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At least 73 records · Page 4

Optimizing Error-Bounded Lossy Compression for Scientific Data With Diverse Constraints

Vast volumes of data are produced by today's scientific simulations and advanced instruments. These data cannot be stored and transferred efficiently because of limited I/O bandwidth, network speed, and storage capacity. Error-bounded lossy compression can be an effective method for addressing these issues: not only can it significantly reduce data size, but it can also control the data distortion based on user-defined error bounds. In practice, many scientific applications have specific requirements or constraints for lossy compression, in order to guarantee that the reconstructed data are valid for post hoc analysis. For example, some datasets contain irrelevant data that should be isolated in particular and users often have intuition regarding value ranges, geospatial regions, and other data subsets that are crucial for subsequent analysis. Existing state-of-the-art error-bounded lossy compressors, however, do not consider these constraints during compression, resulting in inferior compression ratios with respect to user's post hoc analysis, due to the fact that the data itself provides little or no value for post hoc analysis. In this work we address this issue by proposing an optimized framework that can preserve diverse constraints during the error-bounded lossy compression, e.g., cleaning the irrelevant data, efficiently preserving different precision for multiple value intervals, and allowing users to set diverse precision over both regular and irregular regions. We perform our evaluation on a supercomputer with up to 2,100 cores. Experiments with six real-world applications show that our proposed diverse constraints based error-bounded lossy compressor can obtain a higher visual quality or data fidelity on reconstructed data with the same or even higher compression ratios compared with the traditional state-of-the-art compressor SZ. Furthermore, our experiments also demonstrate very good scalability in compression performance compared with the I/O throughput of the parallel file system.

97 MATHEMATICS AND COMPUTING↗

Optimization of In-Field Alpha Spectrometry for Uranium Enrichment Determination in Uranium Hexafluoride

In response to needs identified by the International Atomic Energy Agency (IAEA) research is underway to develop In-Field Alpha Spectrometry (IFAS) as a method to allow IAEA safeguards inspectors to collect samples of uranium hexafluoride (UF6) at processing facilities to assess and verify uranium enrichment. For sample collection, the IFAS method uses Single-Use Destructive Assay (SUDA) samplers, which contain thin zeolite coatings that trap UF6 gas and convert it to the safer, more stable form uranyl fluoride (UO2F2). For alpha spectrometry, the IFAS instrument employs a large area silicon semiconductor transducer to detect and record alpha particle energy-deposition events. Over the past year optimization work has significantly increased the diameter of useful SUDA samples (from 12.7 mm to 48 mm), improved the manufacturability and reproducibility of SUDA samples, increased the area of the IFAS alpha spectrometer sensor from 1.2 cm to 3.1 cm, and improved source positioning within the IFAS. This paper will report on this optimization work, its impacts on IFAS performance, and future plans for IFAS miniaturization, improvements, and testing.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

AI-Science for Performance Optimization and Diagnosis of Science Instrument Federations

Next generation of science workflows are expected to be executed over complex federations composed of supercomputers, science instruments, storage systems and networks, with new additions of the edge and cloud systems and services. The sheer complexity of these multi-domain federations makes it hard to manage them and optimize their performance, as small impedance mismatches (that can dynamically develop between systems) could drastically degrade the entire federation performance. Recent proliferation of Software Defined Everything (SDX) technologies combined with containerization frameworks provide custom instruments that can monitor and collect critical measurements at various levels to support diagnoses and performance optimization; but their data too enormous for human operators and analysts to process and generate decisions. Machine Learning (ML) methods that extract critical parameters, relationships and trends from the data offer general solutions. Artificial Intelligence (AI) and ML methods must be custom-developed for these problems based on solid, rigorous foundations, since black-box approaches are often ineffective and unsound.We propose to develop comprehensive AI-Science for the performance of science federations to (i) monitor and control storage, networks, experiments, and computing systems across multiple domains via softwarization layers, at speeds and scales orders of magnitude superior to current practice, (ii) optimally realize and orchestrate complex workflows with high performance by using dynamic state and performance estimation methods, and (iii) aggregate measurements across sites and time to develop infrastructure-level profiles, optimizations and diagnoses using AI-Science based on foundational principles from ML, game theory, and information fusion areas.

Rao, Nageswara↗

The Kalai-Smorodinsky solution for many-objective Bayesian optimization

An ongoing aim of research in multiobjective Bayesian optimization is to extend its applicability to a large number of objectives. While coping with a limited budget of evaluations, recovering the set of optimal compromise solutions generally requires numerous observations and is less interpretable since this set tends to grow larger with the number of objectives. We thus propose to focus on a specific solution originating from game theory, the Kalai-Smorodinsky solution, which possesses attractive properties. In particular, it ensures equal marginal gains over all objectives. We further make it insensitive to a monotonic transformation of the objectives by considering the objectives in the copula space. A novel tailored algorithm is proposed to search for the solution, in the form of a Bayesian optimization algorithm: sequential sampling decisions are made based on acquisition functions that derive from an instrumental Gaussian process prior. Our approach is tested on four problems with respectively four, six, eight, and nine objectives. The method is available in the R package GPGame available on CRAN at https://cran.r-project.org/package=GPGame.

Game theory↗

Rapid 235 U/ 238 U determination by matrix assisted ionization–time-of-flight mass spectrometry

Matrix-assisted ionization (MAI) of inorganic analytes is a nascent research domain that holds promise for rapid, potentially facility-deployable analytical applications. Here, we present results of MAI uranium isotopic analysis ( 235 U/ 238 U) obtained on the timescale of minutes utilizing simple sample preparation and an ambient ionization time-of-flight mass spectrometer (ToF MS). Experimental MAI-ToF MS characterization of uranium Certified Reference Materials (CRMs) was used to establish method calibration and validate quantitative 235 U/ 238 U determination spanning depleted, natural, and low-enriched uranium isotopic compositions. Secondary standard analyses with total uranium mass loadings of 5–500 ng per analysis yield accurate calibrated 235 U/ 238 U results and relative uncertainties of 4.7–17.2% (approx. ±95% confidence level), with weighted-mean uncertainties approaching 1.5%. This method permits accurate determination of uranium isotopic composition in a sample with uranium content as low as 200 pg for equal atom 235 U: 238 U. Instrument detection limits constrain the minimum uranium mass required to identify the presence of highly enriched uranium (HEU ≥20% 235 U) as only 500 pg using the method presented here. MAI-ToF MS quantitation of relatively extreme isotope ratios ( 235 U/ 238 U ≤ 0.01) is limited by detection of minor 235 U (LoD 100 pg 235 U/analysis ≈ 10 ng total U/analysis), and subsequent method optimization is anticipated to further reduce these limits. These findings underscore the potential of MAI-ToF MS for isotopic characterization of uranium and other inorganic species for both basic and applied science.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Reward based optimization of resonance-enhanced piezoresponse spectroscopy

Dynamic spectroscopies in scanning probe microscopy (SPM) are critical for probing material properties, such as force interactions, mechanical properties, polarization switching, electrochemical reactions, and ionic dynamics. However, the practical implementation of these measurements is constrained by the need to balance imaging time and data quality. Signal to noise requirements favor long acquisition times and high frequencies to improve signal fidelity. However, these are limited on the low end by contact resonant frequency and photodiode sensitivity and on the high end by the time needed to acquire high-resolution spectra or the propensity for sample degradation under high field excitation over long times. The interdependence of key parameters such as instrument settings, acquisition times, and sampling rates makes manual tuning labor-intensive and highly dependent on user expertise, often yielding operator-dependent results. These limitations are prominent in techniques like dual amplitude resonance tracking in piezoresponse force microscopy that utilize multiple concurrent feedback loops for topography and resonance frequency tracking. Here, a reward-driven workflow is proposed that automates the tuning process, adapting experimental conditions in real time to optimize data quality. Furthermore, this approach significantly reduces the complexity and time required for manual adjustments and can be extended to other SPM spectroscopic methods, enhancing overall efficiency and reproducibility.

47 OTHER INSTRUMENTATION↗

X-Ray Fluorescence Quantitative and Qualitative Analysis Using Micro Glass Beads

The fused glass bead method is the accepted 'best practice' method of preparation of samples for X-ray fluorescence (XRF) analysis. It minimizes the effects of sample heterogeneity and simplifies calibration by dissolving the sample into a uniform glass matrix. Glass fusion XRF samples are typically prepared by grinding sample powder with Lithium Tetraborate / Lithium Bromide and fusing the mixture at 1000 deg. C. In most cases sample-to-flux ratios of between 1:1 to 1:10 are used (1:1 for determination of trace elements and 1:10 for major elements). Typical sample mass consumed is in the range of 1000 to 2500 mg. It would be advantageous to reduce this sample mass in cases where the sample material is rare, valuable or highly radioactive. This study examines the effects of using lower sample-to-flux ratios and smaller fusion bead size on the detection and quantification of major and trace elements by XRF analysis. We have employed a micro fused glass bead process, using sample-to-flux ratios of 1:10, 1:15 and 1:25, to determine the effects on measurement precision, accuracy and detection limit. Objectives: - Created micro fused glass beads of a series of standards and andesite sample with sample-to-flux ratios of 1:10, 1:15 and 1:25. - Perform an qualitative analysis of the different sample-to-flux ratio micro beads and compare the results with the 1:5.3 beads routinely used at SRNL. - Quantitate the major components in the different sample-to-flux ratio micro beads using a wavelength dispersive x-ray fluorescence instrument. Advantages: - Reduce sample amount needed. - Speed up waste tank characterization. - Reduce personnel exposure. - Potential sealed source. Fused micro glass beads with sample-to-flux ratios of 1:10, 1:15 and 1:25 were created using sample amounts of 123 mg, 82 mg and 52 mg respectively. It was possible to detect most of the major oxides and some trace elements in the fused micro glass beads with different sample-to-flux ratios. The quantitative analysis showed good linear correlation between the intensity of the analysis and the concentration of the elements. Good precision and accuracy results were obtained for the majority of the major oxides in the three fused micro glass beads with different sample-to-flux ratios. Path Forward: Enhance the precision and accuracy of the method by optimizing different sample preparation steps, such as weighing and sample transfer. Continue to increase the sample-to-flux ratio to determine the minimum amount of sample needed to perform a multielement analysis. Consider the use of synthetic standards to lower the detection limit of the analysis. Used the micro bead sample preparation method to analyze radioactive samples.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Data-driven chaos indicator for nonlinear dynamics and applications on storage ring lattice design

A data-driven chaos indicator concept is introduced to characterize the degree of chaos for nonlinear dynamical systems. The indicator is represented by the prediction accuracy of surrogate models established purely from data. It provides a metric for the predictability of nonlinear motions in a given system. When using the indicator to implement a tune-scan for a quadratic Hénon map, the main resonances and their asymmetric stop-band widths can be identified. When applied to particle transportation in a storage ring, as particle motion becomes more chaotic, its surrogate model prediction accuracy decreases correspondingly. So, the prediction accuracy, acting as a chaos indicator, can be used directly as the objective for nonlinear beam dynamics optimization. This method provides a different perspective on nonlinear beam dynamics and an efficient method for nonlinear lattice optimization. Applications in dynamic aperture optimization are demonstrated as real world examples.

36 MATERIALS SCIENCE↗

Optimization Of In-field Alpha Spectrometry For Uranium Enrichment Determination In Uranium Hexafluoride

In response to needs identified by the International Atomic Energy Agency (IAEA) research is underway to develop In-Field Alpha Spectrometry (IFAS) as a method to allow IAEA safeguards inspectors to collect samples of uranium hexafluoride (UF6) at processing facilities to assess and verify uranium enrichment. For sample collection, the IFAS method uses Single-Use Destructive Assay (SUDA) samplers, which contain thin zeolite coatings that trap UF6 gas and convert it to the safer, more stable form uranyl fluoride (as a dihydrate, UO2F2·2H2O). For alpha spectrometry, the IFAS instrument employs a large area silicon semiconductor transducer to detect and record alpha particle energy-deposition events. Over the past year optimization work has significantly increased the diameter of useful SUDA samples (from 12.7 mm to 48 mm), improved the manufacturability and reproducibility of SUDA samples, increased the area of the IFAS alpha spectrometer sensor from 1.2 cm to 3.1 cm, and improved source positioning within the IFAS. This paper will report on this optimization work, its impacts on IFAS performance, and future plans for IFAS miniaturization, improvements, and testing.

Chichester, David↗

Modeling of transverse stimulated Raman scattering in KDP/DKDP in large-aperture plates suitable for polarization control

Transverse stimulated Raman scattering (TSRS) in potassium dihydrogen phosphate (KDP) and deuterated potassium dihydrogen phosphate (DKDP) plates for large-aperture, inertial confinement fusion (ICF)-class laser systems is a well-recognized limitation giving rise to parasitic energy conversion and laser-induced damage. The onset of TSRS is manifested in plates exposed to the ultraviolet section of the beam. TSRS amplification is a coherent process that grows exponentially and is distributed nonuniformly in the crystal and at the crystal surfaces. To understand the growth and spatial distribution of TSRS energy in various configurations, a modeling approach has been developed to simulate the operational conditions relevant to ICF-class laser systems. Specific aspects explored in this work include (i) the behavior of TSRS in large-aperture crystal plates suitable for third-harmonic generation and use as wave plates for polarization control in current-generation ICF-class laser system configurations; (ii) methods, and their limitations, of TSRS suppression and (iii) optimal geometries to guide future designs.

47 OTHER INSTRUMENTATION↗

RF design of APEX2 two-cell continuous-wave normal conducting photoelectron gun cavity based on multi-objective genetic algorithm

High brightness, high repetition rate electron beams are key components for optimizing the performance of next generation scientific instruments, such as MHz-class X-ray Free Electron Laser (XFEL) and Ultra-fast Electron Diffraction/Microscopy (UED/UEM). In the Advanced Photo-injector EXperiment (APEX)at Berkeley Lab, a photoelectron gun based on a 185.7 MHz normal conducting re-entrant RF cavity, has been proven to be a feasible solution to provide high brightness, high repetition rate electron beam for both XFEL and UED/UEM. Based on the success of APEX, a new electron gun system, named APEX2, has been under development to further improve the electron beam brightness. For APEX2, we have designed a new 162.5 MHz two-cell photoelectron gun and achieved a significant increase on the cathode launching field and the beam exit energy. For a fixed charge per bunch, these improvements will allow for the emittance reduction and hence to an increased beam brightness. The design of APEX2 gun cavity is a complex problem with multiple design goals and restrictions, some even competing each other. In conclusion, for a systematic and comprehensive search for the optimized cavity geometry, we have developed and implemented a novel optimization method based on the Multi-Objective Genetic Algorithm (MOGA).

47 OTHER INSTRUMENTATION↗

Enhancing Camera Calibration for Traffic Surveillance with an Integrated Approach of Genetic Algorithm and Particle Swarm Optimization

Recent advancements in sensor technologies, coupled with signal processing and machine learning, have enabled real-time traffic control systems to effectively adapt to changing traffic conditions. Cameras, as sensors, offer a cost-effective means to determine the number, location, type, and speed of vehicles, aiding decision-making at traffic intersections. However, the effective use of cameras for traffic surveillance requires proper calibration. This paper proposes a new optimization-based method for camera calibration. In this approach, initial calibration parameters are established using the Direct Linear Transformation (DLT) method. Then, optimization algorithms are applied to further refine the calibration parameters for the correction of nonlinear lens distortions. A significant enhancement in the optimization process is achieved through the integration of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) into a combined Integrated GA and PSO (IGAPSO) technique. The effectiveness of this method is demonstrated through the calibration of eleven roadside cameras at three different intersections. The experimental results show that when compared to the baseline DLT method, the vehicle localization error is reduced by 22.30% with GA, 22.31% with PSO, and 25.51% with IGAPSO.

47 OTHER INSTRUMENTATION↗

PAL Experimental Report Form

We constructed the first simultaneous dark- and bright-field X-ray microscope in this experiment, coupling it to simultaneous measurements of the wide-angle Xray diffraction, and the XFEL pulse intensity and energy spectrum on each shot. This experiment established proof of concept for this new advanced measurement technique and demonstrated DFXM at an XFEL for the first time. Within this complex experiment, we also acquired data that advanced our research goals within materials science and mathematics. These included: A preliminary study of how local effects reduce the X-ray damage threshold in diamond; A preliminary study of how X-ray radiation imparts heat into materials based on irreversible phase transitions that occur in boric acid with increasing temperature (based on hydration); A study of X-ray radiation damage from ultrafast thermal cycling and nonthermal melting in bismuth selenide; We also began developing software to automate alignment of compound refractive lenses (CRLs) using stochastic Nelder-Mead optimization methods. This work will expedite and improve the accuracy of alignments for many future experiments using CRLs.

36 MATERIALS SCIENCE↗

Advanced Manufacturing for Nuclear Core Design

Advanced manufacturing technologies are fundamentally altering the way components are designed and manufactured. The potential application space for these technologies within the nuclear industry is broad, with the most benefit realized from the ability to approach the nuclear core design problem from an advanced manufacturing perspective. One of the objectives of the US Department of Energy Office of Nuclear Energy (DOE-NE) Transformational Challenge Reactor (TCR) design and analysis activities is to demonstrate this approach. A mitigation of conventional constraints realized through advanced manufacturing methods opens up the design space, enabling a departure from typical axially uniform pin- and plate-type geometries common to operating nuclear reactors worldwide. The ability to use more heterogenous spatial and material flexibilities increases the demand on the predictability of higher fidelity modeling and simulation tools to be used in the design, analysis, and optimization processes. Leading candidate advanced manufacturing technologies for nuclear applications are additive methods that provide for high dimensional control and incorporation of small design features such as powder bed fusion, laser directed energy deposition, and binder jetting. Potential applications to core design identified during DOE-NE TCR design and analysis activities fall into two categories: those that are uniquely enabled by additive manufacturing technologies and those that are enabled by the characteristics (e.g., repeatability and instrumentation) inherent to these technologies. Identified applications include reducing in-core parasitic materials, improving heat conduction across fuel-cladding gaps, optimizing thermal hydraulic design with flexible coolant flow geometries, reducing uncertainties in manufactured components, optimizing core conditions with design heterogeneities, designing feedback mechanisms using material characteristics, and embedding burnable poisons. These potential applications join a host of nuclear industry advanced manufacturing activities to recapture manufacturing capabilities, reduce manufacturing costs and complexities, reduce deployment time, and enable performance and operational enhancements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Validation of RELAP-7 for Forced Convective and Natural Circulation Reactor Flows

New reactor designs such as small modular reactors and newly proposed passive safety systems rely on natural circulation two-phase flow cooling of the reactor core under accident conditions. Without a pump to drive the flow, the circulation rate is a strong function of void fraction. Under these conditions where the flow rate, pressure drop, and heat transfer are all closely coupled through the mixture density, the accurate prediction of void fraction is pivotal. Furthermore, while these passive systems boast a more reliable cooling option, the sensitivity of the system to two-phase flow instabilities is more likely than in forced convective cooling and can result in dangerous density wave or flow excursion conditions. Improvement of one-dimensional system codes and further development of three-dimensional code capability are all important efforts in addressing these issues. The proposed work is a critical step towards providing confidence through validation of the capability of thermal-hydraulic tools to meet the emerging challenges in reactor simulation. Historically, system analysis codes develop a stiffness over time due to fine-tuning of adjustable code parameters that result in a reluctance or inability to adopt improved models. Therefore, a rigorous effort should be invested in preparation for RELAP-7 to identify required modeling improvements of constitutive relations and validation of the code applicability to the wide range of possible reactor flow conditions. Part of this validation involves the uncertainty quantification which is a critical step in the Code Scaling, Applicability, and Uncertainty (CSAU) methodology and Best-Estimate Plus Uncertainty (BEPU) licensing method. BEPU allows recovery of safety margins and potentially optimizing plant performance, resulting in economic benefit for the reactor operators. Beginning with the collection of past experimental data covering prototypic LWR conditions, this document reviews three critical datasets available for the validation of system codes. The experimental methods, procedures, facilities, instrumentation, and supplementary information are consolidated to aid the validation efforts of this work and future projects. These three datasets (824 conditions) are chosen due to their wide acceptance and demonstrated application for code validation. Two experimental datasets from the Nuclear Power Engineering Corporation (NUPEC) span prototypic conditions of Boiling Water Reactors (BWR) and Pressurized Water Reactors (PWR). These datasets are labeled as the BFBT (BWR Full-size Fine-mesh Bundle Test) and the PSBT (PWR Subchannel and Bundle Test) datasets respectively. The third dataset is taken in an internally heated annulus that is scaled based on a BWR subassembly and includes two-phase flows important to post-blowdown analysis. Together, the datasets consider the full range of pressure and mass flux expected in LWR forced convective flows from steady-state to long term cooling conditions. Recognizing the deficiency of available data under low-pressure, low-flow, a new natural circulation dataset consisting of 107 conditions is obtained. With system pressures ranging between 145 and 950 kPa, natural circulation is driven by a heat flux up to 275 kW/m2 in a 3 m long heated region of the annulus test section which is followed by a 2 m long unheated region before entering a condenser. Stable natural circulation flow rates in this facility were measured to be between 182 and 590 kg/m2-s. Pressure and temperature are measured at ten locations in the facility. In addition, measurements of void fraction, interfacial area concentration, and gas velocity are obtained at five axial locations in the annulus test section. The RELAP5-3D code demonstrates good accuracy for void fraction predictions in BFBT and PSBT benchmarks, but shows relatively large discrepancy in the annulus experiments at lower pressures. In two-phase natural circulation, large oscillations are observed in many system parameters during the simulation of 19 experiment cases which were conducted at low pressures, and the model shows good predictive performance with the remaining 88 experiment cases. However, some discrepancies in void fraction and temperature predictions are found which may require improved constitutive modeling under these low-pressure, low-flow condition. The quantified uncertainty in void fraction predictions in three forced convection benchmarks due to uncertainties in boundary conditions and geometries are relatively small, except for a few cases in the annulus experiment. The output uncertainty of the natural circulation model is quantified by considering the measurement error in boundary conditions, and it is shown that the output uncertainty ranges are relatively small for the range of conditions considered. Through this work, a clear pathway is provided for validation of RELAP7 once the code is available.

42 ENGINEERING↗

Advanced manufacturing of 3D custom boron-carbide collimators designed for complex environments for neutron scattering

Scattered-beam collimation is a very useful method to reduce unwanted backgrounds and to boost the desired sample signal instead. This approach is of particular interest for samples contained within a complex environment that gives rise to much unwanted parasitic scatter. As neutron scattering instrument and techniques advances, small samples are becoming of more and more interest, which necessitates optimized collimation. Here, in this work, we describe a concept for the design and fabrication of advanced scattered-beam collimation 3D printed from B 4 C specifically tailored for samples contained within a complex environment. This concept is demonstrated through the use of a diamond anvil cell for high pressure experimentation, a technique that very typically requires small samples. The collimators here are designed through a modeling procedure via Monte Carlo neutron ray tracing that encompasses the entire system: the instrument, the complex environment and the collimator. Since the first approach of simply scaling up of the print-size was not successful, a novel concept of a multi-part alternate-blade collimator was developed. This approach addresses printing constraints but gives greater flexibility in design. Its performance is computationally compared against an unprintable progressively tighter blade collimator to assess the effect of alternating blades. No strong difference was observed. Its performance was validated through experimentation at the Spallation Neutron Source. The results emphasize the critical importance of ultra-high precision alignment while showing good overall agreement between simulation and experiment and underscore the feasibility of the method and its real-world application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development of A Multi-Spectral Pyrometry Sensor for High-Speed Transient Surface-Temperature Measurements in Combustion-Relevant Harsh Environments

Accurate and high-speed transient surface-temperature measurements of combustion devices including internal combustion (IC) engines, gas turbines, etc., provide validation targets and boundary conditions for computational fluid dynamics models, and are broadly relevant to technology advancements such as performance improvement and emissions reduction. Development and demonstration of a multi-infrared-channel pyrometry-based optical instrument for high-speed surface-temperature measurement is described. The measurement principle is based on multi-spectral radiation thermometry (MRT) and uses surface thermal radiation at four discrete spectral regions and a corresponding emissivity model to obtain surface temperature via non-linear least squares (NLLS) optimization. Rules of thumb for specifying the spectral regions and considerations to avoid interference with common combustion products are developed; the impact of these along with linear and non-linear MRT analysis are assessed as a function of temperature and signal-to-noise ratio. A multi-start method to determine the MRT-solution global optimum is described and demonstrated. The resulting multi-channel transient pyrometry instrument is described along with practical considerations including optical-alignment drift, matching intra-channel transient response, and solution-confidence indicators. The instrument demonstrated excellent >97% accuracy and >99% 2-sigma precision over the 400–800 °C range, with ~20 µs (50 kHz, equivalent to 0.2 cad at 2000 RPM IC-engine operation) transient response in the bench validation.

47 OTHER INSTRUMENTATION↗