Data-Driven Model for Fire Spread using Deep Neural Networks
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COVID-19 dynamics across the US: A deep learning study of human mobility and social behavior
This paper presents a deep learning framework for epidemiology system identification from noisy and sparse observations with quantified uncertainty. The proposed approach employs an ensemble of deep neural networks to infer the time-dependent reproduction number of an infectious disease by formulating a tensor-based multi-step loss function that allows us to efficiently calibrate the model on multiple observed trajectories. The method is applied to a mobility and social behavior-based SEIR model of COVID-19 spread. The model is trained on Google and Unacast mobility data spanning a period of 66 days, and is able to yield accurate future forecasts of COVID-19 spread in 203 US counties within a time-window of 15 days. Interestingly, a sensitivity analysis that assesses the importance of different mobility and social behavior parameters reveals that attendance of close places, including workplaces, residential, and retail and recreational locations, has the largest impact on the effective reproduction number. Furthermore, the model enables us to rapidly probe and quantify the effects of government interventions, such as lock-down and re-opening strategies. Taken together, the proposed framework provides a robust workflow for data-driven epidemiology model discovery under uncertainty and produces probabilistic forecasts for the evolution of a pandemic that can judiciously provide information for policy and decision making. All codes and data accompanying this manuscript are available at https://github.com/PredictiveIntelligenceLab/DeepCOVID19.
60 APPLIED LIFE SCIENCES↗
Computational models of direct and indirect X‐ray breast imaging detectors for in silico trials
Abstract Background To facilitate in silico studies that investigate digital mammography (DM) and breast tomosynthesis (DBT), models replicating the variety in imaging performance of the DM and DBT systems, observed across manufacturers are needed. Purpose The main purpose of this work is to develop generic physics models for direct and indirect detector technology used in commercially available systems, with the goal of making them available open source to manufacturers to further tweak and develop the exact in silico replicas of their systems. Methods We recently reported on an in silico version of the SIEMENS Mammomat Inspiration DM/DBT system using an open‐source GPU‐accelerated Monte Carlo x‐ray imaging simulation code (MC‐GPU). We build on the previous version of the MC‐GPU codes to mimic the imaging performances of two other Food and Drug Administration (FDA)‐approved DM/DBT systems, such as Hologic Selenia Dimensions (HSD) and the General Electric Senographe Pristina (GSP) systems. In this work, we developed a hybrid technique to model the optical spread and signal crosstalk observed in the GSP and HSD systems. MC simulations are used to track each x‐ray photon till its first interaction within the x‐ray detector. On the other hand, the signal spread in the x‐ray detectors is modeled using previously developed analytical equations. This approach allows us to preserve the modeling accuracy offered by MC methods in the patient body, while speeding up secondary carrier transport (either electron–hole pairs or optical photons) using analytical equations in the detector. The analytical optical spread model for the indirect detector includes the depth‐dependent spread and collection of optical photons and relies on a pre‐computed set of point response functions that describe the optical spread as a function of depth. To understand the capabilities of the computational x‐ray detector models, we compared image quality metrics like modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), simulated with our models against measured data. Please note that the purpose of these comparisons with measured data would be to gauge if the model developed as part of this work could replicate commercially used direct and indirect technology in general and not to achieve perfect fits with measured data. Results We found that the simulated image quality metrics such as MTF, NNPS, and DQE were in reasonable agreement with experimental data. To demonstrate the imaging performance of the three DM/DBT systems, we integrated the detector models with the VICTRE pipeline and simulated DM images of a fatty breast model containing a spiculated mass and a calcium oxalate cluster. In general, we found that the images generated using the indirect model appeared more blurred with a different noise texture and contrast as compared to the systems with direct detectors. Conclusions We have presented computational models of three commercially available FDA‐approved DM/DBT systems, which implement both direct and indirect detector technology. The updated versions of the MC‐GPU codes that can be used to replicate three systems are available in open source format through GitHub.
Sengupta, Aunnasha↗
Comparison of observed and predicted gravity profiles over Aphrodite Terra, Venus
Pioneer Venus orbiter (PVO) gravity profiles over Aphrodite Terra are compared with profiles predicted from models of thermal isostasy, mantle convection, and Airy compensation. Topography profiles across Aphrodite are compared to model spreading-ridge profiles in order to further assess this model. Airy compensation depths and convection-layer thicknesses are greater under eastern Aphrodite than western Aphrodite. Compensation depths in the east are greater than most estimates of lithospheric thickness, suggesting that this part of the ridge is dynamically supported. In parts of western Aphrodite, the spreading-ridge model gravity provides a better fit to the data than either Airy compensation or mantle convection. Best-fit spreading rates are between 0.3 and 1.6 cm/yr. Airy compensation and mantle convection cannot be distinguished in most places using only PVO data.
Black, Martin T.↗
A model of concurrent flow flame spread over a thin solid fuel
A numerical model is developed to examine laminar flame spread and extinction over a thin solid fuel in lowspeed concurrent flows. The model provides a more precise fluid-mechanical description of the flame by incorporating an elliptic treatment of the upstream flame stabilization zone near the fuel burnout point. Parabolic equations are used to treat the downstream flame, which has a higher flow Reynolds number. The parabolic and elliptic regions are coupled smoothly by an appropriate matching of boundary conditions. The solid phase consists of an energy equation with surface radiative loss and a surface pyrolysis relation. Steady spread with constant flame and pyrolysis lengths is found possible for thin fuels and this facilitates the adoption of a moving coordinate system attached to the flame with the flame spread rate being an eigen value. Calculations are performed in purely forced flow in a range of velocities which are lower than those induced in a normal gravity buoyant environment. Both quenching and blowoff extinction are observed. The results show that as flow velocity or oxygen percentage is reduced, the flame spread rate, the pyrolysis length, and the flame length all decrease, as expected. The flame standoff distance from the solid and the reaction zone thickness, however, first increase with decreasing flow velocity, but eventually decrease very near the quenching extinction limit. The short, diffuse flames observed at low flow velocities and oxygen levels are consistent with available experimental data. The maximum flame temperature decreases slowly at first as flow velocity is reduced, then falls more steeply close to the quenching extinction limit. Low velocity quenching occurs as a result of heat loss. At low velocities, surface radiative loss becomes a significant fraction of the total combustion heat release. In addition, the shorter flame length causes an increase in the fraction of conduction downstream compared to conduction to the fuel. These heat losses lead to lower flame temperatures, and ultimately, extinction. This extinction mechanism differs from that of blowoff, where the flame is unable to be stabilized due to the high flow velocity.
Ferkul, Paul V.↗
Radiative, Hydrologic, and Circulation Responses to Warming in Cess‐Potter Simulations Using the Global 3.25‐km SCREAM
Using the global 3.25-km Simple Cloud Resolving E3SM Atmosphere Model (SCREAM 3 km), a pair of 13-month Cess-Potter simulations are performed to quantify the radiative feedbacks and the hydrologic and circulation responses to warming. Large-scale aspects of SCREAM 3 km's top-of-atmosphere radiative fluxes, precipitation rates, and circulations are in good agreement with observations and reanalysis, with notable differences, including a drier lower free-troposphere in the Tropics, reduced precipitation and humidity over the Tropical West Pacific, and poleward shifted Southern Hemisphere midlatitude jet. In response to warming, SCREAM 3 km predicts a total radiative feedback within the top 15% of the CMIP5 and CMIP6 models, which puts it substantially higher than the feedback reported by other kilometer-scale models. SCREAM 3 km's high radiative feedback stems from a strongly positive shortwave cloud feedback, most prominent over the mid- and high-latitudes. SCREAM 3 km's high precipitation response also puts it among the highest of CMIP models, whereas its circulation response is within the spread of CMIP models. An ensemble of five perturbed initial condition Cess-Potter simulations with a 12 km version of SCREAM (SCREAM 12 km) is performed to characterize uncertainty and resolution sensitivity. It suggests that the uncertainty from analyzing a pair of 1-year simulations is small compared to the inter-model spread in feedbacks and precipitation response. SCREAM 12 km also produces a strong precipitation response to warming but a much lower cloud feedback and total radiative feedback. The results from these experiments suggest that the spread in climate feedbacks will likely persist in the next generation of kilometer-scale models.
54 ENVIRONMENTAL SCIENCES↗
A Novel use of Direct Simulation Monte-Carlo to Model Dynamics of COVID-19 Pandemic Spread
In this report, we evaluate a novel method for modeling the spread of COVID-19 pandemic. In this new approach we leverage methods and algorithms developed for fully-kinetic plasma physics simulations using Particle-In-Cell (PIC) Direct Simulation Monte-Carlo (DSMC) models. This approach then leverages Sandia-unique simulation capabilities, and High-Performance Computer (HPC) resources and expertise in particle-particle interactions using stochastic processes. Our hypothesis is that this approach would provide a more efficient platform with assumptions based on physical data that would then enable the user to assess the impact of mitigation strategies and forecast different phases of infection. This work addresses key scientific questions related to the assumptions this new approach must make to model the interactions of people using algorithms typically used for modeling particle interactions in physics codes (kinetic plasma, gas dynamics). The model developed uses rational/physical inputs while also providing critical insight; the results could serve as inputs to, or alternatives for, existing models. The model work presented was developed over a four-week time frame, thus far showing promising results and many ways in which this model/approach could be improved. This work is aimed at providing a proof-of-concept for this new pandemic modeling approach, which could have an immediate impact on the COVID-19 pandemic modeling, while laying a basis to model future pandemic scenarios in a manner that is timely and efficient. Additionally, this new approach provides new visualization tools to help epidemiologists comprehend and articulate the spread of this and other pandemics as well as a more general tool to determine key parameters needed in order to better predict pandemic modeling in the future. In the report we describe our model for pandemic modeling, apply this model to COVID-19 data for New York City (NYC), assess model sensitivities to different inputs and parameters and , finally, propagate the model forward under different conditions to assess the effects of mitigation and associated timing. Finally, our approach will help understand the role of asymptomatic cases, and could be extended to elucidate the role of recovered individuals in the second round of the infection, which is currently being ignored.
59 BASIC BIOLOGICAL SCIENCES↗
Temperature Field During Flame Spread over Alcohol Pools: Measurements and Modelling
A principal difference between flame spread over solid fuels and over liquid fuels is, in the latter case, the presence of liquid-phase convection ahead of the leading edge of the flame. The details of the fluid dynamics and heat transfer mechanisms in both the pulsating and uniform flame spread regimes were heavily debated, without resolution, in the 1960s and 1970s; recently, research on flame spread over pools was reinvigorated by the advent of enhanced diagnostic techniques and computational power. Temperature fields in the liquid, which enable determination of the extent of preheating ahead of the flame, were determined previously by the use of thermocouples and repetitive tests, and suggested that the surface temperature does not decrease monotonically ahead of the pulsating flame front, but that there exists a surface temperature valley. Recent predictions support this suggestion. However, others' thermocouple measurements and the recent field measurements using Holographic Interferometry (HI) did not find a similar valley. In this work we examine the temperature field using Rainbow Schlieren Deflectometry (RSD), with a measurement threshold exceeding that of conventional interferometry by a factor of 20:1, for uniform and pulsating flame spread using propanol and butanol as fuels. This technique was not applied before to flame spread over liquid pools, except in some preliminary measurements reported earlier. Noting that HI is sensitive to the refractive index while RSD responds to refractive index gradients, and that these two techniques might therefore be difficult to compare, we utilized a numerical simulation, described below, to predict and compare both types of field for the uniform and pulsating spread regimes. The experimental data also allows a validation of the model at a level of detail greater than has been attempted before.
Miller, Fletcher J.↗
Mid-Pliocene Atlantic Meridional Overturning Circulation simulated in PlioMIP2
In the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2), coupled climate models have been used to simulate an interglacial climate during the mid-Piacenzian warm period (mPWP; 3.264 to 3.025 Ma). Here, we compare the Atlantic Meridional Overturning Circulation (AMOC), poleward ocean heat transport and sea surface warming in the Atlantic simulated with these models. In PlioMIP2, all models simulate an intensified mid-Pliocene AMOC. However, there is no consistent response in the simulated Atlantic ocean heat transport nor in the depth of the Atlantic overturning cell. The models show a large spread in the simulated AMOC maximum, the Atlantic ocean heat transport and the surface warming in the North Atlantic. Although a few models simulate a surface warming of ~8–12°C in the North Atlantic, similar to the reconstruction from Pliocene Research, Interpretation and Synoptic Mapping (PRISM) version 4, most models appear to underestimate this warming. The large model spread and model–data discrepancies in the PlioMIP2 ensemble do not support the hypothesis that an intensification of the AMOC, together with an increase in northward ocean heat transport, is the dominant mechanism for the mid-Pliocene warm climate over the North Atlantic.
Pliocene Model Intercomparison Project Phase 2 (Pl↗
Growth kinetics of the (001) face of TGS below the ferroelectric transition temperature
The growth rates of the (001) face of triglycine sulfate (TGS) from aqueous solutions were measured at 33.55 C in an apparatus which produced a laminar flow of solution past the crystal. The data of growth rate as a function of relative supersaturation were compared with the results of two well-known models: the Burton-Cabrera-Frank (1951) surface diffusion model and the birth-and-spreading growth model. Both models produced good fits to the growth rate data. However, on the basis of the qualitative aspects of the experimentally-observed growth, it is suggested that the correct growth model for these crystals is the Burton-Cabrera-Frank model.
Reiss, D. A.↗
Variability and Predictability of West African Droughts. A Review in the Role of Sea Surface Temperature Anomalies
The Sahel experienced a severe drought during the 1970s and 1980s after wet periods in the 1950s and 1960s. Although rainfall partially recovered since the 1990s, the drought had devastating impacts on society. Most studies agree that this dry period resulted primarily from remote effects of sea surface temperature (SST) anomalies amplified by local land surface-atmosphere interactions. This paper reviews advances made during the last decade to better understand the impact of global SST variability on West African rainfall at interannual to decadal time scales. At interannual time scales, a warming of the equatorial Atlantic and Pacific/Indian Oceans results in rainfall reduction over the Sahel, and positive SST anomalies over the Mediterranean Sea tend to be associated with increased rainfall. At decadal time scales, warming over the tropics leads to drought over the Sahel, whereas warming over the North Atlantic promotes increased rainfall. Prediction systems have evolved from seasonal to decadal forecasting. The agreement among future projections has improved from CMIP3 to CMIP5, with a general tendency for slightly wetter conditions over the central part of the Sahel, drier conditions over the western part, and a delay in the monsoon onset. The role of the Indian Ocean, the stationarity of teleconnections, the determination of the leader ocean basin in driving decadal variability, the anthropogenic role, the reduction of the model rainfall spread, and the improvement of some model components are among the most important remaining questions that continue to be the focus of current international projects.
West Africa↗
Simulating nationwide coupled disease and fear spread in an agent-based model
Human cognitive responses, behavioral responses, and disease dynamics co-evolve over the course of any disease outbreak, and can result in complex feedbacks. We present a dynamic agent-based model that explicitly couples the spread of disease with the spread of fear surrounding the disease, implemented within the EpiCast simulation framework. EpiCast models transmission within a realistic synthetic population, capturing individual-level interactions. In our model, fear propagates through both in-person contact and broadcast media, prompting individuals to adopt protective behaviors that reduce disease spread. In order to better understand these coupled dynamics, we create and compare a range of compartmental models to ensure that introducing additional disease states does not prevent the emergence of multiple waves in these simpler models. Additionally, we compare a range of behavioral scenarios within EpiCast, varying the level and intensity of fear and behavior change. Our results show that the addition of asymptomatic, exposed, and pre-symptomatic disease states can impact both the rate at which an outbreak progresses and its overall trajectory in compartmental models. In EpiCast, the combination of non-local fear spread via broadcasters and strong behavioral responses by fearful individuals generally leads to multiple epidemic waves, an outcome that occurs only within a narrow parameter range when fear spreads purely through local contact. Accounting for the coupled spread of fear and disease is critical for understanding disease dynamics and designing timely, targeted responses to emerging infectious threats.
60 APPLIED LIFE SCIENCES↗
Physics of turbulence spreading and explicit nonlocality
In this paper, we systematically derive a model for turbulence spreading from the basic kinetic equation. The model contains explicit nonlocal nonlinear diffusion and nonlocal growth. When the nonlocality scale parameter δ b (banana width) vanishes, this model reduces to the usual turbulence spreading model. We elucidate the mechanisms of nonlinear saturation and nonlocal growth. Results show that nonlocal effects, especially the nonlocal growth, thicken the turbulence spreading front and increase the speed of front propagation. More turbulence intensity penetrates the stable region when δ b increases. The penetration depth Δ p is proportional to $ \delta_b/L_T $, therefore the fraction of turbulence in the unstable region scales as 1 – δ b* . Lastly, the transport scales the same way.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Cloud Feedback Uncertainty in the Equatorial Pacific Across CMIP6 Models
Cloud feedback is the largest uncertainty in estimating Equilibrium Climate Sensitivity. In this study we focus on the equatorial Pacific, where CMIP6 model cloud feedback spread is notably large. Cloud radiative effects in this region are relevant for the global climate. Our findings show that models predict a consistent shift towards the ascent regime in response to El Nino-like sea surface warming. Models diverge in terms of the radiative impact due to differences in cloud characteristics in ascent and subsidence regimes. Using the observed relationship between circulation regime and cloud radiative effect, we find a reduction in the regional mean cloud feedback estimate from 0.77 to 0.22 W m -2 K -1 , though this does not substantially lessen the model spread in total feedback. Pathways to reduce this spread include: improving confidence in the regional ocean warming pattern, and using observations and models to understand cloud type and circulation interactions.
CMIP6↗
A comparison between the current models of mid-latitude spread F and data from the Arecibo Observatory
The current models of mid-latitude F sub s are studied. The assumptions and derivations of the Reid model, the Scannapieco model, and the Perkins model are presented in detail. Incoherent-scatter data of the density profiles and velocity profiles were obtained in order that the models could be evaluated on the basis of experimental data. Initial studies indicated that the Perkins model was most representative of the data from Arecibo, so a detailed comparison of the predictions of the Perkins model and the data was made. Two of four nights studied are nights with F sub s. The Perkins model is derived in a frame of reference moving with the velocity of the neutral wind; the model is transformed to the rest frame to facilitate comparison with data. Several data handling techniques are introduced. In particular, an integration interval that remains constant in length, but follows the vertical motion of the peak of the F layer is used to obtain the field integrated quantities of the Perkins model.
Imel, G.↗
Models of Wake-Vortex Spreading Mechanisms and Their Estimated Uncertainties
One of the primary constraints on the capacity of the nation's air transportation system is the landing capacity at its busiest airports. Many airports with nearly-simultaneous operations on closely-spaced parallel runways (i.e., as close as 750 ft (246m)) suffer a severe decrease in runway acceptance rate when weather conditions do not allow full utilization. The objective of a research program at NASA Ames Research Center is to develop the technologies needed for traffic management in the airport environment so that operations now allowed on closely-spaced parallel runways under Visual Meteorological Conditions can also be carried out under Instrument Meteorological Conditions. As part of this overall research objective, the study reported here has developed improved models for the various aerodynamic mechanisms that spread and transport wake vortices. The purpose of the study is to continue the development of relationships that increase the accuracy of estimates for the along-trail separation distances available before the vortex wake of a leading aircraft intrudes into the airspace of a following aircraft. Details of the models used and their uncertainties are presented in the appendices to the paper. Suggestions are made as to the theoretical and experimental research needed to increase the accuracy of and confidence level in the models presented and instrumentation required or more precise estimates of the motion and spread of vortex wakes. The improved wake models indicate that, if the following aircraft is upwind of the leading aircraft, the vortex wakes of the leading aircraft will not intrude into the airspace of the following aircraft for about 7s (based on pessimistic assumptions) for most atmospheric conditions. The wake-spreading models also indicate that longer time intervals before wake intrusion are available when atmospheric turbulence levels are mild or moderate. However, if the estimates for those time intervals are to be reliable, further study is necessary to develop the instrumentation and procedures needed to accurately define when the more benign atmospheric conditions exist.
Rossow, Vernon J.↗
A dynamic statistical model for explaining the spread of COVID-19: A New Mexico Case Study.
Abstract not provided.
Shand, Lyndsay↗
A model for equatorial explosive spread F
Explosive spread F was first described by Woodman and LaHoz (1976). In such events the 50 MHz radar signal rises at Jicamarca to 10-20 dB above the noise level within a few milliseconds but then disappears within 100 ms or less. It has been suggested that electric fields from thunderstorms might drive a plasma instability which could cause these echoes, and recent observations (Woodman and Kudeki, 1984) provide convincing evidence for this triggering. Here, the instability mechanism is discussed and it is shown that transient thunderstorm electric fields comparable to those recently observed by rockets in the midlatitude ionosphere could excite a rapidly growing two-stream plasma instability that is driven by the ExB drift of the F region electrons in the short period (less than the ion gyroperiod) before the ions reach the same velocity.
Kelley, M. C.↗