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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Target Diagnostic Menu Lawrence Livermore National Laboratory SYSM-5620: Design Thinking and Systems Engineering

Target Diagnostic’s Engineering Science (TDES) currently supports over 80 diagnostic systems, all of which draw from a fixed budget that covers staff time and procurement. As the division continues to add new diagnostics, demand on these limited resources increases, yet the budget remains unchanged. Shot Responsible Individuals (RIs) have unrestricted freedom to select any number or type of diagnostics for each experiment, often by copying previous shot configurations with only minor modifications. This practice makes it easy to generate new shots but does not encourage critical evaluation of diagnostic necessity. As a result, many diagnostics are routinely included in a shot without a clear justification, and in practice, much of the data collected is not analyzed. The ever-growing arsenal of diagnostics also increases the burden on TDES personnel, requiring more staff for support, maintenance, and service. This environment creates challenges in focusing resources on diagnostics that provide the greatest value to the NIF mission and raises concerns about the continued justification for maintaining all existing systems. The static TDES budget cannot sustain the ongoing growth in demand for new diagnostic systems. Shot RIs currently face no constraints on the number or type of diagnostics they assign to each experiment, often defaulting to previous configurations without critically assessing the necessity of each diagnostic. This results in the routine inclusion of diagnostics whose data may not be analyzed or may no longer directly support the NIF mission. Consequently, TDES is required to maintain and support an expanding set of diagnostics, straining limited resources and risking inefficient use of staff and funding. There is a need for TDES to efficiently allocate limited resources by establishing a process that requires shot RIs to critically evaluate and justify the inclusion of each diagnostic in their experiments. This process should discourage the routine, unexamined inclusion of diagnostics, support the identification of underutilized or obsolete systems, and ensure that only those diagnostics providing the greatest value to the NIF mission are maintained and supported. Ultimately, this approach must enable TDES to operate within budget constraints while maximizing scientific impact and operational efficiency.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Technical Specification Surveillance Interval Extension Using Self-Diagnostics

As part of the Light Water Reactor Sustainability program, an ongoing research effort is being conducted on technical specifications surveillance interval extension of digital equipment in nuclear power plants. The research team is led by Idaho National Laboratory and includes Pacific Northwest National Laboratory, Technology Resources, and Oak Ridge National Laboratory. This research focuses on developing methods for applying the U.S. Nuclear Regulatory Commission (NRC)–approved guidance to implement a licensee-controlled, risk-informed surveillance frequency change program in digital instrumentation and control (I&C) systems that include self-diagnostics and online monitoring (OLM) capabilities. Although approved methods exist for extending technical specifications (TS) surveillance test intervals (STIs) for general equipment, including analog I&C equipment, gaps remain in technology and guidance on crediting newer digital equipment’s internal self-diagnostics and OLM characteristics. Previous research described a general methodology for crediting internal self-diagnostics for extending surveillance test intervals. The methodology used self-diagnostics to detect—and credited recovery from—failure. Self-diagnostics were also applied for performance monitoring during the extended surveillance interval. This report discusses the status of recent activities to evaluate the previously developed methodology using a pilot study. Although both a utility partner for a pilot study and a specific digital asset were identified in FY2020, delays in obtaining proprietary information resulted in a limited ability to fully evaluate the methodology, and further interactions were complicated by the COVID pandemic. Therefore, at that time, the use of public-domain information—along with current processes for surveillance interval extension through a surveillance frequency control program—identified the need to fully assess diagnostic coverage as part of the pilot study. Furthermore, self-diagnostics were also identified as a potential option to replace the drift analyses conducted as part of current STI extension procedures. In FY2022, the project was reconstituted with the industry partner, and information and data were made available by the industry partner to the research team for review. The shared information included failure event descriptions and data for a digital I&C system since its implementation, as well as recent STI extension interval reports developed by the utility partner on that digital I&C system. This report presents an evaluation of this information and data and describes an application of the proposed methodology cited above. The methodology seeks to take advantage of the self-diagnostics and OLM capabilities to reduce risk or reduce the level of qualitative monitoring assessment needed to perform a risk-informed STI extension using existing NRC approved guidance or both. Addressing these issues of STI extension by crediting self-diagnostics is likely to result in benefits for current and future nuclear power plant (NPP) operations, including lowering the barriers to adoption of digital I&C systems and increasing cost savings by deferring or eliminating unneeded preventive maintenance (tasks or checks or activities). Specifically, self-diagnostic and OLM capabilities of newer digital equipment being installed in non-safety and safety applications are designed to detect failures, provide early warning of potential failures, and notify plant operators to take appropriate action to reduce out of service (OOS) time thus protecting safety margins. Moreover, the equipment is expected to provide information that time-related operational degradation is identified early to ensure timely and planned corrective actions instead of a reactive and unplanned approach ahead of an extended-surveillance interval.

42 ENGINEERING↗
DOE OSTI2023

Process-Oriented Diagnostics: Principles, Practice, Community Development, and Common Standards

Process-oriented diagnostics (PODs) aim to provide feedback for model developers through model analysis based on physical hypotheses. However, the step from a diagnostic based on relationships among variables, even when hypothesis driven, to specific guidance for revising model formulation or parameterizations can be substantial. The POD may provide more information than a purely performance-based metric, but a gap between POD principles and providing actionable information for specific model revisions can remain. Furthermore, in coordinating diagnostics development, there is a trade-off between freedom for the developer, aiming to capture innovation, and near-term utility to the modeling center. Best practices that allow for the former, while conforming to specifications that aid the latter, are important for community diagnostics development that leads to tangible model improvements. Promising directions to close the gap between principles and practice include the interaction of PODs with perturbed physics experiments and with more quantitative process models as well as the inclusion of personnel from modeling centers in diagnostics development groups for immediate feedback during climate model revisions. Examples are provided, along with best-practice recommendations, based on practical experience from the NOAA Model Diagnostics Task Force (MDTF). Common standards for metrics and diagnostics that have arisen from a collaboration between the MDTF and the Department of Energy’s Coordinated Model Evaluation Capability are advocated as a means of uniting community diagnostics efforts.

58 GEOSCIENCES↗
DOE OSTI2021

Nuclear diagnostics for Inertial Confinement Fusion (ICF) plasmas

The field of nuclear diagnostics for Inertial Confinement Fusion (ICF) is broadly reviewed from its beginning in the seventies to present day. During this time, the sophistication of the ICF facilities and the suite of nuclear diagnostics have substantially evolved, generally a consequence of the efforts and experience gained on previous facilities. As the fusion yields have increased several orders of magnitude during these years, the quality of the nuclear-fusion-product measurements has improved significantly, facilitating an increased level of understanding about the physics governing the nuclear phase of an ICF implosion. The field of ICF has now entered an era where the fusion yields are high enough for nuclear measurements to provide spatial, temporal and spectral information, which have proven indispensable to understanding the performance of an ICF implosion. At the same time, the requirements on the nuclear diagnostics have also become more stringent. To put these measurements into context, this review starts by providing some historical remarks about the field of ICF and the role of nuclear diagnostics, followed by a brief overview of the basic physics that characterize the nuclear phase and performance of an ICF implosion. A technical discussion is subsequently presented of the neutron, gamma-ray, charged-particle and radiochemistry diagnostics that are, or have been, routinely used in the field of ICF. This discussion is followed by an elaboration of the current view of the next-generation nuclear diagnostics. Since the seventies, the overall progress made in the areas of nuclear diagnostics and scientific understanding of an ICF implosion has been enormous, and with the implementation of new high-fusion-yield facilities world-wide, the next-generation nuclear diagnostics will play an even more important role for decades to come.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Frontier system-on-chip (SoC) technology for microwave diagnostics (invited)

The next generation of fusion reactors, exemplified by projects such as the Demonstration Power Plant following the International Thermonuclear Experimental Reactor, faces the monumental challenge of proving the viability of generating electricity through thermonuclear fusion. This pursuit introduces heightened complexities in diagnostic methodologies, particularly in microwave-based diagnostics. The increased neutron fluence necessitates significant reductions in vessel penetrations and the elimination of internal diagnostics, posing substantial challenges. SoC technology offers a promising solution by enabling the miniaturization, modularization, integration, and enhancing the reliability of microwave systems. After seven years of research, our team successfully pioneered the V- and W-band system-on-chip approach, leading to the development of active transmitters and passive receiver modules applied in practical settings, notably within the DIII-D tokamak project. Arrays of these modules have supported microwave imaging diagnostics. New physics measurement results from the Electron Cyclotron Emission Imaging system on DIII-D provide compelling evidence of improved diagnostics following the adoption of SoC technology. Furthermore, we achieved a breakthrough in developing an F-band SoC, advancing higher frequency capabilities for fusion devices. These achievements represent a significant leap forward in fusion diagnostic technology, marking substantial progress toward establishing reliable and efficient plasma diagnostics for future fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Current advances on Talbot–Lau x-ray imaging diagnostics for high energy density experiments (invited)

Talbot–Lau x-ray interferometry is a refraction-based diagnostic that can map electron density gradients through phase-contrast methods. The Talbot–Lau x-ray deflectometry (TXD) diagnostics have been deployed in several high energy density experiments. To improve diagnostic performance, a monochromatic TXD was implemented on the Multi-Tera Watt (MTW) laser using 8 keV multilayer mirrors (Δθ/θ = 4.5%-5.6%). Copper foil and wire targets were irradiated at 10 14 –10 15 W/cm 2 . Laser pulse length (~10 to 80 ps) and backlighter target configurations were explored in the context of Moiré fringe contrast and spatial resolution. Foil and wire targets delivered increased contrast <30%. The best spatial resolution (<6 μm) was measured for foils irradiated 80° from the surface. Further TXD diagnostic capability enhancement was achieved through the development of advanced data postprocessing tools. The Talbot Interferometry Analysis (TIA) code enabled x-ray refraction measurements from the MTW monochromatic TXD. Additionally, phase, attenuation, and dark-field maps of an ablating x-pinch load were retrieved through TXD. The images show a dense wire core of ~60 μm diameter surrounded by low-density material of ~40 μm thickness with an outer diameter ratio of ~2.3. Attenuation at 8 keV was measured at ~20% for the dense core and ~10% for the low-density material. Instrumental and experimental limitations for monochromatic TXD diagnostics are presented. Enhanced postprocessing capabilities enabled by TIA are demonstrated in the context of high-intensity laser and pulsed power experimental data analysis. Significant advances in TXD diagnostic capabilities are presented. Furthermore, these results inform future diagnostic technique upgrades that will improve the accuracy of plasma characterization through TXD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

The crucial role of diagnostics in achieving ignition on the National Ignition Facility (NIF)

Well over 100 diagnostics can operate on the National Ignition Facility (NIF) as a result of several decades of development on NIF, and before that on Nova, OMEGA, and earlier LLNL lasers. A subset of these have guided the approach to achieving ignition on the NIF in 2022 [H. Abu-Shawareb et al. (Indirect Drive ICF Collaboration), Phys. Rev. Lett. 129(7), 075001 (2022)]. Achieving ignition on NIF has required many types of experiments with this core set of diagnostics, some constraining known unknowns and some revealing surprises—arguably unknown unknowns. Early design work realized that the extreme precision required for ignition on NIF would require fine-tuning by experiment, that is, measuring and adjusting known unknowns. Many examples are given where the use of the core set of ignition diagnostics in experimental arrangements called platforms demonstrated control of the key theoretical parameters defined as shape, adiabat, velocity, and mix. The direction of the adjustments to input conditions is found either by trend analysis or, in many cases, by observing from the diagnostic data the direction to make an adjustment. In addition, diagnostics have revealed some unexpected or neglected known issues, which degrade performance, or unexpected issues, unknown unknowns. Some of these factors had been previously considered, but underestimated or difficult to calculate at the time. The overall methodology can be described as a variant of Popper's falsifiability philosophy [K. Popper, The Logic of Scientific Discovery (Hutchinson, 1974)]. This paper summarizes the role of ignition diagnostics in terms of falsification or validation of theory or experimental setup as well as uncovering unexpected issues. The journey to ignition started in the seventies with a 1-µm wavelength laser producing disastrous results. Diagnostics have guided us to the recent multi-decadal goal of demonstrating ignition and burn in the laboratory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Results from a synthetic model of the ITER XRCS-Core diagnostic based on high-fidelity x-ray ray tracing

A high-fidelity synthetic diagnostic has been developed for the ITER core x-ray crystal spectrometer diagnostic based on x-ray ray tracing. This synthetic diagnostic has been used to model expected performance of the diagnostic, to aid in diagnostic design, and to develop engineering tolerances. The synthetic model is based on x-ray ray tracing using the recently developed xicsrt ray tracing code and includes a fully three-dimensional representation of the diagnostic based on the computer aided design. The modeled components are: plasma geometry and emission profiles, highly oriented pyrolytic graphite pre-reflectors, spherically bent crystals, and pixelated x-ray detectors. Plasma emission profiles have been calculated for Xe 44+ , Xe 47+ , and Xe 51+ , based on an ITER operational scenario available through the Integrated Modelling & Analysis Suite database, and modeled within the ray tracing code as a volumetric x-ray source; the shape of the plasma source is determined by equilibrium geometry and an appropriate wavelength distribution to match the expected ion temperature profile. All individual components of the x-ray optical system have been modeled with high-fidelity producing a synthetic detector image that is expected to closely match what will be seen in the final as-built system. Particular care is taken to maintain preservation of photon statistics throughout the ray tracing allowing for quantitative estimates of diagnostic performance.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Development of a Direct Neutral Density Diagnostic for Fusion Edge Plasmas

As magnetically confined plasmas progress towards ignition and long pulse experiments, measurement and control of the neutral density in the plasma edge has become a critical issue for stability, formation of transport barriers, and fueling. Recent experiments by our research group have demonstrated that is possible to use two-photon absorption laser induced fluorescence (TA-LIF) to directly measure the density of neutral hydrogen in helicon sources and in the HIT-SI3 spheromak. While those experiments validated key elements of a diagnostic system that would enable similar measurements in tokamak plasmas, they did not fully address the issue of performance optimization in the presence of intense background light at the fluorescence wavelength and they also identified a number of other issues that must be resolved before successful TALIF neutral density measurements in a tokamak are likely to be achieved. Additional specific concerns raised during design reviews with the leadership of the DIII-D tokamak facility included: the minimum detection threshold for this TALIF diagnostic (currently ~ 5 x 10 15 m -3 ) and the rate at which neutral density measurements could be obtained. Improving the system performance to reduce the minimum detection threshold and demonstrating a faster rate of density determination are required to advance this diagnostic to the level where it could be considered for implementation on a major tokamak facility in the USA. The key issues that will be addressed through additional technological development are: validation of a new, chromatic aberration-free, xenon calibration scheme; increasing the output power of the laser; and suppression of background emission at the fluorescence wavelength through optimization of the collection optics and gating of the photomultiplier detector with a goal of obtaining a minimum detection threshold of 5 x 10 14 m -3 . Another key technological development, so far only tested in helicon source experiments, is the validation of Doppler-free TALIF as a means of obtaining higher speed, calibrated, neutral density measurements in tokamak-like conditions at the full cadence of the pulsed TALIF laser. In this work, we propose to complete these technological advancements through installation and testing of our prototype TALIF system on the proto-MPEX experiment at Oak Ridge National Laboratory (ORNL). The proto-MPEX facility will provide plasma conditions similar to the edge plasma of a major tokamak experiment but with pulse lengths and pulse repetition rates ideally suited for extensive development of a TALIF neutral density diagnostic. Measurement of the absolute neutral density in the edge of a magnetically confined plasma is necessary for plasma density control; calculation of charge-exchange power losses; control of plasma-wall interactions; determination of the braking of plasma flow; determination of the fuel mixture in deuterium-tritium plasma; and understanding the dynamics of the divertor region in the plasma edge. In terms of potential impact on the worldwide fusion program, we note that in burning plasma experiments, such as ITER, a 100 mJ/pulse Doppler-free TALIF diagnostic should be capable of directly measuring the deuterium/tritium (D/T) isotope ratio in the outer 0.5 to 1.0 m of the plasma radius. The D/T ratio is a critically important parameter for the control and optimization of burning plasmas. Therefore, development of the diagnostic system proposed here is also relevant to long-term US participation in diagnostic development for large tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Diagnostics for PSR Upgrade

This report discusses the diagnostics upgrade plan for the PSR. The PSR diagnostics under discussion include beam position and phase monitor (BPPM), wirescanners, wall current monitors, bunch shape monitors, laser notchers, and diamond array detectors. Existing diagnostics at the PSR include beam position monitors (BPM), a wirescanner, and a wall current monitor. All existing diagnostics need modernization, as part of the PSR upgrade plan. Meanwhile, we will introduce minor changes to improve the existing setups, which will enhance the performance and the longevity of the diagnostics equipment and components in the upgraded PSR operation. On the other hand, new, advanced, and available diagnostic technologies at a high technology readiness level (TRL) can also be considered for implementation for the PSR upgrade. In this note, we go through all types of diagnostics, introducing their basic principle, operating status, and plans for the PSR upgrade.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Optical diagnostics of laser-produced plasmas

Laser-produced plasmas (LPPs) engulf exotic and complex conditions ranging in temperature, density, pressure, magnetic and electric fields, charge states, charged particle kinetics, and gas-phase reactions, based on the irradiation conditions, target geometries, and the background cover gas. The application potential of the LPP is so diverse that it generates considerable interest for both basic and applied research areas. The fundamental research on LPPs can be traced back to the early 1960s, immediately after the invention of the laser. In the 1970s, the laser was identified as a tool to pursue inertial confinement fusion, and since then, several other technologies emerged out of LPPs. These applications prompted the development and adaptation of innovative diagnostic tools for understanding the fundamental nature and spatiotemporal properties of these complex systems. Although most of the traditional characterization techniques developed for other plasma sources can be used to characterize the LPPs, care must be taken to interpret the results because of their small size, transient nature, and inhomogeneities. The existence of the large spatiotemporal density and temperature gradients often necessitates non-uniform weighted averaging over distance and time. Among the various plasma characterization tools, optical-based diagnostic tools play a key role in the accurate measurements of LPP parameters. The optical toolbox contains optical spectroscopy (emission, absorption, and fluorescence), passive and active imaging and optical probing methods (shadowgraphy, Schlieren, interferometry, Thomson scattering, deflectometry, and velocimetry). Each technique is useful for measuring a specific property, and its use is limited to a certain time span during the LPP evolution because of the sensitivity issues related to the selected measuring tool. Therefore, multiple diagnostic tools are essential for a comprehensive insight into the entire plasma behavior. In recent times, the improvements in performance in the lasers and detector systems expanded the capability of the aforementioned passive and active diagnostics tools. Furthermore, this review provides an overview of optical diagnostic tools frequently employed for the characterization of the LPPs and emphasizes techniques, associated assumptions, and challenges. Considering most of the industrial and other applications of the LPP belong to low to moderate laser intensities (10 8 – 10 15 Wcm –2 ), this review focuses on diagnostic tools pertaining to this regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Optical diagnostic design for measuring the radiation front with a mid-leg pumped divertor on DIII-D

The design of an optical diagnostic system to localize the radiation front in a mid-leg pumped divertor configuration on DIII-D is presented. Divertor detachment is a key mechanism for handling power exhaust in tokamaks, and mid-leg pumping offers a promising approach to radiatively dissipate power while maintaining acceptable core performance. To predict the location of the radiation front and design a spectroscopic diagnostic to measure its position, a database of SOLPS-ITER simulations across a range of input powers and gas puffing rates representative of DIII-D operation was employed. These simulations provide self-consistent plasma backgrounds for a Cherab-Raysect synthetic diagnostic framework, which incorporates detailed tokamak geometry and physically accurate ray-tracing. Synthetic simulations of optical sightlines and viewing cone geometry were used to calculate line-integrated emission from the plasma, particularly of the C III 465 nm line, to serve as a proxy for the T e ≈ 7 − 10 eV temperature region associated with the onset and evolution of divertor detachment. Neutral deuterium emission is also evaluated for comparison. The synthetic diagnostic is used to assess the performance of existing DIII-D optical systems, including filterscopes and the Multichord Divertor Spectrometer, and to optimize line-of-sight placement within mechanical and installation constraints. The results provide quantitative guidance for diagnostic implementation on DIII-D and demonstrate the advantage of integrated synthetic diagnostics for divertor design studies and future advanced divertor concepts.

Cherab↗
DOE OSTI2026

Plasma confinement state classification in fusion power plants: Profile reflectometer and ensemble diagnostics

As Fusion Pilot Plants (FPPs) are increasingly viewed as within reach, many engineering challenges remain. Not many diagnostics are expected to be available in a reactor environment. Survivability, maintainability, and limited port space substantially restrict the number of FPP-relevant diagnostics. One remaining challenge is developing tools and devices to extract plasma state information necessary for controlling an FPP from a limited subset of diagnostics. This work is part of an overarching project to address this challenge. The specific diagnostic subset to be used in FPPs is still under debate. We take the approach of developing machine-learning-based tools for different significant plasma state parameters, using already known FPP-viable diagnostics. Previously we developed a plasma confinement mode classifier utilizing the Electron Cyclotron Emission (ECE) diagnostic. Here, we expand on this by developing a Profile Reflectometer (PR) based classifier with 97% test accuracy, and an ensemble model that combines the ECE and PR models into a single model, achieving 99% test accuracy.

Clark, Randall [Univ. of California, San Diego, CA↗
DOE OSTI2026

ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation

A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Infrastructure Team at Lawrence Livermore National Laboratory (LLNL) to facilitate the use of long-term, high-frequency measurements from the ARM Facility in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The Coupled Model Intercomparison Project (CMIP) model data sets are also included in the package to enable model intercomparison as demonstrated in Zhang et al. (2017). The mean of the CMIP model can serve as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, and radiative fluxes, with plan to extend to more fields, such as aerosol and microphysics properties. Process-oriented diagnostics focusing on individual cloud- and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. The version 1.0 package is designed based on data collected at ARM’s Southern Great Plains (SGP) Research Facility, with the plan to extend to other ARM sites. The metrics and diagnostics package is currently built upon standard Python libraries and additional Python packages developed by DOE (such as CDMS and CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first present the input data, which constitutes the core content of the metrics and diagnostics package in section 2, and a user's guide documenting the workflow/structure of the version 1.0 codes, and including step-by-step instruction for running the package in section 3.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Detectors and diagnostics for multiprobe radiography using high-energy short-pulse lasers

Multiprobe radiography requires the following diagnostic capabilities at minimum: radiographic source diagnostics, spectroscopy, imaging, and tomography diagnostics. Depending on the repetition rate of the radiation sources, the diagnostics may be a single-shot diagnostic, such as photographic (radiochromic and X-ray films for high energy photons) films, or a multiple-shot diagnostic for repetitive source operations, such as a high-speed framing camera. Due to the drastically different detector physics of electrons, photons at different energies (keV to 10s of MeV in the radiography context), heavy ions such as protons, alphas, and neutrons, see, for example, Ref. [1, 2] for an overview, different types or configurations of detectors and constructions may be required for multiprobe radiography applications. Some of the common detector metricsinclude, independent of the particle/photon species, sensitivities or efficiency, energy resolution, spatial or temporal resolutions and others. Some unique detection scenarios arise in a multiprobe radiography setting, for example, crosstalk mitigation and particle identification (ID) when X-ray and higher energy photons, relativistic electrons, neutrons, other hadrons, and heavy particles coexist at the detector location.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3

A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Machine-Learning-Based Rotating Detonation Engine Diagnostics: Evaluation for Application in Experimental Facilities

Real-time monitoring of combustion behavior is a crucial step toward actively controlled rotating detonation engine (RDE) operation in laboratory and industrial environments. Various machine learning methods have been developed to advance diagnostic efficiencies from conventional postprocessing efforts to real-time methods. Here this work evaluates and compares conventional techniques alongside convolutional neural network (CNN) architectures trained in previous studies, including image classification, object detection, and time series classification, according to metrics affecting diagnostic feasibility, external applicability, and performance. Real-time, capable diagnostics are deployed and evaluated using an altered experimental setup. Image-based CNNs are applied to externally provided images to approximate dataset restrictions. Image classification using high-speed chemiluminescence images and time series classification using high-speed flame ionization and pressure measurements achieve classification speeds enabling real-time diagnostic capabilities, averaging laboratory-deployed diagnostic feedback rates of 4–5 Hz. Object detection achieves the most refined resolution of 20 μs in postprocessing. Image and time series classification require the additional correlation of sensor data, extending their time-step resolutions to 80 ms. Comparisons show that no single diagnostic approach outperforms its competitors across all metrics. This finding justifies the need for a machine learning portfolio containing a host of networks to address specific needs throughout the RDE research community.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

A Comprehensive Chemistry Evaluation and Diagnostics Package for E3SM – ChemDyg Version 1.1.0

The Chemistry Evaluation and Diagnostics Package (ChemDyg) is an open-source tool designed for the Energy Exascale Earth System Model (E3SM) developed by the U.S. Department of Energy. ChemDyg facilitates routine evaluation, tailored development, and in-depth analysis of atmospheric chemistry through its modular architecture, allowing users to compare model outputs with observational data. Version 1.1.0 introduces a robust set of diagnostic capabilities, including climatology, time evolution of key tracers, diurnal and annual cycle analyses, and extensive budget diagnostics. These features help identify model discrepancies and enhance the representation of atmospheric chemistry in E3SM. Each self-contained diagnostic set includes dedicated scripts and documentation for ease of use. The interactive HTML output improves data accessibility, accelerating chemistry model development. Additionally, ChemDyg's flexible framework allows for customization, enabling users to create unique diagnostic sets for specific scientific contributions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗