Relevant bibliographies by topics / Edge energy

Academic literature on the topic 'Edge energy'

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Published: 9 March 2023
Last updated: 11 March 2023

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Journal articles on the topic "Edge energy"

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Rez, P., and N. K. Menon. "Inner Shell Edge Jump Ratios in Electron Energy Loss Spectrometry." Microscopy and Microanalysis 7, S2 (August 2001): 1170–71. http://dx.doi.org/10.1017/s1431927600031925.

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There has been considerable interest in recent years in simulating the complete electron energy loss (EELS) spectrum to help the analyst make suitable judgments on experimental parameters such as collection angles and acquisition times. The spectrum is characterised by edges that arise from the excitation of inner shell electrons to the first available empty state. The edge threshold is approximately given by the inner shell binding energy. Each edge sits on the background of the tails of all the edges from inner shell excitations of lower energy (see Figl). The background from plasmons decays very quickly with energy and even the broadest plasmon makes a negligible contribution to the intensity for losses above about 150eV. The visibility of an edge (and also the detectability of the corresponding element) can be related to the intensity of the edge compared to the background although it is more common to use the jump ratio, which is the ratio of the intensity in the region after the edge E+B to the intensity of the background in the edge region, B.
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Rajendra, R., and P. Siva Kota Reddy. "On Tosha-degree of an Edge in a Graph." European Journal of Pure and Applied Mathematics 13, no. 5 (December 27, 2020): 1097–109. http://dx.doi.org/10.29020/nybg.ejpam.v13i5.3710.

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In an earlier paper, we have introduced the Tosha-degree of an edge in a graph without multiple edges and studied some properties. In this paper, we extend the definition of Tosha-degree of an edge in a graph in which multiple edges are allowed. Also, we introduce the concepts - zero edges in a graph, $T$-line graph of a multigraph, Tosha-adjacency matrix, Tosha-energy, edge-adjacency matrix and edge energy of a graph $G$ and obtain some results.
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Batson, P. E. "Energy loss extreme — near-edge and pre-edge structure." Proceedings, annual meeting, Electron Microscopy Society of America 46 (1988): 498–99. http://dx.doi.org/10.1017/s0424820100104558.

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During the past several years we have begun to understand many features of the core loss excitations including absolute crosssections, extended fine structure, (EXELFS) and near edge fine structure. (ELNES) In electronic materials near interfaces or defects, we expect the valence and conduction bands to be modified by the existence of isolated resonances, broadening of the band edges, or a completely filled gap region. These electronic changes have been observed with high resolution EELS in the low energy loss region (0-3eV) where direct inter-band transitions are likely. The present work is aimed at determining if pre-edge structure near the core loss scattering may reflect local changes in the electronic structure as well. There are two major experimental difficulties: 1) the necessary energy resolution is of order 0.1-0.3eV in order to define the shape of the core edge; and 2) the energy differential scattering cross section is small (of order 10-23cm2eV-1). At IBM I have addressed these problems by constructing a high resolution energy loss spectrometer system with parallel recording to allow signal collection in reasonable times.
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Matsubara, E., K. Okuda, Y. Waseda, S. N. Okuno, and K. Inomata. "Structural Study of Amorphous Co-Ferrite Film by Anomalous X-Ray Scattering." Zeitschrift für Naturforschung A 45, no. 9-10 (October 1, 1990): 1144–50. http://dx.doi.org/10.1515/zna-1990-9-1011.

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Abstract The structure of amorphous Co-ferrite film grown on a glass substrate was studied by anomalous X-ray scattering (AXS). Co atoms cannot be distinguished from Fe atoms with the usual X-ray diffraction technique. Therefore the AXS method at the Fe and Co K-absorption edges was adopted. In the previous AXS studies only the lower energy side of the absorption edges was adopted. In the previous AXS studies only the lower energy side of the absorption edge was used. In the present case, the lower energy side of the Co K-absorption edge corresponds to the higher energy side of the Fe K-absorption edge. Therefore, in order to overcome this inconvenience, the scattering was measured on both sides of the absorption edge, thus enabling the independent determination of the oxygen coordination numbers around Co and Fe in the ferrite film from the environmental RDFs estimated from the energy differential profiles by coupling with the linear least squares technique.
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Nageswari, P., and P. B. Sarasija. "Edge energy bounds of graphs." Applied Mathematical Sciences 8 (2014): 2101–4. http://dx.doi.org/10.12988/ams.2014.42100.

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CHAPMAN, C. J. "Energy paths in edge waves." Journal of Fluid Mechanics 426 (January 10, 2001): 135–54. http://dx.doi.org/10.1017/s0022112000002184.

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In this paper the energy streamlines, energy paths, and energy streak lines in a steady or unsteady inhomogeneous acoustic field next to an unstable oscillating boundary, such as a vortex sheet or shear layer, are determined. The theory in the paper applies also to an evanescent wave produced by total internal reflection, and to any other type of edge wave, e.g. a coastally or topographically trapped wave in geophysical fluid dynamics. The idea of the paper is that energy velocity, i.e. energy flux divided by energy density, is defined at every point in space and time, not merely when averaged over a cycle. Integration of the ordinary differential equation for energy velocity as a function of position and time gives the energy paths. These paths are calculated explicitly, and are found to have starting and finishing directions very different from those of cycle-averaged paths. The paper discusses the physical significance of averaged and non-averaged energy paths, especially in relation to causality. Many energy paths have cusps, at which the energy velocity is instantaneously zero. The domain of influence of an arbitrary point on the boundary of a steady acoustic edge wave is shown to lie within 45° of a certain direction, in agreement with a known result on shear-layer instability in compressible flow. The results are consistent with flow visualization photographs of near-field jet noise. The method of the paper determines domains of influence and causality in any wave problem with an explicit solution, for example as represented by a Fourier integral.
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Jeon, Joohyung, Soohyun Park, Minseok Choi, Joongheon Kim, Young-Bin Kwon, and Sungrae Cho. "Optimal User Selection for High-Performance and Stabilized Energy-Efficient Federated Learning Platforms." Electronics 9, no. 9 (August 21, 2020): 1359. http://dx.doi.org/10.3390/electronics9091359.

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Federated learning-enabled edge devices train global models by sharing them while avoiding local data sharing. In federated learning, the sharing of models through communication between several clients and central servers results in various problems such as a high latency and network congestion. Moreover, battery consumption problems caused by local training procedures may impact power-hungry clients. To tackle these issues, federated edge learning (FEEL) applies the network edge technologies of mobile edge computing. In this paper, we propose a novel control algorithm for high-performance and stabilized queue in FEEL system. We consider that the FEEL environment includes the clients transmit data to associated federated edges; these edges then locally update the global model, which is downloaded from the central server via a backhaul. Obtaining greater quantities of local data from the clients facilitates more accurate global model construction; however, this may be harmful in terms of queue stability in the edge, owing to substantial data arrivals from the clients. Therefore, the proposed algorithm varies the number of clients selected for transmission, with the aim of maximizing the time-averaged federated learning accuracy subject to queue stability. Based on this number of clients, the federated edge selects the clients to transmit on the basis of resource status.
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Petri, Ioan, Omer Rana, Yacine Rezgui, and Fodil Fadli. "Edge HVAC Analytics." Energies 14, no. 17 (September 2, 2021): 5464. http://dx.doi.org/10.3390/en14175464.

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Integrating data analytics, optimisation and dynamic control to support energy services has seen significant interest in recent years. Larger appliances used in an industry context are now provided with Internet of Things (IoT)-based interfaces that can be remotely monitored, with some also provided with actuation interfaces. The combined use of IoT and edge computing enables connectivity between energy systems and infrastructure, providing the means to implement both energy efficiency/optimisation and cost reduction strategies. We investigate the economic implications of harnessing IoT and edge/cloud technologies to support energy management for HVAC (Heating, Ventilation and Air Conditioning) systems in buildings. In particular, we evaluate the cost savings for building operations through energy optimisation. We use a real use case for energy optimisation as identified in the EU “Sporte2” project (focusing on the energy optimisation of sports facilities) and explore several scenarios in relation to costs and energy optimisation.
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Li, Hui, Yongjun Chen, Yang Yang, Shixin Wang, Ling Bai, and Ling Zhou. "CFD Simulation of Centrifugal Pump with Different Impeller Blade Trailing Edges." Journal of Marine Science and Engineering 11, no. 2 (February 11, 2023): 402. http://dx.doi.org/10.3390/jmse11020402.

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The centrifugal pump is one of the most widely used types of power machinery in the field of ship and ocean engineering, and the shape of the impeller blade trailing edge has an important influence on their performance. To reveal the mechanism of the effect of different trailing edges on external performance, the internal flow of 16 types of impeller blade trailing edges of a centrifugal pump, consisting of Bezier trailing edges, rounding on the pressure side, cutting on the suction side, and the original trailing edge is studied by numerical simulation. The reverse flow, shaft power, and energy loss distribution in the impeller and diffuser along the streamwise direction are analyzed by calculating them on each micro control body sliced from the fluid domain. The entropy production theory and Ω-vortex identification method are used to display the magnitude and location of energy loss and the vortex structure. Finally, a static structural analysis of the impeller with different trailing edges is performed. The results show that different impeller trailing edges can clearly affect the efficiency of the pump, i.e., the thinner the trailing edge, the higher the efficiency, with the thickest model reducing efficiency by 5.71% and the thinnest model increasing efficiency by 0.59% compared to the original one. Changing the shape of the impeller trailing edge has a great influence on the reverse flow, shaft power, and energy loss near the impeller trailing edge and diffuser inlet but has little influence on the leading part of the impeller. The distribution of local entropy production rate, energy loss, and reverse flow along the streamwise direction shows similar rules, with a local maximum near the leading edge of the impeller due to the impact effect, and a global maximum near the impeller trailing edge resulting from strong flow separation and high vortex strength due to the jet-wake flow. Thinning the impeller trailing edge and smoothing its connection with the blade can reduce the vortex strength and entropy production near the impeller trailing edge and diffuser inlet, improve the flow pattern, and reduce energy loss, thus improving the pump efficiency. In all models, the maximum equivalent stress is less than 6.5 MPa and the maximum total deformation is less than 0.065mm. The results are helpful for a deeper understanding of the complex flow mechanism of the centrifugal pump with different blade trailing edges.
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Santitissadeekorn, N., and E. M. Bollt. "Image Edge Respecting Denoising with Edge Denoising by a Designer Nonisotropic Structure Tensor Method." Computational Methods in Applied Mathematics 9, no. 3 (2009): 309–18. http://dx.doi.org/10.2478/cmam-2009-0019.

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AbstractWe consider image denoising as the problem of removing spurious oscillations due to noise while preserving edges in the images. We will suggest here how to directly make infinitesimal adjustment to standard variational methods of image denoising, to enhance desirable target assumption of the noiseless image. The standard regularization method is used to define a suitable energy functional to penalize the data fidelity and the smoothness of the solution. This energy functional is tailored so that the region with small gradient is isotropically smoothed whereas in a neighborhood of an edge presented by a large gradient smoothing is allowed only along the edge contour. The regularized solution that arises in this fashion is then the solution of a variational principle. To this end the associated Euler — Lagrange equation needs to be solved numerically and the half-quadratic minimization is generally used to linearize the equation and to derive an iterative scheme. We describe here a method to modify Euler — Largrange equation from commonly used energy functionals, in a way to enhance certain desirable preconceived assumptions of the image, such as edge preservation. From an algorithmic point of view, we may deem this algorithm as a smoothing by a local average with an adaptive gradient-based weight. However, this algorithm may result in noisy edges although the edge is preserved and noise is suppressed in the low-gradient regions of the image. The main focus here is to present an edge-preserving regularization in the aforementioned view point, and to provide an alternative and simple way to modify the existing algorithm to mitigate the phenomena of noisy edges without explicitly defining step where we specify an energy functional to be minimized.
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Dissertations / Theses on the topic "Edge energy"

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Johansson, Jennifer. "Cooling storage for 5G EDGE data center." Thesis, Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-79126.

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Data centers requires a lot of energy due to that data centers count as the buildings also contains servers, cooling equipment, IT-equipment and power equipment. As the cooling solution for many data centers around the world right now, the compressor-based cooling solution counts for around 40% of the total energy consumption. A non-compressor-based solution that is used in some data centers, but also is in a research phase is the free cooling application. Free cooling means that the outside air is utilized to cool down the data center and there are two main technologies that contains within free cooling: airside free cooling and waterside free cooling. The purpose of this master thesis is to analyze two types of coils; one corrugated and the other one smooth, providing from Bensby Rostfria, to investigate if it is possible to use free cooling in 5G EDGE data center in Luleå, with one of these coils. The investigation will be done during the warmest day in summer. This because, according to weather data, Luleå is one candidate where this type of cooling system could be of use. The project was done through RISE ICE Datacenter where two identical systems was built next to each other with two corrugated hoses of different diameter and two smooth tubes with different diameter. The variables that was measured was the ambient temperature within the data hall, the water temperature in both water tanks, the temperature out from the system, the temperature in to the system and the mass flow of the air that was going to go through the system. The first thing that was done was to do fan curves to easier choose which input voltages for the fans that was of interest to do further analysis on. After that was done, three point was taken where the fan curve was of most increase. The tests were done by letting the corrugated hoses and smooth tubes to be in each of the water tanks and fill it with cold water. It was thereafter the coils that should warm the water from 4,75 °C – 9,75 °C, because of that the temperature in the data center was around 15 °C. The rising in particularly these temperatures was chosen because it is seen that to use free cooling the temperature differences must be at least 5 °C. The tests were done three times to get a more reliable result. All the data was further taken in to Zabbix and to further analysis in Grafana. When one test was done the files was saved from Grafana to Excel for compilation, and thereafter to Matlab for further analysis. The first thing that was analyzed was if the three different tests with the same input voltages gave similar results in the water temperature in the tank and the temperature out from the system. Thereafter, trendlines was built to investigate the temperature differences in and out of the system, the temperature differences in and the water temperature in the tank, the mass flow and the cooling power. That trendline was further in comparison to each other, which was 2D-plots between the cooling power and the temperature differences between the inlet and the water. Thereafter the both coils could compare to each other to see which of them that gave the largest cooling power and was most efficient to install in a future 5G data center module.  The conclusion for this master thesis is that the corrugated hose will give a higher cooling power with higher temperature differences outside, but during the warmest summer day it was distinctly the smooth tube that gave the largest cooling power and therefore the best result. The smooth tube also got, through hand calculations, the larger amount of pipe that was necessary to cool down the 5G module, but the smallest water tank. It was also shown that for the warmest summer day, a temperature in the water tank of 24 °C is the best, compared to 20 °C and 18 °C. The amount of coil that is needed to cool down the data center with a temperature in the water tank at 24 °C and how large the water tank differs between the two types of coils. For the corrugated hose a length of 1.8 km and a water tank of 9.4 m3. As for the smooth tube a length of 1.7 km and a water tank volume of 12 m3.  As can be seen throughout this project is that this type of cooling equipment is not the most efficient for the warmest summer day but could easily be used for other seasons.
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Madhvesh, Ashok. "Crucial edge detection in sensor system under energy constraints." Thesis, Wichita State University, 2009. http://hdl.handle.net/10057/2507.

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Wireless sensor nodes are usually deployed in remote locations for various applications that require monitoring of certain interesting events. Due to this remote operational feature the longevity of the sensor node's lifetime has been a primary concern. Although the sensor nodes available today may be equipped with rechargeable batteries, the minimal energy capacity of such batteries and low recharge rates degrade the sensor's lifetime and achievable performance. Hence, operational algorithms are needed to guarantee high performance with efficient utilization of energy available. In this thesis, considering temporally correlated event phenomena, the important question answered is: "How long should the sensor sleep, and for how long should the sensor stay active?". To achieve this, a sensor activation/deactivation algorithm has been developed that achieves high performance with efficient energy utilization. A sensor loses energy predominantly because of redundant transmissions of sensed data. To avoid this, a sensor was modeled to transmit only the changes sensed in the event-occurrence process, referred to as Crucial Edges or Transitions. In addition, the system model allows the transmission of transitions that are detected late. Several intuitive decision-making policies were compared and the results compared in order to determine the best policy for this problem. This policy was later analyzed usingMarkov chain analysis techniques to derive upper and lower bounds on the achievable performance. The proposed policy achieves high performance under energy balancing constraints, and is deterministic, simple and easy to implement on a sensor node.
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science
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Liu, Wei-Hsin. "Investigation of edge effects in thermoacoustic couple measurements." Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA246393.

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Thesis (M.S. in Engineering Acoustics)--Naval Postgraduate School, December 1990.
Thesis Advisor(s): Atchley, Anthony A. ; Hofler, Thomas J. "December 1990." Description based on title screen as viewed on March 31, 2010. DTIC Descriptor(s): Heat Transfer, Coupling (Interaction), Peak Values, Ratios, Temperature, Thermodynamics, Edges, Isolation, Sensitivity, Regions, Short Range (Time), Profiles, Plates, Internal, Acoustic Arrays, Pressure, Drives, Leading Edges, Mean, Amplitude, Sound Pressure, Stacking, Thermopiles. DTIC Identifier(s): Heat Pumps, Energy Conversion, Energy Storage, Heat Transfer, Thermoacoustic Couples, Theses Author(s) subject terms: Acoustics, Thermoacoustics, Thermoacoustic Heat Transport. Includes bibliographical references (p. 34). Also available in print.
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Chang, Xiaomin. "Sustainable Edge Computing Platform for Energy Management in Smart Homes." Thesis, The University of Sydney, 2018. http://hdl.handle.net/2123/20245.

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There is a growing trend for engaging edge computing to help smart homes to improve the comfort of living for residents. The rapidly rising interest in such deployments, however, does not usually correspond with energy management schemes. In this thesis, we will propose a unified system framework for enabling a sustainable edge computing, while meeting the needs of data processing for smart home applications. Besides, we also designed an edge-based energy management framework for powering smart appliances at home, which aims to enable the use of renewable energy to greatly reduce energy costs for households. To make better use of renewable energy, a modified forecasting approach will be applied in both frameworks, to constantly forecast renewable energy generation. Furthermore, two optimal energy scheduling algorithms for edge devices and one job scheduling algorithm for appliance jobs are also proposed in this thesis. By employing advanced energy disaggregation technique in the edge-based energy management framework, usage pattern and users preference on each appliance can be derived, and thus, each appliance job can be rescheduled based on this information. To evaluate the performance of two edge computing paradigms, two prototype systems have been implemented by using low-cost and easy-to-get hardware. The experiment results demonstrate that renewable energy is completely capable of supporting the reliable running of edge computing devices and smart appliances, and the utilisation of renewable energy increased significantly when our proposed frameworks were employed, compared with when they were not.
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Bozorgchenani, Arash <1989&gt. "Energy and Delay Efficient Computation Offloading Solutions for Edge Computing." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amsdottorato.unibo.it/9356/1/PhD%20Thesis_Arash%20Bozorgchenani.pdf.

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This thesis collects a selective set of outcomes of a PhD course in Electronics, Telecommunications, and Information Technologies Engineering and it is focused on designing techniques to optimize computational resources in different wireless communication environments. Mobile Edge Computing (MEC) is a novel and distributed computational paradigm that has emerged to address the high users demand in 5G. In MEC, edge devices can share their resources to collaborate in terms of storage and computation. One of the computational sharing techniques is computation offloading, which brings a lot of advantages to the network edge, from lower communication, to lower energy consumption for computation. However, the communication among the devices should be managed such that the resources are exploited efficiently. To this aim, in this dissertation, computation offloading in different wireless environments with different number of users, network traffic, resource availability and devices' location are analyzed in order to optimize the resource allocation at the network edge. To better organize the dissertation, the studies are classified in four main sections. In the first section, an introduction on computational sharing technologies is given. Later, the problem of computation offloading is defined, and the challenges are introduced. In the second section, two partial offloading techniques are proposed. While in the first one, centralized and distributed architectures are proposed, in the second work, an Evolutionary Algorithm for task offloading is proposed. In the third section, the offloading problem is seen from a different perspective where the end users can harvest energy from either renewable sources of energy or through Wireless Power Transfer. In the fourth section, the MEC in vehicular environments is studied. In one work a heuristic is introduced in order to perform the computation offloading in Internet of Vehicles and in the other a learning-based approach based on bandit theory is proposed.
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Xia, Chunqiu. "Energy Demand Response Management in Smart Home Environments." Thesis, The University of Sydney, 2018. http://hdl.handle.net/2123/20182.

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ENABLING DEMAND RESPONSE ON ENERGY MANAGEMENT IN SMART HOME With the penetration of the Internet of Things (IoT) paradigm into the household scenario, an increasing number of smart appliances have been deployed to improve the comfort of living in the household. At present, most smart home devices are adopting the Cloud-based paradigm. The increasing electricity overhead from these smart appliances, however, has caused issues, as existing home energy management systems are unable to reduce electricity consumption effectively. To address this issue, we propose the use of an Edge-based computing platform with lightweight computing devices. In our experiments, this Edge-based platform has proven to be more energy efficient when compared to the traditional Cloud-based platform. To further reduce energy tariffs for households, we propose an energy management framework, namely Edge-based energy management System (EEMS), to be used with the Edge-based system that was designed in the first stage of our research. The EEMS is a low infrastructure investment system. A small-scale solar energy harvesting system has also been integrated into this system. The non-intrusive load monitoring (NILM) algorithm has been implemented in appliances monitoring. Regarding to energy management function, the scheduling strategy can also conform to user preference. We have conducted a realistic experiment with several smart appliances and Raspberry Pi. The experiment resulted in the electricity tariff being reduced by 82.3%. The last part of research addresses demand response (DR) technology. With the development of DR, energy management systems such as EEMS are better able to be implemented. We propose the use of an electricity business trading model, integrated with user-side demand response resources. The business trading model can be adopted to manage risks, increase profit and improve user satisfaction. Users will also benefit from tariffs reduction with the use of this model.
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Raffa, Viviana. "Edge/cloud virtualization techniques and resources allocation algorithms for IoT-based smart energy applications." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22864/.

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Nowadays, the installation of residential battery energy storage (BES) has increased as a consequence of the decrease in the cost of batteries. The coupling of small-scale energy generation (residential PV) and residential BES promotes the integration of microgrids (MG), i.e., clusters of local energy sources, energy storages, and customers which are represented as a single controllable entity. The operations between multiple grid-connected MGs and the distribution network can be coordinated by controlling the power exchange; however, in order to achieve this level of coordination, a control and communication MG interface should be developed as an add-on DMS (Distribution Management System) functionality to integrate the MG energy scheduling with the network optimal power flow. This thesis proposes an edge-cloud architecture that is able to integrate the microgrid energy scheduling method with the grid constrained power flow, as well as providing tools for controlling and monitoring edge devices. As a specific case study, we consider the problem of determining the energy scheduling (amount extracted/stored from/in batteries) for each prosumer in a microgrid with a certain global objective (e.g. to make a few energy exchanges as possible with the main grid). The results show that, in order to have better optimization of the BES scheduling, it is necessary to evaluate the composition of a microgrid in such a way as to have balanced deficits and surpluses, which can be performed with Machine Learning (ML) techniques based on past production and consumption data for each prosumer.
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Singh, Navjot. "Planning of Mobile Edge Computing Resources in 5G Based on Uplink Energy Efficiency." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38444.

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Increasing number of devices demand for low latency and high-speed data transmission require that the computation resources to be closer to users. The emerging Mobile Edge Computing (MEC) technology aims to bring the advantages of cloud computing which are computation, storage and networking capabilities in close proximity of user. MEC servers are also integrated with cloud servers which give them flexibility of reaching vast computational power whenever needed. In this thesis, leveraging the idea of Mobile Edge Computing, we propose algorithms for cost-efficient and energy-efficient the placement of Mobile Edge nodes. We focus on uplink energy-efficiency which is essential for certain applications including augmented reality and connected vehicles, as well as extending battery life of user equipment that is favorable for all applications. The experimental results show that our proposed schemes significantly reduce the uplink energy of devices and minimizes the number of edge nodes required in the network.
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Chang, Zhongwen, Pär Olsson, Nils Sandberg, and Dmitry Terentyev. "Interaction Energy Calculations of Edge Dislocation with Point Defects in FCC Cu." KTH, Reaktorfysik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-122396.

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In order to improve the dislocation bias (DB) model of swelling under irradiation, a large scale of atomistic simulation of the interaction in face centered cubic (FCC) Cu model lattice between an edge dislocation (ED) and point defects such as a vacancy, a self-interstital atom (SIA) have been performed for various configurations. It is found dislocation core splits into partial cores after energy relaxation. Interactions with any SIA conficurations is one order of magnitute larger than with a vacancy. The reason that SIA creats a larger dilatation volumn than the vacancy is directly observed from calculation. Furthurmore, within the interaction range, an octahedron position rather than dumbbell in <100> direction is observed in the stable state after relaxation in interactions between a edge dislocation and a dumbbell SIA. Comparision of interaction energy in analytical and atomistic calculation shows that analytical one has a stronger interaction in vacancy-ED systems, suggesting that the bias factor (BF) from analytical calculation is larger than from atomistic calculation.

QC 20130530


Generation IV reactor research and development (GENIUS)
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Pitts, R. A. "Ion energy, sheath potential and secondary electron emission in the tokamak edge." Thesis, Royal Holloway, University of London, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.508346.

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Books on the topic "Edge energy"

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The energy edge. Washington, DC: Life Line Press, 1999.

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The energy edge. New York: Harper Resource, 2000.

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Cutting edge energy technology. San Diego, CA: ReferencePoint Press, Inc., 2017.

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United States. Dept. of Energy and National Association of Manufacturers (U.S.), eds. Energy efficiency: The competitive edge. [Washington, D.C.?]: U.S. Dept. of Energy, 1991.

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Canadian Broadcasting Corporation. The leading edge: Sleep. Montreal: CBC Transcripts, 1985.

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Service, CERA Advisory. Distributed processing: Can "the edge" give companies an edge? : private report. Cambridge, Mass: CERA, 2001.

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Tiwari, Rajeev, Mamta Mittal, and Lalit Mohan Goyal, eds. Energy Conservation Solutions for Fog-Edge Computing Paradigms. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-3448-2.

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Chen, Ying, Ning Zhang, Yuan Wu, and Sherman Shen. Energy Efficient Computation Offloading in Mobile Edge Computing. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16822-2.

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Corporation, Canadian Broadcasting. The leading edge: Migma reactor. Montreal: CBC Transcripts, 1985.

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Canadian Broadcasting Corporation. The leading edge: Gaia hypothesis. Montreal: CBC Transcripts, 1985.

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Book chapters on the topic "Edge energy"

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Bahreini, Tayebeh, Hossein Badri, and Daniel Grosu. "Energy-Aware Capacity Provisioning and Resource Allocation in Edge Computing Systems." In Edge Computing – EDGE 2019, 31–45. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23374-7_3.

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Mukhanov, Lev, and Georgios Karakonstantis. "Improving DRAM Energy-efficiency." In Computing at the EDGE, 123–40. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-74536-3_5.

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Newell, Peter, David Kerner, and Scott Thomas. "Lessons from the Edge." In Springer Proceedings in Energy, 97–105. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15964-5_9.

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Pink, Sarah. "Energy." In Emerging Technologies / Life at the Edge of the Future, 84–97. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003182528-7.

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Radtke, Guillaume, and Gianluigi A. Botton. "Energy Loss Near-Edge Structures." In Scanning Transmission Electron Microscopy, 207–45. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7200-2_5.

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Bergami, Leonardo. "Adaptive Trailing Edge Flap Placement." In Research Topics in Wind Energy, 81–88. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07365-1_5.

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Sena, Arthur Sousa de, Mehar Ullah, and Pedro H. J. Nardelli. "Edge Computing in Smart Grids." In Handbook of Smart Energy Systems, 1–11. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72322-4_106-1.

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Papadimitriou, George, and Dimitris Gizopoulos. "Harnessing Voltage margins for Balanced Energy and Performance." In Computing at the EDGE, 51–90. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-74536-3_3.

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Gelenbe, Erol, and Yunxiao Zhang. "Sharing Energy for Optimal Edge Performance." In SOFSEM 2020: Theory and Practice of Computer Science, 24–36. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38919-2_3.

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Fan, Tiantian, Yeliang Qiu, Congfeng Jiang, and Jian Wan. "Energy Aware Edge Computing: A Survey." In High-Performance Computing Applications in Numerical Simulation and Edge Computing, 79–91. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9987-0_8.

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Conference papers on the topic "Edge energy"

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Gedawy, Hend, Karim Habak, Khaled Harras, and Mounir Hamdi. "An Energy-Aware IoT Femtocloud System." In 2018 IEEE International Conference on Edge Computing (EDGE). IEEE, 2018. http://dx.doi.org/10.1109/edge.2018.00015.

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Brännvall, Rickard, Mikko Siltala, Jonas Gustafsson, Jeffrey Sarkinen, Mattias Vesterlund, and Jon Summers. "EDGE." In e-Energy '20: The Eleventh ACM International Conference on Future Energy Systems. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3396851.3402656.

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Li, Yuanzhe, and Shangguang Wang. "An Energy-Aware Edge Server Placement Algorithm in Mobile Edge Computing." In 2018 IEEE International Conference on Edge Computing (EDGE). IEEE, 2018. http://dx.doi.org/10.1109/edge.2018.00016.

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Loghin, Dumitrel, Lavanya Ramapantulu, and Yong Meng Teo. "On Understanding Time, Energy and Cost Performance of Wimpy Heterogeneous Systems for Edge Computing." In 2017 IEEE International Conference on Edge Computing (EDGE). IEEE, 2017. http://dx.doi.org/10.1109/ieee.edge.2017.10.

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Rausch, Thomas, Cosmin Avasalcai, and Schahram Dustdar. "Portable Energy-Aware Cluster-Based Edge Computers." In 2018 IEEE/ACM Symposium on Edge Computing (SEC). IEEE, 2018. http://dx.doi.org/10.1109/sec.2018.00026.

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Thananjeyan, Shanmuganathan, Chien Aun Chan, Elaine Wong, and Ampalavanapillai Nirmalathas. "Energy-Efficient Mobile Edge Hosts for Mobile Edge Computing System." In 2018 IEEE International Conference on Information and Automation for Sustainability (ICIAfS). IEEE, 2018. http://dx.doi.org/10.1109/iciafs.2018.8913354.

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Pomsar, Ladislav, Alexander Brecko, and Iveta Zolotova. "Brief overview of Edge AI accelerators for energy-constrained edge." In 2022 IEEE 20th Jubilee World Symposium on Applied Machine Intelligence and Informatics (SAMI). IEEE, 2022. http://dx.doi.org/10.1109/sami54271.2022.9780669.

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Zhang, Yiying, Kun Liang, Suxiang Zhang, and Yeshen He. "Applications of edge computing in PIoT." In 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2017. http://dx.doi.org/10.1109/ei2.2017.8245749.

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Giordano, Andrea, Carlo Mastroianni, Luigi Scarcello, and Giandomenico Spezzano. "An Optimization Model for Efficient Energy Exchange in Energy Communities." In 2020 Fifth International Conference on Fog and Mobile Edge Computing (FMEC). IEEE, 2020. http://dx.doi.org/10.1109/fmec49853.2020.9144901.

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Aguirre-Nunez, Jose Alonso, Luis Manuel Garcia-Barajas, Jose de Jesus Hetnandez-Gomez, Juan Pablo Serrano-Rubio, and Rafael Herrera-Guzman. "Energy Monitoring Consumption at IoT-Edge." In 2019 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC). IEEE, 2019. http://dx.doi.org/10.1109/ropec48299.2019.9057094.

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Reports on the topic "Edge energy"

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Karabekov, I. P., and G. R. Neil. Beam energy absolute measurement using K-edge absorption spectrometers. Office of Scientific and Technical Information (OSTI), May 1994. http://dx.doi.org/10.2172/10143355.

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Mirin, A. A., and P. T. Van Dyke. Computing at the leading edge: Research in the energy sciences. Office of Scientific and Technical Information (OSTI), February 1994. http://dx.doi.org/10.2172/10119562.

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Piette, M. A., R. Diamond, and B. Nordman. Final report on the energy edge impact evaluation of 28 new, low-energy commercial buildings. Office of Scientific and Technical Information (OSTI), August 1994. http://dx.doi.org/10.2172/451205.

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Heerwagen, Judith, Joel Loveland, Nancy Quense, John Barnes, Chris Cooksey, Carreen Press, Julian Somers, and Mary Shaughnessey. Energy Edge, Post-Occupancy Evaluation Project: The Eastgate Corporate Center Bellevue, Washington. Office of Scientific and Technical Information (OSTI), June 1990. http://dx.doi.org/10.2172/5571312.

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Fiksel, G., S. C. Prager, R. D. Bengtson, and A. J. Wootton. The perpendicular electron energy flux driven by magnetic fluctuations in the edge of TEXT-U. Office of Scientific and Technical Information (OSTI), June 1995. http://dx.doi.org/10.2172/468595.

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Prinja, A. K., and D. Knoll. Computational support and model development for edge-plasma and energy transport simulations. Progress report, 1989. Office of Scientific and Technical Information (OSTI), December 1989. http://dx.doi.org/10.2172/10176499.

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Anand, Dhananjay, Md Amimul Ehsan, Collin Freiheit, Thomas Linn, and Tzong Hao Chen. Validation Capabilities of the NIST Campus Power System to Evaluate Distributed Control of Grid-Edge Distributed Energy Resources. National Institute of Standards and Technology, August 2021. http://dx.doi.org/10.6028/nist.tn.2173.

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Ferguson, Thomas, Paul Jorgensen, and Jie Chen. The Knife Edge Election of 2020: American Politics Between Washington, Kabul, and Weimar. Institute for New Economic Thinking Working Paper Series, November 2021. http://dx.doi.org/10.36687/inetwp169.

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Abstract:
This paper analyzes the 2020 election, focusing on voters, not political money, and emphasizing the importance of economic geography. Drawing extensively on county election returns, it analyzes how spatial factors combined with industrial structures to shape the outcome. It treats COVID 19’s role at length. The paper reviews studies suggesting that COVID 19 did not matter much, but then sets out a new approach indicating it mattered a great deal. The study analyzes the impact on the vote not only of unemployment but differences in income and industry structures, along with demographic factors, including religion, ethnicity, and race. It also studies how the waves of wildcat strikes and social protests that punctuated 2020 affected the vote in specific areas. Trump’s very controversial trade policies and his little discussed farm policies receive detailed attention. The paper concludes with a look at how political money helped make the results of the Congressional election different from the Presidential race. It also highlights the continuing importance of private equity and energy sectors opposed to government action to reverse climate change as conservative forces in (especially) the Republican Party, together with agricultural interests.
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Muelaner, Jody Emlyn. Decarbonized Power Options for Non-road Mobile Machinery. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, January 2023. http://dx.doi.org/10.4271/epr2023002.

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<div class="section abstract"><div class="htmlview paragraph">Power options for off-road vehicles differ substantially from other commercial vehicles. Battery electrification is suitable for urban construction and light agriculture, but remote mining, forestry, and road building operations will require alternative fuels.</div><div class="htmlview paragraph"><b>Decarbonized Power Options for Non-road Mobile Machinery</b> discusses these domains as well as the potential benefits and challenges of implementing fuels and energy sources such as bioenergy, e-fuels, and alcohol, as well as hydrogen, hydrocarbon, and direct methanol fuel cells.</div><div class="htmlview paragraph"><a href="https://www.sae.org/publications/edge-research-reports" target="_blank">Click here to access the full SAE EDGE</a><sup>TM</sup><a href="https://www.sae.org/publications/edge-research-reports" target="_blank"> Research Report portfolio.</a></div></div>
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Ambrosio, G. White Paper on Leading-Edge technology And Feasibility-directed (LEAF) Program aimed at readiness demonstration for Energy Frontier Circular Colliders by the next decade. Office of Scientific and Technical Information (OSTI), March 2022. http://dx.doi.org/10.2172/1861372.

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