Tsunami Generation, Consequences on Coastlines, and Potential Global Climate Effects due to Asteroids Impacting Earth’s Oceans

2020 ◽  
Author(s):  
Souheil Ezzedine ◽  
Luke Oman ◽  
David Dearborn ◽  
Paul Miller ◽  
Megan Syal
Keyword(s):  
Atmospheric Chemistry ◽  
Water Waves ◽  
Adaptive Mesh Refinement ◽  
Department Of Energy ◽  
Coupling Scheme ◽  
Tsunami Generation ◽  
Ocean Water ◽  
Asteroid Impact ◽  
Structured Adaptive Mesh Refinement ◽  
The Impact

<p>Despite that the annual probability of an asteroid impact on earth is low, but over time, such catastrophic events are inevitable and can have negative global consequences. Several institutions around the world have come together to address global consequences of asteroids impacting earth. For example, interest in assessing the tsunami generation and impact consequences has led us to develop a physics-based framework to seamlessly simulate the event from source (asteroid entry) to ocean impact (splash) to long wave generation, propagation, and their catastrophic risk to people and infrastructure in coastal regions such inundation of the shoreline. The non-linear effects of the asteroid impact on the ocean surface are simulated using the hydrocode GEODYN to create the impact source for the shallow water wave propagation code, SWWP. The GEODYN-SWWP coupling is based on the structured adaptive mesh refinement infrastructure; SAMRAI developed at LLNL. Another consequence of ocean impact is the potentially global effects of an event that would otherwise be of only regional or local importance, should it occur on land. Only a fraction of the total impact energy is converted into water waves that have the ability to globally propagate in the oceans. The remaining energy is consumed by the “evaporation” of the asteroid, the ocean water being transformed into vapor and mist and the fractionization of ocean water and vapor into chlorine and bromine which alter the atmospheric chemistry, therefore impacting globally the Ozone layer and earth temperature. In this paper, we present our scheme of creating the source -- including nonlinear transient cratering and nearfield waves, generating the vapor cloud and the chemical speciation source load of chlorine and bromine to assess the global circulation of those plumes and their effects on the climate. We also present our coupling scheme of the hydrodynamic source using GEODYN with the global atmospheric circulation code GEOSCCM and illustrate the scheme on the PDC 2017 and PDC 2019 asteroid impact scenarios. We illustrate the coupling scheme for asteroids impact along the US, Europe and Asia shorelines. We illustrate, by examples, how the predictions of these numerical tools can help international, state and local government agencies reduce the risks and prepare and implement a  response and recovery plan.  This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.</p>

Automated Quantification of the Impact of Defects on the Mechanical Behavior of Deoxyribonucleic Acid Origami Nanoplates

2017 ◽  
Vol 139 (4) ◽  
Author(s):  
Bowen Liang ◽  
Anand Nagarajan ◽  
Michael W. Hudoba ◽  
Ricardo Alvarez ◽  
Carlos E. Castro ◽  
...  
Keyword(s):  
Mechanical Behavior ◽  
Self Assembly ◽  
Adaptive Mesh Refinement ◽  
Deoxyribonucleic Acid ◽  
Structural Integrity ◽  
Adaptive Mesh ◽  
Dna Origami ◽  
Structured Adaptive Mesh Refinement ◽  
Dna Strands ◽  
The Impact

Deoxyribonucleic acid (DNA) origami is a method for the bottom-up self-assembly of complex nanostructures for applications, such as biosensing, drug delivery, nanopore technologies, and nanomechanical devices. Effective design of such nanostructures requires a good understanding of their mechanical behavior. While a number of studies have focused on the mechanical properties of DNA origami structures, considering defects arising from molecular self-assembly is largely unexplored. In this paper, we present an automated computational framework to analyze the impact of such defects on the structural integrity of a model DNA origami nanoplate. The proposed computational approach relies on a noniterative conforming to interface-structured adaptive mesh refinement (CISAMR) algorithm, which enables the automated transformation of a binary image of the nanoplate into a high fidelity finite element model. We implement this technique to quantify the impact of defects on the mechanical behavior of the nanoplate by performing multiple simulations taking into account varying numbers and spatial arrangements of missing DNA strands. The analyses are carried out for two types of loading: uniform tensile displacement applied on all the DNA strands and asymmetric tensile displacement applied to strands at diagonal corners of the nanoplate.

scholarly journals AMReX: Block-structured adaptive mesh refinement for multiphysics applications

2021 ◽  
pp. 109434202110228
Author(s):  
Weiqun Zhang ◽  
Andrew Myers ◽  
Kevin Gott ◽  
Ann Almgren ◽  
John Bell
Keyword(s):  
Adaptive Mesh Refinement ◽  
Mesh Refinement ◽  
Computational Cost ◽  
Adaptive Mesh ◽  
Uniform Mesh ◽  
Physical Processes ◽  
Structured Adaptive Mesh Refinement ◽  
Core Elements ◽  
Accelerator Design ◽  
Block Structured

Block-structured adaptive mesh refinement (AMR) provides the basis for the temporal and spatial discretization strategy for a number of Exascale Computing Project applications in the areas of accelerator design, additive manufacturing, astrophysics, combustion, cosmology, multiphase flow, and wind plant modeling. AMReX is a software framework that provides a unified infrastructure with the functionality needed for these and other AMR applications to be able to effectively and efficiently utilize machines from laptops to exascale architectures. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving accurate descriptions of different physical processes in complex multiphysics algorithms. AMReX supports algorithms that solve systems of partial differential equations in simple or complex geometries and those that use particles and/or particle–mesh operations to represent component physical processes. In this article, we will discuss the core elements of the AMReX framework such as data containers and iterators as well as several specialized operations to meet the needs of the application projects. In addition, we will highlight the strategy that the AMReX team is pursuing to achieve highly performant code across a range of accelerator-based architectures for a variety of different applications.

scholarly journals Application of random forest regression to the calculation of gas-phase chemistry within the GEOS-Chem chemistry model v10

2019 ◽  
Vol 12 (3) ◽  
pp. 1209-1225 ◽  
Author(s):  
Christoph A. Keller ◽  
Mat J. Evans
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Gas Phase ◽  
Atmospheric Chemistry ◽  
Random Forest Regression ◽  
Data Set ◽  
Gas Phase Chemistry ◽  
Chemical Conditions ◽  
Phase Chemistry ◽  
The Impact

Abstract. Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models are numerically intense, and previous attempts to reduce the numerical cost of chemistry solvers have not delivered transformative change. We show here the potential of a machine learning (in this case random forest regression) replacement for the gas-phase chemistry in atmospheric chemistry transport models. Our training data consist of 1 month (July 2013) of output of chemical conditions together with the model physical state, produced from the GEOS-Chem chemistry model v10. From this data set we train random forest regression models to predict the concentration of each transported species after the integrator, based on the physical and chemical conditions before the integrator. The choice of prediction type has a strong impact on the skill of the regression model. We find best results from predicting the change in concentration for long-lived species and the absolute concentration for short-lived species. We also find improvements from a simple implementation of chemical families (NOx = NO + NO2). We then implement the trained random forest predictors back into GEOS-Chem to replace the numerical integrator. The machine-learning-driven GEOS-Chem model compares well to the standard simulation. For ozone (O3), errors from using the random forests (compared to the reference simulation) grow slowly and after 5 days the normalized mean bias (NMB), root mean square error (RMSE) and R2 are 4.2 %, 35 % and 0.9, respectively; after 30 days the errors increase to 13 %, 67 % and 0.75, respectively. The biases become largest in remote areas such as the tropical Pacific where errors in the chemistry can accumulate with little balancing influence from emissions or deposition. Over polluted regions the model error is less than 10 % and has significant fidelity in following the time series of the full model. Modelled NOx shows similar features, with the most significant errors occurring in remote locations far from recent emissions. For other species such as inorganic bromine species and short-lived nitrogen species, errors become large, with NMB, RMSE and R2 reaching >2100 % >400 % and <0.1, respectively. This proof-of-concept implementation takes 1.8 times more time than the direct integration of the differential equations, but optimization and software engineering should allow substantial increases in speed. We discuss potential improvements in the implementation, some of its advantages from both a software and hardware perspective, its limitations, and its applicability to operational air quality activities.

scholarly journals Effect of Secondary Carbon Nanofillers on the Electrical, Thermal, and Mechanical Properties of Conductive Hybrid Composites Based on Epoxy Resin and Graphite

Materials ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4169
Author(s):  
Marcel Zambrzycki ◽  
Krystian Sokolowski ◽  
Maciej Gubernat ◽  
Aneta Fraczek-Szczypta
Keyword(s):  
Mechanical Properties ◽  
Specific Surface ◽  
Epoxy Resin ◽  
Surface Area ◽  
Specific Surface Area ◽  
Hybrid Composites ◽  
Department Of Energy ◽  
Carbon Nanofillers ◽  
The Impact ◽  
Secondary Carbon

In this work, we present a comparative study of the impact of secondary carbon nanofillers on the electrical and thermal conductivity, thermal stability, and mechanical properties of hybrid conductive polymer composites (CPC) based on high loadings of synthetic graphite and epoxy resin. Two different carbon nanofillers were chosen for the investigation—low-cost multi-layered graphene nanoplatelets (GN) and carbon black (CB), which were aimed at improving the overall performance of composites. The samples were obtained by a simple, inexpensive, and effective compression molding technique, and were investigated by the means of, i.a., scanning electron microscopy, Raman spectroscopy, electrical conductivity measurements, laser flash analysis, and thermogravimetry. The tests performed revealed that, due to the exceptional electronic transport properties of GN, its relatively low specific surface area, good aspect ratio, and nanometric sizes of particles, a notable improvement in the overall characteristics of the composites (best results for 4 wt % of GN; σ = 266.7 S cm−1; λ = 40.6 W mK−1; fl. strength = 40.1 MPa). In turn, the addition of CB resulted in a limited improvement in mechanical properties, and a deterioration in electrical and thermal properties, mainly due to the too high specific surface area of this nanofiller. The results obtained were compared with US Department of Energy recommendations regarding properties of materials for bipolar plates in fuel cells. As shown, the materials developed significantly exceed the recommended values of the majority of the most important parameters, indicating high potential application of the composites obtained.

scholarly journals Analysis of actinic flux profiles measured from an ozonesonde balloon

2015 ◽  
Vol 15 (8) ◽  
pp. 4131-4144 ◽  
Author(s):  
P. Wang ◽  
M. Allaart ◽  
W. H. Knap ◽  
P. Stammes
Keyword(s):  
Atmospheric Chemistry ◽  
Low Cost ◽  
Green Light ◽  
Single Layer ◽  
Radiative Transfer Model ◽  
Cloud Base ◽  
Transfer Model ◽  
Actinic Flux ◽  
Clear Sky ◽  
The Impact

Abstract. A green light sensor has been developed at KNMI to measure actinic flux profiles using an ozonesonde balloon. In total, 63 launches with ascending and descending profiles were performed between 2006 and 2010. The measured uncalibrated actinic flux profiles are analysed using the Doubling–Adding KNMI (DAK) radiative transfer model. Values of the cloud optical thickness (COT) along the flight track were taken from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Cloud Physical Properties (CPP) product. The impact of clouds on the actinic flux profile is evaluated on the basis of the cloud modification factor (CMF) at the cloud top and cloud base, which is the ratio between the actinic fluxes for cloudy and clear-sky scenes. The impact of clouds on the actinic flux is clearly detected: the largest enhancement occurs at the cloud top due to multiple scattering. The actinic flux decreases almost linearly from cloud top to cloud base. Above the cloud top the actinic flux also increases compared to clear-sky scenes. We find that clouds can increase the actinic flux to 2.3 times the clear-sky value at cloud top and decrease it to about 0.05 at cloud base. The relationship between CMF and COT agrees well with DAK simulations, except for a few outliers. Good agreement is found between the DAK-simulated actinic flux profiles and the observations for single-layer clouds in fully overcast scenes. The instrument is suitable for operational balloon measurements because of its simplicity and low cost. It is worth further developing the instrument and launching it together with atmospheric chemistry composition sensors.

scholarly journals The mass impacts on chemosynthetic primary producers: potential implications on anammox communities and their consequences

2018 ◽  
Vol 18 (05) ◽  
pp. 440-444
Author(s):  
Noel Pérez ◽  
Jorge Luis Velazco-Vargas ◽  
Osmel Martin ◽  
Rolando Cardenas ◽  
Jesús Martínez-Frías
Keyword(s):  
Water Column ◽  
Deposition Rate ◽  
Extreme Case ◽  
Chemical Compounds ◽  
Global Scale ◽  
Biogeochemical Cycle ◽  
Potential Influence ◽  
Asteroid Impact ◽  
Global Cooling ◽  
The Impact

AbstractThe potential of a mass asteroid impact on Earth to disturb the chemosynthetic communities at global scale is discussed. Special emphasis is made on the potential influence on anammox communities and their implications in the nitrogen biogeochemical cycle. According to our preliminary estimates, anammox communities could be seriously affected as a consequence of global cooling and the large process of acidification usually associated with the occurrence of this kind of event. The scale of affectations could vary in a scenario like the Chicxulub as a function of the amount of soot, depth of the water column and the deposition rate for sulphates assumed in each case. The most severe affectations take place where the amount of soot and sulphates produced during the event is higher and the scale of time of settlements for sulphates is short, of the order of 10 h. In this extreme case, the activity of anammox is considerably reduced, a condition that may persist for several years after the impact. Furthermore, the impact of high levels of other chemical compounds like sulphates and nitrates associated with the occurrence of this kind of event are also discussed.

scholarly journals Multi-model study of mercury dispersion in the atmosphere: Vertical distribution of mercury species

2016 ◽  
Author(s):  
Johannes Bieser ◽  
Franz Slemr ◽  
Jesse Ambrose ◽  
Carl Brenninkmeijer ◽  
Steve Brooks ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Atmospheric Chemistry ◽  
Lower Troposphere ◽  
Elemental Mercury ◽  
Mercury Species ◽  
Substantial Impact ◽  
Model Studies ◽  
Model Study ◽  
The Impact ◽  
The Vertical Distribution

Abstract. Atmospheric chemistry and transport of mercury play a key role in the global mercury cycle. However, there are still considerable knowledge gaps concerning the fate of mercury in the atmosphere. This is the second part of a model inter-comparison study investigating the impact of atmospheric chemistry and emissions on mercury in the atmosphere. While the first study focused on ground based observations of mercury concentration and deposition, here we investigate the vertical distribution and speciation of mercury from the planetary boundary layer to the lower stratosphere. So far, there have been few model studies investigating the vertical distribution of mercury, mostly focusing on single aircraft campaigns. Here, we present a first comprehensive analysis based on various aircraft observations in Europe, North America, and on inter-continental flights. The investigated models proved to be able to reproduce the distribution of total and elemental mercury concentrations in the troposphere including inter-hemispheric trends. One key aspect of the study is the investigation of mercury oxidation in the troposphere. We found that different chemistry schemes were better at reproducing observed oxidized mercury (RM) patterns depending on altitude. High RM concentrations in the upper troposphere could be reproduced with oxidation by bromine while elevated concentrations in the lower troposphere were better reproduced by OH and ozone chemistry. However, the results were not always conclusive as the physical and chemical parametrizations in the chemistry transport models also proved to have a substantial impact on model results.

scholarly journals Impact of uncertainties in inorganic chemical rate constants on tropospheric composition and ozone radiative forcing

2017 ◽  
Author(s):  
Ben Newsome ◽  
Mat Evans
Keyword(s):  
Rate Constant ◽  
Atmospheric Chemistry ◽  
Rate Constants ◽  
Tropospheric Ozone ◽  
Radiative Forcing ◽  
Transport Model ◽  
Surface Ozone ◽  
Photolysis Rates ◽  
The Impact ◽  
Chemical Rate

Abstract. Chemical rate constants determine the composition of the atmosphere and how this composition has changed over time. They are central to our understanding of climate change and air quality degradation. Atmospheric chemistry models, whether online or offline, box, regional or global use these rate constants. Expert panels synthesise laboratory measurements, making recommendations for the rate constants that should be used. This results in very similar or identical rate constants being used by all models. The inherent uncertainties in these recommendations are, in general, therefore ignored. We explore the impact of these uncertainties on the composition of the troposphere using the GEOS-Chem chemistry transport model. Based on the JPL and IUPAC evaluations we assess 50 mainly inorganic rate constants and 10 photolysis rates, through simulations where we increase the rate of the reactions to the 1σ upper value recommended by the expert panels. We assess the impact on 4 standard metrics: annual mean tropospheric ozone burden, surface ozone and tropospheric OH concentrations, and tropospheric methane lifetime. Uncertainty in the rate constants for NO2 + OH    M →  HNO3, OH + CH4 → CH3O2 + H2O and O3 + NO → NO2 + O2 are the three largest source of uncertainty in these metrics. We investigate two methods of assessing these uncertainties, addition in quadrature and a Monte Carlo approach, and conclude they give similar outcomes. Combining the uncertainties across the 60 reactions, gives overall uncertainties on the annual mean tropospheric ozone burden, surface ozone and tropospheric OH concentrations, and tropospheric methane lifetime of 11, 12, 17 and 17 % respectively. These are larger than the spread between models in recent model inter-comparisons. Remote regions such as the tropics, poles, and upper troposphere are most uncertain. This chemical uncertainty is sufficiently large to suggest that rate constant uncertainty should be considered when model results disagree with measurement. Calculations for the pre-industrial allow a tropospheric ozone radiative forcing to be calculated of 0.412 ± 0.062 Wm−2. This uncertainty (15 %) is comparable to the inter-model spread in ozone radiative forcing found in previous model-model inter-comparison studies where the rate constants used in the models are all identical or very similar. Thus the uncertainty of tropospheric ozone radiative forcing should expanded to include this additional source of uncertainty. These rate constant uncertainties are significant and suggest that refinement of supposedly well known chemical rate constants should be considered alongside other improvements to enhance our understanding of atmospheric processes.

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