ADROIT: An Adaptive Dynamic Refresh Optimization Framework for DRAM Energy Saving In DNN Training

2021 ◽  
Author(s):  
Xinhan Lin ◽  
Liang Sun ◽  
Fengbin Tu ◽  
Leibo Liu ◽  
Xiangyu Li ◽  
...  
Keyword(s):  
Energy Saving ◽  
Adaptive Dynamic ◽  
Optimization Framework

An Optimization Framework for PBCF Energy Saving Devices

2018 ◽  
Author(s):  
Stefano Gaggero ◽  
Diego Villa
Keyword(s):  
Energy Saving ◽  
Optimization Design ◽  
Design Strategy ◽  
Geometrical Parameters ◽  
High Fidelity ◽  
Propulsive Efficiency ◽  
Optimization Framework ◽  
Parametric Description ◽  
Reliable Design ◽  
Dynamics Analyses

The need of continuously improving propulsive efficiency encourages the development of energy saving devices, the understanding of their underlying principles and the validation of their effectiveness. In this work, a design by optimization of Propeller Boss Cap Fin (PBCF) devices is carried out using Computational Fluid Dynamics analyses. RANS calculations (by the OpenFOAM library) are applied in an automatic optimization design approach involving a parametric description of the main characteristics of PBCFs. The optimization is carried out with multiple purposes: identify a reliable design strategy necessary to customize the PBCF geometry based on the propeller functioning and evaluate the influence of alternative configurations and of main geometrical parameters in achieving higher efficiency. The use of high-fidelity RANS calculations confirm that the decrease of the hub vortex strength, the reduction of the net torque and the influence of the additional fins on blades performance are the major contributors to the increase of efficiency. Results of detailed analyses of optimal PBCF configurations show model scale increases of efficiency of about 1%.

scholarly journals Multiparameter Optimization Framework of Cyberphysical Systems: A Case Study on Energy Saving of the Automotive Engine

Actuators ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 330
Author(s):  
Youding Sun ◽  
Zhongpan Zhu ◽  
Aimin Du ◽  
Xinwen Chen
Keyword(s):  
Genetic Algorithm ◽  
Energy Saving ◽  
Dynamic Performance ◽  
Physical Space ◽  
Collaborative Optimization ◽  
Gasoline Direct Injection ◽  
Digital Data ◽  
Automotive Engine ◽  
Optimization Framework ◽  
Multiparameter Optimization

Multiparameter optimization of complex electromechanical systems in a physical space is a challenging task. CPS (Cyberphysical system) technology can speed up the solution of the problem based on data interaction and collaborative optimization of physical space and cyberspace. This paper proposed a general multiparameter optimization framework by combining physical process simulation and clustering genetic algorithm for the CPS application. The utility of this approach is demonstrated in the instance of automobile engine energy-saving in this paper. A 1.8-L turbocharged GDI (gasoline direct injection) engine model was established and calibrated according to the test data and physical entity. A joint simulation program combining CGA (Clustering Genetic Algorithm) with the GDI engine simulation model was set up for the engine multiparameter optimization and performance prediction in cyberspace; then, the influential mechanism of multiple factors on engine energy-saving optimization was analyzed at 2000 RPM (Revolutions Per Minute) working condition. A multiparameter optimization with clustering genetic algorithm was introduced for multiparameter optimization among physical and digital data. The trade-off between fuel efficiency, dynamic performance, and knock risk was discussed. The results demonstrated the effectiveness of the proposed method and that it can contribute to develop a novel automotive engine control strategy in the future.

Subjective Time Preference and Willingness to Pay for an Energy-Saving Durable Good

2001 ◽  
Vol 32 (3) ◽  
pp. 133-141 ◽  
Author(s):  
Gerrit Antonides ◽  
Sophia R. Wunderink
Keyword(s):  
Willingness To Pay ◽  
Energy Saving ◽  
Subjective Time ◽  
Durable Good ◽  
Discount Function ◽  
Hyperbolic Discount ◽  
The One ◽  
Two Parameter ◽  
Difference Effect ◽  
Better Than

Summary: Different shapes of individual subjective discount functions were compared using real measures of willingness to accept future monetary outcomes in an experiment. The two-parameter hyperbolic discount function described the data better than three alternative one-parameter discount functions. However, the hyperbolic discount functions did not explain the common difference effect better than the classical discount function. Discount functions were also estimated from survey data of Dutch households who reported their willingness to postpone positive and negative amounts. Future positive amounts were discounted more than future negative amounts and smaller amounts were discounted more than larger amounts. Furthermore, younger people discounted more than older people. Finally, discount functions were used in explaining consumers' willingness to pay for an energy-saving durable good. In this case, the two-parameter discount model could not be estimated and the one-parameter models did not differ significantly in explaining the data.

Classroom Lighting Energy-Saving Control System Based on Machine Vision Technology

2018 ◽  
pp. 143-149 ◽  
Author(s):  
Ruijie CHENG
Keyword(s):  
Control System ◽  
Machine Vision ◽  
Energy Saving ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Lighting Control ◽  
Lighting Energy ◽  
Neural Network Algorithm ◽  
Energy Saving Control ◽  
Model Algorithm

In order to further improve the energy efficiency of classroom lighting, a classroom lighting energy saving control system based on machine vision technology is proposed. Firstly, according to the characteristics of machine vision design technology, a quantum image storage model algorithm is proposed, and the Back Propagation neural network algorithm is used to analyze the technology, and a multi­feedback model for energy­saving control of classroom lighting is constructed. Finally, the algorithm and lighting model are simulated. The test results show that the design of this paper can achieve the optimization of the classroom lighting control system, different number of signals can comprehensively control the light and dark degree of the classroom lights, reduce the waste of resources of classroom lighting, and achieve the purpose of energy saving and emission reduction. Technology is worth further popularizing in practice.

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