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Journal articles on the topic 'High-energy physics data grid'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Abbott, B., P. Baringer, T. Bolton, et al. "Performance of an Operating High Energy Physics Data Grid: DØSAR-Grid." International Journal of Modern Physics A 20, no. 16 (2005): 3874–76. http://dx.doi.org/10.1142/s0217751x05027850.

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The DØ experiment at Fermilab's Tevatron will record several petabytes of data over the next five years in pursuing the goals of understanding nature and searching for the origin of mass. Computing resources required to analyze these data far exceed capabilities of any one institution. Moreover, the widely scattered geographical distribution of DØ collaborators poses further serious difficulties for optimal use of human and computing resources. These difficulties will exacerbate in future high energy physics experiments, like the LHC. The computing grid has long been recognized as a solution t

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2

Sakamoto, Hiroshi. "Data grid deployment for high energy physics in Japan." Computer Physics Communications 177, no. 1-2 (2007): 239–42. http://dx.doi.org/10.1016/j.cpc.2007.02.061.

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Caspart, René, Patrick Firnkes, Manuel Giffels, et al. "Modeling and Simulation of Load Balancing Strategies for Computing in High Energy Physics." EPJ Web of Conferences 214 (2019): 03027. http://dx.doi.org/10.1051/epjconf/201921403027.

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The amount of data to be processed by experiments in high energy physics (HEP) will increase tremendously in the coming years. To cope with this increasing load, most efficient usage of the resources is mandatory. Furthermore, the computing resources for user jobs in HEP will be increasingly distributed and heterogeneous, resulting in more difficult scheduling due to the increasing complexity of the system. We aim to create a simulation for the WLCG helping the HEP community to solve both challenges: a more efficient utilization of the grid and coping with the rising complexity of the system.

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4

Huang, Tianhang, Tianyi Zhai, Xin Zhang, and Xiaomeng Di. "Electric Power-grid Friendly Characteristic Data Center Energy Consumption Optimization Method." Journal of Physics: Conference Series 2095, no. 1 (2021): 012026. http://dx.doi.org/10.1088/1742-6596/2095/1/012026.

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Abstract With the acceleration of the digitization process, the load of the data center on the power grid continues to increase. During the operation of the data center, the load demand on the power grid is relatively large, and the load demand on the power grid fluctuates greatly. In the Power industry, the average PUE(power usage effectiveness) of data center is above 2, which is extremely unfriendly to the power grid. This paper proposes and summarizes the optimization parameters at various levels, the energy efficiency of software and hardware, and provides a method for optimization throug

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Chen, Ke, Hongkai Wang, Zhangchi Ying, Chengxin Zhang, and Jiaqi Wang. "Online cleaning method of power grid energy anomaly data based on improved random forest." Journal of Physics: Conference Series 2108, no. 1 (2021): 012067. http://dx.doi.org/10.1088/1742-6596/2108/1/012067.

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Abstract Aiming at the problem of high root mean square error of traditional power grid energy anomaly data online cleaning, a power grid energy anomaly data online cleaning method based on improved random forest is designed. Firstly, an outlier data recognition model of isolated forest is designed to identify outliers in the data. Secondly, an improved random forest regression model is established to improve the adaptability of random forest to mixed abnormal data, and the data trend is fitted and predicted. Finally, the improved random forest data cleaning method is used to compensate the mi

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Ahn, S., J. H. Kim, T. Huh, et al. "The Embedment of a Metadata System at Grid Farms at the Belle II." Journal of the Korean Physical Society 59, no. 4 (2011): 2695–701. https://doi.org/10.3938/jkps.59.2695.

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In order to search for new physics beyond the standard model, the next generation of B-factory experiment, Belle II will collect a huge data sample that is a challenge for computing systems. The Belle II experiment, which should commence data collection in 2015, expects data rates 50 times greater than that of Belle. In order to handle this amount of data, we need a new data handling system based on a new computing model, which is a distributed computing model including grid farms as opposed to the central computing model using clusters at the Belle experiment. We have constructed a metadata s

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Domenici, Andrea, Flavia Donno, Gianni Pucciani, Heinz Stockinger, and Kurt Stockinger. "Replica consistency in a Data Grid." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 534, no. 1-2 (2004): 24–28. http://dx.doi.org/10.1016/j.nima.2004.07.052.

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Davies, C. T. H., A. C. Irving, R. D. Kenway, and C. M. Maynard. "International lattice data grid." Nuclear Physics B - Proceedings Supplements 119 (May 2003): 225–26. http://dx.doi.org/10.1016/s0920-5632(03)01509-3.

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Andronico, G., R. Barbera, and A. Falzone. "Grid portal-based data management for lattice QCD data." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 534, no. 1-2 (2004): 76–79. http://dx.doi.org/10.1016/j.nima.2004.07.062.

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10

Klimentov, Alexei, Douglas Benjamin, Alessandro Di Girolamo, et al. "Enabling Data Intensive Science on Supercomputers for High Energy Physics R&D Projects in HL-LHC Era." EPJ Web of Conferences 226 (2020): 01007. http://dx.doi.org/10.1051/epjconf/202022601007.

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The ATLAS experiment at CERN’s Large Hadron Collider uses theWorldwide LHC Computing Grid, the WLCG, for its distributed computing infrastructure. Through the workload management system PanDA and the distributed data management system Rucio, ATLAS provides seamless access to hundreds of WLCG grid and cloud based resources that are distributed worldwide, to thousands of physicists. PanDA annually processes more than an exabyte of data using an average of 350,000 distributed batch slots, to enable hundreds of new scientific results from ATLAS. However, the resources available to the experiment h

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11

Filipowicz, M., V. M. Bystritsky, P. E. Knowles, F. Mulhauser, and J. Woźniak. "Method of Monte Carlo grid for data analysis." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 547, no. 2-3 (2005): 652–62. http://dx.doi.org/10.1016/j.nima.2005.04.010.

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12

Khan, Bilal, Zahid Ullah, and Giambattista Gruosso. "Enhancing Grid Stability Through Physics-Informed Machine Learning Integrated-Model Predictive Control for Electric Vehicle Disturbance Management." World Electric Vehicle Journal 16, no. 6 (2025): 292. https://doi.org/10.3390/wevj16060292.

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Integrating electric vehicles (EVs) has become integral to modern power grids to enhance grid stability and support green energy transportation solutions. EVs emerged as a promising energy solution that introduces a significant challenge to the unpredictable and dynamic nature of EV charging and discharging behaviors. These EV behaviors are performed by grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operations that create unpredictable disturbances in the power grid. These disturbances introduced a nonlinear dynamic that compromises grid stability and power quality. Due to the unpredictable n

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13

Newman, Harvey B. "Data intensive grids and networks for high energy and nuclear physics." Nuclear Physics B - Proceedings Supplements 120 (June 2003): 109–12. http://dx.doi.org/10.1016/s0920-5632(03)01889-9.

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14

Negirla, Paul, Romina Druță, and Ioan Silea. "Availability Improvements through Data Slicing in PLC Smart Grid Networks." Sensors 20, no. 24 (2020): 7256. http://dx.doi.org/10.3390/s20247256.

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An electrical power grid, is an interconnected network for delivering electricity from producers to consumers. Electrical grids vary in size from covering a single building through national grids (which cover whole countries) to transnational grids (which can cross continents). As the rollout of smart meters continues worldwide, there are use-cases where common solutions fail and the network availability of certain meters is very low due to poor communication conditions. This paper proposes a data slicing model for large data files which have to travel securely and reliably throughout the Smar

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Dost, Jeffrey, Marco Mascheroni, Brian Bockelman, et al. "A Lightweight Door into Non-Grid Sites." EPJ Web of Conferences 245 (2020): 07005. http://dx.doi.org/10.1051/epjconf/202024507005.

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The Open Science Grid (OSG) provides a common service for resource providers and scientific institutions, and supports sciences such as High Energy Physics, Structural Biology, and other community sciences. As scientific frontiers expand, so does the need for resources to analyze new data. For example, High Energy Physics experiments such as the LHC experiments foresee an exponential growth in the amount of data collected, which comes with corresponding growth in the need for computing resources. Allowing resource providers an easy way to share their resources is paramount to ensure the grow o

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Kim, Jin-Woo, Jaehee Kim, and Jaeho Lee. "An Adaptive Network Design for Advanced Metering Infrastructure in a Smart Grid." Sensors 22, no. 22 (2022): 8625. http://dx.doi.org/10.3390/s22228625.

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A smart grid is a next-generation intelligent power grid that can maximize energy efficiency by monitoring power information in real time and by controlling the flow of power by introducing IT communication technology to the existing power grid. In order to apply a wireless communication network to a smart grid, it is necessary to be able to efficiently process large amounts of power-related data while enabling a high level of reliability and quality of service (QoS) support. In addition, international standards-based design is essential considering compatibility and scalability. The IEEE 802.

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Feng, Dawei. "(Invited) Thermodynamics-Informed Approach for Organic Molecular Additives in Halide Redox Flow Batteries." ECS Meeting Abstracts MA2025-01, no. 45 (2025): 2398. https://doi.org/10.1149/ma2025-01452398mtgabs.

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With the growing integration of renewable energy sources, the need for efficient, large-scale energy storage solutions becomes increasingly vital for grid stability. Redox flow batteries (RFBs) are a leading candidate for this role, offering scalability and flexibility. This talk presents two innovative approaches to advancing RFB technology for grid energy storage. In the first approach, we perform extensive manual data collection through high-throughput synthesis and testing of aqueous organic redox flow batteries. This method enables the rapid identification and optimization of redox-active

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18

Costa, Michela, and Gianluca Del Papa. "Digital Twins for Intelligent Vehicle-to-Grid Systems: A Multi-Physics EV Model for AI-Based Energy Management." Applied Sciences 15, no. 15 (2025): 8214. https://doi.org/10.3390/app15158214.

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This paper presents a high-fidelity multi-physics dynamic model for electric vehicles, serving as a fundamental building block for intelligent vehicle-to-grid (V2G) integration systems. The model accurately captures complex vehicle dynamics of the powertrain, battery, and regenerative braking, enabling precise energy consumption evaluation, including in AI-driven V2G scenarios. Validated using real-world data from a Citroën Ami operating on urban routes in Naples, Italy, it achieved exceptional accuracy with a root mean square error (RMSE) of 1.28% for dynamic state of charge prediction. This

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19

Ukawa, Akira. "Status of International Lattice Data Grid – An Overview –." Nuclear Physics B - Proceedings Supplements 140 (March 2005): 207–8. http://dx.doi.org/10.1016/j.nuclphysbps.2004.11.251.

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20

Irving, A. C., R. D. Kenway, C. M. Maynard, and T. Yoshié. "Progress in building an International Lattice Data Grid." Nuclear Physics B - Proceedings Supplements 129-130 (March 2004): 159–63. http://dx.doi.org/10.1016/s0920-5632(03)02517-9.

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21

Ali, Muhamad, BT Djoko Laras, Muhfizaturrahmah, and PS Deny. "Design Smart Grid Hybrid in Faculty of Engineering Universitas Negeri Yogyakarta." Journal of Physics: Conference Series 2111, no. 1 (2021): 012003. http://dx.doi.org/10.1088/1742-6596/2111/1/012003.

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Abstract The Faculty of Engineering, Universitas Negeri Yogyakarta (UNY), as one of the educational institutions in Engineering, still uses electrical energy from PT PLN, mainly generated from steam and gas power plants. Dependence on fossil energy can be reduced by utilizing renewable power plants, both solar and wind. For this reason, it is necessary to study the use of a Smart Grid system that can regulate electricity needs by optimizing renewable power plants. The Smart Grid components consist of solar power plants, wind power plants, batteries, inverters, and grid power sources from PLN i

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22

Basu, Shibom, Jakub W. Kaminski, Ezequiel Panepucci, et al. "Automated data collection and real-time data analysis suite for serial synchrotron crystallography." Journal of Synchrotron Radiation 26, no. 1 (2019): 244–52. http://dx.doi.org/10.1107/s1600577518016570.

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At the Swiss Light Source macromolecular crystallography (MX) beamlines the collection of serial synchrotron crystallography (SSX) diffraction data is facilitated by the recent DA+ data acquisition and analysis software developments. The SSX suite allows easy, efficient and high-throughput measurements on a large number of crystals. The fast continuous diffraction-based two-dimensional grid scan method allows initial location of microcrystals. The CY+ GUI utility enables efficient assessment of a grid scan's analysis output and subsequent collection of multiple wedges of data (so-called minise

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23

Berdnikov, A. S. "High order numerical differentiation and approximation of Laplace fields using regular grid data." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 645, no. 1 (2011): 292–99. http://dx.doi.org/10.1016/j.nima.2011.01.056.

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24

Nainar, Karthikeyan, Catalin Iosif Ciontea, Kamal Shahid, et al. "Experimental Validation and Deployment of Observability Applications for Monitoring of Low-Voltage Distribution Grids." Sensors 21, no. 17 (2021): 5770. http://dx.doi.org/10.3390/s21175770.

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Future distribution grids will be subjected to fluctuations in voltages and power flows due to the presence of renewable sources with intermittent power generation. The advanced smart metering infrastructure (AMI) enables the distribution system operators (DSOs) to measure and analyze electrical quantities such as voltages, currents and power at each customer connection point. Various smart grid applications can make use of the AMI data either in offline or close to real-time mode to assess the grid voltage conditions and estimate losses in the lines/cables. The outputs of these applications c

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25

Fajardo, Edgar, Derek Weitzel, Mats Rynge, et al. "Creating a content delivery network for general science on the internet backbone using XCaches." EPJ Web of Conferences 245 (2020): 04041. http://dx.doi.org/10.1051/epjconf/202024504041.

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A general problem faced by opportunistic users computing on the grid is that delivering cycles is simpler than delivering data to those cycles. In this project XRootD caches are placed on the internet backbone to create a content delivery network. Scientific workflows in the domains of high energy physics, gravitational waves, and others profit from this delivery network to increases CPU efficiency while decreasing network bandwidth use.

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26

Traynor, Daniel, and Terry Froy. "Provision and use of GPU resources for distributed workloads via the Grid." EPJ Web of Conferences 245 (2020): 03002. http://dx.doi.org/10.1051/epjconf/202024503002.

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The Queen Mary University of London WLCG Tier-2 Grid site has been providing GPU resources on the Grid since 2016. GPUs are an important modern tool to assist in data analysis. They have historically been used to accelerate computationally expensive but parallelisable workloads using frameworks such as OpenCL and CUDA. However, more recently their power in accelerating machine learning, using libraries such as TensorFlow and Coffee, has come to the fore and the demand for GPU resources has increased. Significant effort is being spent in high energy physics to investigate and use machine learni

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Liu, Xin, and Zhonghua Gou. "Optimizing Photovoltaic-Storage Building Energy Systems: A Comparative Study of Rule-Based and Reinforcement Learning Control for Grid Stability and Self-Consumption." Journal of Physics: Conference Series 3001, no. 1 (2025): 012030. https://doi.org/10.1088/1742-6596/3001/1/012030.

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Abstract With the advancement of energy transition, the adoption of photovoltaic systems in residential buildings has been increasing. However, their intermittent and unstable nature poses challenges to grid stability. Integrating energy storage batteries into building energy systems has emerged as a key solution to enhance grid reliability. Despite this, optimizing battery charging and discharging strategies to achieve self-sufficiency, peak load shaving, and supply-demand balance remains a challenge. This study introduces two battery control strategies: Rule Based Control (RBC) approach and

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Tanwar, Sudeep, Aparna Kumari, Darshan Vekaria, et al. "GrAb: A Deep Learning-Based Data-Driven Analytics Scheme for Energy Theft Detection." Sensors 22, no. 11 (2022): 4048. http://dx.doi.org/10.3390/s22114048.

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Integrating information and communication technology (ICT) and energy grid infrastructures introduces smart grids (SG) to simplify energy generation, transmission, and distribution. The ICT is embedded in selected parts of the grid network, which partially deploys SG and raises various issues such as energy losses, either technical or non-technical (i.e., energy theft). Therefore, energy theft detection plays a crucial role in reducing the energy generation burden on the SG and meeting the consumer demand for energy. Motivated by these facts, in this paper, we propose a deep learning (DL)-base

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Beklemysheva, Katerina, Alexey Vasyukov, and Alexey Ermakov. "Grid-characteristic numerical method for medical ultrasound." Journal of Physics: Conference Series 2090, no. 1 (2021): 012164. http://dx.doi.org/10.1088/1742-6596/2090/1/012164.

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Abstract Grid-characteristic method (GCM) is a fast and reliable numerical method that allows to model wave effects in viscoelastic media with high accuracy, including surface and contact waves. This research is dedicated to the application of GCM to the problem of medical ultrasound. Calculations for High-Intensity Focused Ultrasound (HIFU) were performed on 3D model statements for homogenous and inhomogeneous media, and a qualitative correspondence with experimental data was achieved. Numerical results include estimation of consumed energy (based on Maxwell viscosity model), velocity vector

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Olson, D. L., and J. Perl. "Interfacing interactive data analysis tools with the GRID: the PPDG CS-11 activity." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 502, no. 2-3 (2003): 420–22. http://dx.doi.org/10.1016/s0168-9002(03)00457-1.

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31

Maynard, C. M., and D. Pleiter. "QCDml: First milestones for building an International Lattice Data Grid." Nuclear Physics B - Proceedings Supplements 140 (March 2005): 213–21. http://dx.doi.org/10.1016/j.nuclphysbps.2004.11.116.

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32

Butler, Joel N. "Distributed and/or grid-oriented approach to BTeV data analysis." Nuclear Physics B - Proceedings Supplements 120 (June 2003): 131–35. http://dx.doi.org/10.1016/s0920-5632(03)01893-0.

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33

Hwang, Myunggwon, Yuna Jeong, and Won-Kyung Sung. "Analysis of Learning Influence of Training Data Selected by Distribution Consistency." Sensors 21, no. 4 (2021): 1045. http://dx.doi.org/10.3390/s21041045.

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This study suggests a method to select core data that will be helpful for machine learning. Specifically, we form a two-dimensional distribution based on the similarity of the training data and compose grids with fixed ratios on the distribution. In each grid, we select data based on the distribution consistency (DC) of the target class data and examine how it affects the classifier. We use CIFAR-10 for the experiment and set various grid ratios from 0.5 to 0.005. The influences of these variables were analyzed with the use of different training data sizes selected based on high-DC, low-DC (in

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34

Barisits, Martin, Thomas Beermann, Joaquin Bogado, et al. "Evolution of the open-source data management system Ru-cio for LHC Run-3 and beyond ATLAS." EPJ Web of Conferences 214 (2019): 04054. http://dx.doi.org/10.1051/epjconf/201921404054.

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Rucio, the distributed data management system of the ATLAS experiment already manages more than 400 Petabytes of physics data on the grid. Rucio was incrementally improved throughout LHC Run-2 and is currently being prepared for the HL-LHC era of the experiment. Next to these improvements the system is currently evolving into a full-scale generic data management system for application beyond ATLAS, or even beyond high-energy physics. This contribution focuses on the development roadmap of Rucio for LHC Run-3, such as event level data management, generic meta-data support and increased usage of

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35

Alekseev, Aleksandr, Simone Campana, Xavier Espinal, et al. "On the road to a scientific data lake for the High Luminosity LHC era." International Journal of Modern Physics A 35, no. 33 (2020): 2030022. http://dx.doi.org/10.1142/s0217751x20300227.

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The experiments at CERN’s Large Hadron Collider use the Worldwide LHC Computing Grid, the WLCG, for its distributed computing infrastructure. Through the distributed workload and data management systems, they provide seamless access to hundreds of grid, HPC and cloud based computing and storage resources that are distributed worldwide to thousands of physicists. LHC experiments annually process more than an exabyte of data using an average of 500,000 distributed CPU cores, to enable hundreds of new scientific results from the collider. However, the resources available to the experiments have b

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Beckett, Mark G., Chris R. Allton, Christine T. H. Davies, et al. "Building a scientific data grid with D i GS." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367, no. 1897 (2009): 2471–81. http://dx.doi.org/10.1098/rsta.2009.0050.

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We provide an insight into the challenge of building and supporting a scientific data infrastructure with reference to our experience working with scientists from computational particle physics and molecular biology. We illustrate how, with modern high-performance computing resources, even small scientific groups can generate huge volumes (petabytes) of valuable scientific data and explain how grid technology can be used to manage, publish, share and curate these data. We describe the D i GS software application, which we have developed to meet the needs of smaller communities and we have high

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Cao, O’Rourke, Lyons, and Han. "Home Energy Management System Incorporating Heat Pump Using Real Measured Data." Sensors 19, no. 13 (2019): 2937. http://dx.doi.org/10.3390/s19132937.

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The demand for electricity has been rising significantly over the past years and it is expected to rise further in the coming years due to economic and societal development. Smart grid technology is being developed in order to meet the rising electricity requirement. In order for the smart grid to perform its full functions, the Energy Management Systems (EMSs), especially Home Energy Management Systems (HEMS) are essential. It is necessary to understand the energy demand of the loads and the energy supply either from the national grid or from renewable energy technologies. To facilitate the D

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38

Danyk, A. Yu, and O. O. Sudakov. "Physical bases for determination of scattering kernels from incomplete data in grid-less X-ray imaging." Nuclear Physics and Atomic Energy 22, no. 2 (2021): 189–96. http://dx.doi.org/10.15407/jnpae2021.02.189.

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A mathematical model for the determination of X-ray scattering kernels’ shapes based on incomplete simulation or measurement data was introduced and tested using a mathematical phantom. The model is originally intended for low-dose X-ray imaging without anti-scatter grids. The proposed model fits different kinds of symmetrical and asymmetrical scattering kernels in different tissues well enough for practical applications. Kernels asymmetry is mostly caused by irradiation of the object near the boundaries of different tissues. The model describes a variety of asymmetrical kernels by proposed “s

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Yang, Jingwen, Zhongxiao Chen, Gang Qin, Jiarui Chen, and Kaiqing Fu. "Research on the Structure of Distribution Network Voltage Smart Grid Information System Based On Flexible DC." Journal of Physics: Conference Series 2066, no. 1 (2021): 012037. http://dx.doi.org/10.1088/1742-6596/2066/1/012037.

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Abstract Since the concept of smart grid was defined, it has aroused the interest of many researchers, and many countries have also regarded smart grid as a key research project. Because it is the field of power grid research in the future, the structure of the smart grid becomes more complex with the deepening of research, the scale becomes larger, and the data contained in the system is bound to increase rapidly. Flexible DC grid technology has the characteristics of high reliability, good fault tolerance and good scalability, and can be used to solve some problems encountered in the applica

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Ma, Junpeng, Jianjun Sha, and Feiyan Liu. "Optimal Allocation Algorithm of Grid Side Energy Storage Capacity under Large Scale Wind Farm Connection." Journal of Physics: Conference Series 2087, no. 1 (2021): 012005. http://dx.doi.org/10.1088/1742-6596/2087/1/012005.

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Abstract For grid energy storage capacity configuration is not reasonable, problems such as instability in crossing the river power fluctuations, are proposed based on a large scale wind power grid side under the condition of energy storage capacity of the optimal allocation algorithm, through the use of large-scale wind farm access method to achieve the optimal design of power grid model, so as to quickly solve the micro grid energy storage capacity planning cost and energy consumption data, according to the results. The operation parameters, energy loss and other numerical values of the mode

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Seneviratne, Chatura, Patikiri Arachchige Don Shehan Nilmantha Wijesekara, and Henry Leung. "Performance Analysis of Distributed Estimation for Data Fusion Using a Statistical Approach in Smart Grid Noisy Wireless Sensor Networks." Sensors 20, no. 2 (2020): 567. http://dx.doi.org/10.3390/s20020567.

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Internet of Things (IoT) can significantly enhance various aspects of today’s electric power grid infrastructures for making reliable, efficient, and safe next-generation Smart Grids (SGs). However, harsh and complex power grid infrastructures and environments reduce the accuracy of the information propagating through IoT platforms. In particularly, information is corrupted due to the measurement errors, quantization errors, and transmission errors. This leads to major system failures and instabilities in power grids. Redundant information measurements and retransmissions are traditionally use

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Wospakrik, Marianette, Holger Schulz, Jim Kowalkowski, et al. "Grid-based minimization at scale: Feldman-Cousins corrections for light sterile neutrino search." EPJ Web of Conferences 251 (2021): 02065. http://dx.doi.org/10.1051/epjconf/202125102065.

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High Energy Physics (HEP) experiments generally employ sophisticated statistical methods to present results in searches of new physics. In the problem of searching for sterile neutrinos, likelihood ratio tests are applied to short-baseline neutrino oscillation experiments to construct confidence intervals for the parameters of interest. The test statistics of the form Δχ2 is often used to form the confidence intervals, however, this approach can lead to statistical inaccuracies due to the small signal rate in the region-of-interest. In this paper, we present a computational model for the compu

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Noor, Ahmed Qarabsh, Sabah Sabry Sana, and Ahmed Qarabash Haneen. "Smart grid in the context of industry 4.0: an overview of communications technologies and challenges." Indonesian Journal of Electrical Engineering and Computer Science (IJEECS) 18, no. 2 (2020): 656–65. https://doi.org/10.11591/ijeecs.v18.i2.pp656-665.

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The recent advances in technology, the increased dependence on electrical energy and the emergence of the fourth industrial revolution (Industry 4.0) were all factors in the increased need for smart, efficient and reliable energy systems. This introduced the concept of the Smart Grid (SG). A SG is a potential replacement for older power grids, capable of adapting and distributing energy based on demand. SG systems are complex. They combine various components and have high requirements for real time reliable operation. This paper attempts to provide an overview of SG systems, by outlining SG ar

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Croce, Daniele, Fabrizio Giuliano, Ilenia Tinnirello, and Laura Giarré. "Privacy-Preserving Overgrid: Secure Data Collection for the Smart Grid." Sensors 20, no. 8 (2020): 2249. http://dx.doi.org/10.3390/s20082249.

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In this paper, we present a privacy-preserving scheme for Overgrid, a fully distributed peer-to-peer (P2P) architecture designed to automatically control and implement distributed Demand Response (DR) schemes in a community of smart buildings with energy generation and storage capabilities. To monitor the power consumption of the buildings, while respecting the privacy of the users, we extend our previous Overgrid algorithms to provide privacy preserving data aggregation (PP-Overgrid). This new technique combines a distributed data aggregation scheme with the Secure Multi-Party Computation par

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Aloisio, Alberto, Paolo Branchini, Antonio Budano, et al. "The Argo YBJ Daq System and the GRID Based Data Transfer." IEEE Transactions on Nuclear Science 55, no. 1 (2008): 241–45. http://dx.doi.org/10.1109/tns.2007.909988.

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Su, Jingxin, Ryuji Miyazaki, Toru Tamaki, and Kazufumi Kaneda. "High-Resolution Representation for Mobile Mapping Data in Curved Regular Grid Model." Sensors 19, no. 24 (2019): 5373. http://dx.doi.org/10.3390/s19245373.

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As mobile mapping systems become a mature technology, there are many applications for the process of the measured data. One interesting application is the use of driving simulators that can be used to analyze the data of tire vibration or vehicle simulations. In previous research, we presented our proposed method that can create a precise three-dimensional point cloud model of road surface regions and trajectory points. Our data sets were obtained by a vehicle-mounted mobile mapping system (MMS). The collected data were converted into point cloud data and color images. In this paper, we utiliz

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Din, Jalalud, Hongsheng Su, Sajad Ali, and Muhammad Salman. "Research on Blockchain-Enabled Smart Grid for Anti-Theft Electricity Securing Peer-to-Peer Transactions in Modern Grids." Sensors 24, no. 5 (2024): 1668. http://dx.doi.org/10.3390/s24051668.

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Electricity theft presents a significant financial burden to utility companies globally, amounting to trillions of dollars annually. This pressing issue underscores the need for transformative measures within the electrical grid. Accordingly, our study explores the integration of block chain technology into smart grids to combat electricity theft, improve grid efficiency, and facilitate renewable energy integration. Block chain’s core principles of decentralization, transparency, and immutability align seamlessly with the objectives of modernizing power systems and securing transactions within

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Vesztergombi, G., T. Alber, H. Appelshäuser, et al. "Preliminary results on Pb+Pb collisions from the Grid-TOF data analysed in Budapest." Acta Physica Hungarica A) Heavy Ion Physics 4, no. 1-4 (1996): 55–62. http://dx.doi.org/10.1007/bf03155599.

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Purna Prakash, Kasaraneni, Yellapragada Venkata Pavan Kumar, Kasaraneni Himajyothi, and Gogulamudi Pradeep Reddy. "Comprehensive Bibliometric Analysis on Smart Grids: Key Concepts and Research Trends." Electricity 5, no. 1 (2024): 75–92. http://dx.doi.org/10.3390/electricity5010005.

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Over the years, a rapid evolution of smart grids has been witnessed across the world due to their intelligent operations and control, smart characteristics, and benefits, which can overcome several difficulties of traditional electric grids. However, due to multifaceted technological advancements, the development of smart grids is evolving day by day. Thus, smart grid researchers need to understand and adapt to new concepts and research trends. Understanding these new trends in smart grids is essential for several reasons, as the energy sector undergoes a major transformation towards becoming

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Laveyne, Joannes I., Dimitar Bozalakov, Greet Van Eetvelde, and Lieven Vandevelde. "Impact of Solar Panel Orientation on the Integration of Solar Energy in Low-Voltage Distribution Grids." International Journal of Photoenergy 2020 (February 1, 2020): 1–13. http://dx.doi.org/10.1155/2020/2412780.

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In Belgium, and many other countries, rooftop solar panels are becoming a ubiquitous form of decentralised energy production. The increasing share of these distributed installations however imposes many challenges on the operators of the low-voltage distribution grid. They must keep the voltage levels and voltage balance on their grids in check and are often regulatory required to provide sufficient reception capacity for new power producing installations. By placing solar panels in different inclinations and azimuth angles, power production profiles can possibly be shifted to align more with

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