scholarly journals Rotary-screw systems for rotary kilns

2019 ◽  
Vol 91 ◽  
pp. 02034 ◽  
Author(s):  
Aleksandr Sekisov ◽  
Georgy Serga

The proposed paper examines rotary-screw systems for rotary kilns in the production of expanded clay. To reduce the size, reduce weight, increase productivity, simplify operation, reduce energy consumption in the production of expanded clay, the shell is made screw-shaped and mounted horizontally. Technical solutions protected by six patents of the Russian Federation are proposed, the structures of the shells of rotary kilns are shown, which, in comparison with the known structures of similar purpose, are made screw-shaped with internal spiral grooves. The dependence is proposed for determining the speed of movement of expanded clay pellets in a screw-shaped shell of a rotary kiln. A classification of rotary-screw systems for the production of expanded clay was developed.

2020 ◽  
Vol 26 (3) ◽  
pp. 20-25
Author(s):  
Laurențiu Bogdan Asalomia ◽  
Gheorghe Samoilescu

AbstractThe paper analyses the role of control and monitoring of electro-energetic equipment in order to reduce operational costs, increase profits and reduce carbon emissions. The role of SCADA and EcoStruxure Power systems is presented and analysed taking into account the energy consumption and its savings. The paper presents practical and modern solutions to reduce energy consumption by up to 53%, mass by up to 47% and increase the life of the equipment by adjusting the electrical parameters. The Integrated Navigation System has allowed an automatic control and an efficient management. For ships, the implementation of an energy efficiency design index and new technologies was required for the GREEN SHIP project.


2015 ◽  
Vol 8 (1) ◽  
pp. 206-210 ◽  
Author(s):  
Yu Junyang ◽  
Hu Zhigang ◽  
Han Yuanyuan

Current consumption of cloud computing has attracted more and more attention of scholars. The research on Hadoop as a cloud platform and its energy consumption has also received considerable attention from scholars. This paper presents a method to measure the energy consumption of jobs that run on Hadoop, and this method is used to measure the effectiveness of the implementation of periodic tasks on the platform of Hadoop. Combining with the current mainstream of energy estimate formula to conduct further analysis, this paper has reached a conclusion as how to reduce energy consumption of Hadoop by adjusting the split size or using appropriate size of workers (servers). Finally, experiments show the effectiveness of these methods as being energy-saving strategies and verify the feasibility of the methods for the measurement of periodic tasks at the same time.


Author(s):  
Premkumar Chithaluru ◽  
Rajeev Tiwari ◽  
Kamal Kumar

Background: Energy Efficient wireless routing has been an area of research particularly to mitigate challenges surrounding performance in category of Wireless Networks. Objectives: The Opportunistic Routing (OR) technique was explored in recent times and exhibits benefits over many existing protocols and can significantly reduce energy consumption during data communication with very limited compromise on performance. Methods : Using broadcasting nature of the wireless medium, OR practices to discourse two foremost issues of variable link quality and unpredictable node agility in constrained WSNs. OR has a potential to reduce delay in order to increase the consistency of data delivery in network. Results : Various OR based routing protocols have shown varying performances. In this paper, a detailed conceptual and experimental analysis is carried out on different protocols that uses OR technique for providing more clear and definitive view on performance parameters like Message Success Rate, Packet Delivery Ratio and Energy Consumption.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Liane Bernstein ◽  
Alexander Sludds ◽  
Ryan Hamerly ◽  
Vivienne Sze ◽  
Joel Emer ◽  
...  

AbstractAs deep neural network (DNN) models grow ever-larger, they can achieve higher accuracy and solve more complex problems. This trend has been enabled by an increase in available compute power; however, efforts to continue to scale electronic processors are impeded by the costs of communication, thermal management, power delivery and clocking. To improve scalability, we propose a digital optical neural network (DONN) with intralayer optical interconnects and reconfigurable input values. The path-length-independence of optical energy consumption enables information locality between a transmitter and a large number of arbitrarily arranged receivers, which allows greater flexibility in architecture design to circumvent scaling limitations. In a proof-of-concept experiment, we demonstrate optical multicast in the classification of 500 MNIST images with a 3-layer, fully-connected network. We also analyze the energy consumption of the DONN and find that digital optical data transfer is beneficial over electronics when the spacing of computational units is on the order of $$>10\,\upmu $$ > 10 μ m.


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