays Laboratory, Experimental Test Range (ETR) Flight Research Facility, General Aviation Simulator (GAS), High Intensity Radiated Fields Facility, Human Engineering Methods Laboratory, Hypersonic Facilities Complex, Impact Dynamics Research Facility, Jet Noise Laboratory & Anechoic Jet Facility, Light Alloy Laboratory, Low Frequency Antenna Test Facility, Low Turbulence Pressure Tunnel, Mechanics of Metals Laboratory, National Transonic Facility (NTF), NDE Research Laboratory, Polymers & Composites Laboratory, Pyrotechnic Test Facility, Quiet Flow Facility, Robotics Facilities, Scientific Visualization System, Scramjet Test Complex, Space Materials Research Laboratory, Space Simulation & Environmental Test Complex, Structural Dynamics Research Laboratory, Structural Dynamics Test Beds, Structures & Materials Research Laboratory, Supersonic Low Disturbance Pilot Tunnel, Thermal Acoustic Fatigue Apparatus (TAFA), Transonic Dynamics Tunnel (TDT), Transport Systems Research Vehicle, Unitary Plan Wind Tunnel, and the Visual Motion Simulator (VMS).

Source record↗

Material Removal and Surface Integrity Analysis of Ti6Al4V Alloy after Polishing by Flexible Tools with Different Rigidity

Ti6Al4V alloy has been widely used in many fields, such as aerospace and medicine, due to its excellent biocompatibility and mechanical properties. Most high-performance components made of Ti6Al4V alloy usually need to be polished to produce their specific functional requirements. However, due to the material properties of Ti6Al4V, its polishing process still requires significant development. Therefore, this study aimed to investigate the performance of polishing Ti6Al4V by using tools with different rigidities. Two kinds of bonnet tool were used, namely a pure rubber (PR) bonnet and a semirigid (SR) bonnet. The characterization of material removal and surface integrity after polishing was conducted through a series of experiments on a 6-DOF robotic polishing device. The results demonstrate that both bonnet tools successfully produce nanometric level surface roughness. Moreover, the material removal rate of the SR bonnet tool is significantly higher than that of the PR bonnet, which is consistent with the material removal characteristics of glass polishing in previous research. In addition, the presented analysis on key polishing parameters and surface integrity lays the theoretical foundation for the polishing process of titanium alloy in different application fields.

36 MATERIALS SCIENCE↗

A Tailored Concept of Operations for NASA LSP Integrated Operations

An integral part of the Systems Engineering process is the creation of a Concept of Operations (ConOps) for a given system, with the ConOps initially established early in the system design process and evolved as the system definition and design matures. As Integration Engineers in NASA's Launch Services Program (LSP) at Kennedy Space Center (KSC), our job is to manage the interface requirements for all the robotic space missions that come to our Program for a Launch Service. LSP procures and manages a launch service from one of our many commercial Launch Vehicle Contractors (LVCs) and these commercial companies are then responsible for developing the Interface Control Document (ICD), the verification of the requirements in that document, and all the services pertaining to integrating the spacecraft and launching it into orbit. However, one of the systems engineering tools that have not been employed within LSP to date is a Concept of Operations. The goal of this project is to research the format and content that goes into these various aerospace industry ConOps and tailor the format and content into template form, so the template may be used as an engineering tool for spacecraft integration with future LSP procured launch services.

Systems↗

Tailoring a ConOps for NASA LSP Integrated Operations

An integral part of the Systems Engineering process is the creation of a Concept of Operations (ConOps) for a given system, with the ConOps initially established early in the system design process and evolved as the system definition and design matures. As Integration Engineers in NASA's Launch Services Program (LSP) at Kennedy Space Center (KSC), our job is to manage the interface requirements for all the robotic space missions that come to our Program for a Launch Service. LSP procures and manages a launch service from one of our many commercial Launch Vehicle Contractors (LVCs) and these commercial companies are then responsible for developing the Interface Control Document (ICD), the verification of the requirements in that document, and all the services pertaining to integrating the spacecraft and launching it into orbit. However, one of the systems engineering tools that have not been employed within LSP to date is a Concept of Operations. The goal of this paper is to research the format and content that goes into these various aerospace industry ConOps and tailor the format and content into template form, so the template may be used as an engineering tool for spacecraft integration with future LSP procured launch services. This tailoring effort was performed as the authors final Masters Project in the Spring of 2016 for the Stevens Institute of Technology and modified for publication with INCOSE (Owens, 2016).

Knowledge↗

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments [Slides]

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. The ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

14 SOLAR ENERGY↗

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. Our ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

artificial intelligence↗

Advanced Curation Development of Tools and Methods for Microparticle Curation

The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center is currently developing new tools and methods for the collection, storage, handling and characterization of particles less than 100 microns in diameter, or microparticles. Astromaterials Curation currently maintains four microparticle collections: Cosmic Dust that has been collected in Earth’s stratosphere by ER2 and WB-57 aircraft, Comet 81P/Wild 2 dust returned by NASA’s Stardust spacecraft, interstellar dust that was returned by Stardust, and asteroid Itokawa particles that were returned by the JAXA (Japan Aerospace Exploration Agency)’s Hayabusa spacecraft. NASA Curation is currently preparing for the anticipated return of two new astromaterials collections – asteroid Ryugu regolith to be collected by Hayabusa II spacecraft in 2021 (samples will be provided by JAXA as part of an international agreement), and asteroid Bennu regolith to be collected by the OSIRIS-REx (Origins Spectral Interpretation Resource Identification Security - Regolith Explorer) spacecraft in 2023. In order to maximize the scientific yield from these valuable acquisitions, it will be necessary to develop methods that extend our current microsample handling capabilities. Here we describe recent progress in the development of sample handling techniques that will enhance our microparticle curation capabilities. Further described are: Six-Axis Robot Arms for Particle Manipulation, and Charge-Dissipative Substrates.

Snead, Christopher↗

Pneumatic Sampler (P-Sampler) for the Martian Moons Exploration (MMX)

The Martian Moons eXploration (MMX) mission, led by the Japanese Aerospace Exploration Agency (JAXA), will focus on the exploration of the two Martian moons – Phobos and Deimos (Figure 1). The spacecraft will perform close-up remote sensing and observations of both moons and collect a sample from Phobos for Earth sample return. MMX has set the two mission goals: (1) determining the origin of the Martian moons and (2) observing processes in the circumplanetary environment of Mars, based on remote sensing, in-situ observations, and laboratory analyses of returned samples of Phobos regolith [1-2]. To fulfill the mission goals, MMX employs a double sampling approach: Coring and Pneumatic Samplers (Figure 2).The Coring Sampler (C-Sampler), a core soil tube deployed by a robotic arm, providing access to the building blocks of Phobos beneath the surface (>2 cm), and also collect a mixture of near surface material. The P-Sampler, on the other hand, would selectively sample the surface veneer and provides reference of surface component with the C-Sampler. The double sampling system not only enhances the scientific merits of MMX but also reduces risks associated with the sampling of Phobos. Without enough knowledge of the physical and chemical properties, and the geotechnical conditions of the surface of Phobos (e.g., compositions, temperature gradient/variation, porosity, grain size distribution), having two sampling systems that utilize entirely different sampling approaches is prudent.

Dylan Van Dyne↗

Playbook for UAS: UX of Goal-Oriented Planning & Execution

We are evaluating Playbook for CASAS (Connected Autonomous Smart Aerospace Systems), a tool designed to aid first responders in disaster relief efforts. We are adapting an existing tool, Playbook, to support a future unmanned aircraft system (UAS) swarm demonstration. Playbook for CASAS will be used to plan, edit, and monitor simulated UAS swarms, and we are interested in evaluating the user experience of this prototype as well as developing recommendations for future UAS interfaces. Allocation of roles and responsibilities between human-automation systems is key to promoting productive cooperation between users and automation. Future interfaces, however, must allow for adaptive management of the swarm not a constant split in human-automation control. Our early research indicates that when a single pilot is controlling swarms of robotic agents, such as UAS or ground rovers, operators require a higher level, goal-based interface with usability at its core. Along with that high-level control, users can leverage sensors within the swarm to be notified when lower level actions must be taken by the pilot. First responders working in disaster relief efforts require a high level of situational awareness (SA) and precise control at key moments within a mission. This balance in operator workload paired with SA can lead to improved safety and mission outcomes. Our research below outlines leverage points as well as the balance between human involvement and autonomy in UAS interfaces.

UAS↗

Mineralogical, Elemental, and Tomographic Reconnaissance Investigation for CLPS (METRIC)

METRIC is a robotic science laboratory that can determine the mineralogy, elemental chemistry, micromorphology, and thermophysical properties of planetary regolith. The METRIC suite comprises METRIC XRD/F, an X-ray diffraction/X-ray fluorescence instrument that can determine the mineralogy and elemental chemistry of regolith samples; METRIC XCT, a micro X-ray computed tomography instrument that can be used to evaluate grain/crystallite sizes and textures; METRIC IRS, an imaging spectrometer mounted on a rover that can determine mineralogy and thermophysical properties at the landing site; and a pneumatic sample collection, processing, distribution system developed by Honeybee Robotics. The payload elements could be deployed on a static lander or a rover. Data returned from the METRIC payload would inform origin, formation, and evolution of rocky planetary bodies. METRIC XRD/F draws on heritage from the CheMin instrument on the Mars Science Laboratory (MSL) Curiosity rover [1], with a few important improvements. Like CheMin, METRIC XRD/F operates in transmission geometry and uses piezoelectric actuators on sample cells in a tuning fork geometry to induce convective grain motion of the regolith to create a randomly oriented powder. MSL CheMin uses an energy-sensitive CCD to collect XRD patterns and XRF spectra simultaneously from the same sample cell, resulting in qualitative XRF data. METRIC XRD/F uses two different sample cells, one optimized for XRD and one optimized for XRF, and a silicon drift detector to detect fluoresced X-rays. This improvement to the XRF capabilities provides quantitative geochemical data of major elements down to Z = 11 and allows for the detection of minor and trace elements that are critical for evaluating geologic evolution of the Moon (e.g., P and Th). Modest improvements to the XRD geometry and hardware allow for better angular resolution and the ability to distinguish between members of the pyroxene group. METRIC XCT uses the same geometry and much of the same hardware as METRIC XRD/F, where a CCD would capture images of a regolith sample in a 3 mm diameter sample tube that is rotated 360° in steps <1°. Image brightness can be used to infer compositional data, where brighter materials indicate a higher Z, much like scanning electron microscopy. Data from METRIC XCT complement those from METRIC XRD/F. Particle size, shape, and texture can provide petrologic and provenance information, whereas vesicle size and morphology in volcanic or impact melt lithologies can inform cooling rates. METRIC IRS is a hyperspectral thermal imager that can be mounted to a lander or rover to provide mineralogical data from the broader landing site and help determine whether the samples analyzed by METRIC XRD/F and XCT are representative. The METRIC IRS spectral range (8–14 μm) and resolution (10.8 cm-1) allow for quantitative mineralogy from modelling Reststrahlen bands of major rock-forming minerals (e.g., silicates, phosphates). Radiance cubes can be processed and modelled with an onboard high-performance computer to determine mineral abundances of plagioclase, high-Ca pyroxene, pigeonite, orthopyroxene, olivine, and glass. Regolith samples can be acquired, processed, and delivered to the X-ray instruments via multiple sample handling systems, but the pneumatic sampling systems developed by Honeybee Robotics [e.g., 2] are best suited for relatively low-cost missions that are being competed for the Moon (e.g., NASA’s Payloads and Research Investigations for the Surface of the Moon program). There are pneumatic sampling systems that collect surface material and other systems that pneumatically drill up to ~1 m below the surface, providing material that has not been space weathered and has not been affected by the lander’s exhaust. [1] Blake, D. F., Vaniman, D., Achilles, C., Anderson, R., Bish, D., et al. (2012). Space Sci. Rev. 170, 341-478. https://doi.org/10.1007/s11214-012-9905-1. [2] Zacny, K., Betts, B., Hedlund, M., Long, P., Gramlich, M., Tura, K., Chu, P., Jacob, A., Garcia, A. (2014). IEEE Aerospace Conference, 3-7 March 2014, Big Sky, MT, U.S.A.

X-ray diffraction↗

Laser Based Remote and Rapid Inspection for Composite Plates

Composites have been extensively used in aero structure and become the predominate components in the new airframes. Thus, rapid and effective inspection for composite structures is highly desired in aerospace engineering in order to shorten the certificate cycle for new structures or provide safety guarantee for existing ones. In this paper, a laser based remote Lamb wave inspection system is presented and implemented on composite plates for simulated damage detection. The system employs pulsed laser (PL) and scanning laser Doppler vibrometer (SLDV) for noncontact and remote Lamb wave actuation and wavefield sensing. A composite plate with simulated defect (surface bonded quartz rod) is inspected with the PL-SLDV laser system. Wave scattering are observed in the SLDV acquired wavefield and the damage is further evaluated with wavefield imaging and frequency wavenumber analysis. Potential application towards automatic PL Lamb wave excitation is also explored through employing an industry robotic arm towards rapid inspection.

Lamb waves↗

Advanced silicone materials for soft actuator applications

Soft actuators are at the forefront of the innovation tide in medicine, manufacturing, and aerospace because they are able to mimic the behavior of biological tissue and adapt to complex, unstructured environments. Of all the materials used, silicone-based elastomers have drawn enormous attention since they offer a superb combination of mechanical flexibility, biocompatibility, thermal stability, and long-term durability. In the past few years, there has also been a rapid pace of material evolution, additive manufacturing, and biointegration that has enhanced the performance and applications of silicone-based soft actuators. However, there is no focused and timely review compiling these advances. This review seeks to address that need by critically discussing recent advancements in advanced silicone materials, exploring new fabrication methodologies, and discussing emerging applications that range from wearable devices to implantable robotics. We also present suggestions for directions and the problems which must be addressed in order to further develop the performance and potential of silicone-based soft actuators, justifying the relevance and urgency of this effort.

biocompatibility↗

FLARE: The Far Side Lunar Research Expedition. A design of a far side lunar observatory

This document outlines the design completed by members of Lone Star Aerospace, Inc. (L.S.A.) of a lunar observatory on the far side of the Moon. Such a base would not only establish a long term human presence on the Moon, but would also allow more accurate astronomical data to be obtained. A lunar observatory is more desirable than an Earth based observatory for the following reasons: instrument weight is reduced due to the Moon's weaker gravity; near vacuum conditions exist on the Moon; the Moon has slow rotation to reveal the entire sky; and the lunar surface is stable for long baseline instruments. All the conditions listed above are favorable for astronomical data recording. The technical aspects investigated in the completion of this project included site selection, mission scenario, scientific instruments, communication and power systems, habitation and transportation, cargo spacecraft design, thermal systems, robotic systems, and trajectory analysis. The site selection group focused its efforts on finding a suitable location for the observatory. Hertzsprung, a large equatorial crater on the eastern limb, was chosen as the base site.

Bishop, David W.↗

An OSEE Based Portable Surface Contamination Monitor

Many industrial and aerospace processes involving the joining of materials, require sufficient surface cleanliness to insure proper bonding. Processes as diverse as painting, welding, or the soldering of electronic circuits will be compromised if prior inspection and removal of surface contaminants is inadequate. As process requirements become more stringent and the number of different materials and identified contaminants increases, various instruments and techniques have been developed for improved inspection. One such technique based on the principle of Optically Stimulated Electron Emission (OSEE) has been explored for a number of years as a tool for surface contamination monitoring. Some of the benefits of OSEE are: it's non-contacting; requires little operator training; and has very high contamination sensitivity. This paper describes the development of a portable OSEE based surface contamination monitor. The instrument is suitable for both hand-held and robotic inspections with either manual or automated control of instrument operation. In addition, instrument output data is visually displayed to the operator and may be output to an external computer for archiving or analysis.

Perey, Daniel F.↗

A Portable Surface Contamination Monitor Based on the Principle of Optically Stimulated Electron Emission (OSEE)

Many industrial and aerospace processes involving the joining of materials, require sufficient surface cleanliness to insure proper bonding. Processes as diverse as painting, welding, or the soldering of electronic circuits will be compromised if prior inspection and removal of surface contaminants is inadequate. As process requirements become more stringent and the number of different materials and identified contaminants increases, various instruments and techniques have been developed for improved inspection. One such technique, based on the principle of Optically Stimulated Electron Emission (OSEE), has been explored for a number of years as a tool for surface contamination monitoring. Some of the benefits of OSEE are: it is non-contacting; requires little operator training; and has very high contamination sensitivity. This paper describes the development of a portable OSEE based surface contamination monitor. The instrument is suitable for both hand-held and robotic inspections with either manual or automated control of instrument operation. In addition, instrument output data is visually displayed to the operator and may be sent to an external computer for archiving or analysis.

Perey, D. F.↗

Comparison of Communication Architectures for Spacecraft Modular Avionics Systems

This document is a survey of publicly available information concerning serial communication architectures used, or proposed to be used, in aeronautic and aerospace applications. It focuses on serial communication architectures that are suitable for low-latency or real-time communication between physically distributed nodes in a system. Candidates for the study have either extensive deployment in the field, or appear to be viable for near-term deployment. Eleven different serial communication architectures are considered, and a brief description of each is given with the salient features summarized in a table in appendix A. This survey is a product of the Propulsion High Impact Avionics Technology (PHIAT) Project at NASA Marshall Space Flight Center (MSFC). PHIAT was originally funded under the Next Generation Launch Technology (NGLT) Program to develop avionics technologies for control of next generation reusable rocket engines. After the announcement of the Space Exploration Initiative, the scope of the project was expanded to include vehicle systems control for human and robotics missions. As such, a section is included presenting the rationale used for selection of a time-triggered architecture for implementation of the avionics demonstration hardware developed by the project team

Gwaltney, D. A.↗

Multi-Source Machine Learning and Thermoplastics Enhanced Aerostructure Manufacturing (mTEAM)

RTX Technology Research Center (RTRC), together with Collins Aerospace (Collins) and Oak Ridge National Laboratory (ORNL) has developed an Artificial Intelligence (AI) / Machine Learning (ML) guided solution to advance the manufacturing and assembly of high performance and lightweight thermoplastic composite (TPC) aerospace products. The solution aims to lower risk, cost and lead time for induction heating based welding and consolidation processes for TPC structure. The cost and lead time of part and material specific process development for induction welding (IW) and induction consolidation will be reduced by replacing traditional empirical methods with optimization methods that merge AI/ML and physics-based process simulations and process experiments with sensing and controls. TPC-IW process development is empirical in nature, and uncertainties in material & process behavior exist near & far from the induction coil. Physics-based simulations can be leveraged directly for process optimization but can be too computationally expensive to run in high fidelity and real time to do robust process optimization. The key impact of successful TPC induction consolidation and welding is cost & lead time reduction for part & material specific consolidation and welding recipes. This is an enabler for more rapid deployment of TPC structures via joining assembly, which can reduce energy & cost intensive usage of autoclaves & ovens. The solution aimed to advance the U.S. Department of Energy’s interests in using thermoplastics and automation in composite manufacturing for improvement of products for existing markets via increased production speeds, reduced costs, and lowered use of energy. Welded TPC structures can offer significant weight & energy savings for high-value commercial aerospace & industrial applications compared to metal & thermoset composite structures assembled by mechanical fastening and/or adhesive bonding. The project was organized into two Budget Periods. Budget Period 1 (BP1) was 15 months and its goal was to perform ML process optimization framework development & deployment on lab-coupon aerostructure components. A Go/No-Go Review was performed at the end of BP1 to verify fulfilment of key tasks & milestones to justify a Go Decision to move into the next Budget Period. Budget Period 2 (BP2) was 12 months and its goal was the deployment of the ML framework for ML process optimization of pilot industrial scale aerostructure components. The overall project aim was to develop & demonstrate ML-enhanced modeling framework that learns process-property mapping from multiple data sources at different fidelities. During BP1, the team accomplished key tasks & milestones to demonstrate the concept of multi-source ML for TPC aerostructure consolidation and assembly. First, the team completed documentation of induction based TPC heating requirements including baseline metrics to compare measured results against. Next the team completed demonstration of data generation from physics-based simulations for ML surrogate model generation and demonstrated the integration of physics-based simulation data into multi-source AI/ML algorithms. In parallel, the team established the lab-coupon scale induction welding system and completed a process to label and reduce generated data from physics-based simulation and experiments for ML surrogate models to enable multi-source ML model training & testing. To complete BP1, the team integrated physics-based simulation data and experimental data into multi-source ML algorithms. This was based on the team completing ML deployment of the induction welding on a lab system at RTRC and AI/ML deployment on existing induction welding line at Collins. ORNL visited both Collins and RTRC sites to witness the TPC induction welding process. Then, ORNL designed and constructed a new version of their vision-based sensing system better adapted to acquire process signals of the TPC induction welding process for process anomaly and defect detection. In BP2, the team accomplished key tasks & milestones to scale up multi-source ML for TPC aerostructure consolidation and assembly from the lab-coupon scale to the pilot-industrial scale. In BP2, the team demonstrated real time anomaly & defect detection via experiments performed by ORNL & RTRC. The team completed ML-optimization heating trials for TPC induction consolidation at Collins, and the team confirmed pilot industrial scale experimental data from Collins was compatible with the developed ML pipeline from RTRC. The team completed sub-element scale ML process optimization demonstration at RTRC, where the team leveraged RTRC’s robotic TPC welding setup to de-risk the ML process optimization by performing ML analysis of recorded temperatures to account for complex part features. Then, the team applied its ML-derived control strategies and ML process optimization framework at Collins to the pilot-industrial scale on a demo skin-stiffener part representative of a nacelle aerostructure fan cowl section. The key innovation is the AI/ML framework enabling effective process development of high performance, lightweight, energy efficient TPCs for composite aircraft structures.

36 MATERIALS SCIENCE↗