We introduce the path length probability density function(PPDF) method, which is based on an equivalence theorem and parameterizes the aerosol scattering effect by adding four factors to the atmospheric transmittance ...We introduce the path length probability density function(PPDF) method, which is based on an equivalence theorem and parameterizes the aerosol scattering effect by adding four factors to the atmospheric transmittance model. Using simulated observations in the O2-A band, we examined the utility of the PPDF-based method to account for the aerosol scattering effect. First, observations were simulated using a forward model under different aerosol conditions; PPDF factors were then retrieved using an optimal estimation method; PPDF factors were used to reconstruct the observations; and finally, simulated true observations and reconstructions were compared. Analysis of the difference between the true observations and reconstructions confirmed the utility of the PPDF-based method. Additionally, the O2 band was demonstrated to be an efficient observing band for assisting the remote sensing of atmospheric trace gases in the near-infrared band.展开更多
The conventionally separated treatments for strangelets and strange stars are now unified with a more comprehensive theoretical description for objects ranging from strangelets to strange stars. After constraining the...The conventionally separated treatments for strangelets and strange stars are now unified with a more comprehensive theoretical description for objects ranging from strangelets to strange stars. After constraining the model parameter according to the Witten–Bodmer hypothesis and observational mass–radius probability distribution of pulsars, we investigate the properties of this kind of objects. It is found that the energy per baryon decreases monotonically with increasing baryon number and reaches its minimum at the maximum baryon number, corresponding to the most massive strange star. Due to the quark depletion,an electric potential well is formed on the surface of the quarkpart. For a rotational bare strange star, a magnetic field with the typical strength in pulsars is generated.展开更多
Numerical prediction of turbulent mixing can be divided into two subproblems: to predict the geometrical extent of a mixing region and to predict the mixing properties on an atomic or molecular scale, within the mixin...Numerical prediction of turbulent mixing can be divided into two subproblems: to predict the geometrical extent of a mixing region and to predict the mixing properties on an atomic or molecular scale, within the mixing region. The former goal suffices for some purposes, while important problems of chemical reactions(e.g. flames) and nuclear reactions depend critically on the second goal in addition to the first one. Here we review recent progress in establishing a conceptual reformulation of convergence, and we illustrate these concepts with a review of recent numerical studies addressing turbulence and mixing in the high Reynolds number limit. We review significant progress on the first goal, regarding the mixing region, and initial progress on the second goal, regarding atomic level mixing properties. New results concerning non-uniqueness of the infinite Reynolds number solutions and other consequences of a renormalization group point of view, to be published in detail elsewhere, are summarized here.The notion of stochastic convergence(of probability measures and probability distribution functions) replaces traditional pointwise convergence. The primary benefit of this idea is its increased stability relative to the statistical "noise" which characterizes turbulent flow. Our results also show that this modification of convergence, with sufficient mesh refinement, may not be needed. However, in practice, mesh refinement is seldom sufficient and the stochastic convergence concepts have a role.Related to this circle of ideas is the observation that turbulent mixing, in the limit of high Reynolds number, appears to be non-unique. Not only have multiple solutions been observed(and published) for identical problems, but simple physics based arguments and more refined arguments based on the renormalization group come to the same conclusion.Because of the non-uniqueness inherent in numerical models of high Reynolds number turbulence and mixing, we also include here numerical examples of validation. The algorithm we use here has two essential components. We depend on Front Tracking to allow accurate resolution of flows with sharp interfaces or steep gradients(concentration or thermal), as are common in turbulent mixing problems. The higher order and enhanced algorithms for interface tracking, both those already developed, and those proposed here, allow a high resolution and uniquely accurate description of sample mixing problems. Additionally, we depend on the use of dynamic subgrid scale models to set otherwise missing values for turbulent transport coefficients, a step that breaks the non-uniqueness.展开更多
基金supported by the Key Program of the National Natural Science Foundation of China(Grant No.41130528)
文摘We introduce the path length probability density function(PPDF) method, which is based on an equivalence theorem and parameterizes the aerosol scattering effect by adding four factors to the atmospheric transmittance model. Using simulated observations in the O2-A band, we examined the utility of the PPDF-based method to account for the aerosol scattering effect. First, observations were simulated using a forward model under different aerosol conditions; PPDF factors were then retrieved using an optimal estimation method; PPDF factors were used to reconstruct the observations; and finally, simulated true observations and reconstructions were compared. Analysis of the difference between the true observations and reconstructions confirmed the utility of the PPDF-based method. Additionally, the O2 band was demonstrated to be an efficient observing band for assisting the remote sensing of atmospheric trace gases in the near-infrared band.
基金supported by the National Natural Science Foundation of China (11135011, 11120101005, 11275248, 11475110,11475115, 11575190 and 11525524)the National Key Basic Research Program of China (2013CB834400)+1 种基金the Knowledge Innovation Project of the Chinese Academy of Sciences (KJCX2-EW-N01)supported by the HPC Cluster of SKLTP/ITP-CAS and the Supercomputing Center, CNIC of CAS
文摘The conventionally separated treatments for strangelets and strange stars are now unified with a more comprehensive theoretical description for objects ranging from strangelets to strange stars. After constraining the model parameter according to the Witten–Bodmer hypothesis and observational mass–radius probability distribution of pulsars, we investigate the properties of this kind of objects. It is found that the energy per baryon decreases monotonically with increasing baryon number and reaches its minimum at the maximum baryon number, corresponding to the most massive strange star. Due to the quark depletion,an electric potential well is formed on the surface of the quarkpart. For a rotational bare strange star, a magnetic field with the typical strength in pulsars is generated.
基金supported in part by the Nuclear Energy University Program of the Department of Energy,project NEUP-09-349,Battelle Energy Alliance LLC 00088495(subaward with DOE as prime sponsor),Leland Stanford Junior University 2175022040367A(subaward with DOE asprime sponsor),Army Research Office W911NF0910306This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory,which is supported by the Office of Science of the U.S.Department of Energy under contract DE-AC02-06CH11357.Stony Brook University Preprint number SUNYSB-AMS-12-04
文摘Numerical prediction of turbulent mixing can be divided into two subproblems: to predict the geometrical extent of a mixing region and to predict the mixing properties on an atomic or molecular scale, within the mixing region. The former goal suffices for some purposes, while important problems of chemical reactions(e.g. flames) and nuclear reactions depend critically on the second goal in addition to the first one. Here we review recent progress in establishing a conceptual reformulation of convergence, and we illustrate these concepts with a review of recent numerical studies addressing turbulence and mixing in the high Reynolds number limit. We review significant progress on the first goal, regarding the mixing region, and initial progress on the second goal, regarding atomic level mixing properties. New results concerning non-uniqueness of the infinite Reynolds number solutions and other consequences of a renormalization group point of view, to be published in detail elsewhere, are summarized here.The notion of stochastic convergence(of probability measures and probability distribution functions) replaces traditional pointwise convergence. The primary benefit of this idea is its increased stability relative to the statistical "noise" which characterizes turbulent flow. Our results also show that this modification of convergence, with sufficient mesh refinement, may not be needed. However, in practice, mesh refinement is seldom sufficient and the stochastic convergence concepts have a role.Related to this circle of ideas is the observation that turbulent mixing, in the limit of high Reynolds number, appears to be non-unique. Not only have multiple solutions been observed(and published) for identical problems, but simple physics based arguments and more refined arguments based on the renormalization group come to the same conclusion.Because of the non-uniqueness inherent in numerical models of high Reynolds number turbulence and mixing, we also include here numerical examples of validation. The algorithm we use here has two essential components. We depend on Front Tracking to allow accurate resolution of flows with sharp interfaces or steep gradients(concentration or thermal), as are common in turbulent mixing problems. The higher order and enhanced algorithms for interface tracking, both those already developed, and those proposed here, allow a high resolution and uniquely accurate description of sample mixing problems. Additionally, we depend on the use of dynamic subgrid scale models to set otherwise missing values for turbulent transport coefficients, a step that breaks the non-uniqueness.
