A Minimum Detectable Signal Specification for Photon Doppler Velocimetry
Draft of paper for the Journal of Dynamic Behavior of Materials
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Draft of paper for the Journal of Dynamic Behavior of Materials
The internal structure of protons and neutrons provides insight into both the dynamical behavior of the constitute quarks and gluons, and emergent properties of the nucleons (such as mass, spin, and electromagnetic distributions). Elastic electron-nucleon scattering can probe the elastic electromagnetic form factors of the nucleon. The electric and magnetic form factors, respectively, encode information about the internal charge and magnetization distributions within the nucleon. Precision data for these form factors, over a broad range of the four-momentum transfer squared, Q^2, can benchmark theoretical models describing the strong interaction of nuclear physics. The Super BigBite Spectrometer (SBS) program in Hall A at Jefferson Lab, is a series of high-precision experiments which seek to significantly extend the Q^2 reach of previous data for the nucleon electromagnetic form factors. The first two experiments of this program are known as G_M^n and the neutron Two Photon Exchange (nTPE) and the data were collected from October 2021 to February 2022. Both experiments were conducted with the simultaneous measurement of D(e,e'n) and D(e,e'p) reactions for quasi-elastic electron-deuteron scattering. The scattered electrons were detected in the BigBite Spectrometer, which features multiple large-acceptance Gas Electron Multiplier (GEM) detectors. The Super BigBite Spectrometer provided simultaneous detection of scattered nucleons, and utilized a large acceptance dipole magnet and Hadron Calorimeter (HCal). The G_M^n experiment provides precision measurements of the neutron magnetic form factor, via the ratio method, over a Q^2 range of 3.0 to 13.5 (GeV/c)2. From this data analysis, preliminary values for G_M^n/µ_n G_D are extracted. For Q^2=4.48 (GeV/c)2 we find G_M^n/µ_n G_D=0.9546±0.0132 and for Q^2=4.476 (GeV/c)2 we find G_M^n/µ_n G_D=0.9563±0.0110. These preliminary G_M^n/µ_n G_D values are more precise than existing world data in this Q^2 regime and are consistent with the most recent parameterization of the G_M^n/µ_n G_D world data. The nTPE experiment provides a first measurement of the neutron Rosenbluth Slope and seeks to quantify the two-photon exchange(TPE) contribution to elastic electron-neutron scattering at a fixed Q^2=4.5 (GeV/c)2 with two different beam energies and scattering angle values. For data of the proton form factor ratio, µ_p G_E^p/G_M^p, significant discrepancies exist between values obtained from Rosenbluth Separation and polarization transfer measurement, particularly at large Q^2, and TPE contributions are thought to resolve this discrepancy. The impacts of TPE contributions have not yet been experimentally established for the neutron. From the data analysis presented in this dissertation, a preliminary result for the neutron Rosenbluth Slope is found as S^n=(G_E^n )^2/t_n (G_M^n )^2=0.0916±0.0476 for Q^2=4.48 (GeV/c)2. This value of the neutron Rosenbluth Slope is consistent with the world data extrapolation and the absence of large TPE corrections.
This semiannual status report lists specific accomplishments made on the research of the influence of backup bearings and support structure dynamics on the behavior of rotors with active supports. Papers have been presented representing work done on the T-501 engine model; an experimental/simulation study of auxiliary bearing rotordynamics; and a description of a rotordynamical model for a magnetic bearing supported rotor system, including auxiliary bearing effects. A finite element model for a foil bearing has been developed. Additional studies of rotor/bearing/housing dynamics are currently being performed as are studies of the effects of sideloading on auxiliary bearing rotordynamics using the magnetic bearing supported rotor model.
It is shown that while fluids are very complicated systems having many degrees of freedom, the basic mechanism underlying the observed chaotic behavior of fluid turbulence may not require the consideration of many degrees of freedom. Simple dynamical systems display erratic and chaotic behavior reminiscent of turbulence, the key to which is the 'sensitivity to initial conditions' introduced by Ruelle (1978). Simple models which are sensitive to initial data and have permitted workers to study chaotic behavior are described, with attention to the Lorenz equations, Landau's idea of a continuous transition to turbulence via an infinite cascade of bifurcations, and one-dimensional maps.
The dynamic and static fatigue behavior of Kyocera SN220M sintered silicon nitride at 1000 C was studied. Fractographic analysis of the material failing in dynamic fatigue revealed the presence of slow crack growth (SCG) at stressing rates below 41 MPa/min. Under conditions of static fatigue this material also displayed SCG at stresses below 345 MPa. SCG appears to be controlled by microcracking of the grain boundaries. The crack velocity exponent (n) determined from both dynamic and static fatigue tests ranged from 11 to 16.
This research program investigated changes of dynamical and chemical structure of the lower stratosphere and how they are related to elements of the tropospheric general circulation. These considerations were explored in total ozone data from TOMS on board the Nimbus-7 satellite. It was shown that most of the daily variance of total ozone was accounted for by quasi-horizontal transport of ozone along isentropic surfaces in the lower stratosphere. Air descending along theta surfaces experiences compression that increases the local ozone number density and column abundance. Just the reverse is experienced by air ascending along isentropics surfaces. Together, these mechanisms provide an explanation for ozone "mini-hole" phenomenon, which punctuates the circulation of the Southern Hemisphere.
Abstract not provided
The work described can be divided into two parts. The first part is an investigation of the transient behavior and stability property of a phase conjugate resonator (PCR) below threshold. The second part is an experimental and theoretical study of the PCR's spatiotemporal dynamics above threshold. The time-dependent coupled wave equations for four-wave mixing (FWM) in a photorefractive crystal, with two distinct interaction regions caused by feedback from an ordinary mirror, was used to model the transient dynamics of a PCR below threshold. The conditions for self-oscillation were determined and the solutions were used to define the PCR's transfer function and analyze its stability. Experimental results for the buildup and decay times confirmed qualitatively the predicted behavior. Experiments were carried out above threshold to study the spatiotemporal dynamics of the PCR as a function of Pragg detuning and the resonator's Fresnel number. The existence of optical vortices in the wavefront were identified by optical interferometry. It was possible to describe the transverse dynamics and the spatiotemporal instabilities by modeling the three-dimensional-coupled wave equations in photorefractive FWM using a truncated modal expansion approach.
Collective properties of complex systems composed of many interacting components such as neurons in our brain can be modeled by artificial networks based on disordered systems. We show that a disordered neural network of superconducting loops with Josephson junctions can exhibit computational properties like categorization and associative memory in the time evolution of its state in response to information from external excitations. Superconducting loops can trap multiples of fluxons in many discrete memory configurations defined by the local free energy minima in the configuration space of all possible states. A memory state can be updated by exciting the Josephson junctions to fire or allow the movement of fluxons through the network as the current through them surpasses their critical current thresholds. Simulations performed with a lumped element circuit model of a 4-loop network show that information written through excitations is translated into stable states of trapped flux and their time evolution. Experimental implementation on a high-Tc superconductor YBCO-based 4-loop network shows dynamically stable flux flow in each pathway characterized by the correlations between junction firing statistics. Neural network behavior is observed as energy barriers separating state categories in simulations in response to multiple excitations, and experimentally as junction responses characterizing different flux flow patterns in the network. The state categories that produce these patterns have different temporal stabilities relative to each other and the excitations. This provides strong evidence for time-dependent (short-to-long-term) memories, that are dependent on the geometrical and junction parameters of the loops, as described with a network model.
Substantial progress has been made toward the goals of this research effort in the past six months. A simplified rotor model with a flexible shaft and backup bearings has been developed. The model is based upon the work of Ishii and Kirk. Parameter studies of the behavior of this model are currently being conducted. A simple rotor model which includes a flexible disk and bearings with clearance has been developed and the dynamics of the model investigated. The study consists of simulation work coupled with experimental verification. The work is documented in the attached paper. A rotor model based upon the T-501 engine has been developed which includes backup bearing effects. The dynamics of this model are currently being studied with the objective of verifying the conclusions obtained from the simpler models. Parallel simulation runs are being conducted using an ANSYS based finite element model of the T-501.
Progress over the past year includes the following: A simplified rotor model with a flexible shaft and backup bearings has been developed. A simple rotor model which includes a flexible disk and bearings with clearance has been developed and the dynamics of the model investigated. A rotor model based upon the T-501 engine has been developed which includes backup bearing effects. Parallel simulation runs are being conducted using an ANSYS based finite element model of the T-501. The magnetic bearing test rig is currently floating and dynamics/control tests are being conducted. A paper has been written that documents the work using the T-501 engine model. Work has continued with the simplified model. The finite element model is currently being modified to include the effects of foundation dynamics. A literature search for material on foil bearings has been conducted. A finite element model is being developed for a magnetic bearing in series with a foil backup bearing.
Animal movements are linked to infectious disease dynamics in wildlife through multiple mechanisms across various spatial and temporal scales. For example, infections can impede the movement of infected individuals, but infected hosts can also disperse infectious agents as they move. Individuals inevitably vary in their responses to infections and their roles in determining infection dynamics, which means that considering variation among individuals – whether across species, across time, or within populations – is important for understanding movement-disease relationships and their implications for epidemiology. Here, I draw on studies from multiple systems to examine how variation in movement behavior links to infectious disease epidemiology. For example, a comparative study of habitat selection across multiple waterfowl species highlights that diel behavioral patterns, rather than individual or seasonal variation, is the most important driver of the risk of overlap between waterfowl and poultry farms, and therefore for the risk of avian influenza spillover. Together, these studies show that individual traits interact with the environment to influence the roles of individuals for infectious disease ecology.
Single-atom catalysts (SACs) have garnered significant interest due to their ability to reduce metal particles to the atomic scale, enabling finely tunable local environments and enhanced catalytic properties in terms of reactivity and selectivity. Despite this potential, their application has largely been confined to small-molecule transformations as metal-catalyzed reaction. Here, in this study, we present a diverse single-atom nickel (Ni) catalyst established via a nanoporous carbon (NPC) supported practice. This catalyst represents a breakthrough by achieving the bond formation between carbon and nitrogen and interfacial dynamics in the SAC. The present first principle-based density functional simulations establish the reaction dynamics and catalytic behaviour of such SAC. This dynamic nature comprises an exclusive nitrogen intercalated site showing excellent base effects. This base quickly tunes the interfacial atmosphere, enabling dynamic movement of adatoms into the NPC species, significantly changing the reaction path in Ni SACs due to superior steric effects. The research demonstrates that SACs can extend the capabilities of catalytic systems to include a wider range of complex reactions, offering substantial promise for the development of new, efficient synthetic methods for creating value-added molecular products.
Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.
An experimental study was performed to identify the effects of dynamic strain aging (solute drag) and metallurgical instabilities under thermomechanical loading conditions. The study involved a series of closely controlled thermomechanical deformation tests on the solid-solution-strenghened nickel-base superalloy, Hastelloy X. This alloy exhibits a strong isothermal strain aging peak at approximately 600 C, promoted by the effects of solute drag and precipitation hardening. Macroscopic thermomechanical hardening trends are correlated with microstructural characteristics through the use of transmission electron microscopy. These observations are compared and contrasted with isothermal conditions. Thermomechanical behavior unique to the isothermal database is identified and discussed. The microstructural characteristics were shown to be dominated by effects associated with the highest temperature of the thermomechanical cycle. Results indicate that the deformation behavior of Hastelloy X is thermomechanically path dependent. In addition, guidance is given pertaining to deformation modeling in the context of macroscopic unified theory. An internal state variable is formulated to qualitatively reflect the isotropic hardening trends identified in the TMD experiments.
Highlights: • Crushable aggregates with the real geometry shape are generated by using clump-cluster method. • Flat-Joint Model is adopted as the constitutive law. • The tensile strength is almost not affected by ITZ strength when its strength exceeds 0.8 times that of mortar. • A modified formula that can reflect the functional relationship between the ITZ strength and the TDIF is proposed. The tensile strength is one of the main parameters in the design of concrete structures and has an important influence on the cracking performance and durability of concrete materials. As the weak region in concrete, the strength of the interface transition zone (ITZ) directly affects the dynamic mechanical response of concrete. Meanwhile, considering that the tensile performance of concrete is far weaker than its compressive performance, the study of the strength of ITZ is of great significance to the dynamic tensile fracture characteristics and mechanical properties of concrete. In this paper, a method combining 3D scanning technology and Clump-Cluster was proposed to generate a real geometry shape model of crushable aggregate. On this basis, the 3D discrete element model (DEM) of high-strength concrete was constructed using the Flat-Joint Model (FJM). The effects of the ITZ strength on the failure mode, number of microcracks, tensile strength and strain rate effect of high-strength concrete under strain rates from 0.01/s to 100/s were studied by splitting tensile test. The simulation results indicate that the number of microcracks generated decreases with the increase of ITZ strength, and the proportion of ITZ cracks decreases obviously. When the ITZ strength exceeds the critical value of 0.8 times that of mortar, the tensile strength is almost not affected by ITZ strength. In addition, based on the numerical simulation results, a modified formula that can reflect the functional relationship between the ITZ strength and the dynamic increasing factor of the concrete tensile strength (TDIF) is proposed, and the rationality of the TDIF modified formula is verified.
Solids under high pressures experience a series of regimes, where their microstructure adapts to the applied compression and these key transitions are discussed in this paper. As strain increases, new forces emerge at extreme pressures. A previous study introduced the concept of the weak shock limit (WSL), at which the ambient theoretical shear strength is overcome. Above the WSL, further deformation under strong shock conditions results in electrons occupying higher energy levels as strain increases. As pressure rises further, shock melting occurs in the material and at around three times this melting pressure, the strong shock limit is reached where the driving physics under pressure switches, with electrons forced into higher energy states. This leads to significant reduction in their compressibility due to changes in electronic structure and developing electron degeneracy pressures. A derivation for conditions at this state is presented, which indicates that a dependence of the threshold pressure on the free electron number density defines the limit observed. This correlation suggests that ambient material moduli govern material compression up to nearly 50% strain. These observations show that models should account for different behaviors as dominant physics changes in each regime accessed as shock pressure increases.
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