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At least 1,045 records · Page 58

Charge exchange in solar wind-cometary interactions

A simple model of a cometary spherically symmetrical atmosphere and ionosphere is considered. An analytic solution of the governing equations describing the radial distribution of the neutral and ion densities is found. The new solution is compared to the well-known solution of the equations containing only ionization terms. Neglecting recombination causes a significant overestimate of the ion density in the vicinity of the comet. An axisymmetric model of the solar wind-cometary interaction is considered, taking into account the loss of solar wind ions due to charge exchange. The calculations predict that for active comets, solar wind absorption due to charge exchange becomes important at a few thousand kilometers from the nucleus, and a surface separating the shocked solar wind from the cometary ionosphere develops in this region. These calculations are in reasonable agreement with the few observations available for the ionopause location at comets.

Gombosi, T. I.↗

Concepts for reduction of blade-vortex interaction noise

A model is developed to determine the critical parameters that control noise generation by blade-vortex interaction (BVI). The equations for evaluation BVI are derived. The analysis of BVI using the model reveals that the interaction is dependent on incoming vortex strength, blade lift, the interaction length, and the miss distance of the interaction. Several methods for reduction of the noise source are proposed.

Hardin, J. C.↗

Incorporating an Interactive Fire Plume-Rise Model in the DOE's Energy Exascale Earth System Model Version 1 (E3SMv1) and Examining Aerosol Radiative Effect

The vertical distribution of biomass burning aerosol (BBA) is important in regulating their impacts on weather and climate. The plume-rise process affects the injection height of BBA and interacts with the air parcel lifting and cloud processes. However, these processes are not represented in most global climate models. In this study, we replaced the fixed vertical profiles of monthly BBA emissions in the Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1) with an interactive fire plume-rise model. The vertical distribution of BBA emissions was calculated as a function of ambient thermodynamic conditions from the host E3SMv1, with distributions of fire sizes and sensible heat fluxes derived from the observations. The maximum fire radiative power (FRP) technique was used to determine the fire size. Scaling-FRP technique is used to calculate the wildfire heat release. Daily BBA emission, superimposed with a fire diurnal cycle retrieved from the satellite observation, was included in model simulations. The model shows improved agreement with satellite retrievals and in situ measurement during the National Oceanic and Atmospheric Administration Wildfire Experiment for Cloud chemistry, Aerosol absorption, and Nitrogen campaign. The model-observation comparison demonstrates the importance of the plume-rise model and fire diurnal cycle assumption in determining the BBA fields. We also find that E3SMv1 with new features produces a larger carbonaceous aerosol burden, leading to 0.13 W m –2 warming at the top of atmosphere compared to the default E3SMv1. This highlights the importance of accurately representing the BBA injection height and indicates a no-linear nature in the BBA-induced radiative effect.

54 ENVIRONMENTAL SCIENCES↗

Understanding the causes of satellite–model discrepancies in aerosol–cloud interactions using near-LES simulations of marine boundary layer clouds

Aerosol–cloud interactions (ACI) remain the largest source of uncertainty in model estimates of anthropogenic radiative forcing, primarily because of deficiencies in representing aerosol–cloud microphysical processes that lead to inconsistent cloud liquid water path (LWP) responses to aerosol perturbations between observations and models. To investigate this discrepancy, we conducted a series of large-eddy-scale simulations driven by realistic meteorology over the eastern North Atlantic, and evaluated LWP susceptibility, precipitation processes, and boundary layer thermodynamics using satellite and ground-based observations. Simulated LWP responses show a strong dependence on cloud state. Non-precipitating thin clouds exhibit a modest LWP decrease with increasing cloud droplet number concentration (N d ), consistent in sign but weaker in magnitude than satellite estimates, reflecting enhanced turbulent mixing and evaporation. The largest model-observation discrepancy occurs in non-precipitating thick clouds, where simulated LWP susceptibilities are strongly positive (+0.32) while observations indicate large negative values (−0.69). This discrepancy stems from excessive precipitation driven by underestimated entrainment, overly active accretion, and overly broad drop-size distributions in polluted conditions. While our high-resolution setup mitigates the excessive drizzling common in coarser models and captures key regime transitions, these biases persist – highlighting that improved parameterizations of cloud-top processes, precipitation, and aerosol effects are needed beyond simply increasing model resolution. Additionally, misrepresented moisture inversions in reanalysis introduce a moist bias in cloud-top relative humidity, further amplifying positive LWP susceptibility. Our results also suggest that large negative N d –LWP relationships in observations may reflect internal cloud processes rather than true ACI effects.

Aerosol-cloud interaction↗

Interaction-expansion inchworm Monte Carlo solver for lattice and impurity models

Multiorbital quantum impurity models with general interaction and hybridization terms appear in a wide range of applications, including embedding, quantum transport, and nanoscience. However, most quantum impurity solvers are restricted to a few impurity orbitals, discretized baths, diagonal hybridizations, or density-density interactions. We generalize the inchworm quantum Monte Carlo method to the interaction expansion, and we explore its application to typical single- and multiorbital problems encountered in investigations of impurity and lattice models. Our implementation generically outperforms bare and bold-line quantum Monte Carlo algorithms in the interaction expansion. For the systems studied here, our implementation remains inferior to the more specialized hybridization expansion and auxiliary field algorithms. So, the problem of convergence to unphysical fixed points, which hampers so-called bold-line methods, is not encountered in inchworm Monte Carlo.

36 MATERIALS SCIENCE↗

Computational studies of turbulent merger of corotational vortices

A computational study has been conducted to gain a better understanding of the criteria governing the merger of corotating vortices. The zero-equation and one-equation turbulent-flow models are used to model the interaction of two rolled-up, corotational vortices. A model appropriate for the swirling flow under consideration has been proposed to prescribe the algebraic variation of mixing-length in the flow field. The unsteady, two-dimensional equations in a cross-plane are solved for primitive variables using an implicit finite-difference code. The computed downstream merging distances are in good agreement with available wind tunnel data.

Raj, P.↗

The Martian Dust Cycle: Investigation of the Surface Lifting Component

We have investigated the nature of the annual cycle of suspended dust in the martian atmosphere. This has been undertaken to understand the dynamical processes responsible for lifting dust from the surface, locations where dust is preferentially lifted, and preferred sites for dust deposition upon the surface. Our efforts have involved carrying out a number of numerical simulations with the Ames Mars General Circulation Model (GCM) interactively coupled with an aerosol transport/ micro-physical model. The model generates an annual dust cycle similar to that observed. Various feedbacks are present in the atmosphere/ surface system which enter into the generation of the cycle. Several locations are primary surface sources of dust, while much of the remaining planet's surface acts a sink for suspended dust.

Murphy, James R.↗

A Thermodynamic Model for Nd(III)–Sulfate Interaction at High Ionic Strengths and Elevated Temperatures: Applications to Rare Earth Element Extraction

Neodymium (Nd), a rare earth element (REE), is critical to numerous industries. Neodymium can be extracted from ore concentrates, waste materials, or recycled materials such as recycled Nd-Fe-B permanent magnets. In a standard process, concentrated sulfuric acid (H 2 SO 4 ) is used as an extraction/leaching agent. Therefore, knowledge of Nd(III)–sulfate interaction at high ionic strengths is important for optimization of the extraction process. In addition, sulfate is also a major species in natural surface waters and present in nuclear waste streams. Nd(III) has been used a chemical analog to trivalent actinides in nuclear waste research and development. Consequently, knowledge of Nd(III)-sulfate interactions is also impactful to the field of nuclear waste management. Here, in this study, we have developed a thermodynamic model that can describe the interaction of Nd(III) with sulfate to ionic strengths up to ~ 16.5 mol·kg –1 and to temperatures up to 100 °C. The model adopts the Pitzer formulation to describe activity coefficients of aqueous species. This model can be used to design and optimize a chemical process for REE recovery from ore concentrates, recycled materials, and acid mine drainage (AMD) and to understand the mobility of REEs and actinides in the environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Numerical Models of Human Circulatory System under Altered Gravity: Brain Circulation

A computational fluid dynamics (CFD) approach is presented to model the blood flow through the human circulatory system under altered gravity conditions. Models required for CFD simulation relevant to major hemodynamic issues are introduced such as non-Newtonian flow models governed by red blood cells, a model for arterial wall motion due to fluid-wall interactions, a vascular bed model for outflow boundary conditions, and a model for auto-regulation mechanism. The three-dimensional unsteady incompressible Navier-Stokes equations coupled with these models are solved iteratively using the pseudocompressibility method and dual time stepping. Moving wall boundary conditions from the first-order fluid-wall interaction model are used to study the influence of arterial wall distensibility on flow patterns and wall shear stresses during the heart pulse. A vascular bed modeling utilizing the analogy with electric circuits is coupled with an auto-regulation algorithm for multiple outflow boundaries. For the treatment of complex geometry, a chimera overset grid technique is adopted to obtain connectivity between arterial branches. For code validation, computed results are compared with experimental data for steady and unsteady non-Newtonian flows. Good agreement is obtained for both cases. In sin-type Gravity Benchmark Problems, gravity source terms are added to the Navier-Stokes equations to study the effect of gravitational variation on the human circulatory system. This computational approach is then applied to localized blood flows through a realistic carotid bifurcation and two Circle of Willis models, one using an idealized geometry and the other model using an anatomical data set. A three- dimensional anatomical Circle of Willis configuration is reconstructed from human-specific magnetic resonance images using an image segmentation method. The blood flow through these Circle of Willis models is simulated to provide means for studying gravitational effects on the brain circulation under auto-regulation.

Kim, Chang Sung↗

A Human View Model for Socio-Technical Interactions

The Human View was developed as an additional architectural viewpoint to focus on the human part of a system. The Human View can be used to collect and organize data in order to understand how human operators interact and impact the other elements of a system. This framework can also be used to develop a model to describe how humans interact with each other in network enabled systems. These socio-technical interactions form the foundation of the emerging area of Human Interoperability. Human Interoperability strives to understand the relationships required between human operators that impact collaboration across networked environments, including the effect of belonging to different organizations. By applying organizational relationship concepts from network theory to the Human View elements, and aligning these relationships with a model developed to identify layers of coalition interoperability, the conditions for different levels for Human Interoperability for network enabled systems can be identified. These requirements can then be captured in the Human View products to improve the overall network enabled system.

Handley, Holly A.↗

On the design of an interactive biosphere for the GLAS general circulation model

Improving the realism and accuracy of the GLAS general circulation model (by adding an interactive biosphere that will simulate the transfers of latent and sensible heat from land surface to atmosphere as functions of the atmospheric conditions and the morphology and physiology of the vegetation) is proposed.

Mintz, Y.↗

Molecular modeling of polymer composite-analyte interactions in electronic nose sensors

We report a molecular modeling study to investigate the polymer-carbon black (CB) composite-analyte interactions in resistive sensors. These sensors comprise the JPL electronic nose (ENose) sensing array developed for monitoring breathing air in human habitats. The polymer in the composite is modeled based on its stereoisomerism and sequence isomerism, while the CB is modeled as uncharged naphthalene rings with no hydrogens. The Dreiding 2.21 force field is used for the polymer, solvent molecules and graphite parameters are assigned to the carbon black atoms. A combination of molecular mechanics (MM) and molecular dynamics (NPT-MD and NVT-MD) techniques are used to obtain the equilibrium composite structure by inserting naphthalene rings in the polymer matrix. Polymers considered for this work include poly(4-vinylphenol), polyethylene oxide, and ethyl cellulose. Analytes studied are representative of both inorganic and organic compounds. The results are analyzed for the composite microstructure by calculating the radial distribution profiles as well as for the sensor response by predicting the interaction energies of the analytes with the composites. c2003 Elsevier Science B.V. All rights reserved.

NASA Center JPL↗

Phenomenological theory of the magnetic 90° helical state

We explore a phenomenological phase diagram for the magnetic helical state with 90° turn angle between neighboring spins in the external magnetic field. Such a state is formed by the Eu spin layers in the superconducting iron arsenide RbEuFe 4 As 4 . The peculiarity of this spin configuration is that it is not realized in the standard Heisenberg model with bilinear exchange interactions. A minimum model allowing for such a state requires the biquadratic nearest-neighbor interaction term. In addition, in tetragonal materials, the 90° helix state may be stabilized by the in-plane fourfold anisotropy term, which also fixes helix orientation with respect to the crystal lattice. Such a system has a very rich behavior in the external magnetic field. The magnetic field induces the metamagnetic transition to the double-periodic state with the moment angles (α α -α,-α) with respect to the field for the four subsequent spins. The transition field to this state from the deformed helix is determined by the strength of biquadratic interaction. The transition is second-order for small biquadratic coupling and becomes first-order when this coupling exceeds the critical value. On the other hand, the aligned state at high magnetic field becomes unstable with respect to the formation of an incommensurate fan state, which transforms into the double-periodic state with decreasing magnetic field. The range of this incommensurate state near the saturation field is proportional to square of the biquadratic coupling. In addition, when the magnetic field is applied along one of four the equilibrium moment directions, the deformed helix state experience the first-order rotation transition at the field determined by the fourfold anisotropy.

36 MATERIALS SCIENCE↗

Spiral structure and star formation. I - Formation mechanisms and mean free paths

The wide variety of optical appearances observed in spiral galaxies has encouraged the growth of two theoretical approaches to explain the spiral patterns exhibited by such young objects as OB associations, giant H II regions, and dark dust lanes. These approaches are related to the density wave theory of spiral structure and 'stochastic, self-propagating star formation'. Levinson and Roberts (1981) tried to reconcile these two theoretical approaches, and considered a disk filled with discrete gas clouds. The present investigation is concerned with refinements and extensions of the model of Levinson and Roberts. Attention is given to gravitational forces and dynamical propagation, cloud-cloud collisions, supernova interactions, computational models, a theory concerning the interactions of the gas cloud and stellar association systems, the time evolution of the gas cloud-stellar association systems, and aspects of collisionally triggered star formation.

Roberts, W. W., Jr.↗

Quantitative dissection of Agrobacterium T-DNA expression in single plant cells reveals density-dependent synergy and antagonism

Agrobacterium pathogenesis, which involves transferring T-DNA into plant cells, is the cornerstone of plant genetic engineering. As the applications that rely on Agrobacterium increase in sophistication, it becomes critical to achieve a quantitative and predictive understanding of T-DNA expression at the level of single plant cells. Here we examine if a classic Poisson model of interactions between pathogens and host cells holds true for Agrobacterium infecting Nicotiana benthamiana. Systematically challenging this model revealed antagonistic and synergistic density-dependent interactions between bacteria that do not require quorum sensing. Using various approaches, we studied the molecular basis of these interactions. To overcome the engineering constraints imposed by antagonism, we created a dual binary vector system termed ‘BiBi’, which can improve the efficiency of a reconstituted complex metabolic pathway in a predictive fashion. Our findings illustrate how combining theoretical models with quantitative experiments can reveal new principles of bacterial pathogenesis, impacting both fundamental and applied plant biology.

Alamos, Simon↗

Shift Happens: Building Robust AI Models with Domain Adaptation

Artificial Intelligence (AI) is revolutionizing physics research—from probing the large-scale structure of the Universe to modeling subatomic interactions and fundamental forces. Yet, a major challenge persists: AI models trained on simulations or old experiment / astronomical survey often perform poorly when applied to new data—exposing issues of dataset (domain) shift, model robustness, and uncertainty in predictions. This summer school session will introduce students to common challenges in applying AI across domains and present solutions based on domain adaptation—a set of techniques designed to improve model generalization under domain shift. We will cover foundational ideas, practical strategies, and current research frontiers in this area. Through examples in astrophysics, we'll explore how domain adaptation can help bridge the gap between synthetic and real-world data, improve trust in model outputs, and advance scientific discovery. The concepts discussed are broadly applicable across physics and other scientific disciplines, making this a valuable topic for anyone interested in building robust, transferable AI models for science.

Ciprijanovic, A. [Fermilab] (ORCID:000000031281719↗

AI in Astrophysics: Tackling Domain Shift, Model Robustness and Uncertainty

Artificial Intelligence (AI) is revolutionizing physics research from probing the large-scale structure of the Universe to modeling subatomic interactions and fundamental forces. Yet, a major challenge persists: AI models trained on simulations or old experiment / astronomical survey often perform poorly when applied to new data exposing issues of dataset (domain) shift, model robustness, and uncertainty in predictions. This talk will introduce common challenges in applying AI across domains and present solutions based on domain adaptation a set of techniques designed to improve model generalization under domain shift. We will cover foundational ideas, practical strategies, and current research frontiers in this area. Through examples in astrophysics, we'll explore how domain adaptation can help bridge the gap between synthetic and real-world data, improve trust in model outputs, and advance scientific discovery.

Ciprijanvoic, Aleksandra [Fermilab] (ORCID:0000000↗

Dynamic analysis of space structures including elastic, multibody, and control behavior

The problem is to develop analysis methods, modeling stategies, and simulation tools to predict with assurance the on-orbit performance and integrity of large complex space structures that cannot be verified on the ground. The problem must incorporate large reliable structural models, multi-body flexible dynamics, multi-tier controller interaction, environmental models including 1g and atmosphere, various on-board disturbances, and linkage to mission-level performance codes. All areas are in serious need of work, but the weakest link is multi-body flexible dynamics.

Pinson, Larry↗