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The net result is that FRESIP will produce high quality rotational data for a large (and essentially volume-limited) sample of solar-type stars. Moreover, the observed slight changes in rotation period will indicate the nature and degree of differential rotation on those stars. Both parameters are central to our understanding of the evolution of the Sun.
The surface of the planet Mars is characterized by two different hemispheres: old densely cratered structures in the Southern Uplands, and sparsely cratered younger topographically lower regions covering approximately the northern third of the planet's surface. The model for explaining these global surface structures is characterized by the following features: (1) homogeneous accretion of Mars; (2) formation of a metal melt layer; (3) northward translation of the undifferentiated core due to a Rayleigh-Taylor instability; (4) vigorous convection in the southern parts and formation of the Southern Uplands' crust; (5) fragmentation of the primordial core, slowly dissolving rockbergs, beginning of Tharsis uplift and volcanism; (6) formation of the Northern Lowlands' crust from only weakly differentiated silicatic material; and (7) reaching of the present state with symmetrically placed core and further thermal evolution.
The energy dependence for the singlet sector of Parton Distributions Functions (PDFs) is described by an entangled pair of ordinary linear differential equations. Although there are no exact analytic solutions, it is possible to provide approximated results depending on the assumptions and the methodology adopted. These results differ in their sub-leading, neglected terms and ultimately they are associated with different treatments of the theoretical uncertainties. In this work, a novel analytic approach in Mellin space is presented and a new methodology for obtaining closed and exponentiated analytic solutions is devised. Different results for the DGLAP evolution at Next-Leading-Order are compared, discussing advantages and disadvantages for each solution. The generalizations to higher orders are addressed.
Based on the delays of these (Global Positioning System-GPS)signals, we have generated high resolution global ionospheric TEC (Total Electronic Changes) maps at 15-minute intervals. Using a differential method comparing storm time maps with quiet time maps, we find that the ionopshere during this time storm has increased significantly (the percentage change relative to quiet times is greater than 150 percent) ...These preliminary results (those mentioned above plus other in the paper)indicate that the differential maping method, which is based on GPS network measurements appears to be a useful tool for studying the global pattern and evolution process of the entire ionospheric perturbation.
The nonlinear development of disturbances in stratified shear flows (having a local Richardson number of value less than one quarter) is considered. Such modes are initially fast growing but, like related studies, we assume that the viscous, non-parallel spreading of the shear layer results in them evolving in a linear fashion until they reach a position where their amplitudes are large enough and their growth rates have diminished sufficiently so that amplitude equations can be derived using weakly nonlinear and non-equilibrium critical-layer theories. Four different basic integro-differential amplitude equations are possible, including one due to a novel mechanism; the relevant choice of amplitude equation, at a particular instance, being dependent on the relative sizes of the disturbance amplitude, the growth rate of the disturbance, its wavenumber, and the viscosity of the fluid. This richness of choice of possible nonlinearities arises mathematically from the indicial Frobenius roots of the governing linear inviscid equation (the Taylor-Goldstein equation) not, in general, differing by an integer. The initial nonlinear evolution of a mode will be governed by an integro-differential amplitude equations with a cubic nonlinearity but the resulting significant increase in the size of the disturbance's amplitude leads on to the next stage of the evolution process where the evolution of the mode is governed by an integro-differential amplitude equations with a quintic nonlinearity. Continued growth of the disturbance amplitude is expected during this stage, resulting in the effects of nonlinearity spreading to outside the critical level, by which time the flow has become fully nonlinear.
Recurrent neural networks (RNNs) have recently been extensively applied to model the time evolution in fluid dynamics, weather predictions, and even chaotic systems due to their ability to capture temporal dependencies and sequential patterns in data. Here we present an RNN model based on convolutional neural networks for modeling the nonlinear nonadiabatic dynamics of hybrid quantum-classical systems. The dynamical evolution of the hybrid systems is governed by equations of motion for classical degrees of freedom and von Neumann equation for electrons. The Physics-Aware Recurrent Convolution (PARC) neural network structure incorporates a differentiator-integrator architecture that inductively models the spatiotemporal dynamics of generic physical systems. Here, we apply our RNN approach to learn the space-time evolution of a one-dimensional semiclassical Holstein model after an interaction quench. For shallow quenches (small changes in electron-lattice coupling), the deterministic dynamics can be accurately captured using a single-CNN-based recurrent network. In contrast, deep quenches induce chaotic evolution, making long-term trajectory prediction significantly more challenging. Nonetheless, we demonstrate that the PARC-CNN architecture can effectively learn the statistical climate of the Holstein model under deep-quench conditions.
The inferred compositions of mainbelt asteroids set constraints on the nature and degree of collisional evolution of the asteroids. The existence of a basaltic crust on 4 Vesta seems to require that there has been very little collisional evolution since the presumably ancient solidification of its crust, which is consistent with most recent models of collisional evolution. But interpretations of the compositions of M- and S-type asteroids as collisionally stripped cores of differentiated parent bodies argue for much more extensive collisions. A major problem is presented by the extreme rarity of olivine-rich asteroids and olivine meteorites. Studies of the compositions of members of dynamical families suggest that most supposed families are either not real, or at least are not genetically related fragments of a cosmochemically reasonable precursor body. The mutual incompatibilities among various 'accepted' traits of the asteroids deserve further study in order to develop a self-consistent scenario for the chemical and physical evolution of the asteroids.
Here, this work presents the first application of isotopically labeled LLM-105 (2,6-diamino-3,5-dinitropyrazine-1-oxide) to investigate thermal decomposition pathways. Specially synthesized LLM-105 isotopologues were utilized to isolate the influence of labeled 15 NO 2 nitro groups on the formation of lightgas products. Simultaneous differential scanning calorimetry, thermo-gravimetric, and mass spectrometry measurements were employed to track the evolution of product gases, enabling the direct comparison of isotopically shifted species with unlabeled LLM-105. Key findings show that C 2 N 2 production is mainly dependent on nitrogen sources from either the amine groups or the pyrazine ring (i.e., not the nitro groups). The formation of NO, N 2 , and N 2 O all involves the nitro groups to some extent. NO (nitric oxide) was found to be the predominant gas species directly formed from the nitro group of LLM-105. In contrast, mixed nitrogen isotopologues of N 2 and N 2 O (i.e., 14 N 15 N and 15 NNO) formed more readily in comparison to their pure counterparts (i.e., 15 N 2 and 15 N 2 O). This indicates the amine and/or pyrazine groups of LLM-105, in addition to the nitro group, are involved in the decomposition pathways forming N 2 and N 2 O. In addition, our investigation led to the discovery of two previously unreported decomposition products (CHO and HNCO), which were confirmed through hydrogen labelling utilizing deuterium isotopes. These results provide detailed speciation trends of gaseous products during LLM-105 decomposition, offering new insights into reaction pathways. Experimental data reported here will support the development of a detailed chemical kinetics model for LLM-105, essential for the safe handling of high explosives.
Polymer-derived ceramics (PDCs) remain at the forefront of research for a variety of applications including ultra-high-temperature ceramics, energy storage and functional coatings. Despite their wide use, questions remain about the complex structural transition from polymer to ceramic and how local structure influences the final microstructure and resulting properties. This is further complicated when nanofillers are introduced to tailor structural and functional properties, as nanoparticle surfaces can interact with the matrix and influence the resulting structure. The inclusion of crystalline nanofiller produces a mixed crystalline–amorphous composite, which poses characterization challenges. With this study, we aim to address these challenges with a local-scale structural study that probes changes in a polysiloxane matrix with incorporated copper nanofiller. Composites were processed at three unique temperatures to capture mixing, pyrolysis and initial crystallization stages for the pre-ceramic polymer. We observed the evolution of the nanofiller with electron microscopy and applied synchrotron X-ray diffraction with differential pair distribution function (d-PDF) analysis to monitor changes in the matrix's local structure and interactions with the nanofiller. The application of the d-PDF to PDC materials is novel and informs future studies to understand interfacial interactions between nanofiller and matrix throughout PDC processing.
The gravitational collapse of a rotating cloud or vortex is analyzed by expanding the dependent variables in the equations of motion in two-dimensional Taylor series in the space variables. It is shown that the gravitation and rotation terms in the equations are of first order in the space variables, the pressure gradient terms are of second order, and the turbulent viscosity term is of third order. The presence of a turbulent viscosity insures that the initial rotation is solid-body-like near the origin. The effect of pressure on the collapse process is found to depend on the shape of the initial density disturbance at the origin. Dimensionless collapse times, as well as the evolution of density and velocity, are calculated by solving numerically the system of nonlinear ordinary differential equations resulting from the series expansions. The axial inflow plays an important role and allows collapse to occur even when the rotation is large. An approximate solution of the governing partial differential equations is also given; the equations are used to study the spacial distributions of the density and velocity.
The gravitational collapse of a rotating cloud or vortex is analyzed by expanding the dependent variables in the equations of motion in two-dimensional Taylor series in the space variables. It is shown that the gravitation and rotation terms in the equations are of first order in the space variables, the pressure gradient terms are of second order, and the turbulent viscosity term is of third order. The presence of a turbulent viscosity insures that the initial rotation is solid-body-like near the origin. The effect of pressure on the collapse process is found to depend on the shape of the intial density disturbance at the origin. Dimensionless collapse times, as well as the evolution of density and velocity, are calculated by solving numerically the system of nonlinear ordinary differential equations resulting from the series expansions. The axial inflow plays an important role and allows collapse to occur even when the rotation is large. An approximate solution of the governing partial differential equations is also given, in order to study the spacial distributions of the density and velocity.
The gravitational collapse of a rotating cloud or vortex is analyzed by expanding the dependent variables in the equations of motion in two-dimensional Taylor series in the space variables. It is shown that the gravitational and rotational terms in the equations are of first order in the space variables, the pressure-gradient terms are of second order, and the turbulent-viscosity term is of third order. The presence of turbulent viscosity ensures that the initial rotation is solid-body-like near the origin. The effect of pressure on the collapse process is found to depend on the shape of the initial density disturbance at the origin. Dimensionless collapse times, as well as the evolution of density and velocity, are calculated by solving numerically the system of nonlinear ordinary differential equations resulting from the series expansions. The axial flow is always inward and allows collapse to occur (axially) even when the rotation is large. An approximate solution of the governing partial differential equations is also given in order to study the spatial distributions of the density and velocity.
The major factors in the evolution of the lunar surface have not been determined yet. Huge lava flows and lunar differentiation, though commonly assumed, is in discord with much of the evidence. The alternative is for most of the surface to represent the last stages of accretion of the moon only, with the chemical differentiation having taken place previously in the source material. Radar, seismic, surface exposure, and mascon evidence can then be accounted for. A large-scale surface transport mechanism of soil must then have been present.
Containerless processing using electromagnetic levitation (EML) is a powerful technique in the investigation of reactive molten metal systems. On ground, the power required to overcome the weight of the sample is sufficient to cause significant heating and induce substantial melt convection. In microgravity, the heating and positioning fields may be decoupled and the field strength may be varied to achieve the desired level of convection within the limits set by the geometry of the levitation coil and the sample size. From high-speed digital images of the double recalescence behavior of Fe-Cr-Ni alloys in ground-based testing and in reduced-gravity aboard the NASA KC-135 parabolic aircraft, we have shown that phase selection can be predicted based on a growth competition model. An important parameter in this model is the delay time between primary nucleation and subsequent nucleation of the stable solid within the liquid/metastable solid array. This delay time is a strong function of composition and a weak function of the undercooling of the melt below the metastable liquidus. From the results obtained during the first Microgravity Sciences Laboratory (MSL-1) mission, we also know that convection may significantly influence the delay time, especially at low undercoolings. Currently, it is unclear what mechanism controls the formation of a heterogeneous site that allows nucleation of the austenitic phase on the pre-existing ferrite skeleton. By examining the behavior of the delay time under different convective conditions, we hypothesize that we can differentiate between several of these mechanisms to gain an understanding of how to control microstructural. evolution. We will anchor these predictions by examining samples quenched at different times following primary recalescence in microgravity. A second important parameter in the growth competition model is the identification of the growth rate of the stable phase into the semi-solid array that formed during primary recalescence. Current dendritic growth theory is inadequate in predicting solidification behavior under these conditions as metallographic analyses show that stable phase growth proceeds along the interface between the metastable solid and residual liquid. Since growth velocity is independent of the initial undercooling relative to the metastable liquidus, we hypothesize that purely thermal effects can be separated from other important growth model parameters by careful selection of the liquid composition in a ternary system.
Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving physical systems described by partial differential equations (PDEs). However, their accuracy in dynamical systems, particularly those involving sharp moving boundaries with complex initial morphologies, remains a challenge. Here, this study introduces an approach combining residual-based adaptive refinement (RBAR) with causality-informed training to enhance the performance of PINNs in solving spatio-temporal PDEs. Our method employs a three-step iterative process: initial causality-based training, RBAR-guided domain refinement, and subsequent causality training on the refined mesh. Applied to the Allen-Cahn equation, a widely-used model in phase field simulations, our approach demonstrates significant improvements in solution accuracy and computational efficiency over traditional PINNs. Notably, we observe an ‘overshoot and relocate’ phenomenon in dynamic cases with complex morphologies, showcasing the method’s adaptive error correction capabilities. This synergistic interaction between RBAR and causality training enables accurate capture of interface evolution, even in challenging scenarios where traditional PINNs fail. Our framework not only resolves the limitations of uniform refinement strategies but also provides a generalizable methodology for solving a broad range of spatio-temporal PDEs. The enhanced performance of the RBAR–causality combined framework demonstrates its strong potential for advancing PINN-based modeling of physical systems characterized by complex, evolving interfaces.
A technique is developed for systematically deriving a 'prolongation structure' - a set of interrelated potentials and pseudopotentials - for nonlinear partial differential equations in two independent variables. When this is applied to the Korteweg-de Vries equation, a new infinite set of conserved quantities is obtained. Known solution techniques are shown to result from the discovery of such a structure: related partial differential equations for the potential functions, linear 'inverse scattering' equations for auxiliary functions, Backlund transformations. Generalizations of these techniques will result from the use of irreducible matrix representations of the prolongation structure.
Simple models of the thermal and chemical evolution of a planetary interior are developed to explore the possible consequences of a chemically buoyant depleted mantle layer for planetary evolution. As the depleted layer thickens the melting temperature at the top of the underlying convecting mantle also increases and the degree of partial melting of the mantle added to the depleted layer decreases. As the less depleted mantle with less positive compositional buoyancy is added, the negative thermal buoyancy of the layer eventually exceeds its positive compositional buoyancy. The depleted layer then sinks into and mixes with the convecting interior. On Venus the population of impact craters is indistinguishable from a random distribution over the surface and gives a surface age of about 500 Myr. It is suggested that the above mechanism may explain this episodic global resurfacing of Venus.
The Southern Great Plains 1997 (SGP97) field experiment was conducted in Oklahoma during June-July 1997 to validate the models used for computing remote soil moisture using measurements by microwave radiometers. One of the objectives of SGP97 was to examine the effect of soil moisture on the evolution of the Atmospheric Boundary Layer (ABL) and clouds over the Southern Great Plains (SGP) during the warm season. The LASE (Lidar Atmospheric Sensing Experiment) airborne DIAL (Differential Absorption Lidar) system, which was flown autonomously on the NASA ER-2 aircraft during previous missions, was reconfigured to fly on the NASA P3 research aircraft. During SGP97 LASE was used to study the morning evolution of the ABL, particularly as manifested in the development of the convective boundary layer, and to study the influence of soil moisture variations on the development of ABL. The ABL development is strongly influenced by the surface energy budget, which is in turn influenced by soil moisture, mesoscale meteorology, clouds, and solar insolation. LASE data acquired during this mission are being used to study the ABL water vapor budget, the development of the ABL, spatial and temporal variabilities in the ABL, and the meteorological factors that influence the ABL development. This field experiment also permitted comparisons of LASE water vapor measurements with water vapor profiles acquired by radiosondes launched at the DOE (Department of Energy) Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) site and at NASA/Wallops Flight Facility, as well as with measurements from other SGP97 aircraft.