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NASA NTRS1993

Zonal Two Equation Kappa-Omega Turbulence Models for Aerodynamic Flows

Two new versions of the kappa-omega two-equation turbulence model will be presented. The new Baseline (BSL) model is designed to give results similar to those of the original kappa-omega model of Wilcox, but without its strong dependency on arbitrary freestream values. The BSL model is identical to the Wilcox model in the inner 50% of the boundary-layer but changes gradually to the standard kappa-epsilon model (in a kappa- omega formulation) towards the boundary-layer edge. The free shear layers. The second version of the model is called Shear-Stress Transport (SST) model. It is a variation of the BSL model with the additional ability to account for the transport of the principal turbulent shear stress in adverse pressure gradient boundary-layers. The model is based on Bradshaw's assumption that the principal shear-stress is proportional to the turbulent kinetic energy, which is introduced into the definition of the eddy-viscosity. Both models are tested for a large number of different flowfields. The results of the BSL model are similar to those of the original kappa-omega model, but without the undesirable freestream dependency. The predictions of the SST model are also independent of the freestream values but show better agreement with experimental data for adverse pressure gradient boundary-layer flows.

Menter, Florian R.↗

DOE OSTI2024

Proton and neutron density distributions at supranormal density in low- and medium-energy heavy-ion collisions. II. Central Pb + Pb collisions

This paper represents a continuation of our investigation into the limitations on total, proton, and neutron particle number densities, as well as the asymmetry of proton and neutron density distributions achievable in central heavy-ion collisions. We explore these aspects at low and medium energies within the framework of the Boltzmann-Uhlenbeck-Uehling (pBUU) transport and time-dependent Hartree-Fock (TDHF) models. Previous studies, focusing on symmetric and asymmetric collisions of Ca and Sn nuclei [1], and initial results on Pb-nuclei collisions [2], emphasized the role of the Coulomb interaction in these events. Our findings indicated that: (i) the highest total densities predicted at 𝐸 beam = 800 MeV/nucleon were on the order of ≈ 2.5⁢𝜌 0 (𝜌 0 = 0.16 fm −3 ), (ii) the proton-neutron asymmetry for maximal densities, 𝛿=(𝜌$^{max}_{n}$− 𝜌$^{max}_{p}$)/(𝜌$^{max}_{n}$+𝜌$^{max}_{p}$), did not generally exceed the asymmetry in the initial state of the collision at all beam energies and tended to decrease during the reaction, and (iii) a significant portion of this asymmetry had its microscopic origin in Coulomb forces, masking the pure nuclear contribution. These new findings, particularly relevant in the astrophysical context, are further examined in this work, focusing on the heaviest target-projectile combination 212,208 Pb accessible in an experiment. We introduce the SkT3 Skyrme force model, not previously used for the Pb system, and compare it to the SV-bas and SV-sym34 models to explore the symmetry-energy dependence of the results. Contour plots of nucleonic densities are presented, contrasting the time evolution of the density distributions in low (TDHF) and high (pBUU) models. We also present the evolution of normalized maximal proton, neutron, and total nucleon number density with increasing beam energy in the full pBUU model and the Vlasov approximation, aiming to explore the impact of correlations in the reaction. The time evolution of the proton and neutron density distributions in the plane transverse to the beam direction is illustrated at both low and high beam energy. In conclusion, our detailed examination of the Pb system in this work provides further essential evidence that the aforementioned findings (i)–(iii) are only weakly dependent on system size and a symmetry-energy model, and thus, they are of more general importance.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2014

Real-Time Parameter Estimation Using Output Error

Output-error parameter estimation, normally a post- ight batch technique, was applied to real-time dynamic modeling problems. Variations on the traditional algorithm were investigated with the goal of making the method suitable for operation in real time. Im- plementation recommendations are given that are dependent on the modeling problem of interest. Application to ight test data showed that accurate parameter estimates and un- certainties for the short-period dynamics model were available every 2 s using time domain data, or every 3 s using frequency domain data. The data compatibility problem was also solved in real time, providing corrected sensor measurements every 4 s. If uncertainty corrections for colored residuals are omitted, this rate can be increased to every 0.5 s.

Grauer, Jared A.↗

NASA NTRS2019

MOA-bin-29b: A Microlensing Gas-giant Planet Orbiting a Low-mass Host Star

We report the discovery of a gas-giant planet orbiting a low-mass host star in the microlensing event MOA-bin-29 that occurred in 2006. We find five degenerate solutions with the planet/host-star mass ratio of q ∼ 10(exp−2). The Einstein radius crossing time of all models are relatively short (∼4–7 days), which indicates that the mass of host star is likely low. The measured lens-source proper motion is 5–9 mas/yr depending on the models. Since only finite source effects are detected, we conduct a Bayesian analysis in order to obtain the posterior probability distribution of the lens physical properties. As a result, we find the lens system is likely to be a gas-giant orbiting a brown dwarf or a very late M-dwarf in the Galactic bulge. The probability distributions of the physical parameters for the five degenerate models are consistent within the range of error. By combining these probability distributions, we conclude that the lens system is a gas giant with a mass of M(p)= 0.63(sub +1.13, sub 0.39) M(Jup) orbiting a brown dwarf with a mass of M(h)= 0.06 (sup +0.11, sub -0.04) M(ʘ) at a projected star–planet separation of r⊥ = 0.53(sup +0.89, sub -0.18)au . The lens distance is D(L)= 6.89(sup +1.19, sub -1.19) kpc, i.e., likely within the Galactic bulge.

Iona Kondo↗

DOE OSTI2024

Modeling the effect of wind speed and direction shear on utility‐scale wind turbine power production

Abstract Wind speed and direction variations across the rotor affect power production. As utility‐scale turbines extend higher into the atmospheric boundary layer (ABL) with larger rotor diameters and hub heights, they increasingly encounter more complex wind speed and direction variations. We assess three models for power production that account for wind speed and direction shear. Two are based on actuator disc representations, and the third is a blade element representation. We also evaluate the predictions from a standard power curve model that has no knowledge of wind shear. The predictions from each model, driven by wind profile measurements from a profiling LiDAR, are compared to concurrent power measurements from an adjacent utility‐scale wind turbine. In the field measurements of the utility‐scale turbine, discrete combinations of speed and direction shear induce changes in power production of −19% to +34% relative to the turbine power curve for a given hub height wind speed. Positive speed shear generally corresponds to over‐performance and increasing magnitudes of direction shear to greater under‐performance, relative to the power curve. Overall, the blade element model produces both higher correlation and lower error relative to the other models, but its quantitative accuracy depends on induction and controller sub‐models. To further assess the influence of complex, non‐monotonic wind profiles, we also drive the models with best‐fit power law wind speed profiles and linear wind direction profiles. These idealized inputs produce qualitative and quantitative differences in power predictions from each model, demonstrating that time‐varying, non‐monotonic wind shear affects wind power production.

Energy & Fuels↗

DOE OSTI2019

A computational model for nanosecond pulse laser-plasma interactions

A multi-physics numerical model for laser-induced optical breakdown and laser-plasma interaction in a non-equilibrium gas is presented, accounting for: production of priming electrons via multi-photon ionization, energy absorption, cascade ionization, induced hydrodynamic response, and shock formation and propagation. The gas is governed by the Navier-Stokes equations, with non-equilibrium effects taken into account by means of a two-temperature model. The space-time dependence of the laser beam is modeled with a flux-tube formulation for the Radiative Transfer Equation. The flow governing equations are discretized in space using a second-order finite volume method. The semi-discrete equations are marched in time using an implicit-explicit (IMEX) dual time-stepping strategy, where diffusion and chemistry are solved implicitly, whereas convection is explicit. Application to a 20 ns long 50 mJ pulse laser-induced breakdown in quiescent O 2 shows the advantages of this temporal discretization during and just after the laser pulse, while a less-expensive symmetric Strang splitting (with implicit chemistry) is sufficient for the post-breakdown gas dynamics after ≃ 0.1 μs. The integrated model is shown to reproduce key features of corresponding experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

A comparison of model validation approaches for echo state networks using climate model replicates

As global temperatures continue to rise, climate mitigation strategies such as stratospheric aerosol injections (SAI) are increasingly discussed, but the downstream effects of these strategies are not well understood. As such, there is interest in developing statistical methods to quantify the evolution of climate variable relationships during the time period surrounding an SAI. Feature importance applied to echo state network (ESN) models has been proposed as a way to understand the effects of SAI using a data-driven model. This approach depends on the ESN fitting the data well. If not, the feature importance may place importance on features that are not representative of the underlying relationships. Typically, time series prediction models such as ESNs are assessed using out-of-sample performance metrics that divide the times series into separate training and testing sets. However, this model assessment approach is geared towards forecasting applications and not scenarios such as the motivating SAI example where the objective is using a data driven model to capture variable relationships. Here, in this paper, we demonstrate a novel use of climate model replicates to investigate the applicability of the commonly used repeated hold-out model assessment approach for the SAI application. Simulations of an SAI are generated using a simplified climate model, and different initialization conditions are used to provide independent training and testing sets containing the same SAI event. The climate model replicates enable out-of-sample measures of model performance, which are compared to the single time series hold-out validation approach. For our case study, it is found that the repeated hold-out sample performance is comparable, but conservative, to the replicate out-of-sample performance when the training set contains enough time after the aerosol injection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Inferring Plant Acclimation and Improving Model Generalizability With Differentiable Physics‐Informed Machine Learning of Photosynthesis

Net photosynthesis (A N ) is a key component of the global carbon cycle influencing climate feedback over decadal scales. Although plant acclimation to environmental changes can modify A N , traditional vegetation models in Earth system models (ESMs) often rely on plant functional type (PFT)-specific parameterizations or simplified acclimation assumptions limiting generalizability across time, space, and PFTs. In this study, we developed a differentiable photosynthesis model to learn the environmental dependencies of V c,max25 (maximum carboxylation rate at 25°C, representing photosynthetic capacity), as this genre of hybrid physics-informed machine learning can seamlessly train neural networks and process-based equations together. Compared to PFT-specific parameterization of V c,max25 , learning the environment dependencies of key photosynthetic parameters improved model spatiotemporal generalizability. Applying environmental acclimation to V c,max25 led to substantial variations in global mean A N indicating the need to address acclimation in ESMs. The model effectively captured multivariate observations (V c,max25 , A N , and stomatal conductance (g s )) simultaneously with multivariate constraints, improving generalization across space and PFTs. It also learned sensible acclimation relationships of V c,max25 to different environmental conditions. The model explained more than 54%, 57%, and 62% of the variance of A N , g s , and V c,max25 , respectively, presenting a first global-scale spatial test benchmark of A N and g s . These results highlight the potential for differentiable modeling to enhance process-based modules in ESMs and effectively leverage information from large, multivariate data sets.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1986

Dynamically supported geoid highs over hotspots: Observation and theory

Hotspots are associated with long wavelength geoid highs, an association that is even stronger when the geoid highs associated with subduction zones are removed. These associations are quantified by expanding the hotspot distribution in spherical harmonics and calculating correlation coefficients as a function of harmonic degree. The hotspot distribution spectrum is essentially white, with peaks at degrees 2 and 6. It is correlated positively with the slab residual geoid for degrees 2 to 6, with low seismic velocity in the lower mantle at degree 2, and with low seismic velocity in the upper mantle at degree 6. A variety of fluid mechanical models were tested for hotspots, including lithospheric delamination and hot plumes, by calculating their predicted dynamic geoid responses and comparing them to the observations. These models include the effects of temperature dependent rheology. The preferred hotspot model, based on observations of the geoid and seismic tomography, has plumes preferentially occurring in regions of large scale background temperature highs in a mantle with substantial viscosity increase with depth, although other models are possible.

Richards, M. A.↗

NASA NTRS1988

Dynamically supported geoid highs over hotspots - Observation and theory

Richards, Mark A.↗

NASA NTRS1991

Diurnal variations on a plasmaspheric flux tube - Light ion flows and F region temperature enhancements

The paper concentrates on the diurnal variations on a plasmaspheric flux tube modeled using a time-dependent multispecies one-stream interhemispheric model for plasma flows. The model takes into account the effects of ionization, charge exchange, recombination, collisions, heat conduction, and allows for external heat sources. The simulation is done for June solstice conditions during solar minimum. Focus is placed on the presence of large downward H(+) velocities at about 320-km altitude in the winter (southern) hemisphere, in early morning when the summer hemisphere is sunlit but the winter hemisphere is dark. In addition, an upward H(+) flux is seen in the Southern Hemisphere at altitudes above 2000 km when the sun rises in the northern end.

Guiter, S. M.↗

NASA NTRS2021

Normalization Method and Application for MODIS TEB Assessments using Earth Scene Measurements

Selected Earth targets are commonly used for satellite sensor calibration assessments (e.g. sensor stability and inter-comparisons). Moreover, typical scenes used for the calibration assessment of the thermal emissive bands (TEBs) includeDome Concordia (Dome-C), ocean, desert, and deep convective clouds (DCC). Reference data used for these calibration assessments can come from another band, another instrument, or ground measurements. The Dome-C site, covered with uniformly-distributed permanent snow, is normally used for the assessment of the TEBsat cold temperatures. Furthermore, ocean and desert measurements prove useful for scenes with higher temperatures. The DCC, one of the most consistent and coldest targets, can be used for the TEBs calibration and product stability assessments. MODIS band 31 (~ 11 m) can be used as a reference for these scenes. However, measurements over these scenes have seasonal variations, and the DCC brightness temperatures (BTs) have asymmetrical distributions. These features can introduce additional uncertainty to the stability assessments. A normalization method is applied by using an empirical model to derive reference-dependent BTs. Using the developed empirical model, measurements can be normalized to a reference BT in order to enhance the calibration assessment’s accuracy. This method is evaluated using all four scene types (i.e. ocean, desert, snow (Dome-C), and DCC) and applied to all the Terra and Aqua MODIS TEBs. Stability assessments over the instruments’ entire data records are presented and discussed. The technique can be applied in future efforts to support MODIS TEBs calibration assessments.

MODIS TEB↗

DOE OSTI2024

Modeling hydrodynamic and biomass pyrolysis effects of recycled product gases in a bubbling fluidized bed reactor

Fast pyrolysis of biomass in a fluidized bed reactor is typically conducted in a nitrogen gas environment. Recycling product gas can improve the economics of operating such a system by reducing reliance on pure process streams, but much less is known about how recycling pyrolysis product gas may affect fluidization behavior and pyrolysis kinetics. Therefore, gas effects in a fluidized bed biomass pyrolysis reactor were investigated using engineering correlations, low-order models, and CFD simulations for N 2 , H 2 , CO, CO 2 , and CH 4 carrier gas mixtures. Here, our findings reveal viscosity of a gas mixture can be significantly underestimated depending on the model and correlation. Furthermore, fluidization characteristics such as U mf and gas-solid convective heat transfer can be greatly affected by the gas properties. By utilizing H 2 as the fluidizing gas (instead of N 2 ), while maintaining a constant fluidization ratio (U s /U mf ), the bio-oil yields can be increased ~5%. This is due to the lower density H 2 producing similar hydrodynamics as N 2 at higher gas flow rates. These higher flow rates result in shorter gas residence times, and as a result, less secondary reactions that convert bio-oil to light gases and char. Model results also suggest that bio-oil yield is not significantly affected by the type of carrier gas used, with bio-oil yield varying by ~2% across different gas mixtures while maintaining constant flow rate. In conclusion, this indicates that recycled pyrolytic gas can be used as the carrier gas for biomass pyrolysis.

09 BIOMASS FUELS↗

DOE OSTI2021

Midwest US Croplands Determine Model Divergence in North American Carbon Fluxes

Large uncertainties in North American terrestrial carbon fluxes hinder regional climate projections. Terrestrial biosphere models (TBMs), the essential tools for understanding continental-scale carbon cycle, diverge on whether temperate forests or croplands dominate carbon uptake in North America. Evidence from novel photosynthetic proxies, such as those based on chlorophyll fluorescence, has cast doubt on the “weak cropland, strong forest” carbon uptake patterns simulated by most TBMs. However, no systematic evaluation of TBMs has yet been attempted to pin down space-time patterns that are most consistent with regional CO 2 observational constraints. Here, we leverage atmospheric CO 2 observations and satellite-observed photosynthetic proxies to understand emergent space-time patterns in North American carbon fluxes from a large suite of TBMs and data-driven models. To do so, we evaluate how well the atmospheric signals resulting from carbon flux estimates reproduce the space-time variability in atmospheric CO 2 , as is observed by a network of continuous-monitoring towers over North America. Models with gross or net carbon fluxes that are consistent with the observed CO 2 variability share a salient feature of growing-season carbon uptake in Midwest US croplands. Conversely, the remaining models place most growing-season uptake in boreal or temperate forests. Differences in model explanatory power depend mainly on the simulated annual cycles of cropland uptake—especially, the timing of peak uptake—rather than the distribution of annual mean fluxes across biomes. Our results suggest that improved model representation of cropland phenology is crucial to robust, policy-relevant estimation of North American carbon exchange.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

An Accelerated Approach for Computationally Efficient Evaluation of Deflagration Time During Abnormal Thermal Events

The challenges of modeling abnormal thermal events for explosives of interest to LLNL can be simplified by an accelerated approach to calculate Prout-Tompkins (P-T) parameters describing autocatalytic deflagration. Rather than depending on detailed modeling in multiphysics codes that include chemical reactivity (e.g. ALE3D), the accelerated approach can calculate P-T parameters based solely on experimental time of deflagration measurements for the explosive of interest. We compare deflagration time for five explosives with previously known P-T parameters at conditions typical of abnormal thermal events and demonstrate that the accelerated approach produces deflagration predictions with a maximum error of 3% and an average error of 1.7%. While the accelerated approach may not be applicable to all experimental conditions, it holds promise of rapid derivation of P-T parameters for accurate modeling of abnormal thermal events of interest to LLNL.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Performance of SK-Gd’s Upgraded Real-time Supernova Monitoring System

Among multimessenger observations of the next Galactic core-collapse supernova, Super-Kamiokande (SK) plays a critical role in detecting the emitted supernova neutrinos, determining the direction to the supernova (SN), and notifying the astronomical community of these observations in advance of the optical signal. In 2022, SK has increased the gadolinium dissolved in its water target (SK-Gd) and has achieved a Gd concentration of 0.033%, resulting in enhanced neutron detection capability, which in turn enables more accurate determination of the supernova direction. Accordingly, SK-Gd’s real-time supernova monitoring system has been upgraded. SK_SN Notice, a warning system that works together with this monitoring system, was released on 2021 December 13, and is available through GCN Notices. When the monitoring system detects an SN-like burst of events, SK_SN Notice will automatically distribute an alarm with the reconstructed direction to the supernova candidate within a few minutes. In this paper, we present a systematic study of SK-Gd’s response to a simulated Galactic SN. Assuming a supernova situated at 10 kpc, neutrino fluxes from six supernova models are used to characterize SK-Gd’s pointing accuracy using the same tools as the online monitoring system. The pointing accuracy is found to vary from 3° to 7° depending on the models. However, if the supernova is closer than 10 kpc, SK_SN Notice can issue an alarm with three-degree accuracy, which will benefit follow-up observations by optical telescopes with large fields of view.

Core-collapse supernovae↗

NASA NTRS1978

Pilot-optimal augmentation synthesis

An augmentation synthesis method usable in the absence of quantitative handling qualities specifications, and yet explicitly including design objectives based on pilot-rating concepts, is presented. The algorithm involves the unique approach of simultaneously solving for the stability augmentation system (SAS) gains, pilot equalization and pilot rating prediction via optimal control techniques. Simultaneous solution is required in this case since the pilot model (gains, etc.) depends upon the augmented plant dynamics, and the augmentation is obviously not a priori known. Another special feature is the use of the pilot's objective function (from which the pilot model evolves) to design the SAS.

Schmidt, D. K.↗

NASA NTRS2025

Modeling and Simulation Credibility Assessments of Musculoskeletal Computational Models for Simulating Astronaut Injuries Due to a Poor Spacesuit Fit

The musculoskeletal (MS) system of astronauts is subject to physiological changes, potentially leading to injuries due to the exposure to different gravitational environments experienced during spaceflight. These injuries can occur while an astronaut is performing an Extravehicular Activity (EVA) in space, on lunar or planetary surfaces or while wearing a spacesuit during terrestrial training for an EVA. The OpenSim MS modeling software can assess EVA induced MS injury mechanisms such as muscle strains, ligament injuries and joint injuries. One area of concern, since there are only a few different spacesuit sizes with limited adjustability, is the possibility of a poorly fitting spacesuit. This can cause unnatural joint motions and torques resulting in various MS injuries. A credibility assessment of the OpenSim modeling and simulation procedures is performed per NASA-STD-7009A to provide information on the credibility of the model’s use in simulating EVA related injury mechanisms. The credibility assessment evaluated various OpenSim models against the following eight credibility factors: data pedigree, input pedigree, code verification, solution verification, conceptual validation, referent validation, results uncertainty and results robustness (sensitivity). The models evaluated for EVA injuries will require additional credibility factor analysis and upgrades to the model features, such as adding ligaments to a whole-body model, to reliably predict and analyze the EVA injuries expected to occur due to a poor spacesuit fit. The degree of elevation strategy required to increase the credibility assessment scores will depend on the model complexity and the injury mechanism.

Christopher A. Gallo↗