Hot deformation characteristics of a nitride strengthened martensitic heat resistant steel

Constitutive equations including an Arrhenius term have been applied to analyze the hot deformation behavior of a nitride-strengthened (NS) martensitic heat resistant steel in temperature range of 900–1200 °C and strain rate range of 0.001–10 /s. On the basis of analysis of the deformation data, the stress–strain curves up to the peak were divided into four regions, in sequence, representing four processes, namely hardening, dynamic recovery (DRV), dynamic strain induced transformation (DSIT), and dynamic recrystallization (DRX), according to the inflection points in ∂θ/∂σ∂θ/∂σ and ∂(∂θ/∂σ)/∂σ∂(∂θ/∂σ)/∂σ curves. Some of the inflection points have their own meanings. For examples, the minimum of ∂θ/∂σ∂θ/∂σ locates the start of DRV and the maximum of it indicates the start of DRX. The results also showed that the critical strain of DRX was sensitive to ln(Z) below 40, while the critical stress of DRX was sensitive to it above 40. The final microstructures under different deformation conditions were analyzed in terms of softening processes including DRV, DRX, metadynamic crystallization (MDRX) and DSIT.

Expanded iron uta spectra - Probing the thermal stability limits in AGN clouds

The Fe unresolved transition arrays (UTAs) produce prominent features in the 15-17 Å wavelength range in the spectra of active galactic nuclei (AGNs). Here, we present new calculations of the energies and oscillator strengths of inner-shell lines from Fe XIV, Fe XV, and Fe XVI. These are crucial ions since they are dominant at inflection points in the gas thermal stability curve, and UTA excitation followed by autoionization is an important ionization mechanism for these species. We incorporate these, and data reported in previous papers, into the plasma simulation code Cloudy. This updated physics is subsequently employed to reconsider the thermally stable phases in absorbing media in AGNs. We show how the absorption profile of the Fe XIV UTA depends on density, due to the changing populations of levels within the ground configuration. © 2013. The American Astronomical Society. All rights reserved.

Path-Dependency, Stocks, Switching Points, Flows: Reflections on Long-term Global Change and Local Opportunities

This paper examines the possibilities for peripheral localities to achieve upward mobility in the world-system by “hooking on” to larger processes of world-system accumulation. In particular, is it possible for economies that are dependent on foreign investment to receive a flow of investments that is high enough to overcome the negative impacts of a high stock of foreign investment, thus enabling them to cross a threshold and achieve upward mobility in the world-system? An analysis of therecent experience of the southern Irish “Celtic Tiger” economy during 1990-2000 indicates that such an upward movement is possible on the basis of massive foreign investment inflows. On closer examination, however, the Irish-type model appears to be highly deficient, because a high proportion of growth is illusionary and also on grounds of social desirability and lack of generalizability.

Long-period chromospheric oscillations in network bright points

The spatial variation of chromospheric oscillations in network bright points (NBPs) is studied using high-resolution observations in Ca II K3. Light curves and hence power spectra were created by isolating distinct regions of the NBP via a simple intensity thresholding technique. Using this technique, it was possible to identify peaks in the power spectra with particular spatial positions within the NBPs. In particular, long-period waves with periods of 4-15 minutes (1-4 mHz) were found in the central portions of each NBP, indicating that these waves are certainly not acoustic but possibly due to magnetoacoustic or magnetogravity wave modes. We also show that spatially averaged or low spatial resolution power spectra can lead to an inability to detect such long-period waves.

Automated detection and tracking of solar magnetic bright points

Magnetic bright points (MBPs) in the internetwork are among the smallest objects in the solar photosphere and appear bright against the ambient environment. An algorithm is presented that can be used for the automated detection of the MBPs in the spatial and temporal domains. The algorithm works by mapping the lanes through intensity thresholding. A compass search, combined with a study of the intensity gradient across the detected objects, allows the disentanglement of MBPs from bright pixels within the granules. Object growing is implemented to account for any pixels that might have been removed when mapping the lanes. The images are stabilized by locating long-lived objects that may have been missed due to variable light levels and seeing quality. Tests of the algorithm, employing data taken with the Swedish Solar Telescope, reveal that approximate to 90 per cent of MBPs within a 75 x 75 arcsec(2) field of view are detected.

A study of magnetic bright points in the Na I D1 line.

High-cadence, multiwavelength, optical observations of solar magnetic bright points (MBPs), captured at the disk center using the ROSA and IBIS imaging systems on the Dunn Solar Telescope, are presented. MBPs manifesting in the Na I D-1 core are found to preferentially exist in regions containing strong downflows, in addition to cospatial underlying photospheric magnetic field concentrations. Downdrafts within Na I D-1 bright points exhibit speeds of up to 7 km s(-1), with preferred structural symmetry in intensity, magnetic field, and velocity profiles about the bright point center. Excess intensities associated with G-band and Ca II K observations of MBPs reveal a power-law trend when plotted as a function of the magnetic flux density. However, Na I D-1 observations of the same magnetic features indicate an intensity plateau at weak magnetic field strengths below approximate to 150 G, suggesting the presence of a two-component heating process: one which is primarily acoustic and the other predominantly magnetic. We suggest that this finding is related to the physical expansion of magnetic flux tubes, with weak field strengths (approximate to 50 G) expanding by similar to 76%, compared to a similar to 44% expansion when higher field strengths (approximate to 150 G) are present. These observations provide the first experimental evidence of rapid downdrafts in Na I D-1 MBPs and reveal the nature of a previously unresolved intensity plateau associated with these structures.

The Area Distribution of Solar Magnetic Bright Points

Magnetic bright points (MBPs) are among the smallest observable objects on the solar photosphere. A combination of G-band observations and numerical simulations is used to determine their area distribution. An automatic detection algorithm, employing one-dimensional intensity profiling, is utilized to identify these structures in the observed and simulated data sets. Both distributions peak at an area of approximate to 45,000 km(2), with a sharp decrease toward smaller areas. The distributions conform with log-normal statistics, which suggests that flux fragmentation dominates over flux convergence. Radiative magneto-convection simulations indicate an independence in the MBP area distribution for differing magnetic flux densities. The most commonly occurring bright point size corresponds to the typical width of inter-granular lanes.

Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.

The velocity distribution of solar photospheric magnetic bright points.

We use high spatial resolution observations and numerical simulations to study the velocity distribution of solar photospheric magnetic bright points. The observations were obtained with the Rapid Oscillations in the Solar Atmosphere instrument at the Dunn Solar Telescope, while the numerical simulations were undertaken with the MURaM code for average magnetic fields of 200 G and 400 G. We implemented an automated bright point detection and tracking algorithm on the data set and studied the subsequent velocity characteristics of over 6000 structures, finding an average velocity of approximately 1 km s(-1), with maximum values of 7 km s(-1). Furthermore, merging magnetic bright points were found to have considerably higher velocities, and significantly longer lifetimes, than isolated structures. By implementing a new and novel technique, we were able to estimate the background magnetic flux of our observational data, which is consistent with a field strength of 400 G.