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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Low energy neutron light output characterization of EJ301D and deuterated stilbene with a comparison of light output characterization methods

The neutron-induced light yield of a 2.54 cm diameter by 2.54 cm long right circular cylinder of EJ301D and a (5.08 cm)3 custom made cube of deuterated trans-stilbene-d12 (d-stilbene) were measured over incident neutron energies from 300 keV to 2.2 MeV and 200 keV to 2.4 MeV, respectively. The measurements were performed using a time-of-flight experiment with a Cf-252 source and an approximately 1.5 m flight path. We compare three light output spectrum full energy deposition edge estimation methods: (1) simulating the neutron energy spectrum edge and fitting it to the light output spectrum, (2) using the inflection point of the light output spectrum edge (derivative method, a.k.a. Kornilov’s method), and (3) using an empirical model fit to the edge of the light output spectrum. Both the derivative and equation fit methods do not account for physical processes such as multiple neutron scattering in the detectors. They instead rely on assumptions about the linear shape continuum shape of the light output spectrum and the direct correlation between the location of the spectrum’s inflection point and maximum energy deposition. These assumptions were found to introduce bias into those methods when tested against simulated spectra with known edge locations. When tested against measured spectra the derivative method was found to differ from the simulation fit by greater than 30% at low energies with large discontinuities for adjacent data points above 800 keV incident neutron energy. The empirical equation fitting method was found to also exhibit bias of a similar magnitude, but with significantly more continuous behavior, especially with the lower count data of the smaller volumed EJ301D scintillator. Experimental light output yield for this neutron energy range is reported using the simulated spectrum fitting method because it includes physics neglected by the other methods, and did not exhibit the bias observed in the other methods

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Impact of light output on the timing resolution of organic glass scintillator bars in a dual-ended readout configuration

The effectiveness of detector system modeling and validation depends on the quality of characterization performed on the system. For nuclear nonproliferation applications, which require detectors to address complex and variable field conditions, access to accurate system models is essential. This study presents the timing characterization of organic glass scintillator bars used in an imaging system developed at the University of Michigan. 137 Cs and 60 Co gamma-ray sources were used to determine the coincidence time resolution as a function of measured light output for two Compton scatter events between two organic glass scintillator bars. Timing resolution for two events, each with light output ranging from 100 to 1100 keVee were characterized. The resulting data were fit to a parametric function that was validated to agree with experimental results within ±25 ps. Simulations were performed to establish appropriate calibration points for each organic scintillator, thereby ensuring accurate calibration of light output values during analysis. This work successfully characterized the light output dependence of the coincidence timing resolution of a pair of organic glass detectors for use in an imaging system. Depending on the amount of scintillation light output from the events, the full width at half maximum of the measured coincidence time resolution ranged from 653.2 ± 16.1 ps for low light yields, 100 keVee, to 121.0 ± 8.4 ps for higher yields at 1100 keVee. The insights obtained from the timing resolution behavior will allow for accurate simulation capabilities in future security and verification efforts using scatter-based imaging systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Nonlinear light-output calibration of the oxygenated xylene scintillators used in OMEGA neutron time-of-flight spectrometers

Neutron time-of-flight (nTOF) spectrometers are essential instruments for measuring and evaluating the performance of inertial confinement fusion implosions. The neutron spectrometers utilized for the OMEGA laser include two liquid-based scintillators, each consisting of a large volume filled with xylene that is coupled to four photomultiplier tubes. Analysis of the signal from these detectors requires detailed knowledge of the scintillator’s light output, which is needed to fit the nTOF spectrum, from which the neutron energy spectrum is informed. The light output is nonlinearly proportional to the neutron energy, which, in turn, affects the interpretation of the neutron energy spectrum from a TOF signal. A recent campaign on OMEGA was performed to calibrate the xylene detectors and infer the shape of the light-output curve. The campaign utilized materials with increasing Z placed in the OMEGA target chamber to initiate scattering events with the 14 MeV fusion neutrons. This process leads to the production of backscatter neutrons of varying energies that appear as peaks in the nTOF data. Simulations using a neutron transport code were combined with the measured deuterium–tritium neutron yields to calculate the expected backscattered neutron yields from the well-known scattering cross sections of each material. Furthermore, the neutron-energy dependent light output of the scintillator inferred from the experiment is compared to the light-output curve simulated with a neutron transport code for the following neutron energies: 1.5, 2.5, 6, and 14 MeV.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Adaptive Reinforcement Learning Control for Power Distribution in Multi-Output Resonant Converters

This paper presents an adaptive reinforcement learning (ARL)-based control framework for efficient power distribution in a multi-output resonant converter for UAV applications. The proposed system is based on a high-frequency isolated resonant architecture, where a single energy source supplies multiple propulsion loads through independently controlled output rectifiers, addressing the need for coordinated multi-motor power management. The ARL framework dynamically allocates output power by learning optimal phase-shift control actions under varying load demands and operating conditions. The agent autonomously determines control parameters that maximize conversion efficiency while ensuring accurate power sharing among multiple outputs. In addition, the proposed approach enables adaptive operation without requiring detailed system modeling or manual tuning. Experimental results demonstrate stable and efficient performance over a wide range of operating conditions, confirming the effectiveness and robustness of the learning-based control strategy for multi-output resonant converter system.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
DOE OSTI2025

Time-Varying Output Delay Compensation-A Model-Free Approach and its Application on Cooperative On-Ramp Merging

This paper presents a model-free approach to compensate for time-varying output delay in networked control systems. The proposed architecture combines a model-free observer and the Smith predictor. The model-free observer estimates the current state while handling modeling errors and uncertainties of the system. The Smith predictor moves the effect of time delay outside the control closed-loop using the estimated delayed output and the actual output of the plant. The proposed method is applied to a cooperative on-ramp merging problem. First, an ultra-local model predictive control is implemented to provide a computationally efficient online speed planner agnostic to the vehicle dynamics. After that, a model-free observer is designed to estimate the current state. Finally, the proposed architecture is tested against a time-varying output delay with an upper bound of 200 milliseconds. The results demonstrate the effectiveness of the proposed method with improved tracking of intervehicle distance.

Waleed khan, Muhammad [The University of Texas at ↗
DOE OSTI2024

Light Output Fitting Software

Light output response of scintillators is crucial to the utilization of organic scintillators as effective tools in radiation detection and measurement. While the response is a continuous distribution, the light output corresponding to the maximum energy deposition is crucial in effectively understanding and simulating a detector. There are a variety of fits derived in literature that will vary for every detector material. The Light Output Response Fitter, or LORF Program is a python script designed to easily and quickly compute and plot fits for a variety of scintillator light output models. It includes a stopping power library constructed from SRIM including Organic Glass, EJ309, EJ301, Stilbene, EJ276, and their deuterated counterparts by default, with the ability for the user to add custom stopping power libraries. The user is also capable of importing the python package and utilizing its in-built functions as appropriate. Uses for this capability include plotting and computing a model with known parameters.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

The Scaling and Units of the Elastic Response Term for Rayleigh Waves that is Output by Computer Programs in Seismology (CPS)

We report on the scaling and units of the Rayleigh wave elastic response function A R (ω) that is output from the widely used Computer Programs in Seismology (CPS) to aid in the modeling of ground motion sourced by atmospheric explosions. The program uses mixed units (km, second, km/s, gm/cc) to keep A R (ω) near 10 0 and prevent any numerical underflow or overflow. We compare two models for the response of an elastic half space to the output from CPS. Our application inputs the recommended, mixed unit geological models to determine how researchers must scale this output to obtain physical units for A R (ω) that represents the amplitude scaling for the minimum group velocity (Airy phase) contribution to Rayleigh waves. We determine that a CPS user must scale the output for A R (ω) by 10 -12 (m/km) 2 (g/cc/m 3 /kg) to obtain MKS (meter, kg, second) units and then must multiply this result by the vertical component eigenfunction squared, that is evaluated at the free surface.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Skipper-CCD Output Sensitivity Improvement with a Common Source Cascode Amplifier

A Skipper-CCD output has been traditionally readout in a source follower configuration, also known as common drain, mainly because in this configuration a good compromise between sensitivity, noise and speed is achieved. In this work a different approach is presented: the output transistor is connected in a common source configuration and an external cascode device is added in series, obtaining a voltage gain higher than unity without increasing significantly the parasitic capacitance due to Miller effect and thus increasing the obtained voltage per electron of charge. The proposed output stage improves the sensitivity 3.4 times when compared with the traditionally used stage while keeping almost the same equivalent noise charge.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Output Current Estimation and Control in Primary Side LCC Secondary Side Series Compensated Wireless Power Transfer System without Secondary Side Sensors

The estimation (and control) of the output variables is often challenging for wireless power transfer (WPT) systems. This paper presents a secondary side sensor-less closed loop estimation technique to estimate the output current in a primary side LCC and secondary side series compensated WPT system. Using information of primary side variables, the proposed estimation can estimate the output current over a wide range of load current variations. Results are presented to verify the efficacy of the proposed estimation.

Mukherjee, Subho [ORNL] (ORCID:0009000672297925)↗
DOE OSTI2025

Hot Droughts and Forest Tree Dynamics in the Amazon - Statistical Models, Scripts, Data, and Outputs

This package contains data, outputs, equations, and R scripts for analyses for manuscript entitled "Hot droughts in the Amazon: A window to a future hypertropical climate" by J. Chambers et al., in particular it contains statistical models and analyses for the INPA BIONTE tree mortality study. The Models folder contains details for all statistical models in PDF files. The Scripts folder contains the R scripts for Bayesian Hierarchical Models (two text files) and SEMs (one text file) are separate and reasonably annotated. All data associated with these scripts are in the data folder. The Data folder contains two of the three CSV files used for the analyses and are called by the R scripts. Two of them are part of published datasets (`BIONTE_mortality-rates.csv` from Lima et al. 2024, DOI:10.15486/ngt/1898910 and `SPEI.csv` from Pastorello et al. 2023 DOI:10.15486/ngt/1958257) and also provided in this package for convenience (please see the corresponding datasets for usage and citation terms). The third dataset (`BIONTE_gapfilled_wd.csv`) contains sensitive information and can be obtained by contacting the manuscript lead author. The Outputs folder contains the two output files that provide extra information about the analyses. The file `figuresFeb2025d.pdf` contains all the figures from the manuscript - captions are in the manuscript. The file `ChambersMS.pdf` contains primary results from Bayesian statistical models, regression analyses, and validation steps applied to the tree mortality data from the INPA experiments. The document includes visual summaries, model diagnostics, and leave-one-out (LOO) validation results. A breakdown of file contents can be found in the README file that is part of this package.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Manuscript model outputs, model source code, and figure scripts: The role of geomorphology in mediating biomass allocation impacts on salt-marsh resilience and carbon accumulation

This data package provides model source code (C++), model outputs, and figure generation scripts (R) needed to reproduce the following manuscript: Bruns, Nicholas E., Genevieve L. Noyce, and Matthew L. Kirwan. "The Role of Geomorphology in Mediating Biomass Allocation Impacts on Salt-Marsh Resilience and Carbon Accumulation." Estuarine, Coastal and Shelf Science 327 (December 2025): 109549. https://doi.org/10.1016/j.ecss.2025.109549. This manuscript investigates how geomorphology mediates the impact of biomass allocation shifts on salt marsh persistence and carbon (C) sequestration under sea level rise. We use a 1-D soil-column model (Kirwan and Mudd 2012) to perform experiments across a range of static root:shoot ratios (RSR = 1-4) spanning observed values. The model explicitly simulates interactions between tidal inundation, productivity, inorganic sediment deposition, and organic matter accumulation. Experiments determine whether geomorphic feedbacks amplify, dampen, or leave unchanged the ecosystem response to biomass allocation shifts. A first experiment uses constant sea level rise (2.5 mm/yr) to examine equilibrium dynamics and their influence on carbon accumulation rates across different suspended sediment concentrations (SSC). A second set of experiments calculates threshold sea level rise rates for marsh drowning across RSR and SSC combinations. Final experiments apply accelerating sea level rise scenarios (2000-2200) derived from NOAA projections (Sweet et al. 2022) to generate an envelope of expected responses, quantifying the importance of biomass allocation shifts on marsh carbon accumulation and persistence. All experiments are repeated across SSC ranging from 5-50 mg/L to investigate how these interactions vary in micro-tidal marshes with different sediment supplies. Package contents: * README.txt with detailed description of package contents and instructions for reproducing manuscript figures and model outputs * R scripts for generating all manuscript figures * C++ baseline model code from Kirwan and Mudd (2012) * C++ source code for 4 experimental model variants used in the manuscript, extending above baseline code * Model input files (.csv, .txt) including sea level rise scenarios * Model output files (.txt) used in manuscript analyses Temporal coverage: Model simulations span years 1900-2200, with accelerating sea level rise scenarios for 2000-2200. Key variables: Root:shoot ratio, suspended sediment concentration, carbon accumulation rate, vertical accretion rate, marsh elevation, inundation depth, threshold sea level rise rate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Machine learning model inputs, outputs, and scripts associated with “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions” (Malhotra et al., in prep). This effort was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the contiguous United States (CONUS). New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Associated sediment and water geochemistry and in situ sensor data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689, https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719, and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1603775. This data package is associated with two GitHub repositories found at https://github.com/parallelworks/dynamic-learning-rivers and https://github.com/WHONDRS-Hub/ICON-ModEx_Open_Manuscript. In addition to this readme, this data package also includes two file-level metadata (FLMD) files that describes each file and two data dictionaries (DD) that describe all column/row headers and variable definitions. This data package consists of two main folders (1) dynamic-learning-rivers and (2) ICON-ModEx_Open_Manuscript which contain snapshots of the associated GitHub repositories. The input data, output data, and machine learning models used to guide sampling locations are within dynamic-learning-rivers. The folder is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning (ML) models trained on the data in “input_data”; (3) “examples” contains files for direct experimentation with the machine learning model, including scripts for setting up “hindcast” run; (4) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; and (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please see the top-level README.md in the GitHub repository for more details on the automation. The scripts and data used to create figures in the manuscript are within ICON-ModEx_Open_Manuscript. The folder is organized into four folders which contain the scripts, data, and pdf for each figure. Within the “fig-model-score-evolution” folder, there is a folder called “intermediate_branch_data” which contains some intermediate files pulled from dynamic-learning-rivers and reorganized to easily integrate into the workflows. NOTE: THIS FOLDER INCLUDES THE FILES AT THE POINT OF PAPER SUBMISSION. IT WILL BE UPDATED ONCE THE PAPER IS ACCEPTED WITH ANY REVISIONS AND WILL INCLUDE A DD/FLMD AT THAT POINT. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Processing MCNP Elemental Edit Outputs

The Monte Carlo N-Particle (MCNP) transport code version 6 (also known as MCNP6) has the capability for tracking particles on unstructured mesh (UM) geometry models embedded into constructive solid geometry (CSG) cells. A UM geometry is a collection of elements representing a solid geometry. The first step of MCNP UM modeling is using other software packages to create a finite element mesh representation of a solid 3D geometry. Computer-aided design (CAD) or computer-aided manufacturing (CAM) software is typically used to create a solid geometry model, which is later imported into mesh generation software to create a UM model. The MCNP UM feature was originally designed for models generated by the Abaqus/CAE software. The MCNP code version 6.0 and later can process UM models formatted as Abaqus input files. MCNP can process a UM model consisting of several different element types including linear tetrahedral or hexahedral elements and calculate quantities of interest such as flux and energy deposition at elements. An MCNP UM simulation provides high-fidelity elemental edit (i.e., tally) outputs, which can be further used in multiphysics calculations. The MCNP UM feature was used for multiphysics simulations where quantities of interest calculated by MCNP are used as inputs for heat transfer calculations in Abaqus. MCNP6.3 can produce two types of elemental edit output (EEOUT) file formats: ASCII and HDF5. An EEOUT file type must be requested on an EMBED card while output type (flux or energy deposition) must be requested on an EMBEE card. We wrote Python3 scripts to extract energy deposition values in an ASCII or HDF5 EEOUT file and compute a heat flux profile for an Abaqus heat transfer calculation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

LINAC Longitudinal Simulation and Measurement of Output Energy

The Linac at Fermilab, one of the oldest accelerators on-site, plays a crucial role in delivering 400 MeV proton beams to other accelerating facilities. The beam traveling through Linac needs to be carefully monitored for better accelerator operation. One of the key factors of efficient Linac operation is its longitudinal stability. The stability can minimize Linac loss and maximize beam current. For this purpose, I examined the beam's longitudinal profile, which is crucial for proper beam transfer between its two sections. After careful monitoring of the beam through Linac, we need to ensure that it leaves with desired parameters. The beam coming out from the Linac is subsequently injected into the Booster, a synchrotron that relies on dipole magnets to bend the beam at injection. If the output energy of the beam deviates from the expected value, the beam will bend at an incorrect radius, leading to potential beam loss. Therefore, precise regulation of the output energy is critical for the efficient operation of the accelerator. To address this, I have conducted a thorough examination of the Linac longitudinal simulations and data from Beam Position Monitors (BPMs). My objective is to measure and stabilize the output energy and verify its correspondence with the predicted simulation results. All these analyses are important for efficient operation of the accelerator.

Safaryan, Milena↗
DOE OSTI2024

Output Capacitance Loss of GaN HEMTs in Steady-State Switching

The output capacitance (C OSS ) loss, a loss produced when the device’s output capacitor is charged and discharged, has become a concern for GaN high electron mobility transistors (HEMTs) in high-frequency applications. This work presents a new, easy-to-implement method for the C OSS loss characterization based on the unclamped inductive switching (UIS) setup. As compared to prior approaches, this method involves the device’s ON-state conduction and could measure the C OSS loss in a single pulse and the steady-state switching. The C OSS loss of three types of mainstream commercial GaN HEMTs is characterized, which exhibit some common dependencies including a non-monotonic relation with the dv/dt (or resonance frequency), a linear relation with the ON-state current, a power-law relation with the peak blocking voltage, and little temperature dependence. In addition, their C OSS losses all show minimal distinctions in a single pulse and the steady-state switching, despite the increased on-resistance in the steady-state switching. Furthermore, this suggests that the traps accounting for the C OSS loss possess different de-trapping time constants as compared to the traps governing the dynamic on-resistance. Finally, a unified model is established to describe the C OSS loss of all three types of GaN HEMTs. These results provide important references for the high-frequency application of GaN HEMTs and new insights into the physical origin of their C OSS loss.1

42 ENGINEERING↗
DOE OSTI2025

Upstreamness and downstreamness in input–output analysis from local and aggregate information

Abstract Ranking sectors and countries within global value chains is of paramount importance to estimate risks and forecast growth in large economies. However, this task is often non-trivial due to the lack of complete and accurate information on the flows of money and goods between sectors and countries, which are encoded in input–output (I–O) tables. In this work, we show that an accurate estimation of the role played by sectors and countries in supply chain networks can be achieved without full knowledge of the I–O tables, but only relying on local and aggregate information, e.g., the total intermediate demand per sector. Our method, based on a rank-1 approximation to the I–O table, shows consistently good performance in reconstructing rankings (i.e., upstreamness and downstreamness measures for countries and sectors) when tested on empirical data from the world input–output database. Moreover, we connect the accuracy of our approximate framework with the spectral properties of the I–O tables, which ordinarily exhibit relatively large spectral gaps. Our approach provides a fast and analytically tractable framework to rank constituents of a complex economy without the need of matrix inversions and the knowledge of finer intersectorial details.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Characterization of the First Prototype of the L1K65n Differential-Output Charge-Sensitive Preamplifier ASIC for High-Performance, Low-Background HPGe Detector Readout

Next-generation neutrinoless double-beta (0νββ) decay searches require a large detector/isotope mass and very low radioactive backgrounds. The upcoming LEGEND-1000 experiment (Large Enriched Germanium Experiment for Neutrinoless double-beta Decay) constitute a ton-scale array of several hundred high-purity germanium (HPGe) detectors enriched in 76Ge, the isotope of interest. It aims to reach a sensitivity beyond 10 28 years on the 0νββ decay half-life of 76Ge, necessitating an order of magnitude reduction in background with respect to the state of the art. This will require the implementation of a dedicated application specific integrated circuit (ASIC) preamplifier that will significantly lower background contribution compared to the conventional low-mass front end (LMFE) employed in the Majorana Demonstrator and LEGEND-200 experiments while maintaining or improving energy resolution and other performance parameters. Features include a high (9 MeV) dynamic range with noise low enough to achieve a trigger threshold of <1 keV, a single power supply to reduce background-inducing cabling, and a differential output to maintain signal integrity over several meters of transmission line. The chip would be optimized to operate in liquid argon (87 K) and be able to do so reliably for ten years. Following on from an earlier 180-nm prototype, we have developed a differential-output charge-sensitive preamplifier ASIC fabricated in a 65-nm process, 1×2 mm in size, that addresses these needs. Here, we present recent results from the successful testing and characterization of the first version of this device.

ASIC↗
DOE OSTI2025

Calibration of RAFM Micromechanical Model for Creep Using Bayesian Optimization for Functional Output

A Bayesian optimization procedure is presented for calibrating a multimechanism micromechanical model for creep to experimental data of F82H steel. Reduced activation ferritic martensitic (RAFM) steels based on Fe(8–9)%Cr are the most promising candidates for some fusion reactor structures. Although there are indications that RAFM steel could be viable for fusion applications at temperatures up to 600°C, the maximum operating temperature will be determined by the creep properties of the structural material and the breeder material compatibility with the structural material. Due to the relative paucity of available creep data on F82H steel compared to other alloys such as Grade 91 steel, micromechanical models are sought for simulating creep based on relevant deformation mechanisms. As a point of departure, this work recalibrates a model form that was previously proposed for Grade 91 steel to match creep curves for F82H steel. Due to the large number of parameters (9) and cost of the nonlinear simulations, an automated approach for tuning the parameters is pursued using a recently developed Bayesian optimization for functional output (BOFO) framework (Huang et al., 2021, “Bayesian optimization of functional output in inverse problems,” Optim. Eng., 22, pp. 2553–2574). Incorporating extensions such as batch sequencing and weighted experimental load cases into BOFO, a reasonably small error between experimental and simulated creep curves at two load levels is achieved in a reasonable number of iterations. In conclusion, validation with an additional creep curve provides confidence in the fitted parameters obtained from the automated calibration procedure to describe the creep behavior of F82H steel.

42 ENGINEERING↗