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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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NASA NTRS2013

Estimating the Properties of Hard X-Ray Solar Flares by Constraining Model Parameters

We wish to better constrain the properties of solar flares by exploring how parameterized models of solar flares interact with uncertainty estimation methods. We compare four different methods of calculating uncertainty estimates in fitting parameterized models to Ramaty High Energy Solar Spectroscopic Imager X-ray spectra, considering only statistical sources of error. Three of the four methods are based on estimating the scale-size of the minimum in a hypersurface formed by the weighted sum of the squares of the differences between the model fit and the data as a function of the fit parameters, and are implemented as commonly practiced. The fourth method is also based on the difference between the data and the model, but instead uses Bayesian data analysis and Markov chain Monte Carlo (MCMC) techniques to calculate an uncertainty estimate. Two flare spectra are modeled: one from the Geostationary Operational Environmental Satellite X1.3 class flare of 2005 January 19, and the other from the X4.8 flare of 2002 July 23.We find that the four methods give approximately the same uncertainty estimates for the 2005 January 19 spectral fit parameters, but lead to very different uncertainty estimates for the 2002 July 23 spectral fit. This is because each method implements different analyses of the hypersurface, yielding method-dependent results that can differ greatly depending on the shape of the hypersurface. The hypersurface arising from the 2005 January 19 analysis is consistent with a normal distribution; therefore, the assumptions behind the three non- Bayesian uncertainty estimation methods are satisfied and similar estimates are found. The 2002 July 23 analysis shows that the hypersurface is not consistent with a normal distribution, indicating that the assumptions behind the three non-Bayesian uncertainty estimation methods are not satisfied, leading to differing estimates of the uncertainty. We find that the shape of the hypersurface is crucial in understanding the output from each uncertainty estimation technique, and that a crucial factor determining the shape of hypersurface is the location of the low-energy cutoff relative to energies where the thermal emission dominates. The Bayesian/MCMC approach also allows us to provide detailed information on probable values of the low-energy cutoff, Ec, a crucial parameter in defining the energy content of the flare-accelerated electrons. We show that for the 2002 July 23 flare data, there is a 95% probability that Ec lies below approximately 40 keV, and a 68% probability that it lies in the range 7-36 keV. Further, the low-energy cutoff is more likely to be in the range 25-35 keV than in any other 10 keV wide energy range. The low-energy cutoff for the 2005 January 19 flare is more tightly constrained to 107 +/- 4 keV with 68% probability.

X-rays↗
DOE OSTI2013

ESTIMATING THE PROPERTIES OF HARD X-RAY SOLAR FLARES BY CONSTRAINING MODEL PARAMETERS

We wish to better constrain the properties of solar flares by exploring how parameterized models of solar flares interact with uncertainty estimation methods. We compare four different methods of calculating uncertainty estimates in fitting parameterized models to Ramaty High Energy Solar Spectroscopic Imager X-ray spectra, considering only statistical sources of error. Three of the four methods are based on estimating the scale-size of the minimum in a hypersurface formed by the weighted sum of the squares of the differences between the model fit and the data as a function of the fit parameters, and are implemented as commonly practiced. The fourth method is also based on the difference between the data and the model, but instead uses Bayesian data analysis and Markov chain Monte Carlo (MCMC) techniques to calculate an uncertainty estimate. Two flare spectra are modeled: one from the Geostationary Operational Environmental Satellite X1.3 class flare of 2005 January 19, and the other from the X4.8 flare of 2002 July 23. We find that the four methods give approximately the same uncertainty estimates for the 2005 January 19 spectral fit parameters, but lead to very different uncertainty estimates for the 2002 July 23 spectral fit. This is because each method implements different analyses of the hypersurface, yielding method-dependent results that can differ greatly depending on the shape of the hypersurface. The hypersurface arising from the 2005 January 19 analysis is consistent with a normal distribution; therefore, the assumptions behind the three non-Bayesian uncertainty estimation methods are satisfied and similar estimates are found. The 2002 July 23 analysis shows that the hypersurface is not consistent with a normal distribution, indicating that the assumptions behind the three non-Bayesian uncertainty estimation methods are not satisfied, leading to differing estimates of the uncertainty. We find that the shape of the hypersurface is crucial in understanding the output from each uncertainty estimation technique, and that a crucial factor determining the shape of hypersurface is the location of the low-energy cutoff relative to energies where the thermal emission dominates. The Bayesian/MCMC approach also allows us to provide detailed information on probable values of the low-energy cutoff, E{sub c} , a crucial parameter in defining the energy content of the flare-accelerated electrons. We show that for the 2002 July 23 flare data, there is a 95% probability that E{sub c} lies below approximately 40 keV, and a 68% probability that it lies in the range 7-36 keV. Further, the low-energy cutoff is more likely to be in the range 25-35 keV than in any other 10 keV wide energy range. The low-energy cutoff for the 2005 January 19 flare is more tightly constrained to 107 {+-} 4 keV with 68% probability. Using the Bayesian/MCMC approach, we also estimate for the first time probability density functions for the total number of flare-accelerated electrons and the energy they carry for each flare studied. For the 2002 July 23 event, these probability density functions are asymmetric with long tails orders of magnitude higher than the most probable value, caused by the poorly constrained value of the low-energy cutoff. The most probable electron power is estimated at 10{sup 28.1} erg s{sup -1}, with a 68% credible interval estimated at 10{sup 28.1}-10{sup 29.0} erg s{sup -1}, and a 95% credible interval estimated at 10{sup 28.0}-10{sup 30.2} erg s{sup -1}. For the 2005 January 19 flare spectrum, the probability density functions for the total number of flare-accelerated electrons and their energy are much more symmetric and narrow: the most probable electron power is estimated at 10{sup 27.66{+-}0.01} erg s{sup -1} (68% credible intervals). However, in this case the uncertainty due to systematic sources of error is estimated to dominate the uncertainty due to statistical sources of error.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Local spin dynamics at low temperature in the slowly relaxing molecular chain [Dy(hfac)3(NIT(C6H4OPh))]: A μ{sup +} spin relaxation study

The spin dynamics of the molecular magnetic chain [Dy(hfac){sub 3}(NIT(C{sub 6}H{sub 4}OPh))] were investigated by means of the Muon Spin Relaxation (μ{sup +}SR) technique. This system consists of a magnetic lattice of alternating Dy(III) ions and radical spins, and exhibits single-chain-magnet behavior. The magnetic properties of [Dy(hfac){sub 3}(NIT(C{sub 6}H{sub 4}OPh))] have been studied by measuring the magnetization vs. temperature at different applied magnetic fields (H = 5, 3500, and 16500 Oe) and by performing μ{sup +}SR experiments vs. temperature in zero field and in a longitudinal applied magnetic field H = 3500 Oe. The muon asymmetry P(t) was fitted by the sum of three components, two stretched-exponential decays with fast and intermediate relaxation times, and a third slow exponential decay. The temperature dependence of the spin dynamics has been determined by analyzing the muon longitudinal relaxation rate λ{sub interm}(T), associated with the intermediate relaxing component. The experimental λ{sub interm}(T) data were fitted with a corrected phenomenological Bloembergen-Purcell-Pound law by using a distribution of thermally activated correlation times, which average to τ = τ{sub 0} exp(Δ/k{sub B}T), corresponding to a distribution of energy barriers Δ. The correlation times can be associated with the spin freezing that occurs when the system condenses in the ground state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Toward particle-resolved accuracy in Euler–Lagrange simulations of multiphase flow using machine learning and pairwise interaction extended point-particle (PIEP) approximation

This study presents two different machine learning approaches for the modeling of hydrodynamic force on particles in a particle-laden multiphase flow. Results from particle-resolved direct numerical simulations (PR-DNS) of flow over a random array of stationary particles for eight combinations of particle Reynolds number (Re) and volume fraction (φ) are used in the development of the models. The first approach follows a two-step process. In the first flow prediction step, the perturbation flow due to a particle is obtained as an axisymmetric superposable wake using linear regression. In the second force prediction step, the force on a particle is evaluated in terms of the perturbation flow induced by all its neighbors using the generalized Faxén form of the force expression. In the second approach, the force data on all the particles from the PR-DNS simulations are used to develop an artificial neural network (ANN) model for direct prediction of force on a particle. Due to the unavoidable limitation on the number of fully resolved particles in the PR-DNS simulations, direct force prediction with the ANN model tends to over-fit the data and performs poorly in the prediction of test data. In contrast, due to the millions of grid points used in the PR-DNS simulations, accurate flow prediction is possible, which then allows accurate prediction of particle force. This hybridization of multiphase physics and machine learning is particularly important, since it blends the strength of each, and the resulting pairwise interaction extended point-particle model cannot be developed by either physics or machine learning alone.

42 ENGINEERING↗
DOE OSTI2014

SU-C-9A-04: Alternative Analytic Solution to the Paralyzable Detector Model to Calculate Deadtime and Deadtime Loss

Purpose: Some common methods to solve for deadtime are (1) dual-source method, which assumes two equal activities; (2) model fitting, which requires multiple acquisitions as source decays; and (3) lossless model, which assumes no deadtime loss at low count rates. We propose a new analytic alternative solution to calculate deadtime for paralyzable gamma camera. Methods: Deadtime T can be calculated analytically from two distinct observed count rates M1 and M2 when the ratio of the true count rates alpha=N2/N1 is known. Alpha can be measured as a ratio of two measured activities using dose calibrators or via radioactive decay. Knowledge of alpha creates a system with 2 equations and 2 unknowns, i.e., T and N1. To verify the validity of the proposed method, projections of a non-uniform phantom (4GBq 99mTc) were acquired in using Siemens SymbiaS multiple times over 48 hours. Each projection has >100kcts. The deadtime for each projection was calculated by fitting the data to a paralyzable model and also by using the proposed 2-acquisition method. The two estimates of deadtime were compared using the Bland-Altmann method. In addition, the dependency of uncertainty in T on uncertainty in alpha was investigated for several imaging conditions. Results: The results strongly suggest that the 2-acquisition method is equivalent to the fitting method. The Bland-Altman analysis yielded mean difference in deadtime estimate of ∼0.076us (95%CI: -0.049us, 0.103us) between the 2-acquisition and model fitting methods. The 95% limits of agreement were calculated to be -0.104 to 0.256us. The uncertainty in deadtime calculated using the proposed method is highly dependent on the uncertainty in the ratio alpha. Conclusion: The 2-acquisition method was found to be equivalent to the parameter fitting method. The proposed method offers a simpler and more practical way to analytically solve for a paralyzable detector deadtime, especially during physics testing.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

A divergence-free parametrization for dynamical dark energy

We introduce a new parametrization for the dark energy, led by the same idea to the linear expansion of the equation of state in scale factor a and in redshift z, which diverges neither in the past nor future and contains the same number of degrees of freedom with the former two. We present constraints of the cosmological parameters using the most updated baryon acoustic oscillation (BAO) measurements along with cosmic microwave background (CMB) data and a recent reanalysis of Type Ia supernova (SN) data. This new parametrization allowed us to carry out successive observational analyses by decreasing its degrees of freedom systematically until ending up with a dynamical dark energy model that has the same number of parameters with ΛCDM . We found that the dark energy source with a dynamical equation of state parameter equal −2/3 at the early universe and −1 today fits the data slightly better than Λ.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Improved Search for ν̄ μ →ν̄ e Oscillations in the MiniBooNE Experiment

The MiniBooNE experiment at Fermilab reports results from an analysis of ν¯ e appearance data from 11.27×10²⁰ protons on target in the antineutrino mode, an increase of approximately a factor of 2 over the previously reported results. An event excess of 78.4±28.5 events (2.8σ) is observed in the energy range 200 QE ν <1250 MeV. If interpreted in a two-neutrino oscillation model, ν¯ μ →ν¯ e , the best oscillation fit to the excess has a probability of 66% while the background-only fit has a χ² probability of 0.5% relative to the best fit. The data are consistent with antineutrino oscillations in the 0.01<Δm²<1.0 eV² range and have some overlap with the evidence for antineutrino oscillations from the Liquid Scintillator Neutrino Detector. All of the major backgrounds are constrained by in situ event measurements so nonoscillation explanations would need to invoke new anomalous background processes. The neutrino mode running also shows an excess at low energy of 162.0±47.8 events (3.4σ) but the energy distribution of the excess is marginally compatible with a simple two neutrino oscillation formalism. Expanded models with several sterile neutrinos can reduce the incompatibility by allowing for CP violating effects between neutrino and antineutrino oscillations.

Aguilar-Arevalo, A. A.↗
NASA NTRS1980

Time-average fluxes of heavy ions at the geostationary orbit

Measurements of average proton, helium, carbon, and oxygen fluxes at 6.6 earth radii are reported. The data represent averages obtained on ATS 6 between June 15 and Oct. 3, 1974. The energy range covered was 0.36-1.1 MeV for protons and approximately 1-4 MeV for the heavier ions. The results indicate that above about 1 MeV the heavier ion fluxes dominate over the proton flux on the energy/ion scale. Using two different spectral dependencies to fit the data, the carbon to oxygen concentration ratio for energies above 1 MeV was found to be 0.43 for the power law spectrum and 0.44 for the exponential spectrum. Thus in either case the abundance ratio is consistent with the solar origin of the particles. Similarly, the helium to oxygen concentration ratio is found to be 0.17 for the power law spectrum and 0.28 for the exponential spectrum. This is inconsistent with the solar wind ratio, which is about 10. The results quoted above are based on a very small portion of the distribution function above 1 MeV.

Konradi, A.↗
DOE OSTI2015

Does the presence of planets affect the frequency and properties of extrasolar Kuiper belts? Results from the HErschel DEBRIS and DUNES surveys

The study of the planet–debris disk connection can shed light on the formation and evolution of planetary systems and may help “predict” the presence of planets around stars with certain disk characteristics. In preliminary analyses of subsamples of the Herschel DEBRIS and DUNES surveys, Wyatt et al. and Marshall et al. identified a tentative correlation between debris and the presence of low-mass planets. Here we use the cleanest possible sample out of these Herschel surveys to assess the presence of such a correlation, discarding stars without known ages, with ages <1 Gyr, and with binary companions <100 AU to rule out possible correlations due to effects other than planet presence. In our resulting subsample of 204 FGK stars, we do not find evidence that debris disks are more common or more dusty around stars harboring high-mass or low-mass planets compared to a control sample without identified planets. There is no evidence either that the characteristic dust temperature of the debris disks around planet-bearing stars is any different from that in debris disks without identified planets, nor that debris disks are more or less common (or more or less dusty) around stars harboring multiple planets compared to single-planet systems. Diverse dynamical histories may account for the lack of correlations. The data show a correlation between the presence of high-mass planets and stellar metallicity, but no correlation between the presence of low-mass planets or debris and stellar metallicity. Comparing the observed cumulative distribution of fractional luminosity to those expected from a Gaussian distribution in logarithmic scale, we find that a distribution centered on the solar system’s value fits the data well, while one centered at 10 times this value can be rejected. This is of interest in the context of future terrestrial planet detection and characterization because it indicates that there are good prospects for finding a large number of debris disk systems (i.e., with evidence of harboring planetesimals, the building blocks of planets) with exozodiacal emission low enough to be appropriate targets for an ATLAST-type mission to search for biosignatures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Turbulent Transport by Diffusive Stratified Shear Flows: From Local to Global Models. I. Numerical Simulations of a Stratified Plane Couette Flow

Shear-induced turbulence could play a significant role in mixing momentum and chemical species in stellar radiation zones, as discussed by Zahn. In this paper we analyze the results of direct numerical simulations of stratified plane Couette flows, in the limit of rapid thermal diffusion, to measure the turbulent viscosity and the turbulent diffusivity of a passive tracer as a function of the local shear and the local stratification. We find that the stability criterion proposed by Zahn, namely that the product of the gradient Richardson number and the Prandtl number must be smaller than a critical values (JPr){sub c} for instability, adequately accounts for the transition to turbulence in the flow, with (JPr){sub c}≃0.007. This result recovers and confirms the prior findings of Prat et al. Zahn’s model for the turbulent diffusivity and viscosity, namely that the mixing coefficient should be proportional to the ratio of the thermal diffusivity to the gradient Richardson number, does not satisfactorily match our numerical data. It fails (as expected) in the limit of large stratification where the Richardson number exceeds the aforementioned threshold for instability, but it also fails in the limit of low stratification where the turbulent eddy scale becomes limited by the computational domain size. We propose a revised model for turbulent mixing by diffusive stratified shear instabilities that properly accounts for both limits, fits our data satisfactorily, and recovers Zahn’s model in the limit of large Reynolds numbers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

THE NANOGRAV NINE-YEAR DATA SET: OBSERVATIONS, ARRIVAL TIME MEASUREMENTS, AND ANALYSIS OF 37 MILLISECOND PULSARS

We present high-precision timing observations spanning up to nine years for 37 millisecond pulsars monitored with the Green Bank and Arecibo radio telescopes as part of the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) project. We describe the observational and instrumental setups used to collect the data, and methodology applied for calculating pulse times of arrival; these include novel methods for measuring instrumental offsets and characterizing low signal-to-noise ratio timing results. The time of arrival data are fit to a physical timing model for each source, including terms that characterize time-variable dispersion measure and frequency-dependent pulse shape evolution. In conjunction with the timing model fit, we have performed a Bayesian analysis of a parameterized timing noise model for each source, and detect evidence for excess low-frequency, or “red,” timing noise in 10 of the pulsars. For 5 of these cases this is likely due to interstellar medium propagation effects rather than intrisic spin variations. Subsequent papers in this series will present further analysis of this data set aimed at detecting or limiting the presence of nanohertz-frequency gravitational wave signals.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1981

Application of HCMM data to regional geologic analysis for mineral and energy resource evaluation

Experimentation with several potentially promising techniques led to the selection of a fairly simple scheme for registration of data from the HCMM using an affine transformation. A method based solely on remote sensing was developed to estimate those meteorological effects which are required for thermal inertia mapping. It assumes that the atmospheric fluxes are spatially invariant and that the solar, sky and sensible heat fluxes can be approximated by a simple mathematical form. Coefficients are determined from least squares method by fitting observational data to the thermal model.

Watson, K.↗
NASA NTRS1998

ISO Key Project: Exploring the full range of QUASAR/AGN properties

The PIA (PHOT Interactive Analysis) software was upgraded as new releases were made available by VILSPA. We have continued to analyze our data but, given the large number of still outstanding problems with the calibration and analysis (listed below), we remain unable to move forward on our scientific program. We have concentrated on observations with long (256 sec) exposure times to avoid the most extreme detector responsivity drift problems which occur with a change in observed flux level, ie. as one begins to observe a new target. There remain a significant number of problems with analyzing these data including: (1) the default calibration source (FCS) observations early in the mission were too short and affected by strong detector responsivity drifts; (2) the calibration of the FCS sources is not yet well-understood, particularly for chopped observations (which includes most of ours); (3) the detector responsivity drift is not well-understood and models are only now becoming available for fitting chopped data; (4) charged particle hits on the detector cause transient responsivity drifts which need to be corrected; (5) the "flat-field" calibration of the long-wavelength (array) detectors: C1OO, C200 leaves significant residual structure and so needs to be improved;(6) the vignetting correction, which affects detected flux levels in the array detectors, is not yet available; (7) the intra-filter calibrations are not yet available; and (8) the background above 60 microns has a significant gradient which results in spurious positive and negative "detections" in chopped observations. ISO Observation planning, conferences and talks, ground based observing and other grant related activities are also briefly discussed.

Wilkes, B.↗
NASA NTRS1989

Application of statistical distribution theory to launch-on-time for space construction logistic support

The ability to launch-on-time and to send payloads into space has progressed dramatically since the days of the earliest missile and space programs. Causes for delay during launch, i.e., unplanned 'holds', are attributable to several sources: weather, range activities, vehicle conditions, human performance, etc. Recent developments in space program, particularly the need for highly reliable logistic support of space construction and the subsequent planned operation of space stations, large unmanned space structures, lunar and Mars bases, and the necessity of providing 'guaranteed' commercial launches have placed increased emphasis on understanding and mastering every aspect of launch vehicle operations. The Center of Space Construction has acquired historical launch vehicle data and is applying these data to the analysis of space launch vehicle logistic support of space construction. This analysis will include development of a better understanding of launch-on-time capability and simulation of required support systems for vehicle assembly and launch which are necessary to support national space program construction schedules. In this paper, the author presents actual launch data on unscheduled 'hold' distributions of various launch vehicles. The data have been supplied by industrial associate companies of the Center for Space Construction. The paper seeks to determine suitable probability models which describe these historical data and that can be used for several purposes such as: inputs to broader simulations of launch vehicle logistic space construction support processes and the determination of which launch operations sources cause the majority of the unscheduled 'holds', and hence to suggest changes which might improve launch-on-time. In particular, the paper investigates the ability of a compound distribution probability model to fit actual data, versus alternative models, and recommends the most productive avenues for future statistical work.

Morgenthaler, George W.↗
DOE OSTI2015

Modeling CH 4 and CO 2 cycling using porewater stable isotopes in a thermokarst bog in Interior Alaska: results from three conceptual reaction networks

Quantifying rates of microbial carbon transformation in peatlands is essential for gaining mechanistic understanding of the factors that influence methane emissions from these systems, and for predicting how emissions will respond to climate change and other disturbances. In this study, we used porewater stable isotopes collected from both the edge and center of a thermokarst bog in Interior Alaska to estimate in situ microbial reaction rates. We expected that near the edge of the thaw feature, actively thawing permafrost and greater abundance of sedges would increase carbon, oxygen and nutrient availability, enabling faster microbial rates relative to the center of the thaw feature. We developed three different conceptual reaction networks that explained the temporal change in porewater CO2, CH4, δ13C-CO2 and δ13C-CH4. All three reaction-network models included methane production, methane oxidation and CO2 production, and two of the models included homoacetogenesis — a reaction not previously included in isotope-based porewater models. All three models fit the data equally well, but rates resulting from the models differed. Most notably, inclusion of homoacetogenesis altered the modeled pathways of methane production when the reaction was directly coupled to methanogenesis, and it decreased gross methane production rates by up to a factor of five when it remained decoupled from methanogenesis. The ability of all three conceptual reaction networks to successfully match the measured data indicate that this technique for estimating in-situ reaction rates requires other data and information from the site to confirm the considered set of microbial reactions. Despite these differences, all models indicated that, as expected, rates were greater at the edge than in the center of the thaw bog, that rates at the edge increased more during the growing season than did rates in the center, and that the ratio of acetoclastic to hydrogenotrophic methanogenesis was greater at the edge than in the center. In both locations, modeled rates (excluding methane oxidation) increased with depth. A puzzling outcome from the effort was that none of the models could fit the porewater dataset without generating “fugitive” carbon (i.e., methane or acetate generated by the models but not detected at the field site), indicating that either our conceptualization of the reactions occurring at the site remains incomplete or our site measurements are missing important carbon transformations and/or carbon fluxes. This model–data discrepancy will motivate and inform future research efforts focused on improving our understanding of carbon cycling in permafrost wetlands.

13CH4↗
DOE OSTI2018

Vacuum phase transition solves the H 0 tension

Taking the Planck cosmic microwave background data and the more direct Hubble constant measurement data as unaffected by systematic offsets, the values of the Hubble constant H 0 interpreted within the ΛCDM cosmological constant and cold dark matter cosmological model are in ~3.3σ tension. We show that the Parker vacuum metamorphosis (VM) model, physically motivated by quantum gravitational effects and with the same number of parameters as ΛCDM, can remove the H 0 tension and can give an improved fit to data (up to a mean Δχ 2 = -7.5). It also ameliorates tensions with weak lensing data and the high redshift Lyman alpha forest data. Considering Bayesian evidence, we found in the case of the Planck data set alone positive evidence for a VM model against a cosmological constant both in the six- and nine-parameter framework. When the R16 data set is also considered, we found a strong evidence for the VM model against a cosmological constant in nine-parameter space. Here we separately consider a scale-dependent scaling of the gravitational lensing amplitude, such as provided by modified gravity, neutrino mass, or cold dark energy, motivated by the somewhat different cosmological parameter estimates for low and high CMB multipoles. We find that no such scale dependence is preferred.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A preference for cold dark matter over Superfluid Dark Matter in local Milky Way data

There are many well-known correlations between dark matter and baryons that exist on galactic scales. These correlations can essentially be encompassed by a simple scaling relation between observed and baryonic accelerations, historically known as the Mass Discrepancy Acceleration Relation (MDAR). The existence of such a relation has prompted many theories that attempt to explain the correlations by invoking additional fundamental forces on baryons. The standard lore has been that a theory that reduces to the MDAR on galaxy scales but behaves like cold dark matter (CDM) on larger scales provides an excellent fit to data, since CDM is desirable on scales of clusters and above. However, this statement should be revised in light of recent results showing that a fundamental force that reproduces the MDAR is challenged by local Milky Way dynamics and rotation curve data between 5–18 kpc. In this study, we test this claim on the example of Superfluid Dark Matter. We find that a standard CDM model is preferred over a static superfluid profile assuming a steady-state Galactic disk and discuss the robustness of this conclusion to disequilibrium effects. This preference is due to the fact that the superfluid model over-predicts vertical accelerations, even while reproducing galactic rotation curves. Our results establish an important criterion that any dark matter model must satisfy within the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A data-driven approach to modeling cancer cell mechanics during microcirculatory transport

In order to understand the effect of cellular level features on the transport of circulating cancer cells in the microcirculation, there has been an increasing reliance on high-resolution in silico models. Accurate simulation of cancer cells flowing with blood cells requires resolving cellular-scale interactions in 3D, which is a significant computational undertaking warranting a cancer cell model that is both computationally efficient yet sufficiently complex to capture relevant behavior. Given that the characteristics of metastatic spread are known to depend on cancer type, it is crucial to account for mechanistic behavior representative of a specific cancer’s cells. To address this gap, in the present work we develop and validate a means by which an efficient and popular membrane model-based approach can be used to simulate deformable cancer cells and reproduce experimental data from specific cell lines. Here, cells are modeled using the immersed boundary method (IBM) within a lattice Boltzmann method (LBM) fluid solver, and the finite element method (FEM) is used to model cell membrane resistance to deformation. Through detailed comparisons with experiments, we (i) validate this model to represent cancer cells undergoing large deformation, (ii) outline a systematic approach to parameterize different cell lines to optimally fit experimental data over a range of deformations, and (iii) provide new insight into nucleated vs. non-nucleated cell models and their ability to match experiments. While many works have used the membrane-model based method employed here to model generic cancer cells, no quantitative comparisons with experiments exist in the literature for specific cell lines undergoing large deformation. Here, we describe a phenomenological, data-driven approach that can not only yield good agreement for large deformations, but explicitly detail how it can be used to represent different cancer cell lines. This model is readily incorporated into cell-resolved hemodynamic transport simulations, and thus offers significant potential to complement experiments towards providing new insights into various aspects of cancer progression.

59 BASIC BIOLOGICAL SCIENCES↗