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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

The Atmospheric Effects of HSCT Emissions Simulated by a 3-Wave Interactive Model

An interactive model which couples a semi-spectral dynamical model, a radiative transfer code and a two-dimensional chemistry transport model (2-D CTM), is used to assess the atmospheric effects of the High-Speed Civil Transport (HSCT) engine emissions. The residual mean meridional circulation, the zonal-mean temperature and the eddy diffusion coefficients are calculated using zonal means and three longest zonal waves of dynamical variables integrated in the semi-spectral dynamical model. They are used in the 2-D CTM to simulate the distribution of trace gases in the atmosphere. The simulated ozone is sent to the radiative transfer code to calculate the heating rates, which drive the dynamics. This radiative coupling connects the dynamical and photochemical processes and creates feedback when the atmosphere is perturbed. It is found that in most areas the ozone depletion caused by HSCT emissions calculated using the 3-wave model has the features similar to, but with significantly larger magnitude than that calculated by the AER 2-D CTM with prescribed transport parameters and temperature. The difference is mostly due to the differences in the circulation in the two models. The radiative feedback effects are investigated by comparing the ozone depletion calculated with the baseline dynamics and with the dynamics perturbed by the HSCT emissions. The feedback through changes in the residual mean meridional circulation and the eddy diffusion coefficients has moderate effects on the simulated ozone depletion. It reduced the ozone depletion by 20-30% in northern mid and high-latitudes. However, the feedback through changes in the zonal- mean temperature is negligible.

Shia, R.-L.↗

Global tuning of hadronic interaction models with accelerator-based and astroparticle data

In high-energy and astroparticle physics, event generators play an essential role, even in the simplest data analyses. As analysis techniques become more sophisticated, e.g. based on deep neural networks, their correct description of the observed event characteristics becomes even more important. Physical processes occurring in hadronic collisions are simulated within a Monte Carlo framework. A major challenge is the modeling of hadron dynamics at low momentum transfer, which includes the initial and final phases of every hadronic collision. QCD-inspired phenomenological models used for these phases cannot guarantee completeness or correctness over the full phase space. These models usually include parameters which must be tuned to suitable experimental data. Until now, event generators have been developed and tuned mainly on the basis of data from high-energy physics experiments at accelerators. The wealth of data available from the latest generation of astroparticle experiments has not yet been fully exploited, and in many cases is not satisfactorily described. Both kinds of data sets are complementary as astroparticle experiments provide sensitivity especially to hadrons produced nearly parallel to the collision axis and cover center-of-mass energies up to several hundred TeV, well beyond those reached at colliders so far. In this report, we provide an overview of state-of-the-art event generators and their tuning, including the most relevant inputs from high-energy accelerator and astroparticle experiments. We present a road map that shows, for the first time, how the unified tuning of event generators with accelerator-based and astroparticle data can be performed.

Albrecht, J. [Ruhr U., Bochum, RAPP Ctr.; Ruhr U.,↗

Gas-Particle Interaction Model Development in Plume Surface Interaction Erosion and Cratering

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The GCD PSI Project, planned to be completed over a four year period, contains a Predictive Simulation Capability (PSC) Element focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the PSC Element, the GCD Program also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper describes the activities and accomplishments of the past year in the gas-particle interaction modeling portion of the GCD PSI project. The objectives of this task are to investigate and construct models of particle drag and gas-particle cloud interactions leading to what is known as particle turbulent kinetic energy (PTKE). While drag on a lone particle suspended in a flow gas of gas is well-known, the drag and drag-induced dynamics of a cloud of particles in a gas flow are not. The PSC element of the PSI project requires models of gas-particle cloud interactions to implement in the Gas Granular Flow Solver (GGFS) in order to arrive at a predictive simulation capability for PSI-induced soil erosion, cratering and ejecta transport. Experiments of dilute mixtures of soil particles in supersonic gas flow are being conducted at Johns Hopkins University in order to provide a dataset describing gas-particle cloud interactions. Augmented by a separate funding source are efforts to perform small-scale particle-resolved direct numerical simulations (PR-DNS) and larger scale Eulerian-Lagrangian simulations. Together, these experiments and simulations are being used to devise models of particle cloud drag and particle cloud drag-induced dynamics. The final product of these efforts will be particle drag models suitable for implementation into the GGFS application and a PTKE model suitable for the same purpose.

Jeff West↗

The display of molecular models with the Ames Interactive Modeling System (AIMS)

A visualization of molecular models can lead to a clearer understanding of the models. Sophisticated graphics devices supported by minicomputers make it possible for the chemist to interact with the display of a very large model, altering its structure. In addition to user interaction, the need arises also for other ways of displaying information. These include the production of viewgraphs, film presentation, as well as publication quality prints of various models. To satisfy these needs, the display capability of the Ames Interactive Modeling System (AIMS) has been enhanced to provide a wide range of graphics and plotting capabilities. Attention is given to an overview of the AIMS system, graphics hardware used by the AIMS display subsystem, a comparison of graphics hardware, the representation of molecular models, graphics software used by the AIMS display subsystem, the display of a model obtained from data stored in molecule data base, a graphics feature for obtaining single frame permanent copy displays, and a feature for producing multiple frame displays.

Egan, J. T.↗

Disentangling the physics of the attractive Hubbard model as a fully interacting model of fermions via the accessible and symmetry-resolved entanglement entropies

The complicated ways in which electrons interact in many-body systems such as molecules and materials have long been viewed through the lens of local electron correlation and associated correlation functions. However, quantum information science has demonstrated that more global diagnostics of quantum states like the entanglement entropy can provide a complementary and clarifying lens on electronic behavior. One particularly useful measure that can be used to distinguish between quantum and classical sources of entanglement is the accessible entanglement, the entanglement available as a quantum resource for systems subject to conservation laws, such as fixed particle number, due to superselection rules. In this work, we introduce an algorithm and demonstrate how to compute accessible and symmetry-resolved entanglements for interacting fermion systems. This is accomplished by combining an incremental version of the swap algorithm with a recursive auxiliary field quantum Monte Carlo algorithm recently developed by the authors. We apply these tools to study the pairing and charge density waves exhibited in the paradigmatic attractive Hubbard model via entanglement. We find that the particle and spin symmetry-resolved entanglements and their related full probability distribution functions show very clear—and unique—signatures of the underlying electronic behavior even when those features are less pronounced in conventional correlation functions. Altogether, this work provides a systematic means of characterizing the entanglement within quantum systems that can grant a deeper understanding of the complicated electronic behavior that underlies quantum phase transitions and crossovers in many-body systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Gas-Particle Interaction Model Development in Plume Surface Interaction Erosion and Cratering

The development of a predictive simulation capability for extra-terrestrial Plume Surface Interaction (PSI) environments is undertaken by the Fluid Dynamics Branch at NASA/MSFC under the Game Changing Development (GCD) Program funded by NASA’s Space Technology Mission Directorate (STMD). Predictive simulation capability for propulsive Martian and Lunar landing PSI requires accurate modeling of the complex high-speed plume impingement and resulting gas/particle-cloud and ejecta stream formation. Physics modeling gap analysis during formulation of the PSI project scope identified two particular phenomena of first order importance in gas-particle interactions that lacked existing modeling formulations. The first arises from the lack of models capturing the unsteady drag forces imparted on particles by the rapidly expanding supersonic compressible flow. The second addresses the fluctuating forces and dispersions imparted on both the particle and the fluid resulting from the interference and wake turbulence generated by close proximity particle clouds, dubbed the Particle Turbulent Kinetic Energy(PTKE). Their first order significance has been identified in experiments, but simulation models currently do not exist for either effect. The development of models and the eventual implementation into the Eulerian Gas-Granular Flow Solver (GGFS) simulation tools was constructed as one of four major tasks of the PSI project. In this process, data on particle kinetics and gas-particle interactions are collected from carefully designed experiments of particles embedded in jets. The effects observed in the experiments are then replicated in high-fidelity particle-resolved CFD simulations to inform the formulation of improvements to particle phase drag models for implementations in the more efficient Eulerian-Lagrangian CFD simulations. The resulting models are ultimately ported to the Eulerian-Eulerian models applied for most efficient simulations in PSI production application tools. This paper describes the activities and accomplishments of the past year in the gas-particle interaction modeling task of the PSI project.

Jeff West↗

OC6 Phase II: Integration and verification of a new soil–structure interaction model for offshore wind design

Abstract This paper provides a summary of the work done within the OC6 Phase II project, which was focused on the implementation and verification of an advanced soil–structure interaction model for offshore wind system design and analysis. The soil–structure interaction model comes from the REDWIN project and uses an elastoplastic, macroelement model with kinematic hardening, which captures the stiffness and damping characteristics of offshore wind foundations more accurately than more traditional and simplified soil–structure interaction modeling approaches. Participants in the OC6 project integrated this macroelement capability to coupled aero‐hydro‐servo‐elastic offshore wind turbine modeling tools and verified the implementation by comparing simulation results across the modeling tools for an example monopile design. The simulation results were also compared to more traditional soil–structure interaction modeling approaches like apparent fixity, coupled springs, and distributed springs models. The macroelement approach resulted in smaller overall loading in the system due to both shifts in the system frequencies and increased energy dissipation. No validation work was performed, but the macroelement approach has shown increased accuracy within the REDWIN project, resulting in decreased uncertainty in the design. For the monopile design investigated here, that implies a less conservative and thus more cost‐effective offshore wind design.

17 WIND ENERGY↗

Probabilistic Usage of the Multi-Factor Interaction Model

A Multi-Factor Interaction Model (MFIM) is used to predict the insulating foam mass expulsion during the ascending of a space vehicle. The exponents in the MFIM are evaluated by an available approach which consists of least squares and an optimization algorithm. These results were subsequently used to probabilistically evaluate the effects of the uncertainties in each participating factor in the mass expulsion. The probabilistic results show that the surface temperature dominates at high probabilities and the pressure which causes the mass expulsion at low probabil

Chamis, Christos C.↗

Algebraic Turbulence-Chemistry Interaction Model

The results of a series of Perfectly Stirred Reactor (PSR) and Partially Stirred Reactor (PaSR) simulations are compared to each other over a wide range of operating conditions. It is found that the PaSR results can be simulated by a PSR solution with just an adjusted chemical reaction rate. A simple expression has been developed that gives the required change in reaction rate for a PSR solution to simulate the PaSR results. This expression is the basis of a simple turbulence-chemistry interaction model. The interaction model that has been developed is intended for use with simple one-step global reaction mechanisms and for steady-state flow simulations. Due to the simplicity of the model there is very little additional computational cost in adding it to existing CFD codes.

Norris, Andrew T.↗

A viscous-inviscid interaction model of jet entrainment

A viscous-inviscid interaction model for predicting jet entrainment effects on axisymmetric, nozzle afterbodies at subsonic speeds is presented. The model is based on a displacement thickness correction to the inviscid jet boundary that accounts for mixing-induced streamline deflections in the inviscid region. The displacement correction is shown to be related to the local mass entrainment rate and, for thin mixing layers, the model is shown to be analogous to displacement models used in conventional boundary-layer interaction theory. A method is presented for computing the entrainment rate by an overlaid mixing layer model that accounts for the nonsimilar behavior and pressure gradients occurring in the near field region. An iterative scheme for coupling the model to analyses for the external inviscid flow, the external boundary layer, and the inviscid jet exhaust is also given. Results are presented that illustrate the qualitative behavior of the entrainment interaction under various flow conditions and that demonstrate the validity of the model by comparisons with experiment.

Wilmoth, R. G.↗

Effective shell-model interaction for nuclei “southeast” of 100 Sn

We construct an effective shell-model interaction for the valence space spanned by single-particle neutron and single-hole proton states in 100 Sn. Starting from chiral nucleon-nucleon and three-nucleon forces and single-reference coupled-cluster theory for 100 Sn we apply a second similarity transformation that decouples the valence space. The particle-particle components of the resulting effective interaction can be used in shell model calculations for neutron deficient tin isotopes. The hole-hole interaction can be used to calculate the N=50 isotones south of 100 Sn, and the full particle-hole interaction describes nuclei in the region southeast of 100 Sn. We compute low-lying excited states in selected nuclei southeast of 100 Sn, and find reasonable agreement with data. The presented techniques can also be applied to construct effective shell-model interactions for other regions of the nuclear chart.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Application of large eddy interaction model to a mixing layer

The large eddy interaction model (LEIM) is a statistical model of turbulence based on the interaction of selected eddies with the mean flow and all of the eddies in a turbulent shear flow. It can be utilized as the starting point for obtaining physical structures in the flow. The possible application of the LEIM to a mixing layer formed between two parallel, incompressible flows with a small temperature difference is developed by invoking a detailed similarity between the spectra of velocity and temperature.

Murthy, S. N. B.↗

Particle-Surface Interaction Model and Method of Determining Particle-Surface Interactions

A method and model of predicting particle-surface interactions with a surface, such as the surface of a spacecraft. The method includes the steps of: determining a trajectory path of a plurality of moving particles; predicting whether any of the moving particles will intersect a surface; predicting whether any of the particles will be captured by the surface and/or; predicting a reflected trajectory and velocity of particles reflected from the surface.

Hughes, David W.↗

The impact of neutrino-nucleus interaction modeling on new physics searches

Accurate neutrino-nucleus interaction modeling is an essential requirement for the success of the accelerator-based neutrino program. As no satisfactory description of cross sections exists, experiments tune neutrino-nucleus interactions to data to mitigate mis-modeling. In this work, we study how the interplay between near detector tuning and cross section mis-modeling affects new physics searches. We perform a realistic simulation of neutrino events and closely follow NOvA’s tuning, the first published of such procedures in a neutrino experiment. We analyze two illustrative new physics scenarios, sterile neutrinos and light neutrinophilic scalars, presenting the relevant experimental signatures and the sensitivity regions with and without tuning. While the tuning does not wash out sterile neutrino oscillation patterns, cross section mis-modeling can bias the experimental sensitivity. In the case of light neutrinophilic scalars, variations in cross section models completely dominate the sensitivity regardless of any tuning. Our findings reveal the critical need to improve our theoretical understanding of neutrino-nucleus interactions, and to estimate the impact of tuning on new physics searches. We urge neutrino experiments to follow NOvA’s example and publish the details of their tuning procedure, and to develop strategies to more robustly account for cross section uncertainties, which will expand the scope of their physics program.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points, the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.

Chamis, Christos C.↗

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.

Chamis, Christos C.↗