690 research outputs found
Using an MHD simulation to interpret the global context of a coronal mass ejection observed by two spacecraft
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94753/1/jgra16893.pd
Nonlinear ptychographic coherent diffractive imaging
Ptychographic Coherent diffractive imaging (PCDI) is a significant advance in imaging allowing the measurement of the full electric field at a sample without use of any imaging optics. So far it has been confined solely to imaging of linear optical responses. In this paper we show that because of the coherence-preserving nature of nonlinear optical interactions, PCDI can be generalised to nonlinear optical imaging. We demonstrate second harmonic generation PCDI, directly revealing phase information about the nonlinear coefficients, and showing the general applicability of PCDI to nonlinear interactions
The radial evolution of solar wind speeds
The WSA-ENLIL model predicts significant evolution of the solar wind speed. Along a flux tube the solar wind speed at 1.0 AU and beyond is found to be significantly altered from the solar wind speed in the outer corona at 0.1 AU, with most of the change occurring within a few tenths of an AU from the Sun. The evolution of the solar wind speed is most pronounced during solar minimum for solar wind with observed speeds at 1.0 AU between 400 and 500 km/s, while the fastest and slowest solar wind experiences little acceleration or deceleration. Solar wind ionic charge state observations made near 1.0 AU during solar minimum are found to be consistent with a large fraction of the intermediate-speed solar wind having been accelerated or decelerated from slower or faster speeds. This paper sets the groundwork for understanding the evolution of wind speed with distance, which is critical for interpreting the solar wind composition observations near Earth and throughout the inner heliosphere. We show from composition observations that the intermediate-speed solar wind (400-500 km/s) represents a mix of what was originally fast and slow solar wind, which implies a more bimodal solar wind in the corona than observed at 1.0 AU
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Ambient solar wind's effect on ICME transit times
Most empirical and numerical models of Interplanetary Coronal Mass Ejection (ICME) propagation use the initial CME velocity as their primary, if not only, observational input. These models generally predict a wide spread of 1 AU transit times for ICMEs with the same initial velocity. We use a 3D coupled MHD model of the corona and heliosphere to determine the ambient solar wind's effect on the propagation of ICMEs from 30 solar radii to 1 AU. We quantitatively characterize this deceleration by the velocity of the upstream ambient solar wind. The effects of varying solar wind parameters on the ICME transit time are quantified and can explain the observed spread in transit times for ICMEs of the same initial velocity. We develop an adjustment formula that can be used in conjunction with other models to reduce the spread in predicted transit times of Earth-directed ICMEs
Dietary restriction inhibits bone formation in alveolar bone modeling and remodelling
Objective: Methods: Balb/C mice weaned at the age of 21 days were assigned to one of the following groups: control group fed a regular hard diet ad libitum (food consumption was measured daily), and dietary restricted group (DR) received 75% of the amount of food consumed by the respective control mice the previous day. Body weight of all animals was recorded throughout. Mice were euthanized in groups of ten at 25 and 60 days of experience. Mandibles were dissected, descalcified in EDTA and embedded in paraffin. Buccolingual sections of the mesial root of the first lower molar were stained with hematoxylin-eosin and submitted to histomorphometric studies. Results: At 25 days, DR mice shows bone formation values lower than control animals for modeling and remodeling sides, coupled to an increase with bone at rest values in the modeling side. At 60 days, DR mice shows bone formation values lower than control animals in the modeling side linked with a similar increase in values corresponding to bone resorption and bone at rest. In the remodeling side, no differences in bone formation were observed between control and DR mice. However, high bone resorption and a decrease in bone at rest areas were observed. Conclusions: Dietery restriction impaires bone formation in physiologic alveolar bone modeling and remodeling
The Effects of IVC Modulation on Modern Diesel Engines Equipped with Variable Valve Actuation at High Load and Speed
Modern diesel compression engines are known for their increased durability, fuel economy and torque when compared with their spark ignition gasoline counterparts. These are some of the reasons why diesel engines are preferred in heavy duty applications such as trains and semi-trucks. During the Heavy Duty Federal Test Procedure transient drive cycle, or HDFTP, nearly 85% of the total fuel burned is at speeds greater than 2000 revolutions per minute (RPM) for the studied engine. Therefore, it is desirable to increase the fuel economy at these loads and speeds. It is hypothesized that the use of late intake valve close timing (LIVC) modulation could give an increase in volumetric efficiency from flow momentum. With an increase in volumetric efficiency, the open cycle efficiency (OCE) would increase. This would allow for improvements in the brake thermal efficiency (BTE). With the use of the engine simulator software GT-Power, the effects of IVC variation was explored to serve as a preliminary investigation for a variable valve actuation (VVA) engine in the future. The results from this investigation yielded an increase in volumetric efficiency through late intake valve closure (LIVC). While these findings have not been verified through experimental procedures, there could be a decrease in BSFC because the engine could breathe more efficiently, thereby reducing pumping losses
Deep learning for Gaussian process tomography model selection using the ASDEX Upgrade SXR system
Gaussian process tomography (GPT) is a method used for obtaining real-time
tomographic reconstructions of the plasma emissivity profile in a tokamak,
given some model for the underlying physical processes involved. GPT can also
be used, thanks to Bayesian formalism, to perform model selection -- i.e.,
comparing different models and choosing the one with maximum evidence. However,
the computations involved in this particular step may become slow for data with
high dimensionality, especially when comparing the evidence for many different
models. Using measurements collected by the ASDEX Upgrade Soft X-ray (SXR)
diagnostic, we train a convolutional neural network (CNN) to map SXR
tomographic projections to the corresponding GPT model whose evidence is
highest. We then compare the network's results, and the time required to
calculate them, with those obtained through analytical Bayesian formalism. In
addition, we use the network's classifications to produce tomographic
reconstructions of the plasma emissivity profile, whose quality we evaluate by
comparing their projection into measurement space with the existing
measurements themselves
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