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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Machining-inducted residual strain and ductile-brittle transition in sapphire revealed by X-ray nanoprobe diffraction microscopy

Hard X-ray nanoprobe diffraction microscopy is employed to investigate machining-induced residual lattice strain in single-crystal sapphire following ultra-precision orthogonal plunge cutting. In this study, tilt-series and single-angle acquisition strategies are systematically compared to evaluate their capability for resolving lattice variations associated with the machining process. An analytical framework is developed to enable the efficient and reliable extraction of strains, which serve as strain-based indicators of changes in the dominant deformation mechanism. The measured high-dimensional strain exhibits spatial heterogeneity and systematic evolution along the cutting path, consistent with deformation-regime changes from ductile response to crack-prone behavior.

Liang, Rui↗
DOE OSTI2023

Integrating equity in transportation scenario planning: A systematic review

To address the growing uncertainties in the future transportation industry, planners and engineers have identified and implemented scenario planning, a multi-step and strategic approach, in long-range transportation planning. A comprehensive examination of how equity is envisioned, planned, and analyzed during this process remains absent, despite several key guidelines of scenario planning exercises. This paper conducts a systematic literature review focusing on how equity has been considered and evaluated in scenario planning. The resources include academic papers, agency reports, and materials from the recent scenario planning conference, the 2nd Conference on Scenario Planning in Transportation hosted by the Transportation Research Board. This paper examines equity in scenario planning in three important ways: 1) the ways equity has been integrated across steps; 2) how equity analysis has evolved; and 3) when it is necessary to consider equity. This work adds value to the existing body of knowledge by presenting the policy implications based on the review of the current scenario planning research and practices. Early policy recommendations include the need for more vertical equity evaluations, the construction of robustness and justice indicators, and the adoption of a flexible mindset of planning for rather than being fixated on a single scenario.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Λ Baryon Production in ν¯µ Interactions in the MicroBooNE Detector

The Cabibbo suppressed production of $\Lambda$ baryons in anti-neutrino interactions with nuclei is a rare process that is yet to be measured with a modern neutrino detector with automated reconstruction. The cross section for this process is sensitive to a number of unique nuclear effects, most notably the secondary interactions of the produced hyperon while attempting to escape from the nucleus. Other interactions within the nuclear remnant can impact the estimation of neutrino energy in oscillation measurements, and thus an accurate description of the nuclear environment is required. The strangeness violating hyperon production process is only available to anti-neutrinos. The model of this interaction is implemented into the NuWro neutrino interaction Monte Carlo simulation, and some predictions are presented, focusing on the role of nuclear effects. This model introduces a hyperon-nucleus potential, which calculations from hypernuclear theory permit to be strongly repulsive in th e case of $\Sigma$ baryons. The presence of this potential is found to sculpt the shape of the differential cross section in some variables. The MicroBooNE detector will be described, followed by a description of a measurement of the flux averaged, restricted phase space cross section of Cabibbo suppressed $\Lambda$ baryon production. A sophisticated event selection is employed, as a very large quantity of background neutrino interactions must be removed to perform the measurement with any sensitivity. This selection introduces some novel techniques such as the island finding method, and achieves a background reduction of $\sim 10^6$, with an efficiency of around 7\%. The calculation of the systematic uncertainties will be explained, including two procedures explored to handle sources of background with extremely poor simulation statistics: an in-situ constraint using data from sidebands, and a visual inspection of the data and simulation to remove the troublesome background events. The sensitivity to the $\Lambda$ baryon production cross section is calculated in the form of Bayesian posterior probability distributions, combining the systematic uncertainties with data and simulation statistical uncertainties. As a rare process, the statistical uncertainties are highly non-Gaussian, and the Bayesian approach is applied to include the full shapes of these uncertainties. Data corresponding to $2.2 \times 10^{20}$ protons on target of neutrino mode running and $4.9 \times 10^{20}$ protons on target of anti-neutrino running is analysed. When the data was unblinded, five $\Lambda$ production candidates were selected from the data, consistent with the MC simulation prediction of $5.3 \pm 1.1$ events. The final estimated cross section is $1.8^{+2.0}_{-1.6} \times 10^{-40}$cm$^2/$Ar when employing the sideband constraint procedure. A similar result of $2.0^{+2.2}_{-1.8} \times 10^{-40}$cm$^2/$Ar is obtained when performing the visual scan instead. The methods used in t his analysis are intended to be easily exported to other LArTPC detectors such as the Short Baseline Near Detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Covariate Dependent Sparse Functional Data Analysis

This study proposes a method to incorporate covariate information into sparse functional data analysis. The method aims at cases where each subject has a limited number of longitudinal measurements and is associated with static covariates. This research is motivated by several use cases in practice. One representative example is void swelling, a nuclear-specific material degradation mechanism. Void swelling is affected by many covariates, including alloy composition and irradiation type. How to accurately model the complicated joint effects of such covariates on the swelling process is the key to mitigating the effect of swelling and ensuring safe operation. Unlike most of the existing methods, the proposed method can handle high-dimensional covariates with the informative covariate identification procedure and sparse and irregularly spaced measurements, that is, does not require complete or dense observations. The main innovation of the proposed method is that we model the variation coming from covariates and the variation left conditioned on covariates, such that the functional principal component analysis and Gaussian process can be conducted in a unified manner. Further, we also propose a systematic approach to identify important covariates in the hypothesis testing context. The methodology is demonstrated on applications in nuclear engineering and healthcare and simulation studies.

42 ENGINEERING↗
DOE OSTI2025

Partial wave analysis of 𝑒 + ⁢𝑒 − → 𝜋 + ⁢𝜋 − ⁢𝐽/𝜓 and cross section measurement of 𝑒 + ⁢𝑒 − → 𝜋 ± ⁢𝑍 𝑐 ⁢(3900) ∓ from 4.1271 to 4.3583 GeV

Based on 12.0 fb −1 of 𝑒 + ⁢𝑒 − collision data samples collected by the BESIII detector at center-of-mass energies from 4.1271 to 4.3583 GeV, a partial wave analysis is performed for the process 𝑒 + ⁢𝑒 − → 𝜋 + ⁢𝜋 − ⁢𝐽/𝜓. The cross sections for the subprocesses 𝑒 + ⁢𝑒 − → 𝜋 + ⁢𝑍 𝑐 ⁢(3900) − + c.c. → 𝜋 + ⁢𝜋 − ⁢𝐽/𝜓, 𝑓 0 ⁡(980)⁢(→ 𝜋 + ⁢𝜋 − )⁢𝐽/𝜓, and (𝜋 + ⁢𝜋 − ) S−wave⁢ 𝐽/𝜓 are measured for the first time. The mass and width of the 𝑍 𝑐 ⁢(3900) ± are determined to be 3884.6 ± 0.7 ± 3.3 MeV/𝑐 2 and 37.2 ± 1.3 ± 6.6 MeV, respectively. The first errors are statistical and the second systematic. The final state (𝜋 + ⁢𝜋 − ) S−wave ⁢𝐽/𝜓 dominates the process 𝑒 + ⁢𝑒 − → 𝜋 + ⁢𝜋 − ⁢𝐽/𝜓. By analyzing the cross sections of 𝜋 ±⁢ 𝑍 𝑐 ⁢(3900) ∓ and 𝑓 0 ⁡(980)⁢𝐽/𝜓, 𝑌⁡(4220) has been observed. Its mass and width are determined to be 4225.7 ± 4.1 ± 3.4 MeV/𝑐 2 and 57.5 ± 9.4 ± 12.1 MeV, respectively.

lepton colliders↗
DOE OSTI2022

Cadmium isotope systematics in sedimentary carbonate: Extending the utility of the cadmium isotope palaeo-productivity proxy

The cadmium (Cd) isotope compositions of seven Holocene (<11.7 ka) carbonate sediments, including the bulk carbonate, as well as the > 140 μm (zooplankton), <63 μm and < 20 μm (phytoplankton) fractions, and individual species of foraminifera isolated from the bulk carbonate were obtained for sub-samples processed using the Cd-cleaning and Mg/Ca cleaning methods. The respective Cd isotope systematics of each carbonate archive were then compared with the Cd isotope signature within the ocean using modern seawater data. We show that a constant Cd isotope fractionation factor of -0.25 ± 0.03 ‰ (2SE, n = 4) describes the partitioning of Cd from seawater into the carbonate phase ($Δ^{114}Cd_{CdC O_3 - seawater}$), allowing for accurate reconstructions of the past seawater nutrient regime. The Cd isotope signature of the < 63 µm and < 20 µm (phytoplankton) fractions can display comparable values to those recorded in the modern surface ocean, and can be used to model the magnitude of Cd uptake and utilisation in the past ocean. Individual species of planktic and benthic foraminifera, which inhabit different depths of the water column, can provide a full surface to deep water column reconstruction of the Cd nutrient regime, while infaunal benthic foraminifera can be used to interrogate the Cd isotope systematics of sediment porewaters. Bulk sediment and the > 140 µm (zooplankton) fraction also retain important information relating to the overlying water column Cd isotope systematics and can serve as essential archives for palaeo-productivity reconstructions where the separation of individual components from the bulk sediment is not possible. This new Cd isotope palaeo-productivity toolkit can considerably aid reconstruction efforts and vastly improves the ability to quantify the role of phytoplankton in modulating carbon sequestration through transitions in Earth’s climate evolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Call attention to using DRT and EIS to quantify the contributions of solid oxide cell components to the total impedance

The contributions of anode and cathode processes to solid oxide fuel cell (SOFC) impedance were studied using electrochemical impedance spectroscopy (EIS) and distribution of relaxation time (DRT). Specifically, the role of gas composition at both anode and cathode was explored in a systematic study aimed at deconvoluting, identifying and quantifying the contributions of different anode and cathode processes. Further, five distinct relaxation time distributions were observed in the DRT spectra; although the peaks were ascribed to diffusion and charge transfer processes at the electrodes, it was found that both electrodes contributed to various peaks at the same time. Moreover, it was found that two distinctive operating conditions could return equivalent DRT spectra. While DRT analysis allows to obtain useful information regarding cell performance, extra consideration is needed when assessing and quantifying anodic and cathodic resistances within the SOFC.

08 HYDROGEN↗
DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Mapping Philadelphia's Floodscape: A 35‐Year Analysis of Coastal Urban Flood Hazards and Drivers

Low-lying coastal urban cities face significant flooding risks from river flooding (fluvial), storm surges and high tides (coastal), and intense local rainfall (pluvial). Accurately assessing these hazards requires modeling frameworks capable of capturing both the individual and combined effects of multiple flood drivers, as well as the diversity of flood scenarios that can arise from their interactions. In this study, we implemented a physics-based, high-resolution modeling approach to assess flood hazards in Philadelphia, PA, a coastal city exemplifying multi-driver flood risks over multiple decades (1985–2019), by simulating a wide range of flood events at a 10-m resolution. By integrating watershed, coastal, and urban flood models, we explicitly resolved the interaction between fluvial, pluvial, and coastal processes across the city. From these simulations, we identified flood hazard hotspots and systematically attributed the primary drivers of flooding for each event. The results suggested that 44% of Philadelphia's flood events were compound floods, primarily driven by fluvial-surge and fluvial-pluvial combinations. Notably, 77% of these events involved fluvial flooding, either as a single flood driver or in combination with other drivers, underscoring the dominant role of riverine processes in the city's flood hazard. Overall, this study demonstrates the value of a comprehensive, process-based approach for urban flood hazard assessment and highlights the importance of considering the full spectrum of flood scenarios to inform targeted and adaptive flood management strategies in coastal cities.

Compound flooding↗
DOE OSTI2024

A Tale of Two Catchments: Causality Analysis and Isotope Systematics Reveal Mountainous Watershed Traits That Regulate the Retention and Release of Nitrogen

Abstract Mountainous watersheds are characterized by variability in functional traits, including vegetation, topography, geology, and geomorphology, which determine nitrogen (N) retention, and release. Coal Creek and East River are two contrasting catchments within the Upper Colorado River Basin that differ markedly in total nitrate (NO 3 − ) export. The East River has a diverse vegetation cover, and sinuous floodplains, and is underlain by N‐rich marine shale. At 0.21 ± 0.14 kg ha −1 yr −1 , the East River exports ∼3.5 times more NO 3 − relative to the conifer‐dominated Coal Creek (0.06 ± 0.02 kg ha −1 yr −1 ). While this can partly be explained by the larger size of the East River, the distinct watershed traits of these two catchments imply different mechanisms controlling the aggregate N‐export signal. A causality analysis shows physical and biogenic processes were critical in determining NO 3 − export from the East River catchment. Stable isotope ratios of NO 3 − (δ 15 N NO3 and δ 18 O NO3 ) show the East River catchment is a strong hotspot for biogeochemical processing of NO 3 − at the hillslope soil‐saprolite. By contrast, the conifer‐dominated Coal Creek retained nearly all atmospherically deposited NO 3 − , and its export was controlled by catchment hydrological traits (i.e., snowmelt periods and water table depth). The conservative N‐cycle within Coal Creek is likely due to the abundance of conifer trees, and smaller riparian regions, retaining more NO 3 − overall and reduced processing prior to export. This study highlights the value of integrating isotope systematics to link watershed functional traits to mechanisms of watershed element retention and release.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Simulating Energy and Security Interactions in Semiconductor Manufacturing: Insights from the Intel Minifab Model

Semiconductor manufacturing is a highly complex. Fabrication plants must deal with re-entrant flows to support multiple types of wafers being produced simultaneously, each with their own deadlines and specifications. The manufacturing process itself depends upon the ability to control and programmatically adjust a variety of environmental conditions including temperature, humidity, and air quality. In addition, wafer fabrication consumes large amounts of electricity. Emerging technologies may help reduce the energy footprint of such facilities but can introduce cybersecurity risks. Therefore, this paper presents a modeling and simulation framework to quantify tradeoffs between operational measures of performance, energy consumption, and cybersecurity controls. We augment the Intel Minifab model, with the Purdue Enterprise Reference Architecture (PERA) for cybersecurity as well as tool-level energy consumption data from a real-world semiconductor manufacturing testbed. In this manner, we intend to provide stakeholders with a systematic, data-driven approach to evaluate emerging risks within the manufacturing process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Computational predictions of porosities, pore size distributions, and conductivities of aerosol deposited particulate films

The structure and resulting physical properties of aerosol deposited particulate films are governed by the size distribution and morphology of the depositing particles as well as the physics governing particle deposition. While particulate film deposition processes are qualitatively understood, the link between particle characteristics and deposition physics to film properties has not been probed systematically. Here we apply a combination of Langevin dynamics deposition simulations, Monte Carlo pore size distribution calculations, and predictions of thermal conductivities to better establish such process parameter-film property relationships. Furthermore, we account for partial coalescence, polydispersity, and aggregate deposition. We establish that the deposition of polydisperse and aggregated particles leads to broadening of the pore size distribution function and an increase in the mode pore size. Via a non-continuum gas conductivity model, we show that aerosol deposited films can achieve porosities and thermal conductivities similar to conventional aerogels.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Optimal 1D Ly α forest power spectrum estimation – III. DESI early data

ABSTRACT The 1D power spectrum P1D of the Ly α forest provides important information about cosmological and astrophysical parameters, including constraints on warm dark matter models, the sum of the masses of the three neutrino species, and the thermal state of the intergalactic medium. We present the first measurement of P1D with the quadratic maximum likelihood estimator (QMLE) from the Dark Energy Spectroscopic Instrument (DESI) survey early data sample. This early sample of 54 600 quasars is already comparable in size to the largest previous studies, and we conduct a thorough investigation of numerous instrumental and analysis systematic errors to evaluate their impact on DESI data with QMLE. We demonstrate the excellent performance of the spectroscopic pipeline noise estimation and the impressive accuracy of the spectrograph resolution matrix with 2D image simulations of raw DESI images that we processed with the DESI spectroscopic pipeline. We also study metal line contamination and noise calibration systematics with quasar spectra on the red side of the Ly α emission line. In a companion paper, we present a similar analysis based on the Fast Fourier Transform estimate of the power spectrum. We conclude with a comparison of these two approaches and discuss the key sources of systematic error that we need to address with the upcoming DESI Year 1 analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Impact of Anode to Cathode Crossover in Lithium‐metal Batteries With High‐Nickel Cathodes

The advancement of high-energy-density lithium-metal batteries (LMBs) is hindered by the chemical instability of both lithium-metal anode and high-nickel layered oxide cathodes. While cathode-to-anode crossover is well-documented, the reverse process of anode-to-cathode crossover remains underexplored. Here, we systematically investigate such crossovers and the degradation pathway in pouch cells with a localized high-concentration electrolyte, comparing NMC622, NMC811, and NMC90 cathodes paired with lithium-metal and graphite anodes. Despite delivering higher initial capacities, LMBs exhibit faster capacity fade under long-term cycling at 45 °C. To isolate cathode-side degradation, galvanostatic electrochemical impedance spectroscopy (GEIS) measurements of cycled cathodes paired with delithiated lithium iron phosphate (LFP) counter electrodes reveal significantly higher charge-transfer resistance in cathodes cycled with lithium-metal. Surface characterization via X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) reveals greater electrolyte decomposition on cathodes cycled with lithium metal, leading to thicker, more organic-rich cathode–electrolyte interphases (CEIs), consistent with the elevated charge-transfer resistance observed in GEIS measurements. Notably, NMC90 shows the most pronounced CEI thickening, linking higher cathode surface reactivity to greater susceptibility to anode-to-cathode crossover. This work presents compelling evidence of crosstalk degradation originating from lithium-metal anodes and underscores the importance of cross-interface stability for the design of durable LMBs.

25 ENERGY STORAGE↗
DOE OSTI2026

Super-leading logarithms in top-quark pair production at hadron colliders

To date, the appearance and resummation of “super-leading” logarithms in hadron-hadron collisions has been studied only for massless parton states. We extend the formalism to include an arbitrary number of massive final states. We derive the corresponding anomalous dimension and identify an additional Coulomb phase that gives rise to a new source of super-leading logarithms. We then perform a systematic leading-logarithmic resummation of these contributions for 2 → M processes. Finally, we analyze the numerical impact in partonic scattering processes for $t\bar{t}$ production, including a treatment of the Sommerfeld enhancement observed near threshold.

Effective Field Theories of QCD↗
DOE OSTI2022

An indirect approach to optimize the reaction rates of thermal NO formation for diesel engines

With stringent emission regulations, it has become more important for modern diesel engine manufacturers to accurately predict engine-out nitrogen oxide (NO x ) emissions across a wide range of operating conditions. Thermal NO is the major source of engine-out NO x in modern diesel engines. For thermal NO formation, several earlier studies have recommended the forward and reverse reaction rate coefficients of the rate-limiting reaction (O + N 2 ⇌ NO + N). However, due to deficiencies in sub-models and inadequacies of reduced chemical mechanisms to represent diesel combustion, these recommended values more often than not need to be adjusted in reduced order combustion models to accurately predict engine-out NO x . Hence, in this work a systematic and computationally efficient approach has been proposed to streamline the process of determining the optimum reaction rate coefficients. Here, to develop the optimization approach, four different production diesel engines with different operating conditions in terms of speed, load, and exhaust-gas recirculation have been considered. Numerical simulations have been performed using a detailed zero-dimensional velocity-composition-frequency transported probability density function (0D-VCF-tPDF) model that uses hundreds of notional particles to capture in-cylinder stratification. Four different combinations of hydrocarbon and NO x chemical mechanisms were used to represent chemistry. It was found that for the rate-limiting reaction, the pre-exponent factors (A f1 , A r1 ) and activation energies (E A,f1 , E A,r1 ) of the forward and reverse reaction rates follow a linear band in A f1 - E A,f1 and A r1 - E A,r1 space where predicted engine-out NO x match the measured values closely. By encompassing such bands from different engines and considering constraints on activation energies, a reduced search domain of pre-exponent factors and activation energies was constructed that is expected to be applicable to any diesel engine. Eventually, computationally efficient three-line and one-line search approaches were proposed to determine the optimum values of the pre-exponent factors and activation energies that led to a minimum error between measured and predicted engine-out NO x . Finally, these three-line and one-line NO x optimization approaches were applied to a fifth production diesel engine for which the 0D-VCF-tPDF model showed a very good predictive performance in terms of predicting peak pressure, 50% burn rate, and engine-out NO x when compared to measured and 3D-CFD values.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

A proposed high-intensity radiometer calibration method using concentrated solar radiation

Accurate calibration of irradiance measurement devices, or radiometers, is essential for ensuring the reliability of measurements in high heat applications such as concentrating solar power (CSP), aerospace, defense, and pulsed power systems. Despite the critical need, existing calibration standards and service providers are limited to irradiance levels below 100 kW/m 2 and specific radiation sources, which is insufficient for many applications. For instance, CSP technologies, particularly those under the Department of Energy’s Solar Energy Technologies Office (SETO) Gen 3 program, require accurate measurements of broadband irradiance at levels exceeding 2000 kW/m 2 . In even more extreme scenarios, such as re-entry vehicles, heat levels can surpass 10000 kW/m 2 . Current ISO standards, specifically ISO 14934–2 and ISO 14934–3, are constrained to lower irradiance levels and dependent on black body heat sources, limiting their applicability for high-intensity broadband irradiance measurements, particularly in concentrated solar applications. Here, to address this shortfall, the National Solar Thermal Test Facility (NSTTF) at Sandia National Laboratories (SNL) proposes a calibration method and facility capable of characterizing radiometers up to 2750 kW/m 2 using concentrated solar irradiance. Calibrating with concentrated sunlight is important for solar applications as it aligns the calibration process with the solar spectrum. This alignment is crucial for minimizing systematic errors and avoiding the need for additional corrections that may arise when radiometers designed for solar applications are calibrated using black-body or electrical sources. This paper presents the present day NSTTF characterization facility and procedure, detailing the proposed calibration method and uncertainty quantification. The presented method builds upon 1980′s NSTTF methodology and involves both theoretical and empirical methods to establish a robust relationship between gauge voltage output and irradiance intensity, quantifying both measurement and fitting errors. By addressing the limitations of existing standards and extending the characterization range, this work provides an advancement in the field of high-intensity irradiance measurement and instrumentation characterization.

Gardon gauge↗