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At least 1,369 records · Page 76

Disturbance Dynamics in Transitional and Turbulent Flows

In order to expand the predictive capability of single-point turbulence closure models to account for the early-stage transition regime, a methodology for the formulation and calibration of model equations for the ensemble-averaged disturbance kinetic energy and energy dissipation rate is presented. First the decay of laminar disturbances and turbulence in mean shear-free flows is studied. In laminar flows, such disturbances are linear superpositions of modes governed by the Orr-Sommerfeld equation. In turbulent flows, disturbances are described through transport equations for representative mean quantities. The link between a description based on a deterministic evolution equation and a probability based mean transport equation is established. Because an uncertainty in initial conditions exists in the laminar as well as the turbulent regime, a probability distribution must be defined even in the laminar case. Using this probability distribution, it is shown that the exponential decay of the linear modes in the laminar regime can be related to a power law decay of both the (ensemble) mean disturbance kinetic energy and the dissipation rate. The evolution of these mean disturbance quantities is then described by transport equations similar to those for the corresponding turbulent decaying flow. Second, homogeneous shear flow, where disturbances can be described by rapid distortion theory (RDT), is studied. The relationship between RDT and linear stability theory is exploited in order to obtain a closed set of modeled equations. The linear disturbance equations are solved directly so that the numerical simulation yields a database from which the closure coefficients in the ensemble-averaged disturbance equations can be determined.

Grosch, Chester E.↗

Kepler Data Analysis: Non-Gaussian Noise and Fourier Gaussian Process Analysis of Stellar Variability

We develop a statistical analysis model of Kepler stellar flux data in the presence of planet transits, non-Gaussian noise, and stellar variability. We first develop a model for the Kepler noise probability distribution in the presence of outliers, which make the noise probability distribution non-Gaussian. We develop a signal likelihood analysis based on this probability distribution, in which we model the signal as a sum of the star variability and planetary transits. We argue that these components need to be modeled together if optimal signal is to be extracted from the data. For the stellar variability model we develop an optimal Gaussian process analysis using a Fourier-based Wiener filter approach, where the power spectrum is non-parametric and learned from the data. We develop high dimensional optimization of the objective function, where we jointly optimize all the model parameters, including thousands of star variability modes, and planet transit parameters. We apply the method to Kepler-90 data and show that it gives a better match to the stellar variability than the existing methods, and robustly handles noise outliers. As a consequence, the planet radii have a higher value than what the existing methods give, including splines and celerite.

79 ASTRONOMY AND ASTROPHYSICS↗

An Operational Configuration of the ARPS Data Analysis System to Initialize WRF in the NM'S Environmental Modeling System

The Weather Research and Forecasting (WRF) model is the next generation community mesoscale model designed to enhance collaboration between the research and operational sectors. The NM'S as a whole has begun a transition toward WRF as the mesoscale model of choice to use as a tool in making local forecasts. Currently, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) are running the Advanced Regional Prediction System (AIRPS) Data Analysis System (ADAS) every 15 minutes over the Florida peninsula to produce high-resolution diagnostics supporting their daily operations. In addition, the NWS MLB and SMG have used ADAS to provide initial conditions for short-range forecasts from the ARPS numerical weather prediction (NWP) model. Both NM'S MLB and SMG have derived great benefit from the maturity of ADAS, and would like to use ADAS for providing initial conditions to WRF. In order to assist in this WRF transition effort, the Applied Meteorology Unit (AMU) was tasked to configure and implement an operational version of WRF that uses output from ADAS for the model initial conditions. Both agencies asked the AMU to develop a framework that allows the ADAS initial conditions to be incorporated into the WRF Environmental Modeling System (EMS) software. Developed by the NM'S Science Operations Officer (S00) Science and Training Resource Center (STRC), the EMS is a complete, full physics, NWP package that incorporates dynamical cores from both the National Center for Atmospheric Research's Advanced Research WRF (ARW) and the National Centers for Environmental Prediction's Non-Hydrostatic Mesoscale Model (NMM) into a single end-to-end forecasting system. The EMS performs nearly all pre- and postprocessing and can be run automatically to obtain external grid data for WRF boundary conditions, run the model, and convert the data into a format that can be readily viewed within the Advanced Weather Interactive Processing System. The EMS has also incorporated the WRF Standard Initialization (SI) graphical user interface (GUT), which allows the user to set up the domain, dynamical core, resolution, etc., with ease. In addition to the SI GUT, the EMS contains a number of configuration files with extensive documentation to help the user select the appropriate input parameters for model physics schemes, integration timesteps, etc. Therefore, because of its streamlined capability, it is quite advantageous to configure ADAS to provide initial condition data to the EMS software. One of the biggest potential benefits of configuring ADAS for ingest into the EMS is that the analyses could be used to initialize either the ARW or NMM. Currently, the ARPS/ADAS software has a conversion routine only for the ARW dynamical core. However, since the NIvIM runs about 2.5 times faster than the ARW, it is quite advantageous to be able to run an ADAS/NMM configuration operationally due to the increased efficiency.

Case, Jonathan↗

Scale and rate in CdS pressure-induced phase transition

Here, we describe recent efforts to improve our predictive modeling of rate-dependent behavior at, or near, a phase transition using molecular dynamics simulations. Cadmium sulfide (CdS) is a well-studied material that undergoes a solid-solid phase transition from wurtzite to rock salt structures between 3 and 9 GPa. Atomistic simulations are used to investigate the dominant transition mechanisms as a function of orientation, size and rate. We found that the final rock salt orientations were determined relative to the initial wurtzite orientation, and that these orientations were different for the two orientations and two pressure regimes studied. The CdS solid-solid phase transition is studied, for both a bulk single crystal and for polymer-encapsulated spherical nanoparticles of various sizes.

42 ENGINEERING↗

Direct observation of the exotic β – γ – α decay mode in the T z = – 1 nucleus Na 20

The exotic β – γ – α decay mode of 20 Na has been directly observed for the first time in the Day-one experiment at the Beijing Radioactive Ion-beam Facility. The 20 Na source was produced by using a 100-MeV proton beam bombarding a stack of microporous MgO thick target and delivered as an intense mass separated beam after online ionization. A high-efficiency simultaneous measurement of β, γ, and α transitions enables the β-delayed γ – γ and α – γ coincidence spectroscopy. Here three β – γ – α exotic decay sequences in 20 Na are discovered, which expands the rare decay modes observed in β decay. Moreover, a β – α –decay sequence to the 6130-keV 3 – state of 16 O is observed, which is likely through the 12367-keV 1 + state in 20 Ne. The experimentally deduced B(F) and B(GT) are compared to the shell-model calculation, the allowed β transition strengths can be well accounted for by using sd shell-model space interactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Atomic-scale understanding of oxide growth and dissolution kinetics of Ni-Cr alloys

Aqueous corrosion of metals is governed by formation and dissolution of a passivating, multi-component surface oxide. Unfortunately, a detailed atomistic description is challenging due to the compositional complexity and the need to consider multiple kinetic factors simultaneously. To this end, we combine experiments with a first-principles-derived, multiscale computational framework that transcends thermodynamic descriptions to explicitly simulate the kinetic evolution of surface oxides of Ni-Cr alloys as a function of composition, temperature, pH, and applied voltage. In the absence of pitting, we identify three distinct voltage regimes, which are kinetically dominated by oxide growth, dissolution, and competitive dissolution and reprecipitation. Evolving compositional gradients and oxide thickness are revealed, including a transition between a metastable Ni-Cr mixed oxide and a thick, porous Ni-dominated oxide. Beyond elucidating the underlying physics, we highlight the need for competing kinetics in models to properly predict the transition from passivation to corrosion. Our results provide a key step towards co-design of alloy composition alongside environmental conditions for sustainable use across a variety of critical energy and infrastructure applications.

36 MATERIALS SCIENCE↗

The middle atmospheric response to short and long term solar UV variations: analysis of observations and 2D model results

We have investigated the middle atmospheric response to the 27-day and 11-yr solar UV flux variations at low to middle latitudes using a two-dimensional photochemical model. The model reproduced most features of the observed 27-day sensitivity and phase lag of the profile ozone response in the upper stratosphere and lower mesosphere, with a maximum sensitivity of +0.51% per 1% change in 205 nm flux. The model also reproduced the observed transition to a negative phase lag above 2 mb, reflecting the increasing importance with height of the solar modulated HO(x) chemistry on the ozone response above 45 km. The model revealed the general anti-correlation of ozone and solar UV at 65-75 km, and simulated strong UV responses of water vapor and HO(x) species in the mesosphere. Consistent with previous 1D model studies, the observed upper mesospheric positive ozone response averaged over +/- 40 was simulated only when the model water vapor concentrations above 75 km were significantly reduced relative to current observations. In agreement with observations, the model computed a low to middle latitude total ozone phase lag of +3 days and a sensitivity of +0.077% per 1% change in 205 nm flux for the 27-day solar variation, and a total ozone sensitivity of +0.27% for the 11-yr solar cycle. This factor of 3 sensitivity difference is indicative of the photochemical time constant for ozone in the lower stratosphere which is comparable to the 27-day solar rotation period but is much shorter than the 11-yr solar cycle.

Fleming, Eric L.↗

Flow Control on Low-Pressure Turbine Airfoils Using Vortex Generator Jets

Motivation - Higher loading on Low-Pressure Turbine (LPT) airfoils: Reduce airfoil count, weight, cost. Increase efficiency, and Limited by suction side separation. Growing understanding of transition, separation, wake effects: Improved models. Take advantage of wakes. Higher lift airfoils in use. Further loading increases may require flow control: Passive: trips, dimples, etc. Active: plasma actuators, vortex generator jets (VGJs). Can increased loading offset higher losses on high lift airfoils. Objectives: Advance knowledge of boundary layer separation and transition under LPT conditions. Demonstrate, improve understanding of separation control with pulsed VGJs. Produce detailed experimental data base. Test and develop computational models.

Volino, Ralph J.↗

Coupling to rotational manifolds to improve gas-phase pump–probe spectroscopic models

The physical picture of gas-phase optical transitions is normally presented as an isolated two-level system balanced by upward and downward processes. Isolated models assume a phenomenological treatment of collisional dephasing but do not strictly account for collisional population exchange with the rotational baths. While this assumption is valid under low-intensity conditions, where excitation is rate-limiting, isolated models can deviate from Beer’s Law at sufficient pressures and monochromatic intensities when both collisional broadening and power broadening are comparable to (or greater than) lifetime broadening, which are not uncommon conditions for cavity enhanced spectroscopies in the mid-IR spectral range. Although this problem has been addressed by rate-equation models for linear absorption measurements, a general treatment for multi-level quantum mechanical models suitable for non-linear absorption measurements (two-photon/two-color/pump–probe) is lacking. Isolated models require physical parameter inputs that disagree with expected values by at least an order of magnitude. These non-physical models undermine the ability to predict non-linear signal strengths under untested conditions and thereby limit the potential to optimize the sensitivity of non-linear spectroscopies and to expand their analytical applications (e.g., new analytes and/or buffer gases, changes in cavity free-spectral-range, changes in intracavity powers or wavelengths, and accurate investigation of physical phenomena). In this study, we derive bath-coupled models for gaseous pump–probe spectroscopy by application of the quantum Lindblad equation and detailed balance. Bath-coupled models are shown to fit data consistently across variations in intensity and agree with all physically expected values.

Cavity ring-down spectroscopy↗

Optimizing flow condensation models for next-generation refrigerants in axial micro-fin aluminum tubes

To support the transition to next-generation refrigerants, accurate modelling of heat transfer and pressure drop is essential for designing efficient heat exchangers. Current models, largely based on traditional refrigerants and unexpanded micro-fin tubes, may not reliably predict performance for new refrigerants and expanded micro-fin geometries. This study evaluates four condensation models using experimental data for six A2L refrigerants: R-32, R-454B, R-454C, R-455A, R-1234yf, and R-1234ze(E). For heat transfer models, the Han and Lee (2005) model initially yields the best accuracy (mean absolute Deviation, MAD = 22.1%). To further improve predictions, a correction factor reduces the Cavallini et al. (2009) model’s MAD from 68.2% to 15.4%, while optimization of the Kedzierski and Goncalves (1997) model achieves a MAD of 13.1%. For pressure drop, the Cavallini et al. (1997) model proves most accurate (MAD = 6.4%), with the simpler Haraguchi et al. (1993) model also effective (MAD = 9.4%). Keywords: Flow condensation models, heat transfer coefficient, frictional pressure drop, next-generation refrigerants, aluminum micro-fin tubes

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗

Low-Disturbance Flow Characteristics of the NASA-Ames Laminar Flow Supersonic Wind Tunnel

A unique, low-disturbance (quiet) supersonic wind tunnel has been commissioned at the NASA-Ames Fluid Mechanics Laboratory (FML) to support Supersonic Laminar Flow Control (SLFC) research. Known as the Laminar Flow Supersonic Wind Tunnel (LFSWT), this tunnel is designed to operate at potential cruise Mach numbers and unit Reynolds numbers (Re) of the High Speed Civil Transport (HSCT). The need to better understand the receptivity of the transition phenomena on swept (HSCT) wings to attachment-line contamination and cross-flows has provided the impetus for building the LFSWT. Low-disturbance or "quiet" wind tunnels are known to be an essential part of any meaningful boundary layer transition research. In particular, the receptivity of supersonic boundary layers to wind tunnel disturbances can significantly alter the transition phenomena under investigation on a test model. Consequently, considerable effort has gone into the design of the LFSWT to provide quiet flow. The paper describes efforts to quantify the low-disturbance flows in the LFSWT operating at Mach 1.6, as a precursor to transition research on wing models. The research includes: (1) Flow measurements in both the test section and settling chamber of the LFSWT, using a full range of measurement techniques; (2) Study of the state of the test section boundary layer so far by using a single hot-wire mounted above the floor centerline, with and without boundary layer trips fitted at the test section entrance; (3) The effect of flow quality of unsteady supersonic diffuser flow, joint steps and gaps, and wall vibration.

Wolf, Stephen W. D.↗

Vehicle-Cycle Inventory for Type C School Buses & Intra-City Transit Buses

This report documents the new inventory incorporated into the Research and Development version of Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) 2025 model for the vehicle cycle of Type C school buses and intracity transit buses. The transportation sector contributes significantly to the United States’ energy consumption and resultant emissions (EPA, 2025a). However, public transit plays an important role in mitigating these impacts because it consumes a relatively low amount of energy per passenger (Congressional Budget Office, 2022). Public transit is widely used in the United States; more than 500,000 school buses (EPA, 2025b) and ~75,000 service buses (American Public Transportation Association, 2025) operate in the nation. These are primarily internal combustion engine vehicles (ICEVs) powered by diesel. Original equipment manufacturers (OEMs) are making efforts to electrify U.S. bus fleets by using batteries as a propulsion system to replace internal combustion engines. Electrification can reduce tailpipe emissions, such as particulate matter (with a diameter ≤10 µm [PM 10 ] and with a diameter ≤2.5 µm [PM 2.5 ]) and nitrogen oxides (Jonas et al., 2025; Martinez and Samaras, 2024; EPA, 2025b; Wayne et al., 2009). Hence, any energy and emission impact analysis of public transit must consider both conventional ICEVs and upcoming electric vehicle (EV) options for the school and transit buses that dominate this landscape. To understand the detailed environmental impact profiles of ICEV and EV school and transit buses, it is necessary to conduct a thorough analysis covering both vehicle manufacturing and vehicle use stages. The current literature lacks a detailed vehicle-cycle inventory for school and transit buses, which makes this kind of comparison difficult. To overcome this gap, we developed a comprehensive vehicle-cycle model for school and transit buses in Argonne’s R&D GREET 2025 model. The model is flexible in handling user inputs for key assumptions, such as component weights and material compositions, upstream energy sources for material processing, and vehicle operating parameters, to understand their impacts on energy use and emissions for both school and transit buses. This report is organized as follows: Section 2 provides details on the modeling approach and vehicle specifications (weights and composition of different vehicle components, and vehicle operating parameters) for both school and transit buses. Section 3 provides details on vehicle assembly, disposal, and recycling (ADR) approaches for the two buses. Section 4 includes details about their incorporation into the R&D GREET model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗

On the Role of Friction and Particle Size Distribution in Granular Packings

Packing of particles in a disordered arrangement has tremendous significance in both condensed matter physics and engineering applications. The last three decades have seen remarkable progress in our understanding of the physics of granular packings that has been largely facilitated by a rapid growth in the power of modern computers. Although granular packings are ubiquitous in diverse natural settings, from clogging of powders in hoppers to the crowding of living cells, a significant motivation for modeling granular packings has emerged from a proposal that the transition from a fluid-like state to a solid-like state of a granular material upon increasing volume fraction, called jamming, is intimately related to the origins of glass transition in thermal systems. As such, a majority of modeling efforts have focused on the jamming behavior of an idealized granular material: frictionless, monodisperse sphere. While such studies have illuminated the rich physics of jamming, granular materials in nature and engineering practice are rarely frictionless or monodisperse. The analogous research on the packing of these ‘real-world’ granular materials is still not fully developed. Besides requiring the exploration of a huge parameter space, three key computational considerations have inhibited their modeling: (i) traditional computational methods are not adept at simulating mechanically-stable packings of frictional particles near the jamming transition; (ii) standard algorithms of contact detection in discrete element methods are impractical to simulate granular packings with a wide distribution of particle sizes; (iii) a lack of well-established contact mechanics models of friction that can accurately reproduce experimental data. This chapter will review the latest computational advances to simulate the jamming of size-dispersed frictional particles, and describe the rich microstructural diversity that emerges in their packings.

granular↗

Evaluation of transit-time and electromagnetic flow measurement in a chronically instrumented nonhuman primate model

The Physiology Research Branch at Brooks AFB conducts both human and nonhuman primate experiments to determine the effects of microgravity and hypergravity on the cardiovascular system and to identify the particular mechanisms that invoke these responses. Primary investigative efforts in our nonhuman primate model require the determination of total peripheral resistance, systemic arterial compliance, and pressure-volume loop characteristics. These calculations require beat-to-beat measurement of aortic flow. This study evaluated accuracy, linearity, biocompatability, and anatomical features of commercially available electromagnetic (EMF) and transit-time flow measurement techniques. Five rhesus monkeys were instrumented with either EMF (3 subjects) or transit-time (2 subjects) flow sensors encircling the proximal ascending aorta. Cardiac outputs computed from these transducers taken over ranges of 0.5 to 2.0 L/min were compared to values obtained using thermodilution. In vivo experiments demonstrated that the EMF probe produced an average error of 15% (r = .896) and 8.6% average linearity per reading, and the transit-time flow probe produced an average error of 6% (r = .955) and 5.3% average linearity per reading. Postoperative performance and biocompatability of the probes were maintained throughout the study. The transit-time sensors provided the advantages of greater accuracy, smaller size, and lighter weight than the EMF probes. In conclusion, the characteristic features and performance of the transit-time sensors were superior to those of the EMF sensors in this study.

Non-NASA Center↗

An end-to-end deep learning method for solving nonlocal Allen–Cahn and Cahn–Hilliard phase-field models

Here, we propose an efficient end-to-end deep learning method for solving nonlocal Allen–Cahn (AC) and Cahn–Hilliard (CH) phase-field models. One motivation for this effort emanates from the fact that discretized partial differential equation-based AC or CH phase-field models result in diffuse interfaces between phases, with the only recourse for remediation is to severely refine the spatial grids in the vicinity of the true moving sharp interface whose width is determined by a grid-independent parameter that is substantially larger than the local grid size. In this work, we introduce non-mass conserving nonlocal AC or CH phase-field models with regular, logarithmic, or obstacle double-well potentials. Because of non-locality, some of these models feature totally sharp interfaces separating phases. The discretization of such models can lead to a transition between phases whose width is only a single grid cell wide. Another motivation is to use deep learning approaches to ameliorate the otherwise high cost of solving discretized nonlocal phase-field models. To this end, loss functions of the customized neural networks are defined using the residual of the fully discrete approximations of the AC or CH models, which results from applying a Fourier collocation method and a temporal semi-implicit approximation. To address the long-range interactions in the models, we tailor the architecture of the neural network by incorporating a nonlocal kernel as an input channel to the neural network model. We then provide the results of extensive computational experiments to illustrate the accuracy, predictive capabilities, and cost reductions of the proposed method.

42 ENGINEERING↗

Rarefied flow past a flat plate at incidence

Results of a numerical study using the direct simulation Monte Carlo (DSMC) method are presented for the transitional flow about a flat plate at 40 deg incidence. The plate has zero thickness and a length of 1.0 m. The flow conditions simulated are those experienced by the Shuttle Orbiter during reentry at 7.5 km/s. The range of freestream conditions are such that the freestream Knudsen number values are between 0.02 and 8.4, i.e., conditions that encompass most of the transitional flow regime. The DSMC simulations show that transitional effects are evident when compared with free molecule results for all cases considered. The calculated results demonstrate clearly the necessity of having a means of identifying the effects of transitional flow when making aerodynamic flight measurements as are currently being made with the Space Shuttle Orbiter vehicles. Previous flight data analyses have relied exclusively on adjustments in the gas-surface interaction models without accounting for the transitional effect which can be comparable in magnitude. The present calculations show that the transitional effect at 175 km would increase the Space Shuttle Orbiter lift-drag ratio by 90 percent over the free molecule value.

Dogra, Virendra K.↗

Rarefied flow past a flat plate at incidence

Results of a numerical study using the direct simulation Monte Carlo (DSMC) method are presented for the transitional flow about a flat plate at 40 deg incidence. The plate has zero thickness and a length of 1.0 m. The flow conditions simulated are those experienced by the Shuttle Orbiter during reentry at 7.5 km/s. The range of freestream conditions are such that the freestream Knudsen number values are between 0.02 and 8.4, i.e., conditions that encompass most of the transitional flow regime. The DSMC simulations show that transitional effects are evident when compared with free molecule results for all cases considered. The calculated results demonstrate clearly the necessity of having a means of identifying the effects of transitional flow when making aerodynamic flight measurements as are currently being made with the Space Shuttle Orbiter vehicles. Previous flight data analyses have relied exclusively on adjustments in the gas-surface interaction models without accounting for the transitional effect which can be comparable in magnitude. The present calculations show that the transitional effect at 175 km would increase the Space Shuttle Orbiter lift-drag ratio by 90 percent over the free molecule value.

Dogra, Virendra K.↗