Physical Models of Cognition
This paper presents and discusses physical models for simulationg some aspects of neural intelligence, and in particular, the process of cognition.
neural↗
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Nb SRF cavities applied to searches for beyond the standard model physics
The SRF technology developed for accelerators can be successfully applied to new applications, including quantum computing, dark matter searches and beyond the standard model physics. The ultra-high quality factor of SRF cavities can al-low to achieve unprecedented sensitivity in fields outside of the usual accelerator applications, for examples fundamental and beyond the standard model physics. Applications of SRF cavities for gravitational waves searches are also being investigated. The SQMS Physics and Sensing thrust is working on this effort as it strives to combine SRF cavities with QIS, with a focus on BSM and fundamental physics. Using Nb SRF cavities, we run a proof of principle search for the dark photon dark matter candidate at fixed frequency demonstrating the deepest sensitivity to wavelike dark mater [1]. The Dark SRF experiment uses two 1.3GHz SRF cavities to conduct a light shining through wall (LSW) experiment to attempt producing and detecting dark photons in the laboratory. The results of this first superconducting LSW search were recently published [2] and we are now working on the second phase of the experiment, which will be run in a dilution refrigerator using 2.6GHz SRF cavities. In addition to the limits we have achieved, we will also present the experiments we are currently developing, such as the heterodyne axion DM search [3, 4], the SERAPH series of experiments, and gravitational waves searches based on SRF cavities as proposed in [5-8].
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Advanced Physics Models for Particle-Particle Interactions (UCD final report)
The LDRD "Advanced Physics Models for Particle-Particle Interactions” collaborative research with Professor Jennifer Sinclair Curtis and PhD student Chanh Nguyen at the University of California, Davis involved meso-scale, discrete element method (DEM) modeling of micron-sized particles impacting a substrate. Using DEM, physical insight into the details of particle response upon impact can be obtained. Such details provide the type of information necessary to enhance existing continuum or macro-scale simulation tools so that modeling for material strength and particle breakage models is based on particle physics versus empirical relationships. While molecular dynamics simulations of atoms can also provide physical insight into the particle response to impact, the scale of particles that are treated is on the order of angstroms, not microns. This study gives evidence to the ability of the DEM simulation technique to provide such fundamental, detailed insight for micron-sized particles as a function of particle properties and impact velocity.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Skeletides: A Modular, Simplified Physical Model of Protein Secondary Structure
Three-dimensional (3D) models are essential for visualization and conceptual understanding of complex architectures such as protein structure. Although there is a plethora of software platforms that allow digital depictions of protein structure at an atomic level in silico, physical models are needed to convey an intuitive understanding of biomolecular architecture. However, it is a challenge to represent all the relevant features of proteins in a single physical model due to their sheer structural complexity. Here, we describe a modular protein model that focuses only on representation of the secondary structure—the underlying structural skeleton. The simplified model consists of amino acid units, which can be linked together to reproduce the two most fundamental structural features of protein secondary structure: the relative positions of the amino acid alpha carbon atoms, and the intra-main chain hydrogen bonding pattern. We use 3D printing and magnets to create a set of three modular amino acid building blocks, which when linked together into a chain, can faithfully represent alpha helices, beta sheets, and turns. These simple to make models can be used to quickly assemble the alpha carbon trace of an entire protein domain, which conveys a tactile experience of the complexity of protein skeletal architecture. These models highlight the modularity of protein structure: where a single structural unit, the amino acid, can be linked together to form a larger, regular secondary structure. These models also have a propensity to spontaneously organize into alpha helices and beta sheets, as demonstrated by their ability to autonomously assemble when placed in a circulating water tank. These models provide a missing educational tool to expand knowledge of protein structure, foster deeper insight into protein folding, and inspire greater interest in biomacromolecular architecture.
36 MATERIALS SCIENCE↗
Comparison of analytical and physical modeling of planetesimal accumulation
Three cases for which the analytic solutions to the planetary embryo coagulation equation are known, namely those of constant coagulation rate, of rate proportional to the sum of the masses of the two colliding bodies, and of rate proportional to the product of their masses, are presently used to test the mathematical validity of the Wetherill and Stewart (1989) physical model for the evolution of planetary embryos' mass distribution. In all cases, excellent agreement is found between numerical physical modeling results and those of the analytic solutions. The treatment of the runaway case can proceed via extension of the efforts of Trubnikov (1971).
Wetherill, George W.↗
Interpolating Fields of Carbon Monoxide Data Using a Hybrid Statistical-Physical Model
Atmospheric Carbon Monoxide (CO) is a pollutant gas of which the US congress has mandated regular monitoring, and satellite sensors can be used to retrieve regional concentrations of CO over several vertical layers. However, CO at cloudy locations cannot be observed and have to be estimated from the observed data set, resulting in an interpolation problem. The current state-of-the-art solution is to combine prior information, computed by a deterministic physical model, with observations. However, the deterministic model may introduce uncertainties that do not derive from the data. While sharing certain features with the physical model, this paper presents a Bayesian hierarchical model for interpolating CO on a 3-dimensional spatial grid, across time. To our knowledge such a model has not been considered before. The model is applied to a hypothetical air-quality monitoring scenario, and is compared to existing interpolation methods. The results provide motivation for the use of the statistical model for regional to local applications.
Arellano, A. A.↗
Detecting forest structure and biomass with C-band multipolarization radar - Physical model and field tests
The ability of C-band radar (4.75 GHz) to discriminate features of forest structure, including biomass, is tested using a truck-mounted scatterometer for field tests on a 1.5-3.0 m pygmy forest of cypress (Cupressus pygmaea) and pine (Pinus contorta ssp, Bolanderi) near Mendocino, CA. In all, 31 structural variables of the forest are quantified at seven sites. Also measured was the backscatter from a life-sized physical model of the pygmy forest, composed of nine wooden trees with 'leafy branches' of sponge-wrapped dowels. This model enabled independent testing of the effects of stem, branch, and leafy branch biomass, branch angle, and moisture content on radar backscatter. Field results suggested that surface area of leaves played a greater role in leaf scattering properties than leaf biomass per se. Tree leaf area index was strongly correlated with vertically polarized power backscatter (r = 0.94; P less than 0.01). Field results suggested that the scattering role of leaf water is enhanced as leaf surface area per unit leaf mass increases; i.e., as the moist scattering surfaces become more dispersed. Fog condensate caused a measurable rise in forest backscatter, both from surface and internal rises in water content. Tree branch mass per unit area was highly correlated with cross-polarized backscatter in the field (r = 0.93; P less than 0.01), a result also seen in the physical model.
Westman, Walter E.↗
Advanced Ground Systems Maintenance Physics Models for Diagnostics Project
The project will use high-fidelity physics models and simulations to simulate real-time operations of cryogenic and systems and calculate the status/health of the systems. The project enables the delivery of system health advisories to ground system operators. The capability will also be used to conduct planning and analysis of cryogenic system operations.
Technology Portfolio System↗
Moment constraints on physical models for quasi-periodic oscillations from Galactic X-ray sources
Shot-noise models provide a useful mathematical representation for some physical models for the quasi-periodic oscillations (QPOs) recently observed from several bright Galactic bulge and burst X-ray sources. Expressions are calculated for the first three moments for several versions of QPO shot-noise models that have appeared in the literature. It is shown that measurement of the third moment, together with measurement of the mean intensity and the power spectrum, can provide model-dependent constraints on important parameters of QPO shot-noise models, including the fraction of the X-ray intensity in shots and the shot rate. Under certain condtitions, a complete solution for all the shot-model parameters is possible.
Elsner, R. F.↗
Particle Interaction Physics Model Formulation for 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 Predictive Simulation Capability (PSC) Element is 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 predictive simulation capability, 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 will present the status of implementing and maturing particle-particle interaction constituent physics models essential in simulating the landing surface granular material flow under PSI effects. This gas-particle multi-phase interaction modeling of plume impingement flow on the extra-terrestrial soil material is performed with the Gas-Granular Flow Solver (GGFS) addressed in a companion paper. The response of regolith particle flow induced by lander PSI requires accurate representation of the regolith granular material fluidic behavior and gas-granular interactions. The lunar regolith, as the extreme example, is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking particle shapes for the very jagged particles. The combination of particle shape and size distribution has been identified as major drivers in the complex particle flow response and resulting crater shape characteristics of extraterrestrial granular material. Constituent models for spherical particles can be formulated directly from particle kinetics theory. Complex particle shapes can be modeled by gluing together elemental spherical shapes into composite particles, requiring a Discrete Element Model (DEM) particle kinetics modeling approach to extract data and formulate constituent models. Mixture constituent models for poly-disperse mixtures (i.e, containing distribution of particle sizes) have recently been developed. The required non-spherical particle mixture granular material response closure models are then obtained through small-scale unit physics DEM simulations for the range of particle shapes, mixtures and packing densities. The granular material response closure models are then implemented in the Eulerian granular flow formulation. This DEM-based constituent model extraction process and formulation of poly-disperse particle mixtures has been successfully developed by small business and academic partners in the development of the Gas-Granular Flow Solver (GGFS) simulation program simulation framework. The currently implemented capabilities have reached the capability level of modeling bi-disperse, non-spherical particle mixtures is being continuously extended towards computational modeling of full range irregular particle mixtures. Under the GCD project, this technology is being further developed, transferred to NASA analysts, and matured towards application readiness. The predictive simulation capability team under the GCD project has acquired the modeling tools and processes of the DEM based constituent model formulation from the GGFS development team and is developing the capability to replicate the existing process. This is the first important step towards the ability of the NASA team to independently perform such model development in a production setting. Further efforts are underway to migrate the DEM based model simulation process performed with the academic based tools to more capable Open Source, highly parallelized simulation tools for efficient operation on NASA HPC assets. Evaluation of the currently implemented (such as mono-disperse and bi-disperse spherical and irregular shape particle constituent model applications) and continuously evolving full-range particle physics models in the GGFS tool is performed by the NASA team to advance application readiness of the simulations. Application testing for complex PSI erosions and cratering scenarios such as the Apollo LM is performed for axi-symmetric and full 3D simulations to aid the tool developers in achieving practical application readiness for NASA projects. Important validation and application testing will further be performed against experimental data generated under the GCD PSI project experimental component.
Peter A Liever↗
A Simple Physical Model for Three-Terminal Tandem Cell Operation
We present a simple physical model that explains the device operation of a three-terminal (3T) IBC Si bottom cell platform that enables an efficient 3T tandem. If the IBC cell has two p-n junctions and one high-low junction (bipolar transistor), the two p-n junctions strongly interact via minority carrier diffusion in the base. In a two-BSF junction and one p-n junction IBC platform (single emitter), the BSF terminals interact via ohmic majority carrier current in the base. This interaction creates wide 'generating' power islands in the 2D current J 1 J 2 plane. The area and shape of these islands are determined by dissipative losses in the wafer base and in the cell contacts. Both positive and negative terminal currents are allowed for 3T operation, thus enabling both the top and bottom cells to operate at their full light currents. This opens new possibilities for 3T use in modules.
14 SOLAR ENERGY↗
Constraining Physical Models at Gigabar Pressures
High-energy-density (HED) experiments in convergent geometry are able to test physical models at pressures beyond hundreds of millions of atmospheres. The measurements from these experiments are generally highly integrated and require unique analysis techniques to procure quantitative information. This work describes a methodology to constrain the physics in convergent HED experiments by adapting the methods common to many other fields of physics. As an example, a mechanical model of an imploding shell is constrained by data from a thin-shelled direct-drive exploding-pusher experiment on the OMEGA Laser System using Bayesian inference, resulting in the reconstruction of the shell dynamics and energy transfer during the implosion. The model is tested by analyzing synthetic data from a 1-D hydrodynamics code and is sampled using a Markov chain Monte Carlo to generate the posterior distributions of the model parameters. The goal of this work is to demonstrate a general methodology that can be used to draw conclusions from a wide variety of HED experiments.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Constraining physical models at gigabar pressures
High-energy-density (HED) experiments in convergent geometry are able to test physical models at pressures beyond hundreds of millions of atmospheres. The measurements from these experiments are generally highly integrated and require unique analysis techniques to procure quantitative infor mation. This work describes a methodology to constrain the physics in convergent HED experiments by adapting the methods common to many other fields of physics. As an example, a mechanical model of an imploding shell is constrained by data from a thin-shelled direct-drive exploding-pusher experiment on the OMEGA Laser System using Bayesian inference, resulting in the reconstruction of the shell dynamics and energy transfer during the implosion. The model is tested by analyzing synthetic data from a 1-D hydrodynamics code and is sampled using a Markov chain Monte Carlo to generate the posterior distributions of the model parameters. As a result, the goal of this work is to demonstrate a general methodology that can be used to draw conclusions from a wide variety of HED experiments.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
A generalized physical model of the role of surface effects in modifying intrinsic thermal radiation parameters
Physical model of role of surface topography, and contaminant surface films, infused impurities, pore size, and separation in thermal radiation
TOPOGRAPHY↗
Physical Model of Asteroid 1620 Geographos From Radar and Optical Data
We develop a physical model of asteroid 1620 Geographos using Goldstone delay-Doppler radar images obtained Aug. 1994 (Ostro et al. 1996, Icarus 121, 46-66) with resolution as fine as 75 m, and optical lighcurves obtained in 1969, 1983, and 1993-94 (Magnusson et al. 1996, Icarus 123, 227-244).
asteroid 1620 Geographos delay-Doppler radar image↗
Wind-US Code Physical Modeling Improvements to Complement Hypersonic Testing and Evaluation
This report gives an overview of physical modeling enhancements to the Wind-US flow solver which were made to improve the capabilities for simulation of hypersonic flows and the reliability of computations to complement hypersonic testing. The improvements include advanced turbulence models, a bypass transition model, a conjugate (or closely coupled to vehicle structure) conduction-convection heat transfer capability, and an upgraded high-speed combustion solver. A Mach 5 shock-wave boundary layer interaction problem is used to investigate the benefits of k- s and k-w based explicit algebraic stress turbulence models relative to linear two-equation models. The bypass transition model is validated using data from experiments for incompressible boundary layers and a Mach 7.9 cone flow. The conjugate heat transfer method is validated for a test case involving reacting H2-O2 rocket exhaust over cooled calorimeter panels. A dual-mode scramjet configuration is investigated using both a simplified 1-step kinetics mechanism and an 8-step mechanism. Additionally, variations in the turbulent Prandtl and Schmidt numbers are considered for this scramjet configuration.
Georgiadis, Nicholas J.↗
Global scale, physical models of the F region ionosphere
Consideration is given to the development and verification of global computer models of the F-region which simulate the interactions between physical processes in the ionosphere. The limitations of the physical models are discussed, focusing on the inputs to the ionospheric system such as magnetospheric electric field and auroral precipitation. The possibility of coupling ionospheric models with thermospheric and magnetospheric models is examined.
Sojka, J. J.↗
Assessment of Physics Models for Phase Transition Kinetics
The time dependence of phase diagrams and how to model rate dependent transitions remains one of the key unanswered questions in physics. When a material is loaded dynamically through equilibrium phase boundaries, it is the kinetics that determines the real time expression of a phase transition. Here we report the atomic and nanosecond-scale quantification of kinetics of shock-driven phase transition in multiple materials. We uniquely make use of a both a simple shock as well as shock-and-hold loading pathways compress different crystalline solids and induce structural phase transitions below melt. Coupling shock loading with time-resolved synchrotron x-ray diffraction (DXRD), we probe the structural transformations of these solids in the short-lived high pressure and temperature states generated. The novelty and power of using DXRD for the assessment of kinetics of phase transitions lies in the ability to discover and identify new phases and to examine kinetics without prior knowledge of a material's phase diagram. Our results provide a quantified expression and a physics model of kinetics of formation of high-pressure phases under shock loading: transition incubation time, evolution, completion time and crystallization rate.
36 MATERIALS SCIENCE↗