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At least 307 records · Page 17

Performance of a 2.5 THz Receiver Front-End for Spaceborne Applications

The OH radical plays a significant role in a great many of the known ozone destruction cycles, and has become the focus of an important radiometer development effort for NASA's Earth Observing System Chem I satellite, which will monitor and study many tropospheric and stratospheric gases and is scheduled for launch in 2002. Here we describe the design, fabrication, and testing of a receiver front end used to detect the OH signals at 2.5 THz. This is to be the first Terahertz heterodyne receiver to be flown in space. The challenges of producing the necessary high-performance mixers are numerous, but for this application, there is the added challenge of designing a robust receiver which can withstand the environmental extremes of a rocket launch and five years in space. The receiver front-end consists of the following components: a four-port dual-polarization diplexer, off-axis elliptical feed mirrors, mixers for horizontal and vertical polarization, support structures allowing simple and rugged alignment, low noise IF amplification from 7.7 to 21.1 GHz, and mixer DC bias circuitry. The front-end design, alignment, and operation will be covered in depth, followed by a discussion of the most recent results in receiver noise and dual-mode horn beam patterns. JPL MOMED mixers are employed, and have resulted in receiver noise temperatures of 14,500 K, DSB with LO frequency 2.522 GHz and IF of 12.8 GHz. Horn beam patterns correspond well with theory, with no significant sidelobes above the -25 dB level. Considering the high-quality beam of this receiver, these results are competitive with the best reported in the literature.

Gaidis, Michael C.↗

Restoration of peak vascular conductance after simulated microgravity by maximal exercise

We sought to determine if (i) peak vascular conductance of the calf was reduced following prolonged exposure to simulated microgravity, and (ii) if maximal cycle ergometry performed at the end of microgravity exposure stimulated a restoration of peak calf vascular conductance. To do this, peak vascular conductance of the calf was recorded following ischaemic plantar flexion exercise to fatigue in seven men after 16 days of head-down tilt (HDT) under two conditions: (i) after one bout of maximal supine cycle ergometry completed 24 h prior to performance of ischaemic plantar flexion exercise, and (ii) in a control (no cycle ergometry) condition. Following HDT, peak vascular conductance was reduced in the control condition (0.38 +/- 0.02 to 0.24 +/- 0.02 ml 100 ml-1 min-1 mmHg-1; P = 0.04), but was restored when subjects performed cycle ergometry (0.33 +/- 0.05 to 0.28 +/- 0.04 ml 100 ml-1 min-1 mmHg-1; P = 0.46). After HDT, time to fatigue during ischaemic plantar flexion exercise was not different from pre-HDT 24 h after performance of exhaustive cycle ergometry (120 +/- 24 vs. 122 +/- 19 s), but was decreased in the control condition (116 +/- 11 vs. 95 +/- 8 s; P = 0.07). These data suggest that a single bout of maximal exercise can provide a stimulus to restore peak vascular conductance and maintain time to fatigue during performance of ischaemic plantar flexion exercise.

NASA Discipline Cardiopulmonary↗

FY23 Progress Report on Viscosity and Thermal Conductivity Measurements of Molten Salts

As presented in this report, thermal conductivity and viscosity measurements were performed on key chloride pseudo-binary molten salt systems of relevance to molten salt reactor developers. Thermal conductivity measurements were conducted with a variable gap technique, in which a known heat flux is driven across a molten salt specimen and the temperature difference is measured, allowing calculation of the thermal conductivity. This is achieved by establishing a small gap between the bottom of a cylindrical inner containment, which houses electrical heating elements, and an outer containment, which houses cooling channels; the gap size can be varied by compression of a formed bellows. A new calibration scheme was developed herein, involving a correction factor to the heat flux based on He measurements at various temperatures. Furthermore, the data processing methodology was improved to minimize the impact of radiative heat transfer in the calculation of salt specimen thermal conductivity from the temperature difference measurements. Viscosity measurements were conducted with a rolling ball viscometer, in which a ball rolls some known distance in an angled tubular crucible, and the terminal velocity can be used to calculate the viscosity of the salt. The measurement can be performed in a quartz crucible, with which a standard camera can be used to track the ball, or in a metal crucible, with which x-ray radiography is required to track the ball. A new custom x-ray system was made and dedicated to the rolling ball viscometer to enable high throughput automated measurements with salts which require containment with metal. Both systems have been integrated with a ventilation stack which allows for off-gassing of radioactive material, enabling future measurements with U-bearing salts. The thermal conductivity measurements performed herein were with NaCl-KCl (44 mol% NaCl). This salt system was measured in the previous fiscal year, however the thermal conductivity values obtained were comparatively low, and so the system was remeasured with the aforementioned calibration scheme and improved post-processing techniques. The newly obtained thermal conductivity values for NaCl-KCl (44 mol% NaCl) indicate good agreement with kinetic theory and ab-initio models (within 5–10 %). The viscosity measurements performed herein were with three different compositions of NaCl-KCl: 75, 50, and 25 mol% NaCl; a new calibration scheme was applied to account for variable flow effects in the laminar regime. The results show reasonable agreement with literature (5–20 %, depending on the temperature, composition, and study); however, literature values are likely higher than true values based on pure end-member measurements performed in the comparative studies. The measurements conducted herein do show a trend such that viscosity increases with increasing NaCl concentration, which agrees well with one of two comparative studies. In general, the measurements conducted herein gives confidence in the capability to use these systems to accurately measure thermal conductivity and viscosity of actinide-bearing salts within the next fiscal year.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Production and tests of the ADDC for the Micromegas detector of the ATLAS New Small Wheel

The Large Hadron Collider (LHC) at CERN will perform a series of upgrades to allow luminosity increases during the next physics runs expected from 2022 on. These will also significantly increase the trigger rates of all the detectors. As part of the ATLAS Phase-I upgrade, the current Small Wheel muon detectors will be replaced with state-of-the-art New Small Wheel (NSW) detectors to cope with the increased luminosity of the LHC. The Address in Real Time Data Driver Card (ADDC) is designed to transmit the trigger data from the resistive Micro-Mesh Gaseous Structure (Micromegas) detectors of the NSW. The ART ASIC on the ADDC is a customdesigned chip to receive theAddress in Real Time (ART) signals from theVMMfront-end ASIC and perform hit-selection processing. The processed trigger data is then sent to the Trigger Processor (TP) through optical links. A total of 512 ADDCs will be installed on the detector close to the front-end boards. Therefore, those cards must be able to work properly in a high radiation and magnetic field environment. Furthermore, after four rounds of prototyping, the ADDC production was launched in January of 2019. 600 ADDC boards have been produced and tested with an automated test stand. This test setup can simulate the front-end signals and provide "Level-1 Data Driver Card" (L1DDC) functions as well as part of the TP functions. Thus, the ADDC functionality and stability can be verified without the remaining NSW electronics. This paper describes the ADDC hardware prototype development, radiation and integration testing, and the ADDC automated production test procedure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A computationally efficient modelling of laminar separation bubbles

The goal is to accurately predict the characteristics of the laminar separation bubble and its effects on airfoil performance. Toward this end, a computational model of the separation bubble was developed and incorporated into the Eppler and Somers airfoil design and analysis program. Thus far, the focus of the research was limited to the development of a model which can accurately predict situations in which the interaction between the bubble and the inviscid velocity distribution is weak, the so-called short bubble. A summary of the research performed in the past nine months is presented. The bubble model in its present form is then described. Lastly, the performance of this model in predicting bubble characteristics is shown for a few cases.

Dini, Paolo↗

Characterization of CO2 Binding on Alkaline Metal Oxide Sorbents and DFMs for Combined Capture and Conversion

As the world endures environmental crises associated with climate change and the rise of atmospheric CO2 concentrations from anthropogenic CO2 emission, carbon capture and utilization (CCU) technologies are increasingly necessary. Reactive carbon capture (RCC) technologies, in which capture and conversion of CO2 occur in a single reactor, are more energetically and economically attractive by avoiding the need to purify, compress, and transport the captured CO2. To this end, the development of dual function materials (DFM) that enable CO2 capture and conversion to useful C1 products, namely (1) methane, (2) CO, and (3) methanol, are attractive near-term targets for commercial CCU processes for renewable fuels and chemicals. DFM are composed of sorbents and catalysts co-dispersed on the same high surface area carrier. The sorbent component allows for selective capture of CO2 from a gas stream and the catalyst component subsequently performs the in-situ conversion of the adsorbed CO2 upon introduction of a reactive gas (typically H2). The survey of DFM formulations reveals a variety of sorbent+catalyst combinations of interest. There is, however, a lack of depth in fundamental understanding of how the CO2 binds to these materials and how the subsequent reaction mechanisms are affected, which are critical features for the development of next-generation materials with improved performance. To this end, we will describe in this work the CO2 binding characteristics of established and/or new DFM and their sorbent-only counterparts. The surface CO2 binding mechanism and capture capacity will be probed using techniques such as in-situ DRIFTS, operando TGA, and CO2 chemisorption.

alkaline oxides↗

A Study on Advanced Lithium-Based Battery Cell Chemistries to Enhance Lunar Exploration Missions

NASA's Exploration Technology Development Program (ETDP) Energy Storage Project conducted an advanced lithium-based battery chemistry feasibility study to determine the best advanced chemistry to develop for the Altair lunar lander and the Extravehicular Activities (EVA) advanced lunar surface spacesuit. These customers require safe, reliable energy storage systems with extremely high specific energy as compared to today's state-of-the-art batteries. Based on customer requirements, the specific energy goals for the development project are 220 watt-hours per kilogram (Wh/kg) delivered at the battery level at 0 degrees Celsius (degrees Celcius) at a C/10 discharge rate. Continuous discharge rates between C/5 and C/2, operation over 0 to 30 degrees C, and 200 cycles are targeted. The team, consisting of members from NASA Glenn Research Center, Johnson Space Center, and Jet Propulsion laboratory, surveyed the literature, compiled information on recent materials developments, and consulted with other battery experts in the community to identify advanced battery materials that might be capable of achieving the desired results with further development. A variety of electrode materials were considered, including layered metal oxides, spinel oxides, and olivine-type cathode materials, and lithium metal, lithium alloy, and silicon-based composite anode materials. lithium-sulfur systems were also considered. Hypothetical cell constructs that combined compatible anode and cathode materials with suitable electrolytes, separators, current collectors, headers, and cell enclosures were modeled. While some of these advanced materials are projected to obtain the desired electrical performance, there are risks that also factored into the decision making process. The risks include uncertainties due to issues such as safety of a system containing some of these materials, ease of scaling-up of large batches of raw materials, adaptability of the materials to processing using established or reasonable cost manufacturing techniques, manufacturability of the materials in dimensions required for integration into battery cells of practical capacities, low Technology Readiness levels (TRl), and the ability to achieve the desired performance by the customer need dates. The advanced cell chemistry options were evaluated with respect to multiple quantitative and qualitative attributes while considering their projected performance at the end of the available development timeframe. Following a rigorous ranking process, a chemistry that combines a lithiated nickel manganese cobalt oxide (lithium NMC) cathode with a silicon-based composite anode was selected as the technology that can offer the best combination of safety, specific energy, energy density, and likelihood of success. Tasks over the next three years will focus on development of electrode materials, compatible electrolytes, and separator materials, and integration of promising components to assess their combined performance in working cells. Cells of the chosen chemistry will be developed to TRl 6 by 2014 and will then be transferred to the customers for infusion into their mission paths.

Reid, Concha↗

The value of human data annotation for machine learning based anomaly detection in environmental systems

Anomaly detection is the process of identifying unexpected data samples in datasets. Automated anomaly detection is either performed using supervised machine learning models, which require a labelled dataset for their calibration, or unsupervised models, which do not require labels. While academic research has produced a vast array of tools and machine learning models for automated anomaly detection, the research community focused on environmental systems still lacks a comparative analysis that is simultaneously comprehensive, objective, and systematic. This knowledge gap is addressed for the first time in this study, where 15 different supervised and unsupervised anomaly detection models are evaluated on 5 different environmental datasets from engineered and natural aquatic systems. To this end, anomaly detection performance, labelling efforts, as well as the impact of model and algorithm tuning are taken into account. As a result, our analysis reveals the relative strengths and weaknesses of the different approaches in an objective manner without bias for any particular paradigm in machine learning. Most importantly, our results show that expert-based data annotation is extremely valuable for anomaly detection based on machine learning.

54 ENVIRONMENTAL SCIENCES↗

Virtual Inspection of Advanced Manufacturing via Process-Scale Digital Twins (Abbreviated Report)

Inspection and certification comprise the most significant bottlenecks in advanced manufacturing for NNSA applications, often requiring far more time and resources than the fabrication of the parts themselves. Traditional methods, such as manual review and X-ray computed tomography, are not only slow and costly, but also struggle to provide a clear connection between manufacturing instructions and the final performance of critical components. This gap limits both the agility and assurance needed to support the modernization and safety of the United States nuclear stockpile. In response, our Strategic Initiative established a digital twin framework that integrates realtime process monitoring, automated data analysis, and immersive virtual reality collaboration into a unified inspection pipeline. By leveraging data from sensors, machine instructions, and imaging, we created high-fidelity virtual models of manufactured parts that could be rapidly analyzed and certified. This approach was first demonstrated with Direct Ink Write, and then extended to other manufacturing settings, including conventional (or “subtractive”) manufacturing and to predict the end of life performance of parts per the aging and lifetimes programs. The result is a transformational capability: inspection times have been reduced by a factor of 120,000 without loss of accuracy and while simultaneously improving traceability and confidence in part quality. This framework not only streamlines certification for critical applications, but also positions the national security enterprise to respond more flexibly to emerging challenges, supporting agile manufacturing and digital engineering practices across a broad range of mission-relevant domains.

42 ENGINEERING↗

DMTN-221: Periodicity Analysis in Alert Production

The baselined timeseries features to be computed in Alert Production include a Lomb-Scargle periodogram ran on two classes of variable systems: RR Lyrae and Eclipsing Binaries. Based on a simulated LSST-like cadence light curves taken from the Extended LSST Astronomical Time-series Classification Challenge (ELAsTiCC) we perform an end-to-end test to characterize the periodicity recovery on the Alert Production multi-band light curves. In both variable classes, we found that a single-band Lomb-Scargle implementation yields to a low fraction of recovered periods, with a significant preference on the simple periodic phenomena such as RR Lyrae. We also investigated the results from a multi-band Lomb-Scargle and found an increased fraction of recovered periodicities above 15% for the eclipsing binaries, and over 80$\%$ for the RR Lyrae stars. Our findings suggest that a multi-band Lomb-Scargle should be implemented for searching periodic phenomena through AP. We also asses the computational and scientific performance of several configurations on simulated alert data and find that our current configuration scales linearly with the number of detections while assuming an heuristic frequency grid.

79 ASTRONOMY AND ASTROPHYSICS↗

System performance testing of the DSN radio science system, Mark 3-78

System performance tests are required to evaluate system performance following initial system implementation and subsequent modification, and to validate system performance prior to actual operational usage. Non-real-time end-to-end Radio Science system performance tests are described that are based on the comparison of open-loop radio science data to equivalent closed-loop radio metric data, as well as an abbreviated Radio Science real-time system performance test that validates critical Radio Science System elements at the Deep Space Station prior to actual operational usage.

Berman, A. L.↗

Report to NCSP on FY21 DANCE and NEUANCE measurements of 233 U(η, γ)

The experiment was performed by the end of the CY20 runcycle at LANSCE. Due to transportation issues the material arrived at LANL on 1st December. Two 233 U samples, of 20 mg and 10 mg were produced at LANL by stippling, which has proved a robust, cost-effective method for producing actinide samples in the range of 1-20 mg in a small (<1 cm) diameter with very high efficiency. The 20 mg sample was placed inside NEUANCE on FP14 on 11th December, was measured over 10 days, and the 10 mg sample was placed in the beam for 1 day. The rest of the beam time was used to measure radioactive γ sources for calibration, background measurements and tests to define the 233 U windows required during the data taking, also some measurements were done with a 235 U sample to cross-check the performance and the systematics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Pump-and-Treat Impacts on Aquifer Conditions and the Development of System-Wide Performance Strategies - 20377

The pump-and-treat (P and T) system on the Hanford Site's Central Plateau currently treats multiple contaminants within the 200-ZP-1 operable unit, including nitrate through its biological treatment processes. Although it was initially designed to support the 200-ZP-1 Remedial Action Objectives, the P and T system has evolved in use to address contaminants from other regions of the aquifer as well. The P and T influents are biogeochemically distinct, treating groundwaters with elevated concentrations of cyanide, uranium, technetium-99, and nitrate. Given the varying geochemical signatures from current and potential future sources, operational conditions, and amendments considered for treatment processes, there is a need to identify the impacts that the P and T effluent has on the aquifer, and how the aquifer affects P and T performance. To this end, laboratory efforts have focused on characterizing P and T effluent and its biogeochemical effects on the sediments through a series repacked column experiments. The P and T effluent is rich in particulate matter. A systematic inspection of this particulate matter in the P and T effluent showed significant levels of manganese/iron oxides, calcite crystals, relatively large organic matter molecules, and biomass. Therefore, the column experiments were designed and conducted for four different treatment systems: artificial groundwater, filtered P and T effluent, non-filtered P and T effluent, and chlorinated P and T effluent. Different levels of microbiologically- and geochemically-induced changes in the columns occurred and modified the flow systems. For example, physical filtration occurred in the sediments where the particulate material had accumulated in the top portion of the column. Reactive transport modeling of the laboratory experiments is being carried out so that the reaction network can be extrapolated to the field scale. These simulations will provide predictive evaluations of system performance based on P and T operational changes and aquifer mass loading and capacity estimates. This information can be used to address combined subsurface and operational challenges, such as the need for frequent well redevelopment to maintain injection capacity. This information also provides the technical basis for decisions related to the P and T system operations that support remedy optimization efforts and short- and long-term remedy decisions related to multiple operable units on the Hanford Site Central Plateau. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Improved performance and safety of lithium ion cells with the use of fluorinated carbonate-based electrolytes

There has been increasing interest in developing lithium-ion electrolytes that possess enhanced safety characteristics, while still able to provide the desired stability and performance. Toward this end, our efforts have been focused on the development of lithium-ion electrolytes which contain partially and fully fluorinated carbonate solvents. The advantage of using such solvents is that they possess the requisite stability demonstrated by the hydrocarbon-based carbonates, while also possessing more desirable physical properties imparted by the presence of the fluorine substituents, such as lower melting points, increased stability toward oxidation, and favorable SEI film forming Characteristics on carbon. Specifically, we have demonstrated the beneficial effect of electrolytes which contain the following fluorinated carbonate-based solvents: methyl 2,2,2-trifluoroethyl carbonate (MTFEC), ethyl-2,2,2 trifluoroethyl carbonate (ETFEC), propyl 2,2,2-trifluoroethyl carbonate (PTFEC), methyl-2,2,2,2',2',2' -hexafluoro-i-propyl carbonate (MHFPC), ethyl- 2,2,2,2',2',2' -hexafluoro-i-propyl carbonate (EHFPC), and di-2,2,2-trifluoroethyl carbonate (DTFEC). These solvents have been incorporated into multi-component ternary and quaternary carbonate-based electrolytes and evaluated in lithium-carbon and carbon-LiNio.8Coo.202 cells (equipped with lithium reference electrodes). In addition to determining the charge/discharge behavior of these cells, a number of electrochemical techniques were employed (i.e., Tafel polarization measurements, linear polarization measurements, and electrochemical impedance spectroscopy (EIS)) to further characterize the performance of these electrolytes, including the SEI formation characteristics and lithium intercalatiodde-intercalation kinetics. In addition to their evaluation in experimental cells, cyclic voltammetry (CV) and conductivity measurements were performed on select electrolyte formulations to further our understanding of the trends in stability and ionic mobility imparted by different alkyl substituents in linear carbonates.

li-ion batteries fluorinated carbonate electrolyte↗

Creation of a Rapid High-Fidelity Aerodynamics Module for a Multidisciplinary Design Environment

In the traditional aerospace vehicle design process, each successive design phase is accompanied by an increment in the modeling fidelity of the disciplinary analyses being performed. This trend follows a corresponding shrinking of the design space as more and more design decisions are locked in. The correlated increase in knowledge about the design and decrease in design freedom occurs partly because increases in modeling fidelity are usually accompanied by significant increases in the computational expense of performing the analyses. When running high fidelity analyses, it is not usually feasible to explore a large number of variations, and so design space exploration is reserved for conceptual design, and higher fidelity analyses are run only once a specific point design has been selected to carry forward. The designs produced by this traditional process have been recognized as being limited by the uncertainty that is present early on due to the use of lower fidelity analyses. For example, uncertainty in aerodynamics predictions produces uncertainty in trajectory optimization, which can impact overall vehicle sizing. This effect can become more significant when trajectories are being shaped by active constraints. For example, if an optimal trajectory is running up against a normal load factor constraint, inaccuracies in the aerodynamic coefficient predictions can cause a feasible trajectory to be considered infeasible, or vice versa. For this reason, a trade must always be performed between the desired fidelity and the resources available. Apart from this trade between fidelity and computational expense, it is very desirable to use higher fidelity analyses earlier in the design process. A large body of work has been performed to this end, led by efforts in the area of surrogate modeling. In surrogate modeling, an up-front investment is made by running a high fidelity code over a Design of Experiments (DOE); once completed, the DOE data is used to create a surrogate model, which captures the relationships between input variables and responses into regression equations. Depending on the dimensionality of the problem and the fidelity of the code for which a surrogate model is being created, the initial DOE can itself be computationally prohibitive to run. Cokriging, a modeling approach from the field of geostatistics, provides a desirable compromise between computational expense and fidelity. To do this, cokriging leverages a large body of data generated by a low fidelity analysis, combines it with a smaller set of data from a higher fidelity analysis, and creates a kriging surrogate model with prediction fidelity approaching that of the higher fidelity analysis. When integrated into a multidisciplinary environment, a disciplinary analysis module employing cokriging can raise the analysis fidelity without drastically impacting the expense of design iterations. This is demonstrated through the creation of an aerodynamics analysis module in NASA’s OpenMDAO framework. Aerodynamic analyses including Missile DATCOM, APAS, and USM3D are leveraged to create high fidelity aerodynamics decks for parametric vehicle geometries, which are created in NASA’s Vehicle Sketch Pad (VSP). Several trade studies are performed to examine the achieved level of model fidelity, and the overall impact to vehicle design is quantified.

Aerodynamic Properties↗

End region and current consolidation effects upon the performance of an MHD channel for the ETF conceptual design

It is noted that operating conditions which yielded a peak thermodynamic efficiency (41%) for an EFT-size MHD/steam power plant were previously (Wang et al., 1981; Staiger, 1981) identified by considering only the active region (the primary portion for power production) of an MHD channel. These previous efforts are extended here to include an investigation of the effects of the channel end regions on overall power generation. Considering these effects, the peak plant thermodynamic efficiency is found to be slightly lowered (40.7%); the channel operating point for peak efficiency is shifted to the supersonic mode (Mach number of approximately 1.1) rather than the previous subsonic operation (Mach number of approximately 0.9). Also discussed is the sensitivity of the channel performance to the B-field, diffuser recovery coefficient, channel load parameter, Mach number, and combustor pressure.

Wang, S. Y.↗

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↗

Fundamental insights on ignition and combustion of natural gas in an active fueled pre-chamber spark-ignition system

Pre-chamber spark-ignition (PCSI), either fueled or non-fueled, is a leading concept with the potential to enable diesel-like efficiency in medium-duty (MD) and heavy-duty (HD) natural gas (NG) engines. However, the inadequate scientific base and simulation tools to describe/predict the underlying processes governing PCSI systems is one of the key barriers to market penetration of PCSI for MD/HD NG engines. To this end, experiments were performed in a heavy-duty, optical, single-cylinder engine fitted with an active fueled PCSI module. Furthermore, the spatial and temporal progress of ignition and subsequent combustion of lean-burn natural gas using PCSI system were studied using optical diagnostic imaging and heat release analysis based on main-chamber and pre-chamber pressure measurements.

42 ENGINEERING↗