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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Using Thermodynamic Availability to Predict the Transitional Film Reynolds Number between the Droplet and Jet Modes in Falling Liquid between Horizontal Tubes

The objective of this paper is to propose and validate a model for predicting the transitional film Reynolds number between the droplet and jet modes of falling film flows. The proposed model relies on thermodynamic availability with no fitting to mode transition data. The model directly predicts the numerical values of the transitional film Reynolds numbers at different operating conditions. The results of the model are validated against 43 experimental data points from the literature, which cover 10 working fluids and a wide range of tube geometries. The accuracy of the proposed model in predicting the validation data is -on average- more than 20 % better than that of the widely used Re = a (Ga) b and Re = a (Ga) b (S/ξ) c models. The model also achieves low computation time (less than 30 seconds for the 43 validation data points). The model presented in this paper has the potential of integration with heat transfer, mass transfer, and pressure drop models for optimizing the design and operation of falling film heat and mass exchangers.

42 ENGINEERING↗
DOE OSTI2023

Numerical Simulations of High Prandtl Number Liquid Jets Impinging on a Flat Plate

In this work, 3D simulations of oil jets impinging on a flat, heated wall are presented. The numerical setup uses the Volume of Fluid (VoF) method to model the two-phase flow. A careful grid definition across the liquid film, along with the use of the Conjugate Heat Transfer (CHT) approach allowed local heat transfer to be solved with fine resolution at the wall. Variations of liquid flow rate, liquid temperature and surface temperature allow to cover a wide range of local Reynolds and Prandtl numbers (226 < Re < 2850, 77 < Pr < 161). Resulting surface-averaged heat transfer compares very well with experimental measurements conducted in a previous study. In-depth analysis of the flow has identified expected features from the literature. In particular, the impact of jet axial velocity profiles on the heat transfer distribution in the stagnation zone was clearly stated. The increase in heat transfer when warming the liquid film was also reproduced and explained by a decrease in oil viscosity and an increase in film velocity. All those effects were taken into account in correlations for stagnation and local values of Nusselt number. A grid sensitivity study was also conducted, showing that if the grid solving the thermal boundary layer in the stagnation zone can be coarsened without impacting local and surface-averaged predictions of heat transfer, a minimum resolution (2 to 3 cells) within the thermal boundary layer is however required for an accurate prediction of heat transfer.

conjugate heat transfer↗
DOE OSTI2022

Physics-informed graph neural networks for predicting cetane number with systematic data quality analysis

Designing alternative fuels for advanced compression ignition engines necessitates a predictive model for cetane number (CN). In this study, the physics-informed graph neural networks are introduced for a reliable CN prediction by considering molecular features pertinent to the physical properties of molecules that affect CN. The reliability of measured data is another key factor to consider for improving the predictive model. Various experimental instruments for measuring CN exist, including standard and non-standard methods. In this regard, a systematic data quality analysis was carried out for the total 630 CNs collected from literature and new measurements in this study using Advanced Fuel Ignition Delay Analyzer (AFIDA). The results from this data curation process were reflected in the model by imposing lower sample weights on the data coming from less reliable measurement techniques. This approach effectively maximized the prediction accuracy while incorporating data from all available sources. Using the sample weights decreased the mean absolute error (MAE) up to 0.8 CN units. The accuracy was also improved by introducing the CN-related physical properties (the number of hydrogen bond donors and acceptors); the test set MAE is 5.74 and 7.01 for the model with and without such properties, respectively. Investigating molecular structural effects on CN was also carried out to gain chemical insights into factors used to design new fuel candidates. The dimensionality reduction analysis of feature vectors showed a clear clustering in terms of functional groups and CN and the structural effect derived from the model was consistent with the physicochemical insights. Finally, this physics-informed model and data curation would be helpful for accurate CN prediction and inform rational fuel design.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Stochastic Transport Model for the Cumulative Number of Fissions and Deposited Fission Energy

The stochastic theory of neutron transport is extended to describe the cumulative distribution of fission numbers and deposited fission energy in a multiplying assembly. Solutions for the probability distributions are obtained using analytical approximations and Monte Carlo simulation in lumped geometry and in symmetric homogeneous and heterogeneous spheres. The results show the development of a power-law tail in the steady state fission number and deposited energy distributions when the medium is critical, independent of the fission neutron multiplicity distribution and domain heterogeneity. In contrast, the asymptotic decay is faster than exponential in subcritical media due to rapid chain extinction and in supercritical media due to the increasing probability of chain divergence. Here, a formal asymptotic analysis of the problem in lumped geometry with an arbitrary fission neutron multiplicity confirms the existence of power-law tails at critical.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Quantifying the basic reproduction number and underestimated fraction of Mpox cases worldwide at the onset of the outbreak

In 2022, there was a global resurgence of mpox, with different clinical-epidemiological features compared with previous outbreaks. Sexual contact was hypothesized as the primary transmission route, and the community of men having sex with men (MSM) was disproportionately affected. Because of the stigma associated with sexually transmitted infections, the real burden of mpox could be masked. We quantified the basic reproduction number (R 0 ) and the underestimated fraction of mpox cases in 16 countries, from the onset of the outbreak until early September 2022, using Bayesian inference and a compartmentalized, risk-structured (high-/low-risk populations) and two-route (sexual/non-sexual transmission) mathematical model. Machine learning (ML) was harnessed to identify underestimation determinants. Estimated R 0 ranged between 1.37 (Canada) and 3.68 (Germany). The underestimation rates for the high- and low-risk populations varied between 25–93% and 65–85%, respectively. The estimated total number of mpox cases, relative to the reported cases, is highest in Colombia (3.60) and lowest in Canada (1.08). In the ML analysis, two clusters of countries could be identified, differing in terms of attitudes towards the 2SLGBTQIAP+ community and the importance of religion. Given the substantial mpox underestimation, surveillance should be enhanced, and country-specific campaigns against the stigmatization of MSM should be organized, leveraging community-based interventions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Solid particulate mass and number from ducted fuel injection in an optically accessible diesel engine in skip-fired operation

Ducted fuel injection (DFI) is a new combustion strategy that has been shown to significantly attenuate soot formation in diesel engines. While previous studies have used optical diagnostics and optical filter smoke number methods to show that DFI reduces in-cylinder soot formation and engine-out soot emissions, respectively, this is the first study to measure solid particle number (PN) emissions in addition to particle mass (PM). Furthermore, this study quantitatively evaluates the use of transient particle instruments for measuring particles from skip-fired operation in an optical single cylinder research engine (SCRE). Engine-out PN was measured using an engine exhaust particle sizer following a catalytic stripper, and PM was measured using a photoacoustic analyzer. The study improves on earlier preliminary emissions studies by clearly showing that DFI reduces overall PM by 76%–79% and PN for particles larger than 23 nm by 77% relative to conventional diesel combustion at a 1200-rpm, 13.3-bar gross indicated mean effective pressure operating condition. The degree of engine-out PM reduction with DFI was similar across both particulate measurement instruments used in the work. Through the use of bimodal distribution fitting, DFI was also shown to reduce the geometric mean diameter of accumulation mode particles by 26%, similar to the effects of increased injection pressure in conventional diesel combustion systems. This work clearly shows the significant solid particulate matter reductions enabled by DFI while also demonstrating that engine-out PN can be accurately measured from an optical SCRE operating in a skip-fired mode. Based on these results, it is believed that DFI has the potential to enable fuel savings when implemented in multi-cylinder engines, both by lowering the required frequency of active diesel particulate filter regeneration, and by reducing the backpressure imposed by exhaust filtration systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Update of the Nuclear Criticality Slide Rule: Review of the Estimation of the Number of Fissions

IRSN (France), LLNL (USA) and ORNL (USA) began a long-term collaboration effort in 2015 to update the nuclear criticality Slide Rule (https://ncsp.llnl.gov/analytical-methods/criticality-sliderule) for the emergency response to a nuclear criticality accident. The Slide Rule permits the estimation of neutron and gamma dose rates and integrated doses based upon estimated fission yields, as a function of distance from the fission source, and time after criticality accidents for different critical systems. This paper presents the review of the section “estimation of the number of fissions”, named “fission yield” in the Slide Rule document. This estimation is important because the other information provided by the Slide Rule is directly proportional to the number of fissions. The previous models, based on Hansen and Barbry formulae, will be presented with their associated assumptions and limitations. Then, new proposals will be presented with a comparison to past criticality accidents and experimental data. The new formulae, based on the heat energy equation, cover many types of criticality accidents (solution, dry or low-moderated powder, rods/assemblies in water and dry metal) and require limited information in an emergency situation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Development of a High Min-Entropy Quantum Random Number Generator Based on Amplified Spontaneous Emission

We present the theory, architecture, and performance characteristics of a quantum random number generator (QRNG) which operates in a PCI express form factor-compatible plug-and-play design. The QRNG relies on a thermal light source (in this case, amplified spontaneous emission), which exhibits photon bunching according to the Bose–Einstein (BE) statistics. We demonstrate that 98.7% of the unprocessed random bit stream min-entropy is traceable to the BE (quantum) signal. The classical component is then removed using a non-reuse shift-XOR protocol, and the final random numbers are generated at a 200 Mbps rate and shown to pass the statistical randomness test suites FIPS 140-2, Alphabit, SmallCrush, DIEHARD, and Rabbit of the TestU01 library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Neutron Stars with Baryon Number Violation, Probing Dark Sectors

The neutron lifetime anomaly has been used to motivate the introduction of new physics with hidden-sector particles coupled to baryon number, and on which neutron stars provide powerful constraints. Although the neutron lifetime anomaly may eventually prove to be of mundane origin, we use it as motivation for a broader review of the ways that baryon number violation, be it real or apparent, and dark sectors can intertwine and how neutron star observables, both present and future, can constrain them.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Bayesian Inference of State-Level COVID-19 Basic Reproduction Numbers across the United States

Although many persons in the United States have acquired immunity to COVID-19, either through vaccination or infection with SARS-CoV-2, COVID-19 will pose an ongoing threat to non-immune persons so long as disease transmission continues. We can estimate when sustained disease transmission will end in a population by calculating the population-specific basic reproduction number ℛ0, the expected number of secondary cases generated by an infected person in the absence of any interventions. The value of ℛ0 relates to a herd immunity threshold (HIT), which is given by 1−1/ℛ0. When the immune fraction of a population exceeds this threshold, sustained disease transmission becomes exponentially unlikely (barring mutations allowing SARS-CoV-2 to escape immunity). Here, we report state-level ℛ0 estimates obtained using Bayesian inference. Maximum a posteriori estimates range from 7.1 for New Jersey to 2.3 for Wyoming, indicating that disease transmission varies considerably across states and that reaching herd immunity will be more difficult in some states than others. ℛ0 estimates were obtained from compartmental models via the next-generation matrix approach after each model was parameterized using regional daily confirmed case reports of COVID-19 from 21 January 2020 to 21 June 2020. Our ℛ0 estimates characterize the infectiousness of ancestral strains, but they can be used to determine HITs for a distinct, currently dominant circulating strain, such as SARS-CoV-2 variant Delta (lineage B.1.617.2), if the relative infectiousness of the strain can be ascertained. On the basis of Delta-adjusted HITs, vaccination data, and seroprevalence survey data, we found that no state had achieved herd immunity as of 20 September 2021.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Scaling of Turbulent Viscosity and Resistivity: Extracting a Scale-dependent Turbulent Magnetic Prandtl Number

Turbulent viscosity νt and resistivity ηt are perhaps the simplest models for turbulent transport of angular momentum and magnetic fields, respectively. The associated turbulent magnetic Prandtl number Pr t ≡ ν t /η t has been well recognized to determine the final magnetic configuration of accretion disks. Here, we present an approach to determining these "effective transport" coefficients acting at different length scales using coarse-graining and recent results on decoupled kinetic and magnetic energy cascades. By analyzing the kinetic and magnetic energy cascades from a suite of high-resolution simulations, we show that our definitions of ν t , η t , and Pr t have power-law scalings in the "decoupled range." We observe that Pr t ≈ 1–2 at the smallest inertial-inductive scales, increasing to ≈5 at the largest scales. Furthermore, based on physical considerations, our analysis suggests that Pr t has to become scale independent and of order unity in the decoupled range at sufficiently high Reynolds numbers (or grid resolution) and that the power-law scaling exponents of velocity and magnetic spectra become equal. In addition to implications for astrophysical systems, the scale-dependent turbulent transport coefficients offer a guide for large-eddy simulation modeling.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1966

Grid turbulence at large Reynolds numbers.

Grid turbulence for large Reynolds numbers, noting consistency of power spectra values with Kolmogoroff scaling, decay law and Reynolds number effect on turbulence

GRID↗
NASA NTRS1949

Aerodynamic Study of a Wing-fuselage Combination Employing a Wing Swept Back 63 Degrees : Characteristics at a Mach Number of 1.53 Including Effect of Small Variations of Sweep

Measured values of lift, drag, and pitching moment at a Mach number of 1.53 and Reynolds numbers of 0.31, 0.62, and 0.84 million are presented for a wing-fuselage combination having a wing leading-edge sweep angle of 63 degrees, an aspect ratio of 3.42, a taper ratio of 0.25, and an NACA 64A006 section in the stream direction. Data are also presented for sweep angles of 57.0 degrees, 60.4 degrees, 67.0 degrees, and 69.9 degrees. The experimentally determined characteristics were less favorable than indicated by the linear theory but the experimental and theoretical trends with sweep were in good agreement. Boundary-layer-flow tests showed that laminar boundary-layer separation was the primary cause of the differences between experiment and theory.

REYNOLDS NUMBER EFFECTS - COMPLETE WING↗
NASA NTRS1951

An Investigation of Flow Characteristics at Mach Number 4.04 over 6- and 9-percent-thick Symmetrical Circular-arc Airfoils Having 30-percent-chord Trailing-edge Flaps

Section data obtained from wind-tunnel tests at Mach number 4.04 and Reynolds numbers of about 5.0 times 10 to the 6th power and 8.4 times 10 to the 6th power are presented for 6- and 9-percent-thick symmetrical circular-arc airfoils with 30 percent chord trailing-edge flaps. Pressure distributions, Schlieren photographs, and force and moment coefficients are included.

FLOW, VISCOUS↗
NASA NTRS2020

A Second-Order Closure Turbulence Model: New Heat Flux Equations and No Critical Richardson Number

We formulate a new second-order closure turbulence model by employing a recent closure for the pressure-temperature correlation at the equation level. As a result, we obtain new heat flux equations that avoid the long-standing issue of a finite critical Richardson number. The new, structurally simpler model improves on the Mellor-Yamada 1982 and Galperin et al. 1988 models; key feature includes enhanced mixing under stable conditions facilitating agreement with observational, experimental and high-resolution numerical data sets. The model predicts a planetary boundary layer height deeper than predicted by models with low critical Richardson numbers, as demonstrated in single column model runs of the GISS ModelE general circulation model.

second-order closure turbulence model↗
NASA NTRS2020

Freestream Mach-Number and Temperature Measurement in NASA Langley’s 20-Inch Supersonic Wind Tunnel Using Laser-Induced Thermal Acoustics

We report single-laser-shot (0.3 us) and time-averaged (500 laser shots at 30 Hz repetition rate) measurements of static temperature T and Mach number M in the freestream of NASA Langley’s 20-inch Supersonic Wind Tunnel (SWT), using a nonintrusive optical technique: laser-induced thermal acoustics (LITA). Although the single-shot LITA T measurements show typical standard deviations (SD) of the sample of +- 4% (+- 1-sigma or 68% confidence for random errors), the 1-s averages show SDs of the mean deltaT = +- 0.5 K, or +- 0.3% for flow at T ~ 160 K. The 17-s averages show ± 0.1% SDs of the mean. Both 1-s and 17-s averages agree to within about 1% of SWT’s traditional probe measurements. Additionally, the single-shot LITA M measurements show typical shot-to-shot SDs of the sample of +- 5% (+- 1-sigma), but the 1-s averages indicate 1-sigma SDs of the means deltaM = +- 0.02, or +- 1% for M = 2.0. Extending the time averages to 17 s, SDs of the mean are reduced to about deltaM = +- 0.007, or +- 0.4% (± 1-sigma). The 1-s and 17-s time-averaged LITA-measured Mach numbers also agree with the SWT probe instrumentation to within 1%. Most of the shot-to-shot measurement noise probably arises from the LITA instrument itself (the fundamental limit of Fourier transforming a short-duration data series). Thus the 1-s averages only provide upper limits for the temporal stability of the freestream tunnel flow on 1-s time scales and complement previous work that characterized the SWT spatial uniformity of the flow. They also provide a first noninvasive comparison to the traditional calibrations with physical probes, for both the mean and fluctuating components of the freestream.

Laser-Induced Thermal Acoustics (LITA)↗
NASA NTRS2022

Nonlinear Evolution of Instabilities in a Laminar Separation Bubble at a Hypersonic Mach Number

The development of both convective stationary perturbation as well as global instabilities in the vicinity of a laminar separation bubble above an axisymmetric compression corner in a hypersonic flow is investigated using numerical simulations. The flow configuration of primary interest corresponds to the cone-cylinder-flare model used in experimental measurements in the Boeing/AFOSR Mach-6 Quiet Tunnel at Purdue University. For a flare angle of 10 degrees and a unit Reynolds number of 11.5 x 10 6 m -1 , their surface flow visualizations identified the presence of streamwise elongated thermal streaks near the reattachment position and the dominant azimuthal spacing between the streaks was determined to be approximately 10 degrees (i.e., an azimuthal mode number of 36). Previous linear stability analyses predicted that the amplification characteristics of small amplitude, unsteady, convective instabilities within this flow were consistent with the surface pressure fluctuations measured in the experiment. However, their accompanying analysis of global instabilities had found the separation bubble to be weakly unstable at the 10 degrees flare angle, with the most unstable global mode corresponding to a stationary disturbance with an azimuthal wavenumber of m ≈ 5, which was well below the measured wavenumber of m = 36. Besides confirming the presence of the global instability at these flow conditions, the present numerical simulations quantify the details of the stationary equilibrium state associated with the supercritical bifurcation resulting from the nonlinear saturation of the unstable global mode. Although velocity perturbations associated with the saturated global mode are dominated by the fundamental spanwise wavelength associated with the linear global instability, the surface heat flux downstream of reattachment is dominated by m = 36 in agreement with experimental measurements. However, the shorter wavelength peak ( m = 36) in the azimuthal spectrum is not manifested as streaks with an azimuthal spacing of 10 degrees. An additional simulation of the combined evolution of both unsteady convective and global instabilities indicates that the nonlinear interactions between a broadband spectrum of oblique Mack’s first mode instabilities generate stationary vortex modes with a higher dominant wavenumber ( m = 60) as that observed in the experiments. Additional analyses are performed to predict the global mode behavior at other flare angles and how it differs from the convective centrifugal instability due to concave streamline curvature over the compression corner.

Hypersonic flow↗
NASA NTRS2022

Use of Machine Learning to Reduce Uncertainties in Particle Number Concentration and Aerosol Indirect Radiative Forcing Predicted by Climate Models

The radiative forcing of anthropogenic aerosols associated with aerosol–cloud interactions (RF(sub aci)) remains the largest source of uncertainty in climate prediction. The calculation of particle number concentration (PNC), one of the critical parameters affecting RF(sub aci), is generally simplified in climate models. Here we employ outputs from long-term (30-years) simulations of a global size-resolved (sectional) aerosol microphysics model and a machine-learning tool to develop a Random Forest Regression Model (RFRM) for PNC. We have implemented the PNC RFRM in GISS-ModelE2.1 with a mass-based One-Moment Aerosol module, which is one of CMIP6 models. Compared to the default setting, the GISS-ModelE2.1 simulation based on RFRM reduces the changes of cloud droplet number concentration associated with anthropogenic emissions, and decreases the RF(sub aci) from −1.46 W⋅m(exp −2) to −1.11 W⋅m(exp −2). This work highlights a promising approach based on machine learning to reduce uncertainties of climate models in predicting PNC and RF(sub aci) without compromising their computing efficiency.

Radiative forcing↗