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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Shear reflectivity compensation in full-waveform inversion using least-squares reverse-time migration

SUMMARY The computational cost of elastic-waveform inversion is too high for inverting PP reflections, while using acoustic full-waveform inversion (FWI) is inaccurate because it does not depend on the shear modulus/velocity/impedance that affects elastic PP wavefield amplitudes. To solve this problem, we develop a waveform inversion method that uses acoustic least-squares reverse-time migration (LSRTM) to compensate the shear reflectivity for acoustic FWI. Our method is based on the quasi-elastic-wave equation developed by Chapman et al. (2014). The quasi-elastic-wave equation uses a linearized acoustic-wave equation with shear modulus μ as a virtual source to correct the acoustic PP wavefield amplitudes toward elastic ones. Our waveform inversion method inverts for elastic parameters by minimizing the L2 norm of the difference between recorded and predicted PP reflections modelled using the quasi-elastic-wave equation. Numerical tests on synthetic and field data show that our method can properly handle the amplitudes of elastic PP reflections and provides an accurate estimate of the P- and S-wave velocities/impedances and, in some cases, the density. The method does not need the computationally expensive numerical solution to the elastic-wave equation. It also gives a better estimate of elastic parameters than a pure LSRTM method for elastic PP reflections.

Feng, Zongcai↗
DOE OSTI2021

Bottomonium suppression and elliptic flow using Heavy Quarkonium Quantum Dynamics

We introduce a framework called Heavy Quarkonium Quantum Dynamics (HQQD) which can be used to compute the dynamical suppression of heavy quarkonia propagating in the quark-gluon plasma using real-time in-medium quantum evolution. Using HQQD we compute large sets of real-time solutions to the Schrödinger equation using a realistic in-medium complex-valued potential. We sample 2 million quarkonia wave packet trajectories and evolve them through the QGP using HQQD to obtain their survival probabilities. The computation is performed using three different HQQD model parameter sets in order to estimate our systematic uncertainty. After taking into account final state feed down we compare our results to existing experimental data for the suppression and elliptic flow of bottomonium states and find that HQQD predictions are good agreement with available data for R AA as a function of N part and p T collected at \( \sqrt{s_{\mathrm{NN}}} \) = 5 . 02 TeV. In the case of v 2 for the various states, we find that the path-length dependence of ϒ(1 s ) suppression results in quite small v 2 for ϒ(1 s ). Our prediction for the integrated elliptic flow for ϒ(1 s ) in the 10 – 90% centrality class, which now includes an estimate of the systematic error, is v 2 [ϒ(1 s )] = 0 . 003 ± 0 . 0007 ± \( {}_{0.0013}^{0.0006} \) . We also find that, due to their increased suppression, excited bottomonium states have a larger elliptic flow. Based on this observation we make predictions for v 2 [ϒ(2 s )] and v 2 [ϒ(3 s )] as a function of centrality and transverse momentum.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

The utility of {sup 82}Rb PET for myocardial viability assessment: Comparison with perfusion-metabolism {sup 82}Rb-{sup 18}F-FDG PET

Background: {sup 82}Rb kinetics may distinguish scar from viable but dysfunctional (hibernating) myocardium. We sought to define the relationship between {sup 82}Rb kinetics and myocardial viability compared with conventional {sup 82}Rb and {sup 18}F-fluorodeoxyglucose (FDG) perfusion-metabolism PET imaging. Methods: Consecutive patients (N = 120) referred for evaluation of myocardial viability prior to revascularization and normal volunteers (N = 37) were reviewed. Dynamic {sup 82}Rb 3D PET data were acquired at rest. {sup 18}F-FDG 3D PET data were acquired after metabolic preparation using a standardized hyperinsulinemic-euglycemic clamp. {sup 82}Rb kinetic parameters K{sub 1}, k{sub 2}, and partition coefficient (KP) were estimated by compartmental modeling Results: Segmental {sup 82}Rb k{sub 2} and KP differed significantly between scarred and hibernating segments identified by Rb-FDG perfusion-metabolism (k{sub 2}, 0.42 ± 0.25 vs. 0.22 ± 0.09 min{sup −1}; P < .0001; KP, 1.33 ± 0.62 vs. 2.25 ± 0.98 ml/g; P < .0001). As compared to Rb-FDG analysis, segmental Rb KP had a c-index, sensitivity and specificity of 0.809, 76% and 84%, respectively, for distinguishing hibernating and scarred segments. Segmental k{sub 2} performed similarly, but with lower specificity (75%, P < .001) Conclusions: In this pilot study, {sup 82}Rb kinetic parameters k{sub 2} and KP, which are readily estimated using a compartmental model commonly used for myocardial blood flow, reliably differentiated hibernating myocardium and scar. Further study is necessary to evaluate their clinical utility for predicting benefit after revascularization. [French] French Abstract: Contexte: La cinétique du {sup 82}Rb pourrait être utilisée pour distinguer la fibrose myocardique des zones viables mais dysfonctionnelles (en hibernation). Dans cette étude, nous avons cherché à définir la relation entre la cinétique du {sup 82}Rb et la viabilité myocardique en comparant les images de perfusion et métabolisme myocardique utilisant le {sup 82}Rb et le {sup 18}F-fluorodésoxyglucose (FDG) Méthodes: les données obtenues chez 120 patients consécutifs (N = 120) référés pour évaluation de la viabilité du myocarde avant revascularisation et 37 volontaires considérés normaux (N = 37) ont été étudieés. Les données TEP 3D dynamiques {sup 82}Rb ont été acquises au repos. Les données TEP 3D au {sup 18}F-FDG ont été acquises après préparation métabolique utilisant une pince hyperinsulémique-euglycémique normalisée. Les paramètres k1, k2 et le coefficient de partage (KP) de la cinétique du {sup 82}R bont été évalues par modélisation compartimentale. Résultats: les paramètres k2 et KP de distribution du {sup 82}Rb se sont révélés significativement différent entre les zones tissulaires cicatricielles fibreuses et celles en hibernation identifiées par étude métabolique au FDG (k2, 0,42 ± 0,25 vs. 0,22 ± 0,09 min{sup −1}; P < 0,0001; KP, 1,33 ± 0,62 vs. 2,25 ± 0,98 ml/g; P < 0,0001). Par rapport aux données FDG, le paramètre KP du rubidium a révélé un indice de concordance de 0,809 et une sensibilité et spécificité de 76% et 84%, pour la distinction des segments en hibernation et cicatrisés. Les résultats du paramètre k2 se sont révélés similaires, mais avec une spécificité plus faible calculée à 75% (P < 0,001). Conclusions: Dans cette étude pilote, les paramètres cinétiques k2 et KP de perfusion myocardique au {sup 82}Rb, qui sont facilement estimés à l’aide d’un modèle compartimental couramment utilisé pour flux sanguin myocardique, ont permis de différencier de manière fiable le myocarde cicatricielle des zones myocardiques hibernantes. Une étude plus approfondie est souhaitable pour valider leur utilité clinique en revacularisation. [Spanish] Spanish Abstract: Antecedentes: La cinética con {sup 82}Rb puede distinguir las cicatrices miocárdicas del tejido viable pero disfuncional (hibernante). Buscamos definir la relación entre la cinética del {sup 82}Rb y la viabilidad miocárdica comparada con las imágenes convencionales de PET con {sup 82}Rb y {sup 18}F-flurodeoxyglucosa (FDG). Métodos: se evaluaron a Pacientes Consecutivos (N = 120) referidos para evaluación de viabilidad miocárdica previos a revascularización y voluntarios normales (N = 37). Los datos de PET 3D dinámico con {sup 82}Rb fueron adquiridos en reposo. Los datos de {sup 18}F-FDG 3D PET fueron adquiridos posterior a la preparación metabólica usando un clamp hiperinsulínico-euglucémico. Los patrones cinéticos K1, k2 y el coeficiente de partición (KP) fueron estimados por el modelo compartimental. Resultados: el k2 y KP del {sup 82}Rb permitueron distinguier el tejido cicatricial de los segmentos hibernados identificados por la vía perfusión metabolismo de Rb-FDG (k{sub 2}, 0.42 ± 0.25 vs. 0.22 ± 0.09 min-1; P < .0001; KP, 1.33 ± 0.62 vs. 2.25 ± 0.98 ml/g; P < .0001). En comparación con el análisis de Rb-FDG, el KP segmentario del Rb tuvo un índice-c, sensbilidad y especificidad de 0.809 76 y 84%, respectivamente, para distinguir segmentos hibernantes y cicatriciales. k2 Segmentario tuvo un desempeño similar pero con una menor especificidad (75%, P < .001). Conclusiones: En este estudio piloto, los parámetros cinéticos k2 y KP del {sup 82}Rb, los cuales son estimados usando un modelo compartimental usado comúnmente para flujo sanguíneo miocárdico, diferenciaron el miocardio hibernante del cicatricial. Se necesita estudiar más a fondo para evaluar la utilidad clínica para la predicción del beneficio posterior a la revascularización [Chinese] Chinese Abstract: 背景: 铷-82({sup 82}Rb)药代动力学可能区分梗死与功能受损但存活的心肌(冬眠心肌)。我们将探讨{sup 82}Rb药代动力学与存活心肌的关系,并与常规的{sup 82}Rb和{sup 18}F-氟脱氧葡萄糖(FDG)灌注-代谢PET显像进行比较。 方法: 连续纳入120名血运重建前评估存活心肌的患者和37名正常志愿者。获得静息{sup 82}Rb 3D-PET动态采集数据;采用标准化的高胰岛素 - 正葡萄糖钳夹试验得到{sup 18}F-FDG 3D PET代谢显像数据; 通过房室模型计算{sup 82}Rb动力学参数k{sub 1},k{sub 2}和分配系数(KP)。 结果: 以Rb-FDG灌注代谢显像鉴定疤痕心肌组和冬眠心肌组,两组的{sup 82}Rb节段性 k{sub 2}值和KP值有明显差异(k{sub 2}, 0.42 ± 0.25 vs 0.22 ± 0.09 min{sup −1}; P < .0001; KP, 1.33 ± 0.62 vs 2.25 ± 0.98 ml/g; P < .0001)。以Rb-FDG灌注代谢显像为诊断标准,{sup 82}Rb节段性 KP对疤痕和冬眠心肌鉴别效能的c指数,敏感性和特异性分别是0.809, 76%和84%。节段性k{sub 2}的鉴别效能与KP相似,但特异性较低(75%,P < .001)。 结论: 在本试验性研究中,通过常规用于{sup 82}Rb心肌血流量测定的房室模型计算出的{sup 82}Rb动力学参数k{sub 2}和KP,可以有效的区分冬眠心肌和瘢痕心肌。 但需要进一步的研究来评估其对预测血运重建是否获益的临床价值。.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Transient analysis of advancing contact angle measurements on polished rock surfaces

We report that contact angle measurements for gas-liquid-rock systems are important for modeling multi-phase flow and transport in the subsurface. These data are needed in applications such as the extraction of oil and gas resources, geologic sequestration of carbon dioxide, contaminant fate and transport, and aquifer recharge through the vadose zone. Contact angles are frequently measured with the sessile drop method. Previous research has largely ignored the dynamic behavior of sessile droplets on geologic materials. This study investigates the dynamic behavior of sessile water droplets on prepared rock surfaces in the presence of air. Droplet diameter and advancing contact angle were determined at 0.5 s intervals for ~90 s on flat polished disks of Burlington limestone, Crossville sandstone, Mancos shale, Sierra White granite, Vermilion Bay granite, and Westerly granite using a Krüss DSA 30 Drop Shape Analyzer. The droplet diameter and advancing contact angle data sets were nonlinearly regressed against time using two different two-parameter models. The median coefficients of determination for the fits were 0.85 and 0.96, respectively. The resulting parameter estimates were used to compute the apparent equilibrium contact angle, θ e , for each disk following droplet diameter stabilization. Estimates of θ e ranged from 37.2° for Mancos shale to 75.6° for Burlington limestone. Analysis of variance indicated statistically significant differences in θ e between the rock types at the 95% confidence level. The variability of θe on the polished rock surfaces, as quantified by the coefficient of variation (CV) for θ e , varied between ~3 and ~9%; there were no significant differences in CV between the rock types. Neutron radiography indicated changes droplet morphology over time were due to the spontaneous imbibition of water into the rock matrix. Finally, the transient analysis employed in this study permits a more meaningful estimate of the equilibrium contact angle for rocks than taking the initial value or averaging over time as is frequently done.

58 GEOSCIENCES↗
DOE OSTI2015

A longitudinal study of ventilation rates in California office buildings and self-reported occupant outcomes including respiratory illness absence

Limited evidence has associated lower ventilation rates (VRs) in offices with higher illness-related absence rates. We studied spaces in office buildings, selected without knowledge of their VRs, in three California climate zones. In each study space, real-time logging sensors measured carbon dioxide and thermal parameters for one year. Web-based surveys every three months collected data on occupants’ health outcomes. Using multivariate models, relationships were assessed between CO 2 concentrations, or VRs estimated from CO 2 , and adverse occupant outcomes including respiratory infections and illness absences. For all outcomes, positive associations were hypothesized with higher CO 2 levels (and negative associations with higher VRs). Low survey response limited sample size and study power. In the 16 study spaces, CO 2 concentrations were uniformly low over the year, and most estimated VRs ranged from twice to nine times the California office minimum VR standard (7 L/s or 15 cfm per person). Primary CO 2 and VR metrics had no statistically significant relationships with occupant outcomes. Within the observed range of uniformly low CO 2 and high VRs (mostly 16–42 L/s per person), little variation in contaminant concentrations would be expected, which would explain lack of relationships with occupant outcomes. These high VRs resulted partly from frequently used energy-saving “economizer” cycles in moderate California climates, but VRs at other times also substantially exceeded required VRs. These findings suggest, consistent with theory, that within a higher VR range, increased VRs do not reduce respiratory illness. Further studies are needed to better characterize such relationships.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Process Modeling and Techno-Economic Analysis of a CO 2 Capture Process Using Fixed Bed Reactors with a Microencapsulated Solvent

A detailed model of a capsule containing sodium carbonate solution is developed here to study the microencapsulated carbon capture solvents (MECS). A rigorous vapor–liquid equilibrium model is developed for the Na 2 CO 3 –CO 2 –H 2 O system, where liquid-phase nonideality is modeled by the electrolyte nonrandom two-liquid model. The data from the experiments conducted at the Lawrence Livermore National Laboratory is used to obtain a maximum likelihood estimate of the initial solvent concentration inside the capsules and the parameters for the capsule model. A nonisothermal, dynamic model of a fixed bed contactor filled with these capsules is then developed. In addition to direct steam injection, indirect heating using an embedded heat exchanger is modeled for desorption. Finally, the model is used to simulate temperature swing absorption and desorption cycles. The results of these studies indicate that there is an optimal residence time or superficial flue gas velocity to minimize the bed volume. However, the total energy requirement for desorption monotonically decreases with increased residence time as the proportion of the sensible heat to the total regeneration heat keeps decreasing. Furthermore, heat recovery from the bed is crucial to keep energy penalty for regeneration low. A techno-economic analysis is conducted, and the equivalent annual operating cost (EAOC) is analyzed for two different reactor materials (concrete and carbon-steel) and compared with a system using a conventional monoethanolamine (MEA) solvent. In this work, the minimum EAOC for the MECS fixed bed configuration is approximately 1.8–2.7 times higher than the EAOC for an MEA system with a similar amount of heat recovery (85%). The impact of ±50% uncertainty in the capital cost estimate is also evaluated, and the minimum EAOC is 1.5 times higher than the MEA technology for 85% heat recovery. These results using microencapsulated sodium carbonate solution are a starting point that sets an upper limit on the cost of the MECS carbon-capture system. Improvements to the MECS capsules (e.g., using a higher carbonate concentration and lowering the shell mass transfer resistance) and also exploring other contactor technologies are expected to decrease the system cost and make it more competitive.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2015

REVISITING ULYSSES OBSERVATIONS OF INTERSTELLAR HELIUM

We report the results of a comprehensive reanalysis of Ulysses observations of interstellar He atoms flowing through the solar system, the goal being to reassess the interstellar He flow vector and to search for evidence of variability in this vector. We find no evidence that the He beam seen by Ulysses changes at all from 1994-2007. The direction of flow changes by no more than ∼0.°3 and the speed by no more than ∼0.3 km s{sup –1}. A global fit to all acceptable He beam maps from 1994-2007 yields the following He flow parameters: V {sub ISM} = 26.08 ± 0.21 km s{sup –1}, λ = 75.54 ± 0.°19, β = –5.44 ± 0.°24, and T = 7260 ± 270 K; where λ and β are the ecliptic longitude and latitude direction in J2000 coordinates. The flow vector is consistent with the original analysis of the Ulysses team, but our temperature is significantly higher. The higher temperature somewhat mitigates a discrepancy that exists in the He flow parameters measured by Ulysses and the Interstellar Boundary Explorer, but does not resolve it entirely. Using a novel technique to infer photoionization loss rates directly from Ulysses data, we estimate a density of n {sub He} = 0.0196 ± 0.0033 cm{sup –3} in the interstellar medium.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Congruity of genomic and epidemiological data in modelling of local cholera outbreaks

Cholera continues to be a global health threat. Understanding how cholera spreads between locations is fundamental to the rational, evidence-based design of intervention and control efforts. Traditionally, cholera transmission models have used cholera case-count data. More recently, whole-genome sequence data have qualitatively described cholera transmission. Integrating these data streams may provide much more accurate models of cholera spread; however, no systematic analyses have been performed so far to compare traditional case-count models to the phylodynamic models from genomic data for cholera transmission. Here, we use high-fidelity case-count and whole-genome sequencing data from the 1991 to 1998 cholera epidemic in Argentina to directly compare the epidemiological model parameters estimated from these two data sources. We find that phylodynamic methods applied to cholera genomics data provide comparable estimates that are in line with established methods. Our methodology represents a critical step in building a framework for integrating case-count and genomic data sources for cholera epidemiology and other bacterial pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Bootstrap-determined p values in lattice QCD

We present a general method to determine the probability that stochastic Monte Carlo data, in particular those generated in a lattice QCD calculation, would have been obtained were that data drawn from the distribution predicted by a given theoretical hypothesis. Such a probability, or p -value, is often used as an important heuristic measure of the validity of that hypothesis. The proposed method offers the benefit that it remains usable in cases where the standard Hotelling T 2 methods based on the conventional χ 2 statistic do not apply, such as for uncorrelated fits. Specifically, we analyze q 2 , defined as the correlated χ 2 statistic obtained using an arbitrary covariance matrix estimator, and show how to use the bootstrap as a data-driven method to determine the expected distribution of q 2 for a given hypothesis with minimal assumptions. This distribution can then be used to determine the p -value for a fit to the data. We also describe a bootstrap approach for quantifying the impact upon this p -value of estimating population parameters from a single ensemble of N samples. The overall method is accurate up to a 1 / N bias which we do not attempt to quantify. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

LEAD - LEArning Damage

LEAD is a suite of scripts to enable rapid estimation of model parameters for damage models for ductile materials using machine learning. In its current version, the only supported damage model is TEPLA, though others are planned. The data we train on are comprised of free surface velocity data as well as porosity data. Some details about our method can be found in the preprint LA-UR-23-20468 (arxiv.org/abs/2301.07790)

Blaschke, Daniel↗
DOE OSTI2016

A Statistical Approach For Modeling Tropical Cyclones. Synthetic Hurricanes Generator Model

This manuscript brie y describes a statistical ap- proach to generate synthetic tropical cyclone tracks to be used in risk evaluations. The Synthetic Hur- ricane Generator (SynHurG) model allows model- ing hurricane risk in the United States supporting decision makers and implementations of adaptation strategies to extreme weather. In the literature there are mainly two approaches to model hurricane hazard for risk prediction: deterministic-statistical approaches, where the storm key physical parameters are calculated using physi- cal complex climate models and the tracks are usually determined statistically from historical data; and sta- tistical approaches, where both variables and tracks are estimated stochastically using historical records. SynHurG falls in the second category adopting a pure stochastic approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Predictive coarse-graining

We propose a data-driven, coarse-graining formulation in the context of equilibrium statistical mechanics. In contrast to existing techniques which are based on a fine-to-coarse map, we adopt the opposite strategy by prescribing a probabilistic coarse-to-fine map. This corresponds to a directed probabilistic model where the coarse variables play the role of latent generators of the fine scale (all-atom) data. From an information-theoretic perspective, the framework proposed provides an improvement upon the relative entropy method and is capable of quantifying the uncertainty due to the information loss that unavoidably takes place during the coarse-graining process. Furthermore, it can be readily extended to a fully Bayesian model where various sources of uncertainties are reflected in the posterior of the model parameters. The latter can be used to produce not only point estimates of fine-scale reconstructions or macroscopic observables, but more importantly, predictive posterior distributions on these quantities. Predictive posterior distributions reflect the confidence of the model as a function of the amount of data and the level of coarse-graining. The issues of model complexity and model selection are seamlessly addressed by employing a hierarchical prior that favors the discovery of sparse solutions, revealing the most prominent features in the coarse-grained model. A flexible and parallelizable Monte Carlo – Expectation–Maximization (MC-EM) scheme is proposed for carrying out inference and learning tasks. A comparative assessment of the proposed methodology is presented for a lattice spin system and the SPC/E water model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Application of the Aquifer Impact Model to support decisions at a CO 2 sequestration site

The National Risk Assessment Partnership (NRAP) has developed a suite of tools to assess and manage risk at CO 2 sequestration sites. The NRAP tool suite includes the Aquifer Impact Model (AIM), which evaluates the potential for groundwater impacts from leaks of CO 2 and brine through abandoned wellbores. There are two aquifer reduced-order models (ROMs) included with the AIM tool, a confined alluvium aquifer, and an unconfined carbonate aquifer. The models accept aquifer parameters as a range of variable inputs so they may have broad applicability. The generic aquifer models may be used at the early stages of site selection, when site-specific data is not available. Guidelines have been developed for determining when the generic ROMs might be applicable to a new site. This work considers the application of the AIM to predicting the impact of CO 2 or brine leakage were it to occur at the Illinois Basin Decatur Project (IBDP). Results of the model sensitivity analysis can help guide characterization efforts; the hydraulic parameters and leakage source term magnitude are more sensitive than clay fraction or cation exchange capacity. Sand permeability was the only hydraulic parameter measured at the IBDP site. More information on the other hydraulic parameters could reduce uncertainty in risk estimates. Some non-adjustable parameters are significantly different for the ROM than for the observations at the IBDP site. The generic ROMs could be made more useful to a wider range of sites if the initial conditions and no-impact threshold values were adjustable parameters.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Multiscale Modeling of a Direct Nonoxidative Methane Dehydroaromatization Reactor with a Validated Model for Catalyst Deactivation

Due to the recent boom in shale gas production, aromatics production using direct nonoxidative methane dehydroaromatization (DHA) is being investigated extensively. However, due to rapid coke formation, catalysts in the nonoxidative methane DHA reactors get deactivated, which is one of the critical issues for the commercial success of the methane DHA process. In this paper, a model for catalyst deactivation is developed. Rate models for other DHA reactions are developed by considering the decrease in the catalyst activity with time. Due to the very fast coke formation rate on the fresh catalyst, there is coke formation immediately upon the introduction of the feed. Therefore, an algorithm is developed for estimation of the initial state of the reactor and the kinetic parameters by coupling an iterative direct substitution approach with an optimization approach. Transient experimental data from an in-house reactor are first reconciled and then used for developing the kinetic model including the coke formation model. Using the rate model, a dynamic, heterogeneous, multiscale reactor model with embedded heating is developed. Here, the model couples the catalyst pellet level model with a reactor level model. Impacts of temperature, L/D ratio, and scheduling of reactors on variability in conversion and yield with time are studied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Clutter Distributions for Tomographic Image Standardization in Ground-Penetrating Radar

Multistatic ground-penetrating radar (GPR) signals can be imaged tomographically to produce 3-D distributions of image intensities. In the absence of objects of interest, these intensities can be considered to be estimates of clutter. These clutter intensities spatially vary over several orders of magnitude and vary across different arrays, which makes a direct comparison of these raw intensities difficult. However, by gathering statistics on these intensities and their spatial variation, a variety of metrics can be determined. In this study, the clutter distribution is found to fit better to a two-parameter Weibull distribution than Gaussian or log-normal distributions. Based on the spatial variation of the two Weibull parameters, scale and shape, more information may be gleaned from these data. How well the GPR array is illuminating various parts of the ground, in depth and cross track, may be determined from the spatial variation of the Weibull scale parameter, which may in turn be used to estimate an effective attenuation coefficient in the soil. The transition in depth from clutter- to noise-limited conditions (which is one possible definition of GPR penetration depth) can be estimated from the spatial variation of the Weibull shape parameter. Lastly, the underlying clutter distributions also provide an opportunity to standardize image intensities to determine when a statistically significant deviation from background (clutter) has occurred, which is convenient for buried threat detection algorithm development that needs to be robust across multiple different arrays.

42 ENGINEERING↗
DOE OSTI2015

A cosmological exclusion plot: towards model-independent constraints on modified gravity from current and future growth rate data

Most cosmological constraints on modified gravity are obtained assuming that the cosmic evolution was standard ΛCDM in the past and that the present matter density and power spectrum normalization are the same as in a ΛCDM model. Here we examine how the constraints change when these assumptions are lifted. We focus in particular on the parameter Y (also called G{sub eff}) that quantifies the deviation from the Poisson equation. This parameter can be estimated by comparing with the model-independent growth rate quantity fσ{sub 8}(z) obtained through redshift distortions. We reduce the model dependency in evaluating Y by marginalizing over σ{sub 8} and over the initial conditions, and by absorbing the degenerate parameter Ω{sub m,0} into Y. We use all currently available values of fσ{sub 8}(z). We find that the combination Y-circumflex =YΩ{sub m,0}, assumed constant in the observed redshift range, can be constrained only very weakly by current data, Y-circumflex =0.28{sub −0.23}{sup +0.35} at 68% c.l. We also forecast the precision of a future estimation of Y-circumflex in a Euclid-like redshift survey. We find that the future constraints will reduce substantially the uncertainty, Y-circumflex =0.30{sub −0.09}{sup +0.08} , at 68% c.l., but the relative error on Y-circumflex around the fiducial remains quite high, of the order of 30%. The main reason for these weak constraints is that Y-circumflex is strongly degenerate with the initial conditions, so that large or small values of Y-circumflex are compensated by choosing non-standard initial values of the derivative of the matter density contrast. Finally, we produce a forecast of a cosmological exclusion plot on the Yukawa strength and range parameters, which complements similar plots on laboratory scales but explores scales and epochs reachable only with large-scale galaxy surveys. We find that future data can constrain the Yukawa strength to within 3% of the Newtonian one if the range is around a few Megaparsecs. In the particular case of f(R) models, we find that the Yukawa range will be constrained to be larger than 80 Mpc/h or smaller than 2 Mpc/h (95% c.l.), regardless of the specific f(R) model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks

Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs), cellular growth factors and microRNAs. A subsystem’s gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally–e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org) for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the “state” and “control” in the model refer to its own (internal) and another subsystem’s (external) gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model’s parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation) representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs), seeing the degree to which these can be accounted for by orthologous (internal) versus species-specific (external) TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with evolutionarily ancient functions (e.g. the ribosomal proteins), in contrast to those with more recently evolved functions (e.g., cell-cell communication). This suggests that despite striking morphological differences, some fundamental embryonic-developmental processes are still controlled by ancient regulatory systems.

Biochemistry & Molecular Biology↗
DOE OSTI2021

On the estimation of boundary layer heights: a machine learning approach

Abstract. The planetary boundary layer height (zi) is a key parameter used in atmospheric models for estimating the exchange of heat, momentum, and moisture between the surface and the free troposphere. Near-surface atmospheric and subsurface properties (such as soil temperature, relative humidity, etc.) are known to have an impact on zi. Nevertheless, precise relationships between these surface properties and zi are less well known and not easily discernible from the multi-year dataset. Machine learning approaches, such as random forest (RF), which use a multi-regression framework, help to decipher some of the physical processes linking surface-based characteristics to zi. In this study, a 4-year dataset from 2016 to 2019 at the Southern Great Plains site is used to develop and test a machine learning framework for estimating zi. Parameters derived from Doppler lidars are used in combination with over 20 different surface meteorological measurements as inputs to a RF model. The model is trained using radiosonde-derived zi values spanning the period from 2016 through 2018 and then evaluated using data from 2019. Results from 2019 showed significantly better agreement with the radiosonde compared to estimates derived from a thresholding technique using Doppler lidars only. Noteworthy improvements in daytime zi estimates were observed using the RF model, with a 50 % improvement in mean absolute error and an R2 of greater than 85 % compared to the Tucker method zi. We also explore the effect of zi uncertainty on convective velocity scaling and present preliminary comparisons between the RF model and zi estimates derived from atmospheric models.

54 ENVIRONMENTAL SCIENCES↗