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DOE OSTI2022

Understanding and improving anode performance in an alkaline membrane electrolyzer using statistical design of experiments

The behavior of the oxygen-evolving positive electrode (i.e. anode) in the anion exchange membrane water electrolyzer (AEMEL) is complex and influenced by several factors. Very few studies have been performed to understand oxygen evolution reaction (OER) behavior by optimizing the individual factors that influence performance. Here, this study highlights the effects of catalyst loading, catalyst selection, porous transport layer (PTL) type and conductive additive content. The influence of each factor is elucidated through a design of experiments (DoE) approach with a full statistical analysis. Electrochemical data, alongside Pareto charts, parametric trends and their mutual interactions are discussed. This DoE approach is also helpful in making useful predictions and discovering new combinations to be tested. The end result was a high-performance AEMEL able to operate at a current density of 1.0 A/cm 2 at 1.80 V with IrOx OER and PtNi hydrogen evolution reaction (HER) catalysts using 0.3 M KOH fed to the anode. Even lower operating voltage was observed with PbRuOx catalyst at the anode, 1.64 V @ 1.0 A/cm 2 , though the cell decay rate was higher. Lastly, a IrOx/PtNi cell was stably operated continuously for 30 days (720 h) at 1.0 A/cm 2 . This study can serve as a guide for optimal electrode design with insights into component-performance compromises, which can aid in making design choices and performing techno-economic analyses.

08 HYDROGEN↗

DOE OSTI2025

Low Greenhouse Gas (GHG) Vehicle Technologies Research, Development, Demonstration and Deployment Topic 5 Natural Gas Engine Enabling Technologies

A 10 liter natural gas engine has been developed with significant improvements in efficiency while maintaining ultra low NOx emissions and meeting all other EPA criteria emissions limits. This was accomplished through design and analysis of performance components specifically for operation with natural gas in contrast to current production engines which are a minimally modified diesel engine that retain most diesel design features including a flat deck swirl head. The architecture developed here includes a pent roof cylinder head with tumble charge motion and cooling passages specifically optimized for effective cooling around the spark plug and valve bridges. Also in contrast to current production natural gas engines, EGR was not used, in part to avoid the initial cost and warranty expense associated with EGR systems, but also for performance benefits of faster combustion, reduced risk of misfire and high open cycle efficiency due to the turbocharger’s ability to extract energy from the high temperature exhaust. The exhaust manifold uses high temperature material and thermal mechanical fatigue analysis was completed to ensure the ability to withstand high exhaust temperatures without EGR. Other features include dual overhead cam with late intake valve closing Miller cycle and 14:1 compression ratio steel pistons. Low NOx emissions are achieved with stoichiometric combustion and application of a close coupled plus underfloor three way catalysts. The program target of peak brake thermal efficiency of 42% has been demonstrated along with bsNOx of 0.02 g/hp-hr over HD-FTP and RMCSET emissions cycles.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

CMB-PAInT: An inpainting tool for the cosmic microwave background

Abstract The presence of astrophysical emissions in microwave observations forces us to perform component separation to extract the Cosmic Microwave Background (CMB) signal. However, even in the most optimistic cases, there are still strongly contaminated regions, such as the Galactic plane or those with emission from extragalactic point sources, which require the use of a mask. Since many CMB analyses, especially the ones working in harmonic space, need the whole sky map, it is crucial to develop a reliable inpainting algorithm that replaces the values of the excluded pixels by others statistically compatible with the rest of the sky. This is especially important when working withQandUsky maps in order to obtainE- andB-mode maps which are free fromE-to-Bleakage. In this work we study a method based on Gaussian Constrained Realizations (GCR), that can deal with both intensity and polarization. Several tests have been performed to asses the validation of the method, including the study of the one-dimensional probability distribution function (1-PDF),E- andB-mode map reconstruction, and power spectra estimation. We have considered two scenarios for the input simulation: one case with only CMB signal and a second one including also Planck PR4 semi-realistic noise. Even if we are limited to low resolution maps, N side = 64 ifT,QandUare considered, we believe that this is a useful approach to be applied to future missions such as LiteBIRD, where the target are the largest scales.

Astronomy & Astrophysics↗

DOE OSTI2022

Hybrid Hydraulic-Electric Architecture (HHEA) for Mobile Machines (Final Report)

Traditionally, off-road mobile machines such as excavators and wheel loaders are primarily powered by hydraulics, and throttling valves are used to control their work circuits. In recent years, two general trends are towards more energy efficient systems and electrification. With electrification, both efficiency and control performance can be improved by the elimination of throttling losses and the use of high-bandwidth inverter control. Electrification is generally accomplished with Electro-hydraulic actuators (EHA) but they are limited to lower powered systems due to the high cost of electric machines capable of high power or high torque. This project proposes a new system architecture for off-road vehicles - Hybrid Hydraulic Electric Architecture (HHEA) to improve efficiency and control performance without requiring large electric machines. The widely applicable architecture combines hydraulic power and electric power in such a way that the majority of power is provided hydraulically while electric drives are used to modulate this power. In particular, HHEA utilizes multiple common pressure rails to transmit the majority of power and small electric machines to modulate the power. The energy-saving potential of the the HHEA has been validated for the work circuits of a variety of mobile machines, from small 5-ton excavators to medium sized 20-ton excavators and wheel loaders, and representative duty cycles to reduce energy input by 50-80% compared to the commercial state-of-art load-sensing systems. In addition, the corner power requirements of the electrical machines can be downsized by 85% compared to the EHA approach. Various tradeoff studies have also been conducted, including sensitivities to individual components performances, controllers, accumulator sizes, and variations of the system architecture etc. A control strategy has been developed to maintain or exceed the motion control precision compared to current systems. The motion control strategy consists of a nominal controller, based on a passivity-based backstepping design, and a transition controller, based on least-norn feedforward design. The nominal controller is used in between common pressure rail switches whereas the transition controller compensates for any disturbance that common pressure rail switchings inflict on the system. The control strategy has been experimentally validated on both a medium pressure (200bar) hardware-in-the-loop (HIL) testbed and a high pressure (300+bar) HIL testbed. An efficient and power-dense integrated electric-hydraulic machine consisting of an axial flux electric machine and a radial hydrostatic piston hydraulic machine has been designed, constructed and tested. The machine has an active material power density of 6.1kW/kg, a rated speed of 12500 RPM, and a design efficiency of 85%. This is among the highest power density electric machines using conventional materials. While the integrated machine was designed for modulating the hydraulic power within the HHEA, it can also be used in other applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Computational Design of Alloys for Energy Technologies

Advanced materials that maintain their mechanical performance under elevated temperatures, corrosive environments, and a range of static and evolving stresses are needed to improve the efficiency and reduce the environmental impact of a wide spectrum of energy technologies. For instance, cost-efficient alloys that can withstand high temperatures (e.g., 700 °C) have a critical role in improving the efficiency and economics of power generation to support decarbonization of the energy sector; such is true of both the nuclear and fossil energy sectors. Considering both the threats of the energy crisis, namely soaring costs of greenhouse gas emission-producing energy and climate change, it is essential to increase the pace of material discovery and enable rapid paths for material qualification to advance clean energy technologies. Conventionally, alloy development has followed a slow Edisonian process that uses repeated cycles of making, characterizing, and modifying to arrive at optimum composition and processing conditions to achieve the desired component performance. This optimization is followed by the necessary stepwise materials qualification. Furthermore, the increasing adoption of sound data management and physics-informed machine learning represents the next step in the acceleration of materials design and development. In the integrated computational materials engineering (ICME) approach, computational modeling and simulation data from different length and time scales can be combined with complex microstructural details from multimodal experimental characterization and selective property testing to close the design loop for rapid alloy development.

Computational Design Of Materials↗

DOE OSTI2023

Self-supervised learning of spatiotemporal thermal signatures in additive manufacturing using reduced order physics models and transformers

Microstructure control via additive manufacturing has enormous potential as manufacturers, materials scientists, and designers alike seek to exploit novel fabrication technologies to improve component performance. Recent works have demonstrated the feasibility of producing materials with controlled microstructures across various length scales. However, the experimental approach towards exploring the process-structure space can be laborious and costly. This is particularly true if also considering scan pattern optimization which is well suited for processes such as powder bed fusion electron beam melting. In this work we propose an approach for encoding additive manufacturing layer-wise thermal response signatures using self-supervised representation learning. Thermal simulations from a reduced order model are utilized to estimate the spatiotemporal response during printing. A machine learning framework, using video-transformers, is utilized to efficiently distill spatiotemporal patterns into a compact latent space representation. This latent state representation encodes the relevant physics which is then utilized to establish a data-driven process-structure model for an additively manufactured Ni-based superalloy. In conclusion, the proposed methodology could potentially be used towards in-situ process monitoring, scan pattern experimental design, and component qualification.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Data Center Facility Monitoring with Physics Aware Approach

U.S. Department of Energy's National Renewable Energy Laboratory (NREL) hosts one of the world's most energy-efficient HPC data centers; this system uses component-level warm-water liquid cooling to efficiently remove heat from the data center and capture it for reuse in the building or rejection to the atmosphere. Given the complexity of this system, building data-driven tools for holistically monitoring and operating the entire data center is a priority for ensuring maximal efficiency and resiliency. In this advanced smart facility, over one million metrics are recorded per minute using state-of-the-art streaming data architecture and software to capture and process the state of the system in real time. Here we detail two efforts to effectively analyze, visualize, and interpret this large volume streaming data. We have developed a novel, flexible system for identifying and visualizing individual metric anomalies and component performance across the data center through automatic metadata extraction and physically-motivated visualization for quick interpretation. Additionally, to directly connect system maintenance to data stream processing we explore a physics informed multi-metric drift and anomaly detection application to detect scale-build up in heat exchangers.

anomaly detection↗

DOE OSTI2021

Integrating helicoid channels for passive control of fiber alignment in direct-write 3D printing

3D printing of fiber-reinforced composites has been receiving increasing attention as an efficient additive approach enabling lightweight, functional, and high-performance components required for industrial applications. The properties of fiber composites significantly depend on internal microstructures, including fiber orientation, distribution, and degree of alignment. Although multiple strategies have been introduced for controlling the fiber composites microstructures, these strategies are mostly active approaches relying on additional control of mechatronics parts, external forces, or intentionally introduced unstable flows inside narrow nozzles. These methods suffer from higher risk of nozzle clogging and requiring extra parts in 3D printing. Here, we introduce helicoid channels into extrusion system as a passive approach to control the fiber alignment without any additional moving parts in direct-write 3D printing. The helicoid channels automatically guide the composite inks and align fibers before flowing into narrow nozzle space, avoiding clogging and improving printability. The analyses indicate that both helicoid surface to volume ratio and helix angle affect the pre-alignment of fibers, leading to tunable mechanical properties of printed fiber-reinforced composites with increased stiffness and strength up to 77.6% and 47.8%, respectively.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A scalable digital platform for the use of digital twins in additive manufacturing

We report that while Additive Manufacturing promises to reshape the manufacturing landscape, challenges related to part, and process qualification hinder its widespread adoption. The Instance-Qualified approach seeks to qualify individual parts, even for processes with high variability, by leveraging the concept of a digital twin. This work proposes a scalable cyberphysical infrastructure to enable the construction and use of such digital twins. This work also introduces the concept of an Augmented Intelligence Relay, which allows Artificial Intelligence algorithms to predict component performance for a given application even when it is impractical to perform a large number of physical tests.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Mesoporous Thin Film Architectures: Addressing Material Demands through Molecular Self-Assembly

Mesoporous thin films spark interest across a wide range of disciplines due to their tunable nanostructures, large internal surface areas, and strong compatibility with planar optical, electronic, and microfluidic devices. While attention in the porous materials community has shifted toward macroporous or disordered nanoporous systems, a resurgence in mesoporous thin film research is underway, driven by new molecular self-assembly methods, advanced materials chemistry, and improved characterization techniques. The integration of high-χN block copolymer design, kinetically persistent micelle templating, and postdeposition processing protocols now allows control over structural parameters such as pore size, wall thickness, porosity, and connectivity. These advances have overcome many of the thermodynamic and processing constraints that previously limited widespread adoption. Rather than serving only as high-surface-area supports, mesoporous thin films are engineered as active interfaces where responsive chemistries and nanoscale confinement act in tandem. Embedding switchable ligands, thermoresponsive polymers, redox mediators, or ion-selective groups directly within the pore walls enables real-time control over transport, optical, and electrochemical properties. These capabilities open up new directions in adaptive coatings, gated membranes, and fast-response biosensors. To further expand their functional scope, mesoporous films are integrated into hierarchical and multicomponent architectures. Techniques such as triblock terpolymer templating, crack-directed assembly, and nanoimprint lithography allow for control over spatial organization on the micron and submicron scale and pore system orientation. This enables programmable anisotropy, enhanced molecular diffusion, and wavelength-selective photonic behavior, essential for next-generation sensing, catalysis, and energy applications. Such structural and functional complexity requires equally sophisticated characterization. Multimodal and in situ techniques can track material dynamics under operational conditions. Recent progress includes extended-range ellipsometric porosimetry (EP) for hierarchical architectures, vacuum EP for interface energetics, time-resolved EP for diffusion kinetics, and correlative AFM-SAXS mapping. The introduction of advanced neutron-based spectroscopies, particularly quasielastic neutron scattering (QENS), promises to provide real-time access to ion transport dynamics and segmental motion under nanoscale confinement, offering a path toward deeper mechanistic understanding of structure-performance correlations in mesoporous systems. This Account reflects the technical advances made and the interdisciplinary collaborations that have shaped our collective vision. The particular dimensions of mesopores enable us to subtly tune interactions at the molecular, interfacial, and mesoscopic levels that permit us to harness nanoconfinement. What emerges is a versatile, modular platform capable of chemical gating, energy transduction, and sensing with a level of tunability unmatched by other porous materials. We highlight critical challenges including the need for more robust large-area processing, a deeper understanding of dynamic behavior under cycling, and better integration with device-level architectures. Our strategies support the transition of mesoporous thin films into active high-performance components in next-generation energy, environmental, and biomedical systems.

oxides↗

DOE OSTI2023

Commercial Vehicle Electrification Evaluation Toolkit (CVEET)

The CVEET can identify and characterize charging and battery capacity challenges for class 3-8 commercial vehicle electrification, including battery electric and plug in hybrid vehicles for various trucks, vans and buses, over a wide range of vehicle operation. The tool can help build the understanding of the impact of commercial vehicle electrification on energy consumption, payload penalty, and GHG (i.e., CO2) emissions. The tool employs a quantitative approach to estimate electric vehicle energy consumption, characterize component performance and determine appropriate charging assumptions to conduct a comprehensive priority analysis of MD/HD vehicle electrification using public domain data.

Gao, Zhiming↗

DOE OSTI2025

Design Assessment of Brayton Cycles for Combined Heat and Power from Nuclear Power Plants

Brayton cycles (BCs) are gaining renewed interest for use in high-temperature nuclear reactors for power production. This study explores the potential of nuclear Brayton systems in industrial combined heat and power (CHP) production. After a review of the historical deployment and technical development of BC systems for nuclear and cogeneration applications several BCs in CHP configurations are assessed when applied to representative high-temperature reactor types. The analysis emphasizes process heat delivery options, electrical efficiency, and component performance for the case of a direct cycle—Helium BC in a high temperature gas reactor, and an open-air Brayton cycle with a high temperature gas reactor. The results highlight thermodynamic trade-offs in cogeneration operation, particularly in recuperated configurations, and compare BC-based CHP with conventional Rankine cycle (RC) performance. Key findings suggest Helium BCs offer viable CHP performance primarily at lower process heat temperatures, with open air cycles being less efficient. The work also demonstrates trade-off between CHP performance and power production performance with a detailed comparison to where steam RC has better performance. The work is designed to be used as a reference work when cogeneration is proposed from high temperature reactors alongside the use of BCs.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

U.S. Effort Support to Examinations at Fukushima - Meeting Notes with Updated Information Requests (FY2020)

Much is still not known about the end-state of core materials in each unit that was operating on March 11, 2011 at the Fukushima Daiichi Nuclear Power Station (Daiichi). Information obtained from Daiichi is required to inform Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This document, which has been updated to include Fiscal Year 2020 (FY2020) information, summarizes results from a U.S. effort to review Daiichi information and extract insights to enhance the safety of existing and future nuclear power plant designs. This U.S. effort, which was initiated in 2014 by the Department of Energy Office of Nuclear Energy (DOE-NE), is completed by a group of experts in reactor safety and plant operations that identify examination needs and evaluate recent Daiichi examination data to address these needs. Since its inception, comprehensive annual reports were issued that document significant safety insights being obtained in areas of special emphasis: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties related to severe accident modeling progression, these insights have and continue to be used to update guidance for severe accident prevention, mitigation, and emergency planning. Reduced uncertainties in modeling the events at Daiichi improve the realism of reactor safety evaluations that inform future D&D activities. For FY2020, it was decided that the program would gain more benefit from a more concise report that emphasizes new information and insights that affect prior findings and recommendations from the U.S. experts participating in this effort. A key aspect of prior U.S. efforts, the updated list of information requests, is included in this letter report to ensure that they are transmitted to organizations within Japan. In addition, findings and associated recommendations are provided regarding information presented by TEPCO Holdings, Nuclear Damage Compensation and Decommissioning Facilitation Corporation (NDF), and the Japan Atomic Energy Agency (JAEA). This letter report also continues to emphasize how information obtained from the affected reactors at Daiichi has been and will continue to be used to update severe accident management strategies, improve maintenance activities (especially in areas of radiation protection) and reduce uncertainties in systems analysis code models. In addition, recommendations are included that would expand the use of this information to provide insights regarding maintenance, radiation protection, design, and siting activities of existing and new reactors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

SAM Co-Development to Support Fluoride-salt-cooled High-temperature Reactor Design and Licensing (CRADA 2018-18177 Final Report)

This project aims to raise the SAM code's technical and commercial maturity level to enable the Kairos Power ("Kairos") to use SAM to support its KP-FHR design analysis and licensing application. Argonne National Laboratory ("Argonne") has actively developed and maintained SAM, a modern system-level analysis tool for advanced nonlight water reactors safety analysis. Kairos is currently actively pursuing development of an FHR design and associated technology, and consequently requires a pedigreed safety analysis tool. The purpose of this project is to increase the maturity of the SAM code for the modeling and simulation of the KP-FHR design, thus enabling its use in safety analyses that support licensing application. Argonne will primarily be responsible for software design, development, and testing; while Kairos will be responsible for software requirements, assessment of software capabilities, needs, gaps, and priorities, and development of proprietary models. The research and development activities for the joint SAM development project include: a series of identification and prioritization studies on design characteristics, event sequences, relevant phenomena, and software capabilities; SAM capability enhancements for specific KP-FHR systems and components; performing code verification and validations; integrating uncertainty quantification (UQ), model calibration, and sensitivity analysis (SA) techniques in safety analyses; and raising the software quality rigor level for commercial-grade applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

U.S. Efforts in Support of Examinations at Fukushima Daiichi- November 2020 Meeting Notes with Updated Information Requests

Much is still not known about the end-state of core materials in each unit that was operating on March 11, 2011 at the Fukushima Daiichi Nuclear Power Station (Daiichi). Information obtained from Daiichi is required to inform Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. commercial nuclear power plants. This document summarizes results from the Fiscal Year 2021 (FY2021) U.S. effort to review Daiichi information and extract insights to enhance the safety of existing and future nuclear power plant designs. This U.S. effort, which was initiated in 2014 by the Department of Energy Office of Nuclear Energy (DOE-NE), is completed by a group of experts in reactor safety and plant operations that identify examination needs and evaluate recent Daiichi examination data to address these needs. Since its inception, annual reports were issued that document significant safety insights being obtained in areas of special emphasis: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties related to severe accident modeling progression, these insights have and continue to be used to update guidance for severe accident prevention, mitigation, and emergency planning. Reduced uncertainties in modeling the events at Daiichi improve the realism of reactor safety evaluations that inform future D&D activities. A key aspect of prior U.S. efforts, the updated list of information requests, is included in this FY2021 report to ensure that they are transmitted to organizations within Japan. This report also continues to emphasize how information obtained from the affected reactors at Daiichi has been and will continue to be used to update severe accident management strategies and reduce uncertainties in systems analysis code models. In addition, recommendations are included that would expand the use of this information to provide insights regarding maintenance, radiation protection, design, and siting activities for existing and new reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

U.S. Efforts in Support of Examinations at Fukushima Daiichi (November 2021 Meeting Notes with Updated Information Requests)

Information obtained from Fukushima Daiichi Nuclear Power Station (Daiichi) is required to inform future Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. commercial nuclear power plants. This document summarizes results from the Fiscal Year 2022 (FY2022) U.S. effort to review Daiichi information and extract insights to enhance the safety of existing and future nuclear power plant designs. This U.S. effort, which was initiated in 2014 by the Department of Energy Office of Nuclear Energy, is completed by a group of experts in reactor safety and plant operations that identify examination needs and evaluate recent Daiichi examination data to address these needs. Fukushima-related information and associated discussions during forensics meetings benefit operating, new, and advanced reactors. Significant safety insights are being obtained in several areas: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties related to severe accident modeling progression, these insights have and continue to be used to update guidance for severe accident prevention, mitigation, and emergency planning. As discussed in this document, revised operator guidance was successfully used to improve operator response during a loss of off-site power event at the Duane Arnold Energy Center plant. Reduced uncertainties in modeling the events at Daiichi improve the realism of reactor safety evaluations that inform future D&D activities. U.S. evaluations of information from Fukushima and input regarding future examinations are of interest to several organizations within Japan. Meeting presentations by Japan describe how comments and recommendations documented in prior U.S. forensics effort reports, including consensus information requests developed by forensics effort participants, are considered in future Fukushima D&D activities. As discussed in this report, TEPCO Holdings considered these information requests in their D&D planning activities. An updated list of consensus information requests is included in this FY2022 report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Biofouling Analysis for Wave Energy Piston Design: CRADA 542 [Abstract only]

Triton System’s Wave Energy Converter (WEC) uses an oscillating water column approach to provide small scale power to ocean observing and navigational buoys. Biofouling and corrosion are a major concern for all ocean-deployed components, especially when mechanical motion is involved. Triton Systems will collaborate with PNNL to evaluate seals, materials, and component performance in a controlled biofouling test environment. Results from this testing will be used to improve seal design and material selection, mitigating risk of premature failure during open water testing and evaluation.

16 TIDAL AND WAVE POWER↗

DOE OSTI2022

Quantifying Thermal Output of Energetic Materials (LDRD Final Report)

We present the results of an LDRD project, funded by the Nuclear Deterrence IA, to develop capabilities for quantitative assessment of pyrotechnic thermal output. The thermal battery igniter is used as an exemplar system. Experimental methodologies for thermal output evaluation are demonstrated here, which can help designers and engineers better specify pyrotechnic components , provide thermal output guidelines for new formulations, and generate new metrics for assessing component performance and margin given a known failure condition. A heat-transfer analysis confirms that the dominant mode of energy transfer from the pyrotechnic output plume to the heat pellet is conduction via deposition of hot titanium particles. A simple lumped-parameter model of titanium particle heat transfer and a detailed multi-phase model of deposition heat transfer are discussed. Pyrotechnic function, as defined by "go/no-go" standoff testing of a heat pellet, is correlated with experimentally measured igniter plume temperature, titanium metal particle temperature, and energy deposition. Three high-speed thermal diagnostics were developed for this task. A three-color imaging pyrometer, acquiring 100k images per second on three color channels, is deployed for measurement of titanium particle temperatures. Complimentary measurements of the overall igniter plume emission ("color") temperature were conducted using a transmission-grating spectrograph in line-imaging mode. Heat flux and energy deposition to a cold wall at the heat-pellet location were estimated using an eroding thermocouple probe, with a frequency response of ~5 kHz. Ultimate "go/no-go" function in the igniter/heat-pellet system was correlated with quantitative thermal metrics, in particular surface energy deposition and plume color temperature. Titanium metal-particle and plume color temperatures both experience an upper bound approximated by the 3245-K boiling point of TiO 2 . Average metal-particle temperatures remained nearly constant for all standoff distances at T = 2850 K, ± 300 K, while plume color temperature and heat flux decay with standoff—suggesting that heat-pellet failure results from a drop in metal-particle flux and not particle temperature. At 50% likelihood of heat-pellet failure, peak time-resolved plume color temperatures drop well below TiO 2 boiling to ~2000 - 2200 K, near the TiO 2 melting point. Estimates of peak heat flux decline from up to 1 GW/m 2 for near-field standoffs to below 320 MW/m 2 at 50% failure likelihood.

36 MATERIALS SCIENCE↗