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

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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Comprehensive rate coefficients for electron-collision-induced transitions in hydrogen

Energy-changing electron-hydrogen atom collisions are crucial to regulating the energy balance in astrophysical and laboratory plasmas and are relevant to the formation of stellar atmospheres, recombination in H II clouds, primordial recombination, three-body recombination, and heating in ultracold and fusion plasmas. Computational modeling of electron-hydrogen collision has been attempted through quantum mechanical scattering state-to-state calculations of transitions involving low-lying energy levels in hydrogen (with principal quantum number n < 7) and at large principal quantum numbers using classical trajectory techniques. Analytical expressions are proposed that interpolate the current quantum mechanical and classical trajectory results for electron-hydrogen scattering in the entire range of energy levels for nearly the entire temperature range of interest in astrophysical environments. An asymptotic expression for the Born cross section is interpolated with a modified expression previously derived for electron-hydrogen scattering in the Rydberg regime using classical trajectory Monte Carlo simulations. The derived formula is compared to existing numerical data for transitions involving low principal quantum numbers, and the dependence of the deviations on temperature is discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Experimental Observations of the Topology of Convolutional Neural Network Activations

Topological data analysis (TDA) is a branch of computational mathematics, bridging algebraic topology and data science, that provides compact, noise-robust representations of complex structures. Deep neural networks (DNNs) learn millions of parameters associated with a series of transformations defined by the model architecture resulting in high-dimensional, difficult to interpret internal representations of input data. As DNNs become more ubiquitous across multiple sectors of our society, there is increasing recognition that mathematical methods are needed to aid analysts, researchers, and practitioners in understanding and interpreting how these models' internal representations relate to the final classification. In this paper we apply cutting edge techniques from TDA with the goal of gaining insight towards interpretability of convolutional neural networks used for image classification. We use two common TDA approaches to explore several methods for modeling hidden layer activations as high-dimensional point clouds, and provide experimental evidence that these point clouds capture valuable structural information about the model's process. First, we demonstrate that a distance metric based on persistent homology can be used to quantify meaningful differences between layers and discuss these distances in the broader context of existing representational similarity metrics for neural network interpretability. Second, we show that a mapper graph can provide semantic insight as to how these models organize hierarchical class knowledge at each layer. These observations demonstrate that TDA is a useful tool to help deep learning practitioners unlock the hidden structures of their models.

topological data analysis, deep learning↗
DOE OSTI2018

Microseismicity cloud can be substantially larger than the associated stimulated fracture volume: the case of the Paralana Enhanced Geothermal System

Here, the goal of hydraulic stimulation is to increase formation permeability in the near vicinity of a well. However, there remain technical challenges around measuring the outcome of this operation. During two Enhanced Geothermal System (EGS) stimulations in South Australia, Paralana in 2011 and Habanero in 2003, extensive catalogs of microseismicity were recovered. It is often assumed that shear failure of existing fractures is the main mechanism behind both the induced earthquakes and any permeability enhancement. This underpins a common notion, that the seismically active volume is also the stimulated reservoir. In this paper, we compute the density of earthquake hypocenters and provide evidence that, under certain conditions, this spatiotemporal quantity is a reasonable proxy for pore pressure increase. We then apply an inverse modeling approach that uses the earthquake observations and a modified reservoir simulator to estimate the parameters of a permeability evolution relation. The regime implied by the data indicates that most permeability enhancement occurred very near to the wellbore and was not coincident with the bulk of the seismicity, whose volume was about two orders of magnitude larger. Thus, we conclude that, in some cases, it is possible for permeability enhancement and induced seismicity to be decoupled, in which case the seismically active volume is a poor indicator of the stimulated reservoir. Our results raise serious questions about the effectiveness of hydroshearing as a stimulation mechanism in EGS. Finally, this study extends our understanding of the complex processes linking earthquakes, fluid pressure, and permeability in both natural and engineered settings.

58 GEOSCIENCES↗
DOE OSTI2016

WE-AB-207B-07: Dose Cloud: Generating “Big Data” for Radiation Therapy Treatment Plan Optimization Research

Purpose: To provide a tool to generate large sets of realistic virtual patient geometries and beamlet doses for treatment optimization research. This tool enables countless studies exploring the fundamental interplay between patient geometry, objective functions, weight selections, and achievable dose distributions for various algorithms and modalities. Methods: Generating realistic virtual patient geometries requires a small set of real patient data. We developed a normalized patient shape model (PSM) which captures organ and target contours in a correspondence-preserving manner. Using PSM-processed data, we perform principal component analysis (PCA) to extract major modes of variation from the population. These PCA modes can be shared without exposing patient information. The modes are re-combined with different weights to produce sets of realistic virtual patient contours. Because virtual patients lack imaging information, we developed a shape-based dose calculation (SBD) relying on the assumption that the region inside the body contour is water. SBD utilizes a 2D fluence-convolved scatter kernel, derived from Monte Carlo simulations, and can compute both full dose for a given set of fluence maps, or produce a dose matrix (dose per fluence pixel) for many modalities. Combining the shape model with SBD provides the data needed for treatment plan optimization research. Results: We used PSM to capture organ and target contours for 96 prostate cases, extracted the first 20 PCA modes, and generated 2048 virtual patient shapes by randomly sampling mode scores. Nearly half of the shapes were thrown out for failing anatomical checks, the remaining 1124 were used in computing dose matrices via SBD and a standard 7-beam protocol. As a proof of concept, and to generate data for later study, we performed fluence map optimization emphasizing PTV coverage. Conclusions: We successfully developed and tested a tool for creating customizable sets of virtual patients suitable for large-scale radiation therapy optimization research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing

Abstract We study the performance of a cloud-based GPU-accelerated inference server to speed up event reconstruction in neutrino data batch jobs. Using detector data from the ProtoDUNE experiment and employing the standard DUNE grid job submission tools, we attempt to reprocess the data by running several thousand concurrent grid jobs, a rate we expect to be typical of current and future neutrino physics experiments. We process most of the dataset with the GPU version of our processing algorithm and the remainder with the CPU version for timing comparisons. We find that a 100-GPU cloud-based server is able to easily meet the processing demand, and that using the GPU version of the event processing algorithm is two times faster than processing these data with the CPU version when comparing to the newest CPUs in our sample. The amount of data transferred to the inference server during the GPU runs can overwhelm even the highest-bandwidth network switches, however, unless care is taken to observe network facility limits or otherwise distribute the jobs to multiple sites. We discuss the lessons learned from this processing campaign and several avenues for future improvements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Audits Made Simple

A company just got notified there is a big external audit coming in 3 months. Getting ready for an audit can be challenging, scary, and full of surprises. This Gold Paper describes a typical audit from notification of the intent to audit through disposition of the final report including Best Practices, Opportunities for Improvement (OFI), and issues that must be fixed. Good preparation can improve the chances of success. Ensuring the auditors understand the environment and requirements is paramount to success. It helps the auditors understand that the enterprise really does think that security is important. Understanding and following a structured process ensures a smooth audit process. Ensuring follow-up on OFIs and issues in a structured fashion will also make the next audit easier. It is important to keep in mind that the auditors will use the previous report as a starting point. Now the only worry is the actual audit and subsequent report and how well the company has done. “Virtualization, mobilization, and cloud technology have created new points of entry into business, leaving them vulnerable to covert cyber-attacks,” states a report by Ernst & Young. Executives are struggling with the potential for a data breach, and resolving this business risk is high on their agenda. While most audit committee members are financially solid, they lack knowledge of technology issues, making understanding of this risk difficult. Success with an audit helps management understand the risk management is accepting, highlight gaps in security, and generate ideas on how to improve. These results are an important aspect of managing the business risk.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Predicting the influence of particle size on the glass transition temperature and viscosity of secondary organic material

Abstract Atmospheric aerosols can assume liquid, amorphous semi-solid or glassy, and crystalline phase states. Particle phase state plays a critical role in understanding and predicting aerosol impacts on human health, visibility, cloud formation, and climate. Melting point depression increases with decreasing particle diameter and is predicted by the Gibbs–Thompson relationship. This work reviews existing data on the melting point depression to constrain a simple parameterization of the process. The parameter $$\xi $$ ξ describes the degree to which particle size lowers the melting point and is found to vary between 300 and 1800 K nm for a wide range of particle compositions. The parameterization is used together with existing frameworks for modeling the temperature and RH dependence of viscosity to predict the influence of particle size on the glass transition temperature and viscosity of secondary organic aerosol formed from the oxidation of $$\alpha $$ α -pinene. Literature data are broadly consistent with the predictions. The model predicts a sharp decrease in viscosity for particles less than 100 nm in diameter. It is computationally efficient and suitable for inclusion in models to evaluate the potential influence of the phase change on atmospheric processes. New experimental data of the size-dependence of particle viscosity for atmospheric aerosol mimics are needed to thoroughly validate the predictions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

ResStock™ v3.2.0 [SWR-19-15 and SWR-20-07]

The ResStock™ analysis tool was built on NREL's OpenStudio® platform, and is a project geared at modeling existing residential building stocks at national, regional, or local scales with a high-degree of granularity (e.g., one physics-based simulation model for every 200 dwelling units), using the EnergyPlus® simulation engine. Information about ComStock™, a sister tool for modeling the commercial building stock, can be found here: https://www.nrel.gov/buildings/comstock.html This repository contains: Housing characteristics of the U.S. residential building stock, in the form of conditional probability distributions stored as tab-separated value (.tsv) files. Comments at the bottom of each file document data sources and assumptions for each. A library of housing characteristic "options" that translate high-level characteristic parameters into arguments for OpenStudio measures, and which are referenced by the housing characteristic .tsv files and building energy upgrades defined in project definition files Project definition files: v2.3.0 and later: buildstockbatch YML files openable in any text editor v2.2.5 and prior: Project folder openable in PAT Unit-level OpenStudio Measures for automatically constructing OpenStudio Models of each representative dwelling unit model: v3.0.0 and later: OpenStudio-HPXML Measures v2.5.0 and prior: OpenStudio Measures Higher-level OpenStudio Measures for controlling simulation inputs and outputs This repository does not contain software for running ResStock simulations, which can be found as follows: Versions 2.3.0 and later only support the use of buildstockbatch for deploying simulations on high-performance or cloud computing. Version 2.3.0 also removed separate projects for single-family detached and multifamily buildings, in lieu of a combined project_national representing the U.S. residential building stock. See the changelog for more details. Versions 2.2.5 and prior support the use of the publicly available OpenStudio-PAT software as an interface for deploying simulations on cloud computing. Read the documentation for v2.2.5.

Horowitz, Scott↗
DOE OSTI2020

Analytically Derived Piezoelectric Ejecta Data Transformations, with Implications for Claims of Experimentally Observed Self-Similarity

Building upon a previously documented analytic formalism, we derive a set of data transformations that relate piezoelectrically inferred time-dependent ejecta masses, dynamical ejecta cloud densities, and "radiographic" ejecta cloud density distributions. These transformation rules are derived rigorously, with careful attention to the assumption of instant ejecta production which is inherent in the piezoelectric mass inference procedure. Some of these relationships have not appeared previously in the literature, including solutions for the unique ejecta velocity distribution and radiographic ejecta cloud density distribution consistent with the instant-production assumption for a given piezoelectrically inferred mass dataset. In deriving the latter, we prove that—again subject to the ubiquitous instant-creation assumption—measurements at a single sensor are sufficient to determine properties of the ejecta cloud everywhere at all times. Other data transformation relationships have appeared in the literature without a rigorous derivation, or have been stated in forms that obscure the key mathematical relationships. We apply these results to arguments for self-similar ejecta cloud evolution, thereby deriving mathematical expressions by which claims of self-similarity may be examined. We prove that one analysis used in the literature to claim experimental evidence of a short ejecta production timescale—and consequently of self-similar cloud evolution—in fact places no constraint the ejecta production interval and therefore does not support the associated conclusion. We also provide a potentially useful uniqueness proof.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2017

Microwave Passive Ground-Based Retrievals of Cloud and Rain Liquid Water Path in Drizzling Clouds: Challenges and Possibilities

Satellite and ground-based microwave radiometers are routinely used for the retrieval of liquid water path (LWP) under all atmospheric conditions. The retrieval of water vapor and LWP from ground-based radiometers during rain has proved to be a difficult challenge for two principal reasons: the inadequacy of the nonscattering approximation in precipitating clouds and the deposition of rain drops on the instrument's radome. In this paper, we combine model computations and real ground-based, zenith-viewing passive microwave radiometer brightness temperature measurements to investigate how total, cloud, and rain LWP retrievals are affected by assumptions on the cloud drop size distribution (DSD) and under which conditions a nonscattering approximation can be considered reasonably accurate. Results show that until the drop effective diameter is larger than similar to 200 mu m, a nonscattering approximation yields results that are still accurate at frequencies less than 90 GHz. For larger drop sizes, it is shown that higher microwave frequencies contain useful information that can be used to separate cloud and rain LWP provided that the vertical distribution of hydrometeors, as well as the DSD, is reasonably known. The choice of the DSD parameters becomes important to ensure retrievals that are consistent with the measurements. A physical retrieval is tested on a synthetic data set and is then used to retrieve total, cloud, and rain LWP from radiometric measurements during two drizzling cases at the atmospheric radiation measurement Eastern North Atlantic site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

CERES MODIS Cloud Product Retrievals for Edition 4--Part I: Algorithm Changes

The Edition 2 (Ed2) cloud property retrieval algorithm system was upgraded and applied to the MODerate-resolution Imaging Spectroradiometer (MODIS) data for the Clouds and the Earth's Radiant Energy System (CERES) Edition 4 (Ed4) products. New calibrations for solar channels and the use of the 1.24-μm channel for cloud optical depth (COD) over snow improve the daytime consistency between Terra and Aqua MODIS retrievals. Use of additional spectral channels and revised logic enhanced the cloud-top phase retrieval accuracy. A new ice crystal reflectance model and a CO₂-channel algorithm retrieved higher ice clouds, while a new regional lapse rate technique produced more accurate water cloud heights than in Ed2. Ice cloud base heights are more accurate due to a new cloud thickness parameterization. Overall, CODs increased, especially over the polar (PO) regions. The mean particle sizes increased slightly for water clouds, but more so for ice clouds in the PO areas. New experimental parameters introduced in Ed4 are limited in utility, but will be revised for the next CERES edition. As part of the Ed4 retrieval evaluation, the average properties are compared with those from other algorithms and the differences between individual reference data and matched Ed4 retrievals are explored. Part II of this article provides a comprehensive, objective evaluation of selected parameters. More accurate interpretation of the CERES radiation measurements has resulted from the use of the Ed4 cloud properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Insights of Boundary Layer Turbulence Over the Complex Terrain of Central Himalaya from GVAX Field Campaign

Limited observations hinder understanding of turbulent characteristics in mountainous terrain resulting from heating or cooling of slopes, wind, vertical motions, and heat or moisture advection, which disperse aerosols and other pollutants over the region. In this study, the 1290 MHz radar wind profiler data are utilized to compute the boundary layer height (BLH), the refractive index structure constant (C n 2 ), and the energy dissipation rate (ε) over the central Himalayan site for the period of November 2011 to March 2012, from the intense Ganges Valley Aerosol Experiment (GVAX) field measurements. The radar wind profiler (RWP) based estimation of BLH and ε is validated against the radiosonde, representing the effectiveness of the datasets for further investigation. The strong seasonal variation of log C n 2 and log ε, with average values of ≈ -12 m -2/3 and -2 m 2 s -3 , respectively, is associated with the mountain-induced local circulations and stability in the atmospheric boundary layer. The weak stratification during weak flow is found to be responsible for deep mixing, particularly in the nocturnal boundary layer in spring. Furthermore, the level of cloud cover significantly impacts the strength of turbulence, with the highest cloud cover resulting in a substantial increase in log C n 2 (approximately -11 m -2/3 ) due to intense updraft and downdraft motions compared to clear skies. Additionally, the distribution of aerosol loading across the site, coupled with the behavior of BLH, atmospheric stability, and orographic-induced circulations, implies distinctive seasonal mechanisms for transporting aerosols toward the mountains. This study offers valuable insights into the diurnal and seasonal patterns of turbulent mixing and the mechanisms behind the transport of pollutants through boundary layer processes over the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

DISTANCE SCALE ZERO POINTS FROM GALACTIC RR LYRAE STAR PARALLAXES

We present new absolute trigonometric parallaxes and proper motions for seven Population II variable stars-five RR Lyr variables: RZ Cep, XZ Cyg, SU Dra, RR Lyr, and UV Oct; and two type 2 Cepheids: VY Pyx and {kappa} Pav. We obtained these results with astrometric data from Fine Guidance Sensors, white-light interferometers on Hubble Space Telescope. We find absolute parallaxes in milliseconds of arc: RZ Cep, 2.12 {+-} 0.16 mas; XZ Cyg, 1.67 {+-} 0.17 mas; SU Dra, 1.42 {+-} 0.16 mas; RR Lyr, 3.77 {+-} 0.13 mas; UV Oct, 1.71 {+-} 0.10 mas; VY Pyx, 6.44 {+-} 0.23 mas; and {kappa} Pav, 5.57 {+-} 0.28 mas; an average {sigma}{sub {pi}}/{pi} = 5.4%. With these parallaxes, we compute absolute magnitudes in V and K bandpasses corrected for interstellar extinction and Lutz-Kelker-Hanson bias. Using these RR Lyrae variable star absolute magnitudes, we then derive zero points for M{sub V} -[Fe/H] and M{sub K} -[Fe/H]-log P relations. The technique of reduced parallaxes corroborates these results. We employ our new results to determine distances and ages of several Galactic globular clusters and the distance of the Large Magellanic Cloud. The latter is close to that previously derived from Classical Cepheids uncorrected for any metallicity effect, indicating that any such effect is small. We also discuss the somewhat puzzling results obtained for our two type 2 Cepheids.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

A COMPARATIVE ASTROCHEMICAL STUDY OF THE HIGH-MASS PROTOSTELLAR OBJECTS NGC 7538 IRS 9 AND IRS 1

We report the results of a spectroscopic study of the high-mass protostellar object NGC 7538 IRS 9 and compare our observations to published data on the nearby object NGC 7538 IRS 1. Both objects originated in the same molecular cloud and appear to be at different points in their evolutionary histories, offering an unusual opportunity to study the temporal evolution of envelope chemistry in objects sharing a presumably identical starting composition. Observations were made with the Texas Echelon Cross Echelle Spectrograph, a sensitive, high spectral resolution (R {lambda}/{Delta}{lambda} {approx_equal} 100,000) mid-infrared grating spectrometer. Forty-six individual lines in vibrational modes of the molecules C{sub 2}H{sub 2}, CH{sub 4}, HCN, NH{sub 3}, and CO were detected, including two isotopologues ({sup 13}CO, {sup 12}C{sup 18}O) and one combination mode ({nu}{sub 4} + {nu}{sub 5} C{sub 2}H{sub 2}). Fitting synthetic spectra to the data yielded the Doppler shift, excitation temperature, Doppler b parameter, column density, and covering factor for each molecule observed; we also computed column density upper limits for lines and species not detected, such as HNCO and OCS. We find differences among spectra of the two objects likely attributable to their differing radiation and thermal environments. Temperatures and column densities for the two objects are generally consistent, while the larger line widths toward IRS 9 result in less saturated lines than those toward IRS 1. Finally, we compute an upper limit on the size of the continuum-emitting region ({approx}2000 AU) and use this constraint and our spectroscopy results to construct a schematic model of IRS 9.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Exascale Programming Approaches for Accelerated Climate Modeling for Energy

The Accelerated Climate Modeling for Energy (ACME) program is a leading-edge climate and Earth system model designed to address the U.S. Department of Energy (DOE) mission needs. The ACME project involves collaboration between seven National Laboratories, the National Center for Atmospheric Research, four academic institutions, and one private-sector company. The ACME project funds ongoing efforts to ensure the model continues to make efficient use of DOE Leadership Computing Facilities (LCFs) in order to best address the three driving grand challenge science questions:Water cycle: How will more realistic portrayals of features important to the water cycle (resolution, clouds, aerosols, snowpack, river routing, land use) affect river flow and associated freshwater supplies at the watershed scale?Cryosphere systems: Could a dynamical instability in the Antarctic ice sheet be triggered within the next 40 years?Biogeochemistry: What are the contributions and feedbacks from natural and managed systems to current greenhouse gas fluxes, and how will those factors and associated fluxes evolve in the future?

Norman, Matthew↗
DOE OSTI2022

Final Technical Report for "Cloud-based Low-Scaling Quantum Chemistry Simulations for Materials"

The objective of phase I was to develop the basic infrastructure for performing efficient hybrid DFT calculations on solid materials with a turnaround time amenable to the use in large-scale data-driven approaches. To fulfill the goal we have developed a novel algorithm that significantly reduces the cost of exchange matrix formation. The algorithm does so by making use of three ingredients (a) interpolative decomposition of the electron integrals (b) robust pseudospectral method and (c) occ-RI approach. Our published work demonstrates that the algorithm is orders of magnitude faster than any other hybrid-DFT method and is on the order of only 3-4 times slower than pure DFT. All steps of the algorithm developed during phase I can be accelerated to the point that, for large enough systems, the diagonalization of the Fock matrix will become the most expensive step. To treat such large systems we have created an interface to the ASCR-funded PEXSI library. The PEXSI method is used to compute the density matrix directly from the Fock matrix in a manner that preserves the sparsity of the local representation.

Shiozaki, Toru↗
DOE OSTI2012

Community Modeling and Long-Term Predictions of the Integrated Water Cycle. Report from the September 2012 Workshop

Water is a key component of the earth and human systems due to its strong interactions with the energy cycle and its vital roles in the energy-water-land system. Uncertainties in predicting the integrated water cycle can limit our abilities to address the energy and environmental challenges today and in the future. Modeling the integrated water cycle contributes to the Department of Energy’s (DOE) core competencies in integrative modeling, drawing from unique and highly relevant research on cloud, aerosol, terrestrial ecosystem, carbon cycle, and subsurface processes, as well as climate and earth system modeling and integrated assessment modeling. Synthesizing new process knowledge and innovative computational methods in integrated models of the human-earth system can advance predictive capabilities relevant to DOE missions. This report describes the DOE workshop on Community Modeling and Long-Term Predictions of the Integrated Water Cycle, held September 2012 in Washington DC. The workshop serves as a launching point and major organizing event to identify challenges and plan the development of next-generation human-earth system models for improving long-term predictions of the regional-scale integrated water cycle. More specifically, the workshop aims to: identify core modeling capabilities while identifying key research gaps, with an emphasis on improving model fidelity; reveal relevant and critical capabilities and needs for observations, analytical frameworks, and data management that underpin the development, testing, and validation of our main models and model components; engage the research community in strategies for improving synthesis and integration; elucidate opportunities for collaborations within DOE and with other agencies and institutions that have complementary and essential expertise in specific aspects of the water cycle; and improve understanding of the nature and characteristics of long-term scientific information requirements for DOE’s energy and environmental missions and, as appropriate, for mission needs of other partner agencies. The workshop benefited from substantial inputs provided by the broad scientific community and interagency participation. The topical and crosscutting research challenges identified at the workshop have been synthesized into three overarching Science Grand Challenges and three Integrative Modeling Experiments summarized in this report. These challenges represent remarkable opportunities for interagency collaborations to improve predictions of the integrated water cycle for significant scientific and user impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

UNDERSTANDING TRENDS ASSOCIATED WITH CLOUDS IN IRRADIATED EXOPLANETS

Unlike previously explored relationships between the properties of hot Jovian atmospheres, the geometric albedo and the incident stellar flux do not exhibit a clear correlation, as revealed by our re-analysis of Q0-Q14 Kepler data. If the albedo is primarily associated with the presence of clouds in these irradiated atmospheres, a holistic modeling approach needs to relate the following properties: the strength of stellar irradiation (and hence the strength and depth of atmospheric circulation), the geometric albedo (which controls both the fraction of starlight absorbed and the pressure level at which it is predominantly absorbed), and the properties of the embedded cloud particles (which determine the albedo). The anticipated diversity in cloud properties renders any correlation between the geometric albedo and the stellar flux weak and characterized by considerable scatter. In the limit of vertically uniform populations of scatterers and absorbers, we use an analytical model and scaling relations to relate the temperature-pressure profile of an irradiated atmosphere and the photon deposition layer and to estimate whether a cloud particle will be lofted by atmospheric circulation. We derive an analytical formula for computing the albedo spectrum in terms of the cloud properties, which we compare to the measured albedo spectrum of HD 189733b by Evans et al. Furthermore, we show that whether an optical phase curve is flat or sinusoidal depends on whether the particles are small or large as defined by the Knudsen number. This may be an explanation for why Kepler-7b exhibits evidence for the longitudinal variation in abundance of condensates, while Kepler-12b shows no evidence for the presence of condensates despite the incident stellar flux being similar for both exoplanets. We include an 'observer's cookbook' for deciphering various scenarios associated with the optical phase curve, the peak offset of the infrared phase curve, and the geometric albedo.

79 ASTRONOMY AND ASTROPHYSICS↗