The radiated energy budget of Chromospheric Plasma in a major solar flare deduced from multi-wavelength observations

This paper presents measurements of the energy radiated by the lower solar atmosphere, at optical, UV, and EUV wavelengths, during an X-class solar flare (SOL2011-02-15T01:56) in response to an injection of energy assumed to be in the form of nonthermal electrons. Hard X-ray observations from RHESSI were used to track the evolution of the parameters of the nonthermal electron distribution to reveal the total power contained in flare accelerated electrons. By integrating over the duration of the impulsive phase, the total energy contained in the nonthermal electrons was found to be >2 × 1031 erg. The response of the lower solar atmosphere was measured in the free–bound EUV continua of H i (Lyman), He i, and He ii, plus the emission lines of He ii at 304 Å and H i (Lyα) at 1216 Å by SDO/EVE, the UV continua at 1600 Å and 1700 Å by SDO/AIA, and the white light continuum at 4504 Å, 5550 Å, and 6684 Å, along with the Ca ii H line at 3968 Å using Hinode/SOT. The summed energy detected by these instruments amounted to ~3 × 1030 erg; about 15% of the total nonthermal energy. The Lyα line was found to dominate the measured radiative losses. Parameters of both the driving electron distribution and the resulting chromospheric response are presented in detail to encourage the numerical modeling of flare heating for this event, to determine the depth of the solar atmosphere at which these line and continuum processes originate, and the mechanism(s) responsible for their generation.

A Significance-Driven Programming Framework for Energy-Constrained Approximate Computing

Approximate execution is a viable technique for energy-con\-strained environments, provided that applications have the mechanisms to produce outputs of the highest possible quality within the given energy budget.
We introduce a framework for energy-constrained execution with controlled and graceful quality loss. A simple programming model allows users to express the relative importance of computations for the quality of the end result, as well as minimum quality requirements. The significance-aware runtime system uses an application-specific analytical energy model to identify the degree of concurrency and approximation that maximizes quality while meeting user-specified energy constraints. Evaluation on a dual-socket 8-core server shows that the proposed
framework predicts the optimal configuration with high accuracy, enabling energy-constrained executions that result in significantly higher quality compared to loop perforation, a compiler approximation technique.

Exploiting Significance of Computations for Energy-Constrained Approximate Computing

Approximate execution is a viable technique for environments with energy constraints, provided that applications are given the mechanisms to produce outputs of the highest possible quality within the available energy budget. This paper introduces a framework for energy-constrained execution with controlled and graceful quality loss. A simple programming model allows developers to structure the computation in different tasks, and to express the relative importance of these tasks for the quality of the end result. For non-significant tasks, the developer can also supply less costly, approximate versions. The target energy consumption for a given execution is specified when the application is launched. A significance-aware runtime system employs an application-specific analytical energy model to decide how many cores to use for the execution, the operating frequency for these cores, as well as the degree of task approximation, so as to maximize the quality of the output while meeting the user-specified energy constraints. Evaluation on a dual-socket 16-core Intel platform using 9 benchmark kernels shows that the proposed framework picks the optimal configuration with high accuracy. Also, a comparison with loop perforation (a well-known compile-time approximation technique), shows that the proposed framework results in significantly higher quality for the same energy budget.

Modeling energy consumption in error-prone IEEE 802.11-based wireless ad-hoc networks

In the IEEE 802.11 MAC layer protocol, there are different trade-off points between the number of nodes competing for the medium and the network capacity provided to them. There is also a trade-off between the wireless channel condition during the transmission period and the energy consumption of the nodes. Current approaches at modeling energy consumption in 802.11 based networks do not consider the influence of the channel condition on all types of frames (control and data) in the WLAN. Nor do they consider the effect on the different MAC and PHY schemes that can occur in 802.11 networks. In this paper, we investigate energy consumption corresponding to the number of competing nodes in IEEE 802.11's MAC and PHY layers in error-prone wireless channel conditions, and present a new energy consumption model. Analysis of the power consumed by each type of MAC and PHY over different bit error rates shows that the parameters in these layers play a critical role in determining the overall energy consumption of the ad-hoc network. The goal of this research is not only to compare the energy consumption using exact formulae in saturated IEEE 802.11-based DCF networks under varying numbers of competing nodes, but also, as the results show, to demonstrate that channel errors have a significant impact on the energy consumption.

Study on Hybrid Heat-Gas-Power Flow Algorithm for Integrated Community Energy System: 区域综合能源系统电/气/热混合潮流算法研究

With the integration of combined heat and power (CHP) units, air-conditioners and gas boilers, power, gas, and heat systems are becoming tightly linked to each other in the integrated community energy system (ICES). Interactions among the three systems are not well captured by traditional methods. To address this issue, a hybrid power-gas-heat flow calculation method was developed in this paper. In the proposed method, an energy hub model was presented to describe interactions among the three systems incorporating various CHP operating modes. In addition, three operating modes were proposed for the ICES including fully decoupled, partially coupled, and fully coupled. Numerical results indicated that the proposed algorithm can be used in the steady-state analysis of the ICES and reflect interactions among various energy systems.

A Reliability Assessment Approach for the Urban Energy System and Its Application in Energy Hub Planning

With the increasing utilization of combined heat and power plants (CHP), electrical, gas, and thermal systems are becoming tightly integrated in the urban energy system (UES). However, the three systems are usually planned and operated separately, ignoring their interactions and coordination. To address this issue, the coupling point of different systems in the UES is described by the energy hub model. With this model, an integrated load curtailment method is proposed for the UES. Then a Monte Carlo simulation based approach is developed to assess the reliability of coordinated energy supply systems. Based on this approach, a reliability-optimal energy hub planning method is proposed to accommodate higher renewable energy penetration. Numerical studies indicate that the proposed approach is able to quantify the UES reliability with different structures. Also, optimal energy hub planning scheme can be determined to ensure the reliability of the UES with high renewable penetration.

A Simple Model to Quantify Radiolytic Production following Electron Emission from Heavy-Atom Nanoparticles Irradiated in Liquid Suspensions

We present a simple model for a component of the radiolytic production of any chemical species due to electron emission from irradiated nanoparticles (NPs) in a liquid environment, provided the expression for the G value for product formation is known and is reasonably well characterized by a linear dependence on beam energy. This model takes nanoparticle size, composition, density and a number of other readily available parameters (such as X-ray and electron attenuation data) as inputs and therefore allows for the ready determination of this contribution. Several approximations are used, thus this model provides an upper limit to the yield of chemical species due to electron emission, rather than a distinct value, and this upper limit is compared with experimental results. After the general model is developed we provide details of its application to the generation of HO(•) through irradiation of gold nanoparticles (AuNPs), a potentially important process in nanoparticle-based enhancement of radiotherapy. This model has been constructed with the intention of making it accessible to other researchers who wish to estimate chemical yields through this process, and is shown to be applicable to NPs of single elements and mixtures. The model can be applied without the need to develop additional skills (such as using a Monte Carlo toolkit), providing a fast and straightforward method of estimating chemical yields. A simple framework for determining the HO(•) yield for different NP sizes at constant NP concentration and initial photon energy is also presented.

Energy Optimization of Memory Intensive Parallel Workloads

Energy consumption is an important concern in modern multicore processors. The energy consumed by a multicore processor during the execution of an application can be minimized by tuning the hardware state utilizing knobs such as frequency, voltage etc. The existing theoretical work on energy minimization using Global DVFS (Dynamic Voltage and Frequency Scaling), despite being thorough, ignores the time and the energy consumed by the CPU on memory accesses and the dynamic energy consumed by the idle cores. This article presents an analytical energy-performance model for parallel workloads that accounts for the time and the energy consumed by the CPU chip on memory accesses in addition to the time and energy consumed by the CPU on CPU instructions. In addition, the model we present also accounts for the dynamic energy consumed by the idle cores. The existing work on global DVFS for parallel workloads shows that using a single frequency for the entire duration of a parallel application is not energy optimal and that varying the frequency according to the changes in the parallelism of the workload can save energy. We present an analytical framework around our energy-performance model to predict the operating frequencies (that depend upon the amount of parallelism) for global DVFS that minimize the overall CPU energy consumption. We show how the optimal frequencies in our model differ from the optimal frequencies in a model that does not account for memory accesses. We further show how the memory intensity of an application affects the optimal frequencies.

A multi vector energy analysis for interconnected power and gas systems

This paper presents the first multi vector energy analysis for the interconnected energy systems of Great Britain (GB) and Ireland. Both systems share a common high penetration of wind power, but significantly different security of supply outlooks. Ireland is heavily dependent on gas imports from GB, giving significance to the interconnected aspect of the methodology in addition to the gas and power interactions analysed. A fully realistic unit commitment and economic dispatch model coupled to an energy flow model of the gas supply network is developed. Extreme weather events driving increased domestic gas demand and low wind power output were utilised to increase gas supply network stress. Decreased wind profiles had a larger impact on system security than high domestic gas demand. However, the GB energy system was resilient during high demand periods but gas network stress limited the ramping capability of localised generating units. Additionally, gas system entry node congestion in the Irish system was shown to deliver a 40% increase in short run costs for generators. Gas storage was shown to reduce the impact of high demand driven congestion delivering a reduction in total generation costs of 14% in the period studied and reducing electricity imports from GB, significantly contributing to security of supply.

Optimal day-ahead scheduling of integrated urban energy systems

An optimal day-ahead scheduling method (ODSM) for the integrated urban energy system (IUES) is introduced, which considers the reconfigurable capability of an electric distribution network. The hourly topology of a distribution network, a natural gas network, the energy centers including the combined heat and power (CHP) units, different energy conversion devices and demand responsive loads (DRLs), are optimized to minimize the day-ahead operation cost of the IUES. The hourly reconfigurable capability of the electric distribution network utilizing remotely controlled switches (RCSs) is explored and discussed. The operational constraints from the unbalanced three-phase electric distribution network, the natural gas network, and the energy centers are considered. The interactions between the electric distribution network and the natural gas network take place through conversion of energy among different energy vectors in the energy centers. An energy conversion analysis model for the energy center was developed based on the energy hub model. A hybrid optimization method based on genetic algorithm (GA) and a nonlinear interior point method (IPM) is utilized to solve the ODSM model. Numerical studies demonstrate that the proposed ODSM is able to provide the IUES with an effective and economical day-ahead scheduling scheme and reduce the operational cost of the IUES.

Foraging ecology, fluctuating food availability and energetics of wintering brent geese

Changing energy requirements and dramatic shifts in food availability are major factors driving behaviour and distribution of herbivores. We investigate this in wintering East Canadian High Arctic light-bellied brent geese Branta bernicla hrota in Northern Ireland. They followed a sequential pattern of habitat use, feeding on intertidal Zostera spp. in autumn and early winter before moving to predominantly saltmarsh and farmland in late winter and early spring. Night-time feeding occurred throughout and made a considerable contribution to the birds' daily energy budget, at times accounting for > 50% of energy intake. Nocturnal feeding, however, is limited to the intertidal, possibly because of predation risk on terrestrial habitat, and increases with moonlight. The amount of Zostera spp., declined dramatically after the arrival of birds, predominantly, but not entirely, due to consumption by the birds. Birds gained fat reserves in the first 2 months but then this was dramatically lost as their major food source collapsed and their daily energy intake declined. Single birds consistently fared worse than paired birds and pairs with juveniles fared better than those without suggesting a benefit of having a family to compete for food. Many birds leave the Lough at this time of reduced Zostera spp. for other sea inlets in Ireland but some remain. Body condition of the latter gradually improved in early spring and reflected a heavy reliance on terrestrial habitats, particularly farmland, to meet the birds' daily energy requirements. However, even in the period immediately before migration to the breeding ground, the birds did not regain the amount of abdominal fatness observed in November. The dramatic changes in available food and requirements of the birds drive the major changes seen in foraging behaviour as the birds evade starvation in the wintering period.

The VLT-FLAMES Tarantula Survey XI. A census of the hot luminous stars and their feedback in 30 Doradus

Context. The VLT-FLAMES Tarantula Survey has an extensive view of the copious number of massive stars in the 30 Doradus (30 Dor) star forming region of the Large Magellanic Cloud. These stars play a crucial role in our understanding of the stellar feedback in more distant, unresolved star forming regions. Aims. The first comprehensive census of hot luminous stars in 30 Dor is compiled within a 10 arcmin (150 pc) radius of its central cluster, R136. We investigate the stellar content and spectroscopic completeness of the early type stars. Estimates were made for both the integrated ionising luminosity and stellar wind luminosity. These values were used to re-assess the star formation rate (SFR) of the region and determine the ionising photon escape fraction. Methods. Stars were selected photometrically and combined with the latest spectral classifications. Spectral types were estimated for stars lacking spectroscopy and corrections were made for binary systems, where possible. Stellar calibrations were applied to obtain their physical parameters and wind properties. Their integrated properties were then compared to global observations from ultraviolet (UV) to far-infrared (FIR) imaging as well as the population synthesis code, Starburst99. Results. Our census identified 1145 candidate hot luminous stars within 150 pc of R136 of which >700 were considered to be genuine early type stars and contribute to feedback. We assess the survey to be spectroscopically complete to 85% in the outer regions (>5 pc) but only 35% complete in the region of the R136 cluster, giving a total of 500 hot luminous stars in the census which had spectroscopy. Only 31 were found to be Wolf-Rayet (W-R) or Of/WN stars, but their contribution to the integrated ionising luminosity and wind luminosity was ~ 40% and ~ 50%, respectively. Similarly, stars with M > 100 M (mostly H-rich WN stars) also showed high contributions to the global feedback, ~ 25% in both cases. Such massive stars are not accounted for by the current Starburst99 code, which was found to underestimate the integrated ionising luminosity of R136 by a factor ~ 2 and the wind luminosity by a factor ~ 9. The census inferred a SFR for 30 Dor of 0.073 ± 0.04 M yr . This was generally higher than that obtained from some popular SFR calibrations but still showed good consistency with the far-UV luminosity tracer as well as the combined Hα and mid-infrared tracer, but only after correcting for Hα extinction. The global ionising output was also found to exceed that measured from the associated gas and dust, suggesting that ~6 % of the ionising photons escape the region. Conclusions. When studying the most luminous star forming regions, it is essential to include their most massive stars if one is to determine a reliable energy budget. Photon leakage becomes more likely after including their large contributions to the ionising output. If 30 Dor is typical of other massive star forming regions, estimates of the SFR will be underpredicted if this escape fraction is not accounted for.

Optimization by quantum annealing: Lessons from simple cases

We investigate the basic behavior and performance of simulated quantum annealing (QA) in comparison with classical annealing (CA). Three simple one-dimensional case study systems are considered: namely, a parabolic well, a double well, and a curved washboard. The time-dependent Schrodinger evolution in either real or imaginary time describing QA is contrasted with the Fokker-Planck evolution of CA. The asymptotic decrease of excess energy with annealing time is studied in each case, and the reasons for differences are examined and discussed. The Huse-Fisher classical power law of double-well CA is replaced with a different power law in QA. The multiwell washboard problem studied in CA by Shinomoto and Kabashima and leading classically to a logarithmic annealing even in the absence of disorder turns to a power-law behavior when annealed with QA. The crucial role of disorder and localization is briefly discussed.