Interplanetary diffusion and cosmic ray modulation.
Interplanetary particle diffusion model analysis in terms of energy, position in space, direction and time
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Interplanetary particle diffusion model analysis in terms of energy, position in space, direction and time
This paper presents the results of the works carried out jointly at Stanford University and Ames Research Center under a grant from the Ballistic Missile Defense Organization (BMDO) (formerly the Strategic Defense Initiative Organization) to explain and understand the results of the two flight experiments, Bow Shock Ultra-Violet 1 and Bow Shock Ultra-Violet 2, carried out by the Organization. A portion of the material contained in this paper has been reported elsewhere in open literature. However, this paper provides (1) the details of scientific contents not available in those literature, (2) the links among those and the logical order of the efforts involved, and (3) some materials not contained in any open literature. The first author is responsible for execution of the work; the second author directed the work of the first author. In the two flight experiments mentioned above, the spectra of radiation in the ultraviolet wavelength range incident on the stagnation point of a blunt body were measured at the flight speeds of 3.8 and 5.2 km/sec over a wide range of altitudes. The results were compared first with the calculations made using the original version of the NEQAIR/STRAP codes written earlier by the second author. At low altitudes, the calculations agreed with the measurement. However, at high altitudes, the calculations underestimated the intensity of the radiation by several orders of magnitudes. A shock tube experiment was carried out at CALSPAN and a plasma-torch experiment was carried out at Stanford University to produce experimental data to help explain the discrepancy. In addition, the shock tube experiment at Ames Research Center carried out independently of the BMDO was also found to be relevant to this question. In this paper, several theoretical models are developed and calculations using the models were carried out to explain the results not only of the flight experiments but also of the CALSPAN, Stanford, and Ames experiments. The are: (1) the diffusion model for the rotational mode to explain the slowness of rotational excitation, (2) assignment of different vibrational temperatures and different relaxation rates for different molecules, and (3) the modification of the NEQAIR code to accommodate the new experimental data. This paper shows that the discrepancy between the flight data and calculation is smaller with the present model, but is still substantial.
This paper reports on ongoing research in the area of numerical simulations of hybrid plume dynamics, and describes the basic mechanisms for energy and particle transport. The solution approach assumes cylindrical geometry and includes a multiplicity of atomic reactions, as well as the presence of a strong magnetic field. The principal reactions are electron impact ionization, and resonant charge exchange between hot ions and cold neutrals. Radial particle and energy transport is mainly by diffusion. The present description includes a modified Bohm diffusion model for plasma in the core of the plume, and classical neutral particle diffusion in the cooler regions of the flow. Neutrals are allowed to 'free stream' in the low density regions, where the collision mean-free-path becomes comparable, or even larger than the characteristic dimensions of the system. A parameteric scan of the various regimes of interest has been completed and the most significant results are presented.
Experiments with a surface processes model of large-scale (1-1000 km) long-term (1-100 m.y.) erosional denudation are used to establish the controls on the evolution of a model escarpment that is related to the rifting of a continent. The mdoel describes changes in topographic form as a result of sumultaneous short- and long-range mass transport representing hillslope (diffusive) processes and fluvial transport (advection), repsectively. Fluvial entrainment is modeled as a first-order kinetic reaction which reflects the erodibility of the substrate, and therefore the fluvial system is not necessarily carrying at capacity. One dimensional and planform models demonstrate that the principal controls on the evolution of an initially steep model escarpment are (1) antecedent topography/drainage; (2) the timesale (or equivalently a length scale) in the fluvial entrainment reaction; (3) the flexural response of the lithosphere to denudation; and (4) the relative efficiencies of the short- and long-range transport processes. When rainfall and substrate lithology are uniform, a significant amount of discharge draining over the escarpment top causes it to degrade. Only when the top of the model escarpment coincides with a drainage divide can escarpment retreat occur for these conditions. An additional requirement for retreat of a model escarpment without decline is a long reaction time scale for fluvial entrainment. This corresponds to a substrate that is hard to detach by flucial erosion, and therefore to fluvial erosion that is not transport limited. Coninuous backtilting of an escarpment due ot flexural isostatic uplift in response to denudational unloading helps maintain the scarp top as a divide. It is essntial if the escarpment gradient is to be preserved during retreat in a uniform lithology. Low flexural rigidieties propote steep and slowly retreating escarpments. For given rainfall and substrate conditions, the morphology of a retraeating model escarpment is determined by the ratio of hte short-range diffusive and long range advective transport efficiencies. A low ration (which is interpreted to correspond to a more humid, temperate climate) produces a convex upper slope, and concave lower slope morphology and only major escarpments are predicted to preserve a high scarp gradient. Lithological contrasts in hte model produce more complex morphologies and predict the formation of scarps crowned by an erosionaly resistant caprock. However, resistant caprocks are not an essential requirement for model scarps to retreat. We conclude that the inferred controls and model behavior are both consistent with the present-day morphology of rifted continental margins and with modern conceptual models of landscape evolution.
A microscopic diffusion model is developed to represent solute transport in the boundary layer of a growing zeolite crystal. This model is used to describe the effect of gravity on particle shape and solute distribution. Particle dynamics and crystal growth kinetics serve as the boundary conditions of flow and convection-diffusion equations. A statistical rate theory is used to obtain the rate of solute transport across the growing interface, which is expressed in terms of concentration and velocity of solute species. Microgravity can significantly decrease the solute velocity across the growing interface compared to its earth-based counterpart. The extent of this reduction highly depends on solute diffusion constant in solution. Under gravity, the flow towards the crystal enhances solute transport rate across the growing interface while the flow away from crystals reduces this rate, suggesting a non-uniform growth rate and thus an elliptic final shape. However, microgravity can significantly reduce the influence of flow and obtain a final product with perfect spherical shape. The model predictions compare favorably with the data of space experiment of zeolites grown in space.
We have studied the transport and loss of H(+), He(+), and He(++) ions in the Earth's quiet time ring current (1 to 300 keV/e, 3 to 7 R(sub E), Kp less than 2+, absolute value of Dst less than 11, 70 to 110 degs pitchangles, all LT) comparing the standard radial diffusion model developed for the higher-energy radiation belt particles with measurements of the lower energy ring current ions in a previous paper. Large deviations of that model, which fit only 50% of the data to within a factor of 10, suggested that another transport mechanism is operating in the ring current. Here we derive a modified diffusion coefficient corrected for electric field effects on ring current energy ions that fit nearly 80% of the data to within a factor of 2. Thus we infer that electric field fluctuations from the low-latitude to midlatitude ionosphere (ionospheric dynamo) dominated the ring current transport, rather than high-latitude or solar wind fluctuations. Much of the remaining deviation may arise from convective electric field transport of the E less than 30 keV particles. Since convection effects cannot be correctly treated with this azimuthally symmetric model, we defer treatment of the lowest-energy ions to a another paper. We give chi(exp 2) contours for the best fit, showing the dependence of the fit upon the internal/external spectral power of the predicted electric and magnetic field fluctuations.
Abstract While a large latitudinal displacement of the westerly jet brings about disproportionate socioeconomic impacts over Northern Hemisphere midlatitude continents, it is not well understood as to whether the winter circulation will become wavier or less in response to climate change. Here, using observations and large ensembles of climate models, we show that changes in atmospheric waviness can be estimated from the optimal structures of the westerly jet for wavier circulation, which are obtained from an advection‐diffusion model. Thus, the changes in westerly jet structure in climate models under climate change provide a physical constraint on changes in atmospheric waviness, indicating that the North Atlantic wave activity will experience a robust decline in a warmer climate, while future North Pacific wave activity is obscured by model uncertainty rather than internal variability. These findings highlight the changes to jet stream structure as a constraint for regional circulation waviness in a changing climate.
Here, we introduce a generative modeling framework for thermodynamic computing, in which structured data are synthesized from noise by the natural time evolution of a physical system governed by Langevin dynamics. While conventional diffusion models use neural networks to perform denoising, here the information needed to generate structure from noise is encoded by the dynamics of a thermodynamic system. Training proceeds by maximizing the probability with which the computer generates the reverse of a noising trajectory, which ensures that the computer generates data with minimal heat emission. We demonstrate this framework within a digital simulation of a thermodynamic computer. If realized in analog hardware, such a system would function as a generative model that produces structured samples without the need for artificially injected noise or active control of denoising.
We report a new measurement of the cosmic-ray isotopic composition of aluminum in the low-energy range form 75 to 206 MeV per nucleon.This measurement was made using the high-energy telescope of the CRS experiment on the Voyager 1 and 2 spacecraft during the time period from 1977 to 1993 with an average solar modulation level about 497 MV, roughly the same as at Earth near sunspot minimum. We obtain approximately 430 Al events of which approximately 35 are Al-26 and 395 are Al-27. The Al isotopes were separated with an average mass resolution sigma of 0.35 amu. Our interpretation of the isotopic composition of cosmic-ray aluminum is based on a standard Leaky-Box model for the interstellar propagation of cosmic-ray nuclei using the latest cross sections of the New Mexico-Saclay collaboration as well as a disk-halo diffusion model. From our observed ratio Al-26/Al-27 of 8.3 +/- 2.4 % we deduce an average interstellar density of about 0.52 (+0.26, -0.2) atoms per cu cm. This density is larger than the value of 0.28 (+0.14, -0.11) atoms per cu cm we found from an analysis of the observed abundance of the longer lived Be-10 made using data from the Voyager detectors over almost the same time interval and using essentially the same propagation program.
The disappearance of the surface tension of the interface of a binary mixture, measured using the dynamic surface light scattering technique, is slower for a binary mixture of higher density contrast. A comparison with a naive diffusion model, expected to provide a lower limit for the speed of dissolution in the absence of gravity shows that the interfacial surface tension disappears much slower than even by diffusion with the effect becoming much more pronounced when density contrast between the liquid phases is increased. Thus, the factor most likely to be responsible for this anomalously slow dissolution is gravity. A mechanism could be based on the competition between diffusive relaxation and sedimentation at the dissolving interface.
We extend the particle-flow neural assisted simulations (arnassus) framework of fast simulation and reconstruction to entire collider events. In particular, we use two generative artificial intelligence tools, continuous normalizing flows and diffusion models, to create a set of reconstructed particle-flow objects conditioned on truth-level particles from CMS Open Simulations. While previous work focused on jets, our updated methods now can accommodate all particle-flow objects in an event along with particle-level attributes like particle type and production vertex coordinates. This approach is fully automated, entirely written in Python, and GPU-compatible. Using a variety of physics processes at the LHC, we show that the extended arnassus is able to generalize beyond the training dataset and outperforms the standard, public tool elphes.
Point defects directly impact solar cell device performance by limiting the carrier lifetime. In this work, density functional theory calculations are first used to determine the formation energy and diffusion energy barriers of dominant defects in Cu(In,Ga)Se 2 . Next, continuum reaction–diffusion models are developed to analyze the redistribution of defects during manufacturing processes. We estimate defect capture cross sections using a first-principles-based approach. Here, these cross sections are combined with our calculated defect profiles and trap energy levels to parameterize a Shockley–Read–Hall recombination model, which we implement into a device simulator to predict carrier lifetimes and device performance. In that way, a predictive technology computer aided design model is built to predict and optimize the performance of Cu(In,Ga)Se 2 solar cells.
Here, we present a computational tool, TweedleDEE, for empirically modeling diffuse gamma-ray background emission in a 1° region of the sky, using publicly available gamma-ray data off-axis from the region of interest. This background model allows a user to perform a purely data-driven search for anomalous localized sources of gamma-ray emission, including new physics. A major application of this tool would be in searching for dark matter annihilation in newly discovered astrophysical targets. For this purpose, we derive a scaling relation for determining velocity-dependent 𝐽-factors using only the stellar parameters, which can be broadly applied to obtain dark matter constraints from new targets. As an application of these tools, we use TweedleDEE and MADHATv2 to perform the first search for dark matter annihilation in the newly discovered Leo VI dwarf spheroidal galaxy, and present model constraints for a variety of choices of the annihilation channel and velocity dependence of the cross section.
The problem of the origin of the cosmic rays is still uncertain. As a theory, it should explain the support of particles and energy, the mechanism of acceleration and propagation as well as some important features obtained directly from cosmic ray experiments, such as the power spectrum and the knee. There are two kinds of models for interpreting the knee of the cosmic ray spectrum. One is the leaky box model. Another model suggests that the cut-off rigidity of the main sources causes the knee. The present paper studies the spectrum and the anisotropy of cosmic rays in an isotropic diffuse model with explosive discrete sources in an infinite galaxy.
The reverse water gas shift (RWGS) reaction is a key pathway for CO 2 utilization, particularly within Power-to-X process chains aimed at sustainable fuel and chemical production. Countercurrent chemical looping (CL-RWGS) using non-stoichiometric oxides can overcome equilibrium limitations of conventional RWGS reactors, enabling significantly higher CO 2 conversions. However, modeling the limiting performance of such systems is challenging due to their multiphase nature and coupled spatial and temporal variation in chemical composition. In this work, we present a discretized batch equilibrium model that simulates CL-RWGS reactors as a series of localized equilibrium exchanges between gas and solid elements. The model is numerically stable, computationally efficient, and free of kinetic source terms, making it well-suited for parametric studies and system-level integration. It is validated against established convection–diffusion models and shown to predict reasonable upper bounds on experimental results. Application of the model to a range of oxygen carrier materials identifies cerium–zirconium solid solutions, particularly Ce 0.80 Zr 0.20 O 2 , as a promising class offering superior oxygen storage characteristics compared to state-of-the-art La 0.6 Sr 0.4 FeO 3 . This framework provides a robust platform for materials screening, reactor sizing, and performance optimization in chemical looping systems. The model implementation is available as open-source software to support further research and development.
A single-stage membrane process has been designed for using facilitated transport membranes (FTMs) to decarbonize the coal-derived syngas from an integrated gasification combined cycle (IGCC) power plant. The necessary process model and costing method have also been developed to assess the technical feasibility and process economics. In order to account for the carrier saturation phenomenon associated with FTMs, a homogeneous reactive diffusion model is integrated into the process model. The techno-economic study reveals that the mitigated carrier saturation upon bulk CO 2 removal can lead to appreciable increases in the CO 2 permeance and CO 2 /H 2 selectivity, which can be utilized to achieve 95% CO 2 purity and 95% H 2 recovery with a CO 2 /H 2 selectivity of 50 at the complete carrier saturation. FTMs with different facilitated transport characteristics can also be arranged in a hybrid membrane configuration to render a H 2 recovery of 99% and a cost of electricity of $\$118.5$ /MWh, which is 12.5% lower than that of the benchmark Selexol process.
The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three dimensional concentration fields from atmospheric diffusion models. General conditions are derived for the "reconstructability' of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data is developed.
The ability of a zeolite shell to enhance the selective conversion of hydrocarbons through diffusional limitations was investigated using a multi-scale model of a fixed-bed reactor. The impact of shell thickness and molecule/pore size on the catalytic performance of silicalite-1 zeolite encapsulated nickel catalyst pellets for steam reforming of C1-C7 hydrocarbons is reported. A reaction–diffusion model using kinetic expressions established in literature was employed. The model was verified through comparison with reported experimental results for steam reforming data over a temperature range of 748 – 1113 K and pressure of 1 – 10 bar. Comparisons are also made against experimental data for steam reforming in the presence of a zeolite shell. Evaluation of the Weisz-Prater criterion for both the core and encapsulated catalyst confirmed mass transfer limitation induced by the utilization of a zeolite shell. The model was used to suggest an optimal thickness that balances diffusional limitations imposed by the zeolite layer on methane versus that of the heavier hydrocarbons. The optimum thickness varied as a function of hydrocarbon size and shape which determined the diffusion rates. For toluene and heptane, a 50 nm thick shell was sufficient to wholly prevent reaction. Hydrocarbons like propane and butane required a shell 7.5 and 5 μm thick. Increasing the gas-hourly-space-velocity from 10,000 to 60,000 h –1 caused a decrease in the optimum shell thickness. Furthermore, this approach can be modified for application to other mixed hydrocarbon systems to predict optimal catalyst design.